Attività scientifica

Pubblicazioni su riviste internazionali

Titolo: Patterns of restricted and repetitive behaviors in Autism spec-trum disorders: a cross-sectional video-recording study. Preli-minary report. (2021)

Autore: Enzo Grossi 1, Elisa Caminada 1, Michela Goffredo 2,*, Beatrice Vescovo 1, Tristana Castrignano 1, Daniele Piscitelli 3,4, Giulio Valagussa 1,3, Marco Franceschini 2,5, Franco Vanzulli 1

Info: Brain Sciences, September 27th 2020


Background: Several instruments have been proposed to investigate restricted, repetitive behaviors (RRBs) in individuals with Autism Spectrum Disorder (ASD). Systematic video obser-vations may overcome questionnaire and interview limitations to investigate RRBs. This study aimed to analyze stereotypic patterns through video-recordings and to determine the correlation between the number and appearance of RRBs to ASD severity;
Methods: Twenty health profes-sionals wearing a body cam recorded 780 specific-RRBs during everyday activities of 67 individu-als with ASD (mean age:14.2 ± 3.72 years) for three months. Each stereotypy was classified ac-cording to its complexity pattern (i.e., simple or complex) based on body parts and sensory chan-nels involved.
Results: The RRBs spectrum for each subject ranged from 1 to 33 different patterns (mean: 11.6 ± 6.82). Individuals with a lower number of stereotypies shown a lower ASD severity compared to subjects with a higher number of stereotypies (p=0.044). No significant differences were observed between individuals exhibiting simple (n=40) and complex patterns (n=27) of ste-reotypies on ASD severity, age, sex, and the number of stereotypes;
Conclusions: This study rep-resents the first attempt to systematically document expression patterns of RRBs with a da-ta-driven approach. This may provide a better understanding of the pathophysiology and man-agement of RRBs.


1 Autism Research Unit, “Villa Santa Maria” Foundation, Tavernerio, Italy
2 Neurorehabilitation Research Laboratory, Department of Neurological and Rehabilitation Sciences, IRCSS San Raffaele Pisana, Rome, Italy
3 School of Medicine and Surgery, University of Milano Bicocca, Milano, Italy
4 School of Physical and Occupational Therapy, McGill University, Montreal, Canada
5 Department of Human Sciences and Promotion of the Quality of Life, San Raffaele University, Rome, Italy.

Titolo: Artificial Neural Networks Analysis of Polysomnographic and Clinical Features in Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS): From Sleep Alterations To “Brain Fog” (2021)

Autore: Antonella Gagliano, Monica Puligheddu, Nadia Ronzano, Patrizia Congiu, Marcello Tanca, Ida Cursio, Sara Carucci, Stefano Sotgiu, Enzo Grossi, Alessandro Zuddas

Info: Nature and Science of Sleep, accepted.


Abstract: Study objectives: PANS (Pediatric Acute Onset Neuropsychiatric Syndrome) is thought to be the result of several mechanisms and multiple etiologies, ranging from endocrine/metabolic causes to postinfectious autoimmune and neuroinflammatory disorders. Sleep disorders represent one of the most frequent manifestations of PANS, involving around 80% of patients. The present study describes the clinical and polysomnographic features in a group of PANS children identifying the relationships between sleep disorders and other PANS symptoms.
Methods: All participants underwent a clinical evaluation including polysomnography, cognitive assessment and blood chemistry examination. A data mining approach with fourth-generation Artificial Neural Networks has been used in order to discover subtle trends and associations among variables.
Results: Polysomnography showed abnormality in 17 out of 23 recruited subjects (73.9%). In particular, in accordance with AASM criteria, 8/17 children (47%) had ineffective sleep, 10/17 (58.8%) fragmented sleep, (47.1%) Periodic Limb Movement Disorder (PLMD) and 11/17 (64.7%) REM-Sleep Without Atonia (RSWA). Most patients had more than one sleep disorder. Notably, among the 19/23 patients diagnosed with Tic/Tourette Disorder, 8/19 (42.1%) show PLMD and 10/19 (52.6%) RSWA. Artificial Neural Network methodology and the Auto-Contractive Map exploited the links among the full spectrum of variables revealing the simultaneous connections among them,
facing the complexity of PANS phenotype.
Conclusion: Sleep disorders represent, for prevalence and impact on quality of life, a cardinal symptom in patients with PANS. Thus, considering the weight of sleep disorders on diagnosis and prognosis of PANS, we could consider the possibility of including them among the major diagnostic criteria.

Titolo: Autism Spectrum Disorder from the Womb to Adulthood: Suggestions for a Paradigm Shift. (2021)

Autore: Cristina Panisi, Franca Rosa Guerini, Provvidenza Maria Abruzzo, Federico Balzola, Pier Mario Biava, Alessandra Bolotta, Marco Brunero, Ernesto Burgio, Alberto Chiara, Mario Clerici, Luigi Croce, Carla Ferreri, Niccolò Giovannini, Alessandro Ghezzo, Enzo

Info: Journal of personalized medicine 11: 2. Jan.



The wide spectrum of unique needs and strengths of Autism Spectrum Disorders (ASD) is a challenge for the worldwide healthcare system. With the plethora of information from research, a common thread is required to conceptualize an exhaustive pathogenetic paradigm. The epidemiological and clinical findings in ASD cannot be explained by the traditional linear genetic model, hence the need to move towards a more fluid conception, integrating genetics, environment, and epigenetics as a whole. The embryo-fetal period and the first two years of life (the so-called 'First 1000 Days') are the crucial time window for neurodevelopment. In particular, the interplay and the vicious loop between immune activation, gut dysbiosis, and mitochondrial impairment/oxidative stress significantly affects neurodevelopment during pregnancy and undermines the health of ASD people throughout life. Consequently, the most effective intervention in ASD is expected by primary prevention aimed at pregnancy and at early control of the main effector molecular pathways. We will reason here on a comprehensive and exhaustive pathogenetic paradigm in ASD, viewed not just as a theoretical issue, but as a tool to provide suggestions for effective preventive strategies and personalized, dynamic (from womb to adulthood), systemic, and interdisciplinary healthcare approach.

Titolo: Communication improvement reduces BPSD: a music therapy study based on artificial neural networks. (2021)

Autore: Alfredo Raglio1, Daniele Bellandi2, Luca Manzoni3, Enzo Grossi4

Info: Neurological sciences: official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology Jan.


Literature showed the effects of music therapy on behavioral disturbances, cognitive functions, and on quality of life in people with dementia. Especially, relational active music therapy approach is oriented to reduce behavioral disturbances increasing communication, especially non-verbal communication.
This study aimed at exploring the connection between the baseline characteristics of responders and the positive outcome of the intervention, but also the close relationship between the behavioral disturbances and the core of the therapeutic intervention (the relationship/communication improvement).
Linear correlation index between input variables and the presence of a critical improvement of behavioral symptoms according Neuropsychiatric Inventory and a semantic connectivity map were used to determine, respectively, variables predictive of the response and complex connections between clinical variables and the relational nature of active music therapy intervention.
The dataset was composed of 27 variables and 70 patients with a moderate-severe stage of dementia and behavioral disturbances.
Themain predictive factor is the Barthel Index, followed by NPI and some of its sub-items (mainly, Disinhibition, Depression, Hallucinations, Irritability, AberrantMotor Activity, and Agitation). Moreover, the semantic map underlines how the improvement in communication/relationship is directly linked to “responder” variable. “Responder” variable is also connected to “age,” “Mini Mental
State Examination,” and sex (“female”).
The study confirms the appropriateness of active music therapy in the reduction of behavioral disturbances and also highlights how unsupervised artificial neural networks models can support clinical practice in defining predictive factors and exploring the correlation between characteristics of therapeutic-rehabilitative interventions and related outcomes.

1 Music Therapy Research Laboratory, Istituti Clinici Scientifici Maugeri IRCCS, Via Maugeri, 27100, Pavia, Italy
2 Geriatric Department, Fondazione Istituto Ospedaliero di Sospiro, Sospiro, CR, Italy
3 Department of Mathematics and Geosciences, University of Trieste, Trieste, Italy
4 Villa Santa Maria Foundation, Tavernerio, CO, Italy

Titolo: Detection of an Autism EEG Signature From Only Two EEG Channels Through Features Extraction and Advanced Machine Learning Analysis (2020)

Autore: Enzo Grossi1, Giovanni Valbusa2, Massimo Buscema3,4

Info: Clinical EEG and Neuroscience



Background and Objective.
In 2 previous studies, we have shown the ability of special machine learning systems applied to standard EEG data in distinguishing children with autism spectrum disorder (ASD) from non-ASD children with an overall accuracy rate of 100% and 98.4%, respectively. Since the equipment routinely available in neonatology units employ few derivations,
we were curious to check if just 2 derivations were enough to allow good performance in the same cases of the above mentioned studies.
A continuous segment of artifact-free EEG data lasting 1 minute in ASCCI format from C3 and C4 EEG channels present in 2 previous studies, was used for features extraction and subsequent analyses with advanced machine learning systems. A features extraction software package (Python tsfresh) applied to time-series raw data derived 1588 quantitative features. A special hybrid system called TWIST (Training with Input Selection and Testing), coupling an evolutionary algorithm named Gen-D and a backpropagation neural network, was used to subdivide the data set into training and testing sets as well as to select features yielding the maximum amount of information after a first variable selection performed with linear correlation index threshold.
After this intelligent preprocessing, 12 features were extracted from C3-C4 time-series of study 1 and 36 C3-C4 time-series of study 2 representing the EEG signature. Acting on these features the overall accuracy predictive capability of the best artificial neural network acting as a classifier in deciphering autistic cases from typicals (study 1) and other neuropsychiatric disorders (study 2) resulted in 100 % for study 1 and 94.95 % for study 2.
The results of this study suggest that also a minor part of EEG contains precious information useful to detect autism if treated with advanced computational algorithms. This could allow in the future to use standard EEG from newborns to check if the ASD signature is already present at birth.

1 Autism Research Unit, Villa Santa Maria Foundation, Tavernerio, Italy
2 Bracco Imaging, Milan, Lombardia, Italy
3 Semeion Research Centre, Rome, Italy
4 Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA

Titolo: Possible tics diagnosed as stereotypies in patients with severe autism spectrum disorder: a video-based evaluation (2020)

Autore: Cristiano Termine1, Enzo Grossi2, Valentina Anelli1, Ledina Derhemi1, Andrea E. Cavanna3,4,5,6

Info: Neurological Sciences: official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology Jan.



The association of stereotypies and tics is not rare in children with severe autism spectrum disorder (ASD). The differential diagnosis between stereotypies and tics in this patient population can be difficult; however, it could be clinically relevant because of treatment implications.
A total of 108 video recordings of repetitive behaviors in young patients with stereotypies in the context of ASD were reviewed by a movement disorders expert and a trainee, in order to assess the prevalence of possible co-morbid tics. The Modified Rush Videotape Rating Scale (MRVS) was used to rate tic frequency and severity.
Out of 27 patients with stereotypies (24 males; mean age 14 years), 18 (67%) reported possible tics. The most frequently observed tics were eye blinking, shoulder shrugging, neck bending, staring, and throat clearing. The mean MRVS score was 5, indicating mild tic severity. The only significant difference between patients with tics and patients without tics was the total number of stereotypies, which was higher in the subgroup of patients without tics (p = 0.01).
Expert review of video-recordings of repetitive behaviors in young patients with ASD and stereotypies suggests the possibility of a relatively high rate of co-morbid tics. These findings need to be integrated with a comprehensive clinical assessment focusing on the diagnostic re-evaluation of heterogeneous motor manifestations.

1 Child Neuropsychiatry Unit, Department of Medicine and Surgery, University of Insubria, Varese, Italy
2 Department of Autism Research, “Villa Santa Maria” Child and Adolescent Neuropsychiatry Rehabilitation Unit, Tavernerio, CO, Italy
3 Michael Trimble Neuropsychiatry Research Group, University of Birmingham & BSMHFT, Birmingham, UK
4 School of Life & Health Sciences, Aston University, Birmingham, UK
5 Sobell Department of Motor Neuroscience & Movement Disorders, Institute of Neurology & University College London, London, UK
6 Department of Neuropsychiatry, National Centre for Mental Health, 25 Vincent Drive, Birmingham B15 2FG, UK

Titolo: Use of an Artificial Neural Network to Identify Patient Clusters in a Large Cohort of Patients with Melanoma by Simultaneous Analysis of Costs and Clinical Characteristics (2020)

Autore: Giovanni Damiani, Alessandra Buja, Enzo Grossi, Michele Rivera, Anna De Polo, Giuseppe De Luca, Manuel Zorzi, Antonella Vecchiato, Paolo Del Fiore, Mario Saia, Vincenzo Baldo, Massimo Rugge, Carlo Riccardo Rossi, Gianfranco Damiani

Info: Acta dermato-venereologica Nov.

Titolo: Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs) (2020)

Autore: Giovanni Damiani, Rosalynn R Z Conic, Paolo D M Pigatto, Carlo G Carrera, MD Chiara Franchi, D Angelo Cattaneo, Piergiorgio Malagoli, Radhakrishna Uppala, Dennis Linder, Nicola L Bragazzi, Enzo Grossi

Info: Journal of Drugs in Dermatology SPECIAL TOPIC 19: 12


Background: Drug resistance to biologics in psoriasis therapy can occur – it may be acquired during a treatment or else present itself from the beginning. To date, no biomarkers are known that may reliably guide clinicians in predicting responsiveness to biologics. Biologics may pose a substantial economic burden. Secukinumab efficiently targets IL-17 in the treatment of psoriasis.
Objective: To assess the “fast responder” patient profile, predicting it from the preliminary complete blood count (CBC) and clinical examination.
Materials and Methods: From November 2016 to May 2017 we performed a multicenter prospective open label pilot study in three Italian reference centers enrolling bio-naive plaque psoriasis patients, undergoing the initiation phase secukinumab treatment (300mg subcutaneous at week 0,1,2,3,4). We define fast responders as patients having achieved at least PASI 75 at the end of secukinumab induction phase. Clinical and CBC data at week 0 and at week 4 were analyzed with linear statistics, principal component analysis, and artificial neural networks (ANNs), also known as deep learning. Two different ANNs were employed: Auto Contractive Map (Auto-CM), an unsupervised ANNs, to study how this variables cluster and a supervised ANNs, Training with Input Selection and Testing (TWIST), to build the predictive model.
Results: We enrolled 23 plaque psoriasis patients: 19 patients were responders and 4 were non-responders. 30 attributes were examined by Auto-CM, creating a semantic map for three main profiles: responders, non-responders and an intermediate profile. The algorithm yielded 5 of the 30 attributes to describe the 3 profiles. This allowed us to set up the predictive model. It displayed after training testing protocol an overall accuracy of 91.88% (90% for responders and 93,75% for non-responders).
Conclusions: The present study is possibly the first approach employing ANNs to predict drug efficacy in dermatology; a wider use of ANNs may be conducive to useful both theoretical and clinical insight.

Titolo: Development of Machine Learning models to predict RT-PCR results for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data (2020)

Autore: Thomas Langer, Martina Favarato, Riccardo Giudici, Gabriele Bassi, Roberta Garberi, Fabiana Villa, Hedwige Gay, Anna Zeduri, Sara Bragagnolo, Alberto Molteni, Andrea Beretta, Matteo Corradin, Mauro Moreno, Chiara Vismara, Carlo Federico Perno, Massimo Bus

Info: Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine


Background: Reverse Transcription-Polymerase Chain Reaction (RT-PCR) for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) diagnosis currently requires quite a long time span. A quicker and more efficient diagnostic tool in emergency departments could improve management during this global crisis. Our main goal was assessing the accuracy of artificial intelligence in predicting the results of RT-PCR for SARS-COV-2, using basic information at hand in all emergency departments.
Methods: This is a retrospective study carried out between February 22, 2020 and March 16, 2020 in one of the main hospitals in Milan, Italy. We screened for eligibility all patients admitted with influenza-like symptoms tested for SARS-COV-2. Patients under 12 years old and patients in whom the leukocyte formula was not performed in the ED were excluded. Input data through artificial intelligence were made up of a combination of clinical, radiological and routine laboratory data upon hospital admission. Different Machine Learning algorithms available on WEKA data mining software and on Semeion Research Centre depository were trained using both the Training and Testing and the K-fold cross-validation protocol.
Results: Among 199 patients subject to study (median [interquartile range] age 65 [46-78] years; 127 [63.8%] men), 124 [62.3%] resulted positive to SARS-COV-2. The best Machine Learning System reached an accuracy of 91.4% with 94.1% sensitivity and 88.7% specificity.
Conclusion: Our study suggests that properly trained artificial intelligence algorithms may be able to predict correct results in RT-PCR for SARS-COV-2, using basic clinical data. If confirmed, on a larger-scale study, this approach could have important clinical and organizational implications.

Titolo: Guidelines for the Perplexed: How to Maximize Colonoscopy Efficiency During the COVID?19 Pandemic (2020)

Autore: Enzo Grossi1, Fabio Pace2

Info: Digestive Diseases and Sciences, September 2020



The recent SARS-CoV-2 pandemic behaved like a tsunami for many healthcare systems worldwide, as for example in the USA, India and Europe. Restricting the observation angle to the field of gastroenterology, a great number of new relevant clinical data have been produced in an exceedingly short period of time, such as the observation that the disease, originally considered as a respiratory illness, commonly features a variety of gastrointestinal intestinal symptoms and that the digestive system appears to be involved in disease pathogenesis [1 –3 ]. From the organizational site, endoscopy suites have been forced to suspend non-urgent procedures in order to re-allocate human resources to the care of COVID- 19 positive inpatients during the early phase of pandemic [4 –6 ] and are now planning how to gradually return to pre- COVID routine endoscopy activity [7 ]. The consequences of delaying the return to routine endoscopy are seriously impacting the health system; in the USA alone, a hypothetical suspension of elective endoscopy for 6 months is predicted to delay the diagnosis of over 2800 colorectal cancers and 22,000 adenomatous polyps with malignant potential [8 ]. The 6-month mortality rate for those eventually diagnosed with colorectal cancer is predicted to increase by 6.5% [9 ]. Nevertheless, the problem of re-starting nonurgent procedures while the COVID pandemic is ongoing with the need of maintaining protective measures and social distancing is present, the volume of procedures is going to overwhelm existing resources, resulting in a backlog of procedures. Thus, as Xiao et al. [10 ] propose in this issue of Digestive Diseases and Sciences , the policy of appropriately triaging and rescheduling endoscopic procedures, in particular screening and surveillance colonoscopy, should be based on specific and timely adopted new guidelines. Here probably lies one of the most important problems: which national or international guidelines should be adopted for the purpose? Recommendations have been changing rapidly and need to be updated, mainly due to the new development of worldwide sustained community transmission of COVID- 19 [11 ]; moreover, at least 21 specific recommendations are available for endoscopy during the COVID-19 pandemic elaborated by a pool of 93 international and national societies as identified in a recent review [12 ].
Xiao et al. adopted pre-COVID era guidelines, namely those of the US Multi-Society Task Force (USMSTF) published in 2017 [13 ] and updated in 2020 [14 ] as a guide to expanding access to endoscopy. In their single-center observational study of patients scheduled for open-access (OA) colonoscopy ordered by a primary physician over a six-week period during the COVID-19 pandemic, they found that up to one-fifth of colonoscopies can be rescheduled into a future year based on USMTSTF guidelines [14 ]. Interestingly enough, roughly 75% of these inappropriately scheduled colonoscopies were non-adherent to the above guidelines, whereas the remaining 25% was due to inappropriate use of family history by the primary care physician (PCP). Thus, the study confirms that: a) PCPs recommend repeat colonoscopy sooner than guidelines suggest [15 , 16 ]; and b) a significant proportion of open access colonoscopies for colorectal cancer prevention are indeed inappropriate, confirming the figure of nearly 8% according to a recent review by Kapila et al. [17 ]. Thus, the question arises of how to improve the use of OA colonoscopy for CRC screening and surveillance, since this might reduce the volume of procedures without delaying CRC detection. Xiao et al. suggest that this can be accomplished by incorporating guidelines at two points of care, namely following the index colonoscopy and in the PCP’s office. Nonetheless, as authors admit, often the PCP simply follows inappropriate recommendations provided by the endoscopist, suggesting lack of awareness or disagreement with existing guidelines. Indeed, predictors for poor adherence to guidelines have been carefully examined and suggested [18 ]. This pushes back to the general issue of how can effective guidelines be proposed and updated, with the conclusion that continuing education is mandatory, in particular in these times of rapidly changing clinical paradigms.


1 Villa Santa Maria Foundation, Tavernerio, Italy
2 Division of Gastroenterology, ASST Bergamo Est, Seriate, BG, Italy

Titolo: Relationship between tip-toe behavior and soleus - gastrocnemius muscle lengths in individuals with autism spectrum disorders (2020)

Autore: Giulio Valagussa1,2, Valeria Balatti1, Luca Trentin1, Daniele Piscitell2,3, Momoko Yamagata4,5, Enzo Grossi1

Info: Journal of Orthopaedics



About 20% of individuals with autism spectrum disorders (ASD) showed tip-toe behavior (TTB). This behavior may be related to a decreased ankle joint range of motion (ROM) in dorsiflexion. Physiologically, gastrocnemius (GM) and soleus (SM) muscles influence ankle ROM independently. However, no studies investigated the relationship between the amount of time individuals with ASD spend in TTB and GM and SM muscle lengths.

To evaluate the relationship between three mutually exclusive clinical patterns of TTB i.e., during standing, walking and running (TTB Class 1), or during walking and running (TTB Class 2), or only when running (TTB Class 3), and GM and SM muscle lengths.

Sixty-nine individuals with ASD (average age: 14.1 ± 3.6 years, 56 males) were enrolled. In a clinical setting, SM and GM muscle lengths of both legs were assessed through a manual goniometer. Measurements were performed by two trained assessors blinded to TTB classifications.

Individuals with ASD classified as TTB Class 1 demonstrated a shortening of both GM and SM compared with NO-TTB and TTB Class 3 individuals.

Our results support the relationship between TTB severity and GM and SM shortening assessed by a decreased ankle joint ROM in dorsiflexion. Further studies are needed to determine the factors associated with TTB and decreased ankle ROM.


1 Autism Research Unit, Villa Santa Maria Foundation, Via IV Novembre 15, Tavernerio, CO, Italy
2 School of Medicine and Surgery, University of Milano Bicocca, Milano, Italy
3 School of Physical & Occupational Therapy, McGill University, Montreal, Canada
4 Faculty of Human Development, Graduate School of Human Development and Environment, Kobe University, Japan
5 Human Health Sciences, Graduate School of Medicine, Kyoto University, Japan

Titolo: Effects of Probiotic Supplementation on Behavioral and Gastrointestinal Symptoms in Autism Spectrum Disorders: a Randomized Controlled Trial (2020)

Autore: Elisa Santocchi1, Letizia Guiducci2, Margherita Prosperi1, 3, Sara Calderoni1, 3*, Melania Gaggini2, Fabio Apicella1, Raffaella Tancredi1, Paola Mastromarino4, Enzo Grossi5, Amalia Gastaldelli2, Maria Aurora Morales2, Filippo Muratori1,3

Info: Frontiers in Psychiatry, 550593, 2020



The microbiota-gut-brain axis has been recently r cognized as a key modulator of neuropsychiatric health. In this framework, probiotics (recently named “psychobiotics”) may modify brain activity and function, possibly improving the behavioral profiles of children with Autism Spectrum Disorder (ASD). We evaluated the effects of probiotics on autism in a double-blind randomized,
placebo-controlled trial of 85 preschoolers with ASD (mean age, 4.2 years; 84% boys). Participants were randomly assigned to probiotics (De Simo e Formulation) (n=42) or placebo (n=43) for six months. Sixty-three (74%) children completed the trial. No differences between groups were detected on the primary outcome measure, the Total Autism Diagnostic Observation Schedule - Calibrated Severity Score (ADOS-CSS). An exploratory secondary analysis on subgroups of children with or without Gastrointestinal Symptoms (GI group, n= 30; NGI group, n=55) revealed in the NGI group treated with probiotics a significant decline in ADOS scores as compared to that in the placebo group, with a mean reduction of 0.81 in Total ADOS CSS and of 1.14 in Social-Affect ADOS CSS over six months. In the GI group treated with probiotics we found greater improvements in some GI symptoms, adaptive functioning, and sensory profiles than in the GI group treated with placebo. These results suggest potentially positive effects of probiotics on core autism symptoms in a subset of ASD children independent of the specific intermediation of the probiotic effect on GI symptoms. Further studies are warranted to replicate and extend these promising findings on a wider population with subsets of ASD patients which share targets of intervention on the microbiota-gut-brain axis.


1 Fondazione Stella Maris (IRCCS), Italy,
2 Institute of Clinical Physiology, Italian National Research Council, Italy,
3 University of Pisa, Italy,
4 Department of Public Health and Infectious Diseases, Faculty of Pharmacy and Medicine, Sapienza University of Rome, Italy,
5 Villa Santa Maria Foundation, Tavernerio, Italy

Titolo: Physiological Profile Assessment of Posture in Children and Adolescents with Autism Spectrum Disorder and Typically Developing Peers (2020)

Autore: Cecilia Perin1, Giulio Valagussa1,2, Miryam Mazzucchelli1, Valentina Gariboldi1,3, Cesare Giuseppe Cerri1, Roberto Meroni4, Enzo Grossi2, Cesare Maria Cornaggia1, Jasmine Menant5, Daniele Piscitelli1,6

Info: Brain Sciences, September 27th 2020



A sound postural system requires sensorimotor integration. Evidence suggests that individuals with Autism Spectrum Disorder (ASD) present sensorimotor integration impairments. The Physiological Profile Assessment (PPA) can be used to evaluate postural capacity assessing five physiological subsets (i.e., vision, reaction time, peripheral sensation, lower limb strength, balance); however, no studies applied the PPA in young individuals. Therefore, this study aimed to investigate the PPA in children and adolescents with ASD compared with age-matched typically developing (TD) individuals and examine the relationship between the PPA subset within the ASD and TD participants according to different age groups. Percentiles from the PPA were obtained from the TD children and adolescents (n = 135) for each test. Performances of the individuals with ASD (n = 18) were examined relative to the TD percentiles. ASD participants’ scores were above the 90th percentile (i.e., poor performance) in most sensory, motor and balance parameters. Performance in most of the PPA tests significantly improved with older age in the TD group but not in the ASD group. The study findings support the use of the PPA in TD children and adolescents while further research should investigate postural capacity in a larger ASD sample to enhance the understanding of sensorimotor systems contributing to compromised postural control.


1 School of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, Italy
2 Autism Research Unit, “Villa Santa Maria” Foundation, 22038 Como, Italy
3 ASST Rhodense, Ospedale “G. Salvini”, 20024 Milan, Italy
4 Department of Physiotherapy, LUNEX International University of Health, Exercise and Sports, Differdange, 4671 Luxembourg, Luxembourg
5 Neuroscience Research Australia and School of Public Health and Community Medicine, University of New South Wales, Sydney, NSW 2052, Australia
6 School of Physical and Occupational Therapy, McGill University, Montreal, QC H3G 1Y5, Canada
7 School of Physical Therapy and Athletic Training, Pacific University, Hillsboro, OR 97123, USA

Titolo: Prediction of Resting Energy Expenditure in Children: May Artificial Neural Networks Improve Our Accuracy? (2020)

Autore: Valentina De Cosmi, Alessandra Mazzocchi, Gregorio Paolo Milani, Edoardo Calderini, Silvia Scaglioni, Silvia Bettocchi, Veronica D'Oria, Thomas Langer, Giulia C I Spolidoro, Ludovica Leone, Alberto Battezzati, Simona Bertoli, Alessandro Leone, Ramona Silv

Info: Journal Clinical Medicine 9, 1026


The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE prediction. We enrolled 561 healthy children (2-17 years). Nutritional status was classified according to World Health Organization (WHO) criteria, and 113 were obese. REE was measured using indirect calorimetry and estimated with WHO, Harris-Benedict, Schofield, and Oxford formulae. The ANNs considered specific anthropometric data to model REE. The mean absolute error (mean ± SD) of the prediction was 95.8 ± 80.8 and was strongly correlated with REE values ( = 0.88). The performance of ANNs was higher in the subgroup of obese children (101 ± 91.8) with a lower grade of imprecision (5.4%). ANNs as a novel approach may give valuable information regarding energy requirements and weight management in children.

Titolo: Exceptionally high COVID-19 viral load and very long duration of shedding in a young pauci-symptomatic child with autism resident in an Italian nursing home (2020)

Autore: Enzo Grossi1, Vittorio Terruzzi1

Info: Journal of Infection, august 28th 2020



Few studies so far have focused on the duration of COVID- 19 detection in asymptomatic or pauci-symptomatic subjects1,2. In asymptomatic adults, the median time from the first positive test to the first of two consecutive negative tests ranges between 7 and 23 days. Only two case-report studies have concerned children, with a detectable virus for 10 days3 and for 17 days4.
There are multiple reports of prolonged viral shedding in peo- ple infected with SARS-CoV-2 but the presence of viral RNA on a test does not necessarily correlate with infectivity5–8.
The duration of quarantine required after clinical recovery to definitively prevent transmission is therefore uncertain.
We report a case of exceptionally high viral load and extremely slow SARS-CoV-2 RNA shedding in a toddler resident in Villa Santa Maria rehabilitation Institute, a well-known Nursing Home in the Lombardy region.
An Italian child with autism and severe intellectual disability, nine years old, resident in our Institute from 2018, on April 20th developed a cough and nasal discharge. On the evening of April 21st, a moderate fever (38.3 C°) was registered, disappearing on the morning of 22nd. All symptoms vanished from the 22nd after- noon.
At the objective examination, no clinical signs of lung involve- ment were noticed. The child underwent nose-pharyngeal swab for COVID-19 virus detection on April 24th.
Quantitative RT-PCR indicated a viral load corresponding to a Cycle Threshold(CT) value = 6 (10.5 log10 copies/mL). After this first swab other five repeated tests performed approximatively ev- ery two-three week confirmed the detection of COVID RNA with CT values of 29,30,36,26, 34 along the following twelve weeks (Fig. 1), till July 15th, date of the last positive swab. The subject was main- tained in isolation for all this period considering viral load levels potentially related to infectivity as those registered. The first nega- tive swab was registered on August 4th followed by a second neg- ative swab on August 6th. At this latter date a high specific IgG response was registered with S/CO titers (Log2) >10.
Throughout this period the subject remained asymptomatic. Blood examination tests revealed the presence of marked neu- tropenia (neutrophil count=930/ml) and a low percentage of CD4 helper lymphocytes (25%).
This case suggests that in pauci-symptomatic children excep- tionally high viral load can be detected and consequently the virus shedding can take a long duration, 82 days precisely. Careful mon- itoring with repeated tests at regular intervals checking CT values is important to establish the duration of the infectivity, which, as suggested by recent studies9,10 can be considered absent only with CT values above 34.

Notes: 1 Villa Santa Maria Foundation, Tavernerio, Italy 

Titolo: Vagus nerve Stimulation decreases the levels of pro-inflammatory cytokines in fdrug-resistant pediatric patients: correlation of serum findings and clinical outcome (2020)

Autore: Maria Vittoria Bonavina, Daniele Grioni, Francesco Saettini, Concetta Luisi, Giovanna D’amico, Andrea Trezza, Valentina Baro, Luca Denaro, Domenico D’Avella, Andrea Landi

Info: Submitted to Epilepsy Research

Titolo: COVID-19 in Italy and extreme data mining (2020)

Autore: Paolo Massimo Buscema1, 2, Francesca Della Torre1, Marco Breda1, Giulia Massini1, Enzo Grossi3

Info: Physica A, 557, 2020



Abstract: In this article we want to show the potential of an evolutionary algorithm called Topological Weighted Centroid (TWC). This algorithm can obtain new and relevant information from extremely limited and poor datasets. In a world dominated by the concept of big (fat?) data we want to show that it is possible, by necessity or choice, to work profitably even on small data. This peculiarity of the algorithm means that even in the early stages of an epidemic process, when the data are too few to have sufficient statistics, it is possible to obtain important information. 

To prove our theory, we addressed one of the most central issues at the moment: the COVID-19 epidemic. In particular, the cases recorded in Italy have been selected. Italy seems to have a central role in this epidemic because of the high number of measured infections. Through this innovative artificial intelligence algorithm, we have tried to analyze the evolution of the phenomenon and to predict its future steps using a dataset that contained only geospatial coordinates (longitude and latitude) of the first recorded cases. 

Once the coordinates of the places where at least one case of contagion had been officially diagnosed until February 26th, 2020 had been collected, research and analysis was carried out on: outbreak point and related heat map (TWC alpha); probability distribution of the contagion on February 26th (TWC beta); possible spread of the phenomenon in the immediate future and then in the future of the future (TWC gamma and TWC theta); how this passage occurred in terms of paths and mutual influence (Theta paths and Markov Machine). Finally, a heat map of the possible situation towards the end of the epidemic in terms of infectiousness of the areas was drawn up. The analyses with TWC confirm the assumptions made at the beginning.


1 Semeion Research Center of Sciences of Communication, via Sersale, 117, 00128 Rome, Italy

2 University of Colorado at Denver, Department of Mathematical and Statistical Sciences, Denver, CO, US

3 Villa Santa Maria Foundation, Tavernerio (Como), Italy

Titolo: Oscillation of SARS CoV-2 RNA load in a cohort of children and adolescents with neuro-psychiatric disorders resident in a nursing home of Lombardy Region (Italy) (2020)

Autore: Enzo Grossi1, Lucy Costantino2, Fulvio Ferrara2, Vittorio Terruzzi1

Info: Journal of Infection, July 8th 2020



Abstract: COVID-19 has heavily affected nursing homes for elderly people in Italy and particularly in the Lombardy region, causing uncount- able deaths. From the moment the pandemic slowly faded, there has been a pressing scientific and social need to define a limit of time and of viral load beyond which the positivity of RT-PCR loses its meaning, to reduce the isolation of the subjects in the nursing homes beyond the clinical and public health utility. 
While the decline in viral infectivity seems to decline in one or two weeks since symptom onset1-2 the RT-PCR positivity may per- sist for several weeks after the resolution of symptoms3-6. Since there is a minimal risk for persistently-positive recovered patients to shed infectious virus, many of them remain hospitalized, or in shelter-in-place, for a much longer time than necessary, with sig- nificant social distress and economic commitment. 
Few data are available so far in children and adolescent nursing homes regarding quantitative RT-PCR (qRT-PCR) registered during the COVID-19 pandemic. 
Fifty-two children and adolescents (41 males 11 females: mean age 14.8, range 6–18 years) affected by neuropsychiatric disorders and resident in Villa Santa Maria Rehabilitation Institute, a well- known nursing home in Lombardy region, underwent a series of qRT-PCR on nose-pharyngeal swabs from April 27 to July 4th, 2020. 
Thirty-two subjects had symptoms suggestive of COVID-19 infec- tion, like fever, cough, and or diarrhea while 20 were asymp- tomatic. Sixty-two percent of symptomatic subjects and 50% of asymptomatic subjects resulted positive to COVID-19 with a total of 30 positive cases (25 males - 5 females; mean age 14.1 years). 
Subjects showing positivity to the test were monitored through- out with repeated tests on a 1–2-week basis until the obtainment of two consecutive negative tests. We had to wait till July 4th to certify the negative turning of all subjects. 
Interesting details of viral load in the 30 subjects positive at RT-PCR were observed according to different subgroup characteris- tics. The initial viral load of 25 males was significantly higher than 5 females (median [IQR] males: 19 [14 – 23,5] vs. 27 [24–29], re- spectively; p = 0.01 by Mann-Whitney test). 
Initial viral load observed in 21 symptomatic subjects resulted substantially higher in comparison with 9 asymptomatic subjects (median [IQR] with symptoms: 20 [15 –27] vs. 22 [16.5–25], re- spectively; the difference anyway resulted statistically not signifi- cant (p = 0.8 Mann–Whitney test). The viral load at the first swab in 16 subjects who remained still positive at second swab was higher in comparison with 14 subjects who resulted negative at second swab. Also in this case the difference resulted statistically not significant (median CT[IQR] still positive: 19.5 [14.5 –23.7] vs. 22 [17.7–27], respectively (p = 0.4 Mann–Whitney test). 
Twenty subjects underwent more than two RT-PCR tests until permanent negative turning. 
Fig. 1 shows the oscillation of viral load in the subsequent 97 swabs, performed along 12 weeks after the first swab. A marked oscillation of viral load value was observed, also with negative swabs turning positive. 
This study shows that in children and adolescents found pos- itive at COVID-19 RT-PCR being resident in a nursing home the time required for a definitive disappearance of the virus from nose-pharyngeal swab can overcome two months. Along this pe- riod is possible to observe the existence of discrete oscillation in COVID-19 viral load count in line with the results of a recent Ital- ian study7. Given these findings, the WHO resolution for releasing COVID-19 patients from isolation seems reasonable to avoid unnec- essary social burden.

Notes: 1 Villa Santa Maria Institute, Tavernerio, Italy 2 Centro Diagnostico Italiano, Milano, Italy

Titolo: COVID-19: the Italian Drama (2020)

Autore: Ernesto Burgio, Joseph Bellanti, Gian Carlo Di Renzo, Enzo Grossi, Rodolfo Guzzi, Giuseppe Remuzzi

Info: Wall Street Journal



In December 2019, a new potentially pandemic Coronavirus made its appearance in the province of Wuhan, China. From there, the epidemic began to spread to the rest of China, then to Asia and all over the world. Today, cases are reported in over one hundred countries, in Asia, Europe, North America, South America, Africa and Oceania. The feared transmission of the virus from human to human has been confirmed in all these regions and in Europe, also by asymptomatic subjects. It is difficult to understand why these data have long been underestimated, above all in the West Countries. Only on March 11th 2020 the WHO declared the pandemic alarm. To date, April 13th 2020, the confirmed cases in the world are 1.844.863 and the confirmed deaths 117.021 (20.465 in Italy vs. 3.351 recorded in China and 222 in South Korea). The situation appears particularly serious in Northern Italy, and more recently also in UK (11,329 deaths), France (14,946 deaths), Spain (17,489 deaths) and above all United States of America (21,972 deaths), with the number of cases doubling every day in Madrid and New York city. Italy has currently recorded 16.400 infected healthcare workers and 116 medical doctors dead. In this paper, we will try to explain why Italy has become the second epicenter of the world epidemics after China, and why the containment strategies and preventive measures adopted so far by the Italian government still do not seem to be sufficiently adequate in slowing the expansion of the COVID-19 outbreak.

Titolo: Pediatric Acute-onset Neuropsychiatric Syndrome (PANS): a data mining approach to very specific constellation of clinical variables (2020)

Autore: Antonella Gagliano 1, Cecilia Galati 2, Massimo Ingrassia 3, Massimo Ciuffo 4, Maria Ausilia Alquino 2, Marcello G. Tanca 1, Sara Carucci 1, Alessandro Zuddas 1, Enzo Grossi 5

Info: Journal of Child and Adolescent Psychopharmacology, 28 May 2020


Objectives: Paediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder presenting with: unusually abrupt onset obsessive compulsive disorder (OCD) or severe eating restrictions, with at least two concomitant cognitive, behavioural, or affective symptoms such as anxiety, obsessive-compulsive behaviour,
irritability/depression. This study describes the clinical and laboratory variables of 39 children (13 female and 26 male) with a mean age at recruitment of 8.6 years (SD 3.1).

Methods: Using a mathematical approach based on Artificial Neural Networks, the putative associations between PANS working criteria, as defined at the NIH in July 2010 (Swedo et al. 2012), were explored by the Auto Contractive Map (Auto-CM) system, a mapping method able to compute the multi-dimensional association of strength of each variable with all other variables in predefined dataset.

Results: The PANS symptoms were strictly linked to one another on the semantic connectivity map, shaping a central “diamond” encompassing anxiety, irritability/Oppositional defiant disorder (ODD) symptoms, obsessive-compulsive symptoms, behavioural regression, sensory motor abnormalities, school performance deterioration, sleep disturbances, emotional lability/depression. The semantic connectivity map also showed the aggregation between PANS symptoms and laboratory and clinical variables. In particular, the emotional lability/depression resulted as a highly connected hub linked to autoimmune disease in pregnancy, allergic and atopic disorders and low Natural Killer percentage. Also anxiety symptoms were shown strongly related with recurrent infectious disease remarking the possible role of infections as a risk factor for PANS.

Conclusion: Our data mining approach shows a very specific constellation of symptoms having strong links to laboratory and clinical variables consistent with PANS feature.


1 Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, & “G. Brotzu” Hospital Trust, Cagliari, Italy
2 Division of Child Neurology and Psychiatry, Department of Pediatrics, University of Messina. Messina, Italy
3 Division of Psychology, Department of Humanities and Social Sciences, University of Messina, Messina, Italy
4 Department of Cognitive Psychological Pedagogical Sciences and Cultural Studies, University of Messina, Messina, Italy
5 Autism Research Unit, Villa Santa Maria Foundation, Tavernerio, Italy

Titolo: Artificial Neural Network Analysis of Bone Quality DXA Parameters Response to Teriparatide in Fractured Osteoporotic Patients (2020)

Autore: Carmelo Messina 1 2 , Luca Petruccio Piodi 3 , Enzo Grossi 4 , Cristina Eller-Vainicher 5 , Maria Luisa Bianchi 6 , Sergio Ortolani 6 , Marco Di Stefano 7 , Luca Rinaudo 8 , Luca Maria Sconfienza 1 2 , Fabio Massimo Ulivieri 9

Info: PLoS One, 15 (3), e0229820, 11 Mar 2020


Teriparatide is a bone-forming therapy for osteoporosis that increases bone quantity and texture, with uncertain action on bone geometry. No data are available regarding its influence on bone strain. To investigate teriparatide action on parameters of bone quantity and quality and on Bone Strain Index (BSI), also derived from DXA lumbar scan, based on the mathematical model finite element method. Forty osteoporotic patients with fractures were studied before and after two years of daily subcutaneous 20 mcg of teriparatide with dual X-ray photon absorptiometry to assess bone mineral density (BMD), hip structural analysis (HSA), trabecular bone score (TBS), BSI. Spine deformity index (SDI) was calculated from spine X-ray. Shapiro-Wilks, Wilcoxon and Student's t test were used for classical statistical analysis. Auto Contractive Map was used for Artificial Neural Network Analysis (ANNs). In the entire population, the ameliorations after therapy regarded BSI (-13.9%), TBS (5.08%), BMD (8.36%). HSA parameters of femoral shaft showed a worsening. Dividing patients into responders (BMD increase >10%) and non-responders, the first presented TBS and BSI ameliorations (11.87% and -25.46%, respectively). Non-responders presented an amelioration of BSI only, but less than in the other subgroup (-6.57%). ANNs maps reflect the mentioned bone quality improvements. Teriparatide appears to ameliorate not only BMD and TBS, but also BSI, suggesting an increase of bone strength that may explain the known reduction in fracture risk, not simply justified by BMD increase. BSI appears to be a sensitive index of TPD effect. ANNs appears to be a valid tool to investigate complex clinical systems.


1 IRCCS Istituto Ortopedico Galeazzi, Milano, Italy.
2 Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milano, Italy.
3 Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, UO Gastroenterologia ed Endoscopia Digestiva, Milano, Italy.
4 Villa Santa Maria Foundation, Centro di Riabilitazioni Neuropsichiatrica, UO Autismo, Tavernerio (CO), Italy.
5 Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, UO Endocrinologia, Milano, Italy.
6 IRCCS Istituto Auxologico, UO Endocrinologia e Malattie del Metabolismo, Milano, Italy.
7 A.O.U. Città della Salute e della Scienza di Torino, Presidio Molinette, Corso Bramante, Torino, Italy.
8 TECHNOLOGIC Srl, Lungo Dora Voghera, Torino, Italy.
9 Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, UO Medicina Nucleare, Milano, Italy.

Titolo: Machine Learning Systems and Precision Medicine: A Conceptual And Experimental Approach To Single Individual Statistics (2020)

Autore: Enzo Grossi, Giulia Massini, Massimo Buscema

Info: Artificial Intelligence in Precision Health. From Concept to Applications 1st Edition Debmalya Barh Ed. Elsevier 2020 pp. 91-119


Background and Objective: The translation of precision medicine in clinical practice will depend mostly from the possibility to make statistical inference at individual level, exactly positioning a new case in the taxonomy space (diagnosis) or in the time space (prognosis). As matter of the fact clinical epidemiology and medical statistics have not been suited to answer specific questions at the individual level. They focus on groups of individuals and not on single individuals. Classical statistics by definition needs samples to work, and samples by definition are always greater than one. This explains why for traditional statistics the single individual is a sort of moving and vague target to intercept. The objective of this paper is to show the feasibility of the use of potent machine learning system developed at Semeion Institute in approaching the problem of single individual statistics in a consistent and sound way.

Methods. Three cases studies relevant to different unsupervised machine learning systems are shown: a) the use of Self Organizing Maps to determine the confidence interval of a quality of life scale total score in seven new individual subjects having a group of 1000 individuals as reference data set; b) the use of the evolutionary algorithm “Pick and Squash Tracking” (PST) to cluster and discriminate patients affected by Barrett disease from those affected by simple gastroesophageal reflux disease, c) the use of Auto-CM system, a fourth generation artificial neural network, to map individual patients with and without acute myocardial infarction on the basis of genetic, clinical traits and classical risk factors. A further case study is described relying on the use of supervised machine learning systems, based on the concept of Fermi mathematics.

Results. The three unsupervised methods proved to be reliable and easily applicable to real world examples in term of readability, accuracy and reproducibility. The confidence interval related to seven new cases in the first case study allowed the clinician to identify easily the outlier. The accuracy of the map projection with PST algorithm in the second case study allowed an immediate visual evidence of the degree of membership of each individual subject to the two diagnostic classes. In the third case study the overall accuracy of clustering obtained by Auto-Cm system resulted to be 93%.The conceptual advantages obtainable are explained. The fourth method shows that is possible by using several independent classification models on the same individual to establish a degree of confidence of the prediction and therefore to overcome the dogma by which it is not possible to make a statistical inference when a sample is composed by just one subject.

Conclusions: Machine learning systems have the potential to allow the real translation of precision medicine philosophy in the real world.

Titolo: Bacterial network community in fecal and endoluminal Microbiota after colonoscopy (2020)

Autore: Gabriele Meroni, Fabio Pace, Enzo Grossi, Valentina Casini, Lorenzo Drago

Info: The new microbiologica 43: 1. Mar.


Abstract: The gut microbiota is a complex and dynamic ecosystem with a strong influence on the host's health. Several factors can modify the gut's bacterial composition, often leading to the onset of intestinal dysbiosis. Therefore, it is essential not only to evaluate the quantitative bacterial changes occurring in the human microbiota but also to characterize relationships existing among all the microorganisms. This study aimed to evaluate the impact of bowel cleansing on the fecal microbiota network by highlighting differences between fecal microflora before and after colonoscopy, and luminal samples during colonoscopy. Fecal and luminal samples, previously analyzed by mean of Next-Generation Sequencing (NGS) for their bacterial abundance, were further processed by a method based on Artificial Neural Network (ANN) architecture. The bowel lavage had a strong effect on the intestinal microbiota network, leading to significant changes in the distribution of different bacterial hubs potentially involved in the microbiota homeostasis. Furthermore, the fecal and luminal microbiota showed a different bacterial network, characterized by distinct microbial hubs. In particular, the latter seemed to be rich in potentially pathogenic bacteria which, in physiological conditions, are counteracted by fecal microorganisms.

Titolo: Artificial Neural Networks allow Response Prediction in Squamous Cell Carcinoma of the Scalp Treated with Radiotherapy (2020)

Autore: Giovanni Damiani 1,2,3,4,^,*, Enzo Grossi ^,5, Emilio Berti 1,2, Rosalynn RZ Conic 4, Uppala Radhakrishna 6, Alessia Pacifico 7, Nicola L Bragazzi 8, Roberta Piccinno 1,2, † and Michael Dennis Linder 9 †,*

Info: In press, Journal of the European Academy of Dermatology and Venereology



Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumors affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) without lymph node involvement, multiple or extensive lesions, for patients refusing surgery, for patients with a poor general medical status, as adjuvant for incompletely excised lesions and/or as a palliative treatment. To date, prognostic risk factors in scalp cSCC patients are poorly characterized.

To identify patterns of patients with higher risk of post-radiotherapy recurrence

A retrospective observational study was performed on scalp cSCC patients with histological diagnosis who underwent conventional radiotherapy (50-120 kV) (between 1996 and 2008, follow-up from 1 to 140 months, median 14 months). Out of the 79 enrolled patients, 22(27.8%) had previously undergone a surgery. Two months after
radiotherapy, 66(83.5%) patients achieved a complete remission, 6(7.6%) a partial remission, whereas 2(2.5%) proved non-responsive to the treatment and 5 cases were lost to follow-up. Demographical and clinical data were preliminarily analyzed with classical descriptive statistics and with principal component analysis. All data were then re-evaluated with a machine learning-based approach using a 4th generation artificial neural networks(ANNs)-based algorithm.

ANNs analysis revealed four scalp cSCC profiles among radiotherapy responsive patients, not previously described: namely, 1) stage T2 cSCC type, aged 70-80 years; 2) frontal cSCC type, aged <70 years; 3) non-recurrent nodular or nodulo-ulcerated, stage T3 cSCC type, of the vertex and treated with >60 Grays (Gy); and 4) flat, occipital, stage T1 cSCC type, treated with 50-59 Gy. The model uncovering these four predictive profiles displayed 85.7% sensitivity, 97.6% specificity, and 91.7% overall accuracy.

Patient profiling/phenotyping with machine learning may be a new, helpful method to stratify patients with scalp cSCCs who may benefit from a RT-treatment.



1 Phototherapy Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
2 Dermatology Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico di Milano, Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Milan, Italy
3 Young Dermatologists Italian Network, Centro Studi GISED, Bergamo, Italy
4 Department of Dermatology, Case Western Reserve University, Cleveland, Ohio, USA
5 Fondazione Villa Santa Maria, Tavernerio, Como, Italy
6 Department of Obstetrics and Gynecology, Oakland University William Beaumont School of Medicine, Royal Oak, Michigan, USA
7 Clinical Dermatology Department, IRCCS S. Gallicano Dermatological Institute, Rome, Italy
8 School of Public Health, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
9 Ben Gurion University of the Negev, Beer Sheva Israel
^ Equally contributed as first authors.
† Equally contributed as last authors.

Titolo: Going to the museum makes you happy: pilot study with people with cognitive disabilities at the Museo Teatrale alla Scala (2019)

Autore: Annamaria Ravagnan*; Antonia Castelnuovo**; Enzo Grossi**

Info: Available as preprint on Researchgate



The aim of this study is to highlight the feasibility of an aesthetic experience in Museo Teatrale alla Scala in seventeen adolescents and adult subjects suffering from different forms of neuro-psychiatric diseases, guests of the Villa Santa Maria Institute, an Italian Rehabilitation Center.
The experience consisted in a guided tour in the museum coupled by an opera performance in the exedra room of the Museo Teatrale alla Scala, such as the adaptation of Mozart's Magic Flute. The measurement of the impact of this experience on psychological well-being, carried out through the use of a special analogue chromatic scale, allowed to establish a strong emotional impact with a statistically significant increase in the momentary psychological well-being in all three groups.
This pilot study confirms that art is able to stimulate parts of the brain that remain intact even after the onset of neuro-psychiatric diseases and that the measurement of temporary wellbeing is feasible even in the presence of cognitive deficit.


*ICOM Italia
** Fondazione Villa Santa Maria – Tavernerio

Titolo: Metabolic syndrome is a risk factor for colorectal adenoma and cancer: a study in a White population using the harmonized criteria (2019)

Autore: Angelo Milano, Maria Antonia Bianco, Luigi Buri, Livio Cipolletta, Enzo Grossi, Gianluca Rotondano, Francesco Tessari, Konstantinos Efthymakis and Matteo Neri on behalf of NEOCOSM (NEOplasia del COlon e Sindrome Metabolica) Study Group

Info: Therapeutic Advances in Gastroenterology


Background: Metabolic syndrome (MetS) has been associated with colorectal adenomas and cancer. However, MetS definitions have changed over time, leading to a heterogeneity of patients included in previous studies and a substantial inextensibility of observations across time or eastern and western populations. Our aim was to evaluate the association of ‘harmonized’ criteria-defined MetS and its individual components with colorectal neoplasia and cancer in a western population.

Methods: In this multicenter, cross-sectional study, we prospectively evaluated consecutive outpatients who underwent open-access colonoscopy over a 3-month period. MetS was diagnosed according to the 2009 ‘harmonized’ criteria.

Results: Out of 5707 patients enrolled, we found 213 cancers (3.7%), 1614 polyps (28.3%), 240 nonpolypoid lesions (4.2%), 95 laterally spreading tumors (1.6%). Polyps presented histological low-grade dysplasia in 72.9% of samples, while in 9.8%, high-grade dysplasia or in situ carcinoma was present; dysplasia rates for nonpolypoid lesions were 66.2% (low-grade) and 2.9% (high-grade/in situ carcinoma), while for laterally spreading tumors, 29.6% and 37%, respectively. Overall, MetS prevalence was 41.6%. MetS correlated with both adenomas [odds ratio (OR): 1.76, 95% confidence interval (CI) 1.54–2.00] and cancer (OR: 1.92, 95% CI 1.42–

2.58). MetS was the only risk factor for such colonic lesions in subjects younger than 50 years. For all colonic neoplasia, we found MetS and not its individual components to be significantly associated.

Conclusions: MetS is risk factor for cancer and adenoma in Whites, especially when younger than 50 years. MetS patients might be considered as a high-risk population also in colorectal cancer screening programs.



- Matteo Neri, Department of Medicine and Aging Sciences and Center of Aging Sciences and Translational Medicine (CeSI-MeT), ‘G.D.’ Annunzio University and Foundation, Chieti, Italy - Digestive Endoscopy and Gastroenterology Unit, ‘SS Annunziata’ University Hospital, Chieti, Italy 

- Angelo Milano and Konstantinos Efthymakis, Department of Medicine and Aging Sciences and Center of Aging Sciences and Translational Medicine (CeSI-MeT), ‘G.D.’ Annunzio University and Foundation, Chieti, Italy - Digestive Endoscopy and Gastroenterology Unit, ‘SS Annunziata’ University Hospital, Chieti, Italy

- Maria Antonia Bianco, Livio Cipolletta and Gianluca Rotondano, Division of Gastroenterology and Digestive Endoscopy Unit, Hospital ‘A Maresca’, Torre del Greco, Italy 

- Luigi Buri, Gastroenterology and Digestive Endoscopy Unit, Cattinara Hospital, Trieste, Italy

- Enzo Grossi, Villa Santa Maria Foundation, Como,Italy

- Francesco Tessari, Electronic Data Processing, Idea 99 Srl, Padova, Italy

Titolo: Artificial neural networks help to better understand the interplay between cognition, mediterranean diet and physical performance. Clues from TRELONG study  (2019)

Autore: Maurizio Gallucci, Claudia Pallucca, Maria Elena Di Battista, Bertrand Fougère, Enzo Grossi 

Info: In press, Journal of Alzheimer's Disease


Abstract: Background: Nutrition plays an important role in the aging process. Adherence to the Mediterranean diet (MedDiet) has been shown to be associated with lower rates of diseases. Cognitive status seems to be strongly interrelated with physical well-being, so that one influences the other. Physical performance measures are not only associated with clinical and subclinical age-related modifications, but are also able to predict disability, institutionalization, and mortality. 

Objective: To evaluate prospectively the associations between Mediterranean-Style Dietary Pattern Score (MSDPS), clinical characteristics, and cognition of the population sample of The TREVISO LONGEVA (TRELONG) Study, in Treviso, Italy. 

Methods: Global cognition, physical performance measures, MSDPS, and other clinical features were detected in 2010 in 82 men and 108 women. These characteristics were evaluated in relation to the physical performance measures identified 3.8 years later in 2013 in the same subjects, using a semantic connectivity map, through Auto-CM system, to grasp further and non-linear associations between variables which might remain, otherwise, undetected. Results: The Auto-CM system’s map shows a close association between better levels of global cognition and MSDPS in 2010 and higher physical performance in 2013. On the other hand, worse levels of global cognition and MSDPS in 2010 are associated with lower physical performance in 2013. 

Conclusion: The prevention models for successful aging may benefit from integrated programs that include cognitive, physical, and dietary interventions, since these aspects are mutually interrelated.


Titolo: Urban – Rural dwellers’ well-being determinants: When the city size matters. The case of Italy (2019)

Autore: Federica Viganó (a), Enzo Grossi (b), Giorgio Tavano Blessi (c)

Info: In press on City, Culture and Society



In the last 50 years, the worldwide trend concerning urbanization has been accompanied by the rural exodus toward urban and me- tropolitan areas. As mentioned from several studies and reports (United Nations, 2006 and 2010; Sørensen 2014; Lenzi & Perrucca, 2016), the percentage of those living in urban context rose over the 50% of the worldwide population, a percentage that reached almost the 75% within EU border.
The reason behind the growing interest in setting up in urban spaces is related to a wide range of direct influences and positive externalities generated by these areas on individual development, in comparison to rural ones. According to the literature on agglomeration economies, cities and urban areas are linked to benefits like higher productivity and wages, more learning opportunities and exchanges, higher rate of in- novation and creativity, more public services or other aspects that might positively influence individuals‘ development. If, on the one side, cities have become a major attractor for human development, on the other side this dynamic have also negative counterparts connected with different elements, the increased city size, the higher costs of living, the higher environmental costs (pollution or congestion), potential social conflicts. All these elements are threatening the individuals’ develop- ment, playing a role in choosing a place to live and work.
Starting from the 80s’ a large number of contributes concentrated on the perception of the individual quality of life within urban and rural contexts. Focusing the attention on the most economically developed countries, specifically in Europe, the quality of life has been increasing over the time when living in urban surroundings, this when considering both, subjective and objective well-being data. The gap between rural and urban in favor of urban areas can be explained with a lower level of opportunities in terms of e.g. access to public services, lower individual income, less employment opportunities, lower level of education and critical transport. If, at a first sight, it can be observed that conurbation, provides higher advantages in urban contexts, the size of those (vil- lages, town, cities and metropolises) matters in relation to the life sa- tisfaction, particularly in those realms not related to objective indicators such as education or income, but to subjective ones such as individual evaluation of their life or perceived quality of the environ- ment where they live. Towns and villages appear to be keener in sup- plying relational net and collaboration between residents than cities; a community feeling and a stronger social cohesion in these contexts brings toward a positive perception of individual well-being. Moreover, another aspect that might positively affect individual well-being it is the closeness to the natural environment, more frequent in small cities, town and rural areas in comparison with large cities and metropolitan areas. It is widely reported that living close to a natural space and using it for leisure activities promote a greater contribution to both physical and psychological individual well-being. Additional elements appear to be determinant such as the cultural supply, participation to voluntary, and community activities, which may prompt the activation of biolo- gical effects in individual and thus foster individual well-being.
The article aims to investigate the difference of individual psycho- logical well-being provided by living in rural and urban contexts, by enquiring the possible determinants related to both objective and sub- jective aspects. To this end, a cross-sectional survey was undertaken in the autumn of 2010 on a statistical representative sample (1500 polled) of residents living in both urban and rural areas in Italy. The survey has been modeled on the PGWBI (Psychological General Well-Being Index), an instrument specifically targeted to measure individual subjective well-being, used for the evaluation of the impact of different subjective well-being determinants. The questionnaire gathered a bounce of the main socio-demographic characteristics such as gender, age, education, income, diseases, employment, and civil status, which are listed as major objective well-being determinants in the well-being literature. Furthermore, information concerning other possible determinants re- lated to subjective dimension such as social and community involve- ment, cultural and leisure participation, sport activities, have been collected in order to provide a much comprehensive understanding of the influence of the different determinants on individual subjective well-being in relation to the size scale (urban vs. rural).


a) Freie Universität Bozen – Libera Università di Bolzano
b) University of Bologna and Villa Santa Maria Institute, Tavernerio, Italy
c) Free University of Bolzano, IULM University, Milan, Italy


Titolo: The “MS-ROM/IFAST” Model, a Novel Parallel Nonlinear EEG Analysis Technique, Distinguishes ASD Subjects From Children Affected With Other Neuropsychiatric Disorders With High Degree of Accuracy (2019)

Autore: Enzo Grossi1, Massimo Buscema2, 3, Francesca Della Torre2, Ronald J Swatzyna4

Info: Clinical EEG and Neuroscience


Background and Objective. 

In a previous study, we showed a new EEG processing methodology called Multi-Scale Ranked Organizing Map/Implicit Function As Squashing Time (MS-ROM/IFAST) performing an almost perfect distinction between computerized EEG of Italian children with autism spectrum disorder (ASD) and typically developing children. In this study, we assessed this system in distinguishing ASD subjects from children affected with other neuropsychiatric disorders (NPD). 
At a psychiatric practice in Texas, 20 children diagnosed with ASD and 20 children diagnosed with NPD were entered into the study. Continuous segments of artifact-free EEG data lasting 10 minutes were entered in MS-ROM/IFAST. From the new variables created by MS-ROM/IFAST, only 12 has been selected according to a correlation criterion. The selected features represent the input on which supervised machine learning systems (MLS) acted as blind classifiers. 
The overall predictive capability in distinguishing ASD from other NPD cases ranged from 93% to 97.5%. The results were confirmed in further experiments in which Italian and US data have been combined. In this analysis, the best MLS reached 95.0% global accuracy in 1 out of 3 classes distinction (ASD, NPD, controls). This study demonstrates the value of EEG processing with advanced MLS in the differential diagnosis between ASD and NPD cases. The results were not affected by age, ethnicity and technicalities of EEG acquisition, confirming the existence of a specific EEG signature in ASD cases. To further support these findings, it was decided to test the behavior of already trained neural networks on 10 Italian very young ASD children (25-37 months). In this test, 9 out of 10 cases have been correctly recognized as ASD subjects in the best case. 
These results confirm the possibility of an early automatic autism detection based on standard EEG.

Notes: 1 - Villa Santa Maria Institute, Neuropsychiatric Rehabilitation Center, Autism Unit, Tavernerio (Como), Italy 2 - Semeion Research Centre of Sciences of Communication, Rome, Italy 3 - Department of Mathematical and Statistical Sciences, University of Colorado at Denver, CO, USA 4 - Tarnow Center for Self-Management, Houston, TX, USA

Titolo: Severe Bitter Taste Associated with Apremilast (2019)

Autore: G Damiani 1, 3 2, NL Bragazzi 4, E Grossi 5, S Petrou 6, D Radovanovic 7, M Rizzi 8, F Atzeni 9, P Sarzi-Puttini 10, P Santus 7, PD Pigatto 2, 3, C Franchi 2

Info: Dermatologic Therapy




1-Study Center of Young Dermatologists Italian Network (YDIN), GISED, Bergamo, Italy

2-Clinical Dermatology, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy

3-Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy

4-School of Public Health, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy

5-Villa Santa Maria Foundation, Tavernerio, Italy

6-St. George's University School of Medicine, Grenada, West Indies

7-Department of Biomedical and Clinicl, Sciences (DIBIC), University of Milan, Milan, Italy

8-Respiratory Unit "Luigi Sacco" University Hospital; ASST Fatebenefratelli-SaccoMilan, Italy

9-Rheumatology Unit, University of Messina, Italy 10-Rheumatology Unit, "Luigi Sacco" University Hospital; ASST Fatebenefratelli-Sacco, Milan, Italy

Titolo: Directional Relationship between Vitamin D Status and Prediabetes: a New Approach From Artificial Neural Network in a Cohort of Workers with Overweight-Obesity (2019)

Autore: a Luisella Vigna, b Amedea Silvia Tirelli, c Enzo Grossi, d Stefano Turolo, e Laura Tomaino, b Filomena Napolitano, f Massimo Buscema, a Luciano Riboldi

Info: Journal of the American College of Nutrition


Abstract: Objective 
Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and Vitamin D (25(OH)D) concentrations, strong evidence on the direction of causality between these factors is still lacking. This gap could 
be addressed by means of artificial neural networks (ANN) analysis 
Retrospective observational study was carried out by means of an innovative data mining analysis –known as auto-contractive map (AutoCM)-, and semantic mapping 
followed by Activation and Competition System on data of workers referring to an occupational-health outpatient clinic Parameters analyzed included weight, height, waist circumference, BMI, percentage of fat mass, glucose, insulin, HbA1c, creatinine, total cholesterol, low and high density lipoprotein, triglycerides, uric acid, fibrinogen, homocysteine, CRP, diastolic and systolic blood pressure, and 25(OH)D. 
The study included 309 workers. Of these 23.6% were overweight or obese with rates of I, II and III level-obesity, respectively of 40.5%, 23.3% and 12.6%. All mean biochemical values were in normal range, except for T-Chol, HDL, LDL, CRP, and 
25(OH)D. HbAC1 was between 39-46 mmol/mol in 51.78%. 25(OH)D levels were sufficient in only 12.6%. Highest inverse correlation for hyperglycemia onset was with BMI and waste circumference, suggesting a protective role of 25(OH)D against their increase. Auto- CM processing and the semantic map evidenced direct association of 25(OH)D with high link strength (0.99) to low CRP levels and low HDL levels. Low 25(OH)D lead to changes in glucose which affected metabolic syndrome biomarkers, first of which HOMA index and blood glucose insulin, but not 25(OH)D. 
The use of ANN suggests a key role of 25(OH)D respect to all considered metabolic parameters in the development of diabetes and evidences a causation between low 25(OH)D and high glucose concentrations.


a Department of Preventive Medicine, Occupational Health Unit, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy

b Department of Clinical Chemistry and Microbiology, Bacteriology and Virology Units; Ospedale Maggiore Policlinico, Milan, ITALY

c Villa Santa Maria Foundation, Tavernerio, Italy

d Pediatric Nephrology & Dialysis, Milano Fondazione IRCCS Cà Grande Ospedale Maggiore Policlinico, University of Milan, 20122 Milan, Italy

e Pediatric Intermediate Care Unit, Department of Clinical and Community Health Sciences (DISCCO), Fondazione IRCCS Ospedale Cà Granda-Ospedale Maggiore Policlinico, University of Milan, 20122 Milan, Italy

f Semeion Research Centre of Sciences of Communication, Rome, Italy and University of Colorado, Denver, CO, USA

Titolo: Motor skills as moderators of core symptoms in Autism Spectrum Disorders: preliminary data from an exploratory analysis with Artificial Neural Networks (2018)

Autore: Francesca Fulceri 1, Enzo Grossi 2, Annarita Contaldo 1, Antonio Narzisi 1, Fabio Apicella 1, Ilaria Parrini 1, Raffaella Tancredi 1, Sara Calderoni 1, 3*, Filippo Muratori 1, 3

Info: Frontiers


Motor disturbances have been widely observed in children with autism spectrum disorder (ASD), and motor problems are currently reported as associated features supporting the diagnosis of ASD in the current Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Studies on this issue reported disturbances in different motor domains, including both gross and fine motor areas as well as coordination, postural control, and standing balance. However, they failed to clearly state whether motor impairments are related to demographical and developmental features of ASD. Both the different methodological approaches assessing motor skills and the heterogeneity in clinical features of participants analyzed have been implicated as contributors to variance in findings. However, the non-linearity of the relationships between variables may account for the inability of the traditional analysis to grasp the core problem suggesting that the “single symptom approach analysis” should be overcome.
Artificial neural networks (ANNs) are computational adaptive systems inspired by the functioning processes of the human brain particularly adapted to solving non-linear problems. This study aimed to apply the ANNs to reveal the entire spectrum of the relationship between motor skills and clinical variables. 32 male children with ASD [mean age: 48.5 months (SD: 8.8); age range: 30-60 months] were recruited in a tertiary care university hospital. A multidisciplinary comprehensive diagnostic evaluation was associated with a standardized assessment battery for motor skills, the Peabody Developmental Motor Scale-Second Edition.
Exploratory analyses were performed through the ANNs. The findings revealed that poor motor skills were a common clinical feature of preschoolers with ASD, relating both to the high level of repetitive behaviors and to the low level of expressive language. Moreover, unobvious trends among motor, cognitive and social skills have been detected.
In conclusion, motor abnormalities in preschoolers with ASD were widespread, and the degree of impairment may inform clinicians about the severity of ASD core symptoms. Understanding motor disturbances in children with ASD may be relevant to clarify neurobiological basis and ultimately to guide the development of tailored treatments.


1 Fondazione Stella Maris (IRCCS), Italy,
2 Autism Research Unit, Villa Santa Maria Scs, Italy,
3 Università degli Studi di Pisa, Italy

Titolo: Artificial neural networks help to identify disease subsets and to predict lymphoma in primary Sjögren’s syndrome (2018)

Autore: Chiara Baldini1, Francesco Ferro1, Nicoletta Luciano1, Stefano Bombardieri1, Enzo Grossi2

Info: Clinical and Experimental Rheumatology 2018, 36 (Suppl. 112): S137-S144



Abstract: Objective. Primary Sjögren’s syndrome (pSS) is a complex chronic systemic disorder, for which specific and effective therapeutic interventions are still lacking. In this era of precision medicine, there is a clear need for a better definition of disease phenotypes to foster the research of novel specific biomarkers and new therapeutic targets. 
The main objectives of this work are:1) to compare Auto Contractive Map (AutoCM), a data mining tool based on an artificial neural network (ANN) versus conventional Principal Component Analysis (PCA) in discriminating different pSS subsets and 2) to specifically focus on variables predictive of MALT-NHL development, assessing the previsional gain of the predictive models developed. 
Methods. Out of a historic cohort of 850 patients, we selected 542 cases of pSS fulfilling the AECG criteria 2002. Thirty-seven variables were analysed including: patient demographics, glandular symptoms, systemic features, biological abnormalities and MALT-NHLs. AutoCM was used to compute the association of strength of each variable with all other variables in the dataset. PCA was applied to the same data set. 
Results. Both PCA and AutoCM confirmed the associations between autoantibody positivity and several pSS clinical manifestations, highlighting the importance of serological biomarkers in pSS phenotyping. However, AutoCM allowed us to clearly distinguish pSS patients presenting with predominant glandular manifestations and no or mild extra-glandular features from those with a more severe clinical presentation. 
Out of 542 patients, we had 27 cases of MALT-NHLs. The AutoCM highlighted that, besides other traditional lymphoproliferative risk factors (i.e. salivary gland enlargement, low C4, leukocytopenia, cryoglobulins, monoclonal gammopathy, disease duration), rheumatoid factor was strongly associated to MALT-NHLs development. By applying data mining analysis, we obtained a predictive model characterised by a sensitivity of 92.5% and a specificity of 98%. If we restricted the analysis to the seven most significant variables, the sensitivity of the model was 96.2% and its specificity 96%. 
Conclusion. Our study has shed new light on the possibility of using novel tools to extract hidden, previously unknown and potentially useful information in complex diseases like pSS, facing the challenge of disease phenotyping as a prerequisite for discovering novel specific biomarkers and new therapeutic targets.

Notes: 1.Rheumatology Unit, University of Pisa

2.Villa Santa Maria Foundation, Tavernerio, Italy

Titolo: Artificial Neural Networks (ANNs) as a Reliable Tool for the Assessment of Fracture Risk in Postmenopausal Women (2018)

Autore: Gloria Bonaccorsi1, Carlo Cervellati2, Enzo Grossi3, Enrica Fila1, Leo Massari4, Nicola Veronese5, Francesco Pio Cafarelli6, Giuseppe Guglielmi6, 7*

Info: British Journal of Research ISSN 2394-3718



Abstract: Artificial neural networks (ANNs) are a computational tool, based on highly non-linear mathematics models with potential applications in the prediction of osteoporotic fractures. 
Therefore, the present study aimed to evaluate the potential of ANNs analysis in the prediction of bone fragility fractures in post-menopausal women. ANNs prognostic performance in identifying vertebral morphometric deformity was compared with that of the widely used tool FRAX® in a sample of 587 Caucasian postmenopausal women underwent densitometry and morphometric analyses for the detection of vertebral fractures. 
The analysis of areas under the curve (AUCs) showed that sensitivity for ANNs (74%) almost doubled that found for FRAX ® (38%), with the latter presenting a specificity higher than the proposed tool (96 vs. 77%). Overall, ANN-based analysis was able to highlight high-risk patients with a global higher accuracy (74%) compared to that obtained by FRAX (67%). 
In conclusion, our data showed that compared to WHO’s algorithm ANNs had higher sensitivity in identifying vertebral deformity, thus suggesting a “promising role” in the prediction of osteoporotic fracture in postmenopausal women. However, further studies on larger sample are needed to definitely establish the clinical reliability of ANNs.

Notes: 1.Department of Morphology, Surgery and Experimental Medicine, Menopause and Osteoporosis Centre, University of Ferrara, Via Boschetto 29, 44124, Ferrara, Italy

2.Department of Biomedical and Specialist Surgical Sciences, Section of Medical Biochemistry, Molecular Biology and Genetics, University of Ferrara, Via Borsari 46, 44121, Ferrara, Italy

3.Villa Santa Maria Foundation, Via IV Novembre, 22038 Tavernerio (CO), Italy

4.Department of Morphology, Surgery and Experimental Medicine, Section of Orthopedic Clinic, University of Ferrara, Via Aldo Moro 8, 44124, Cona, Ferrara, Italy

5.National Research Council, Neuroscience Institute, Aging Branch, via Giustiniani, 2, 35128, Padova, Italy

6.Department of Clinical and Experimental Medicine, Foggia University School of Medicine, Via L. Pinto, 1, Foggia, Italy

7.Department of Radiology, Scientific Institute Hospital “Casa Sollievo della Sofferenza”, San Giovanni Rotondo, Italy

Titolo: Plasma Fatty Acid Profile as Biomarker of Coronary Artery Disease: a Pilot Study Using Fourth Generation Artificial Neural Networks (2018)

Autore: E Dozio*, E Vianello*, E Grossi**, L Menicanti***, G Schmitz****, M M Corsi Romanelli*, *****

Info: Journal of Biological Regulators & Homeostatic Agents, Vol. 32, no. 4, 79-85 (2018)


Abstract: Many studies, focused on identifying new biomarkers for coronary artery disease (CAD) risk computation and monitoring, suggested a potential diagnostic role for fatty acids (FA). In the present study, we explored the potential diagnostic role of FA by using a data mining approach based on fourth generation artificial neural networks (ANN). Forty-one male subjects were enrolled. According to coronary angiography, 31 displayed CAD and 10 did not (non-CAD, control group). FA analysis was performed on plasma samples using a gas chromatography-mass spectrometry system and analyses were performed by an ANN method. The variables most closely related to CAD were low levels of alpha-linolenic acid, eicosapentaenoic acid, eicosatetraenoic and docosahexaenoic acids. High levels of 1,1-dimethoxyhexadecane, total dimethyl acetals and docosatetraenoic acid were related to non-CAD condition. This subset of variables, which were most closely correlated to the target diagnosis, achieved a consistent predictive rate. The average accuracy obtained was 76.5%, with 93% of sensitivity and 60% of specificity. The area under the ROC curve was equal to 0.79. In conclusion, our study highlighted the association between different plasma FA species, CAD and non-CAD conditions. The specific subset of variables could be of interest as a new diagnostic tool for CAD management.


Notes: *Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy

**Villa Santa Maria Institute, Tavernerio, Como, Italy

***Department of Cardiac Surgery, I.R.C.C.S. Policlinico San Donato, San Donato Milanese, Milan, Italy

****Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, Regensburg, Germany

*****Service of Laboratory Medicine 1-Clinical Pathology, I.R.C.C.S. Policlinico San Donato, San Donato Milanese, Milan, Italy

Titolo: Toe walking assessment in autism spectrum disorder subjects: a systematic review (2018)

Autore: Giulio Valagussa*,**, Luca Trentin*, Alessio Signori***, Enzo Grossi*

Info: Accepted by Autism Research


Abstract: There is increasing evidence that autism spectrum disorder (ASD) subjects have also motor impairments. Toe walking (TW) is a phenomenon that can be found in ASD subjects during gait, even if this condition was found not to be necessarily related only to walking, since these children often also stand and run on their tiptoes. Since persistent TW in ASD subjects may contribute to secondary shortening of the Achilles’s tendon, it becomes important to have an assessment tool and/or outcome measure for both the clinical and rehabilitative settings. The aim of this systematic review is to critically evaluate and describe the methods employed to assess toe-walking in ASD subjects. 
The systematic review protocol was previously registered on PROSPERO. We conducted an extensive literature search in PubMed, CINAHL, PsycINFO, The Cochrane Library, and Scopus databases. There were no restrictions on the types of study design eligible for inclusion. Ten studies were included in the systematic review. Risk of bias of the included studies was conducted using the following instruments depending on the study types: STROBE Statement, Cochrane risk of bias tool, and CARE checklist. Almost all the included studies (8/10) proposed a TTB assessment only during walking. Nine out of ten of the included studies assessed TTB using a qualitative methodology. 
The results evidenced the heterogeneity of qualitative methods and a lack of a structured quantitative test to assess toe walking 
in ASD subjects.

Notes: *Autism Research Unit, Villa Santa Maria Foundation, Tavernerio (CO), Italy

**School of Medicine and Surgery – University of Milano Bicocca, Milan, Italy

***Department of Health Sciences (DISSAL), Section of Biostatistics, University of Genoa, Genoa, Italy

Titolo: Magic Moments: Determinants of Stress Relief and Subjective Wellbeing from Visiting a Cultural Heritage Site (2018)

Autore: Enzo Grossi (1), Giorgio Tavano Blessi (2), Pier Luigi Sacco (2, 3, 4)

Info: Culture, Medicine and Psychiatry



Abstract: We provide an experimental evaluation of the impact of aesthetic experiences in terms of stress reduction (cortisol levels) and wellbeing increase. The test experience is a visit to the vault of the Sanctuary of Vicoforte, Italy. Data have been collected using a double step method. A structured interview in relation to the individual subjective well-being has been administered to a sample of 100 subjects. 
In addition, a sample of their saliva has been taken, and its cortisol level measured, before and after the experience, and likewise for momentary wellbeing measured on a Visual Analogous Scale. Subjects reported an average increase of 40% in wellbeing and a decrease of the 60% in the cortisol level. The recorded cortisol level values dropped on average well beyond the decrease normally associated to its circadian cycle. The modulating role of various variables has been appreciated, and profiling of the typical subjects who are wellbeing respondents/non-respondents and cortisol respondents/non-respondents has been carried out. 
We conclude that aesthetic experience seems to have a noticeable impact on individual physical and mental health. In both dominions, cultural participation intensity is significantly correlated to the response. The study underlines the potential of the arts and culture as a new platform for public health practices and new approaches to welfare policy design.

Notes: 1 Villa Santa Maria Institute, Tavernerio, Italy 2 IULM University, Milan, Italy 3 FBK-IRVAPP, Trento, Italy 4 Harvard University and MetaLAB (at) Harvard, Cambridge, MA, USA

Titolo: Determinants of metabolic syndrome in obese workers: gender differences in perceived job-related stress and in psychological characteristics identified using artificial neural networks (2018)

Autore: Luisella Vigna (1), Amelia Brunani (2), Agostino Brugnera (3), Enzo Grossi (4), Angelo Compare (3), Amedea S. Tirelli (5), Diana M. Conti (1), Gianna M. Agnelli (1), Lars L. Andersen (6, 7), Massimo Buscema (8, 9), Luciano Riboldi (1)

Info: Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity



Objective: The metabolic syndrome (MS) is a multifactorial disorder associated with a higher risk of developing cardiovascular diseases and type 2 diabetes. However, its pathophysiology and risk factors are still poorly understood. In this study, we investigated the associations among gender, psychosocial variables, job-related stress and the presence of MS in a cohort of obese Caucasian workers. 

Methods: A total of 210 outpatients (142 women, 68 men) from an occupational medicine service was enrolled in the study. Age, BMI, waist circumference, fasting glucose, blood pressure, triglycerides and HDL cholesterol were collected to define MS. In addition, we evaluated eating behaviors, depressive symptoms, and work-related stress. Data analyses were performed with an artificial neural network algorithm called Auto Semantic Connectivity Map (AutoCM), using all available variables. 

Results: MS was diagnosed in 54.4 and 33.1% of the men and women, respectively. AutoCM evidenced gender-specific clusters associated with the presence or absence of MS. Men with a moderate occupational physical activity, obesity, older age and higher levels of decision-making freedom at work were more likely to have a diagnosis of MS than women. Women with lower levels of decision-making freedom, and higher levels of psychological demands and social support at work had a lower incidence of MS but showed higher levels of binge eating and depressive symptomatology. 

Conclusion: We found a complex gender-related association between MS, psychosocial risk factors and occupational determinants. The use of these information in surveillance workplace programs might prevent the onset of MS and decrease the chance of negative long-term outcomes. 

Level of evidence Level V, observational study.


Notes: 1 Department of Preventive Medicine, Occupational Health Unit, Clinica del Lavoro Luigi Devoto, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico 2 Rehabilitation Medicine, IRCCS Istituto Auxologico Italiano, S. Giuseppe Hospital, Verbania, Italy 3 Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy 4 Villa Santa Maria Foundation, Tavernerio, Italy 5 Laboratory of Clinical Chemistry and Microbiology, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy 6 National Research Centre for the Working Environment, Copenhagen, Denmark 7 Sport Sciences, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark 8 Semeion Research Centre of Sciences of Communication, Rome, Italy 9 University of Colorado, Denver, CO, USA

Titolo: Current Knowledge on Endocrine Disrupting Chemicals (Edcs) from Animal Biology to Humans, From Pregnancy to Adulthood: Highlights from A National Italian Meeting (2018)

Autore: Maria Elisabeth Street *, Sabrina Angelini, Sergio Bernasconi, Ernesto Burgio, Alessandra Cassio, Cecilia Catellani, Francesca Cirillo, Annalisa Deodati, Enrica Fabbrizi, Vassilios Fanos, Giancarlo Gargano, Enzo Grossi, Lorenzo Iughetti, Pietro Lazzeroni

Info: International Journal of Molecular Sciences


Wildlife has often presented and suggested the effects of endocrine disrupting chemicals (EDCs). Animal studies have given us an important opportunity to understand the mechanisms of action of many chemicals on the endocrine system and on neurodevelopment and behaviour, and to evaluate the effects of doses, time and duration of exposure. Although results are sometimes conflicting because of confounding factors, epidemiological studies in humans suggest effects of EDCs on prenatal growth, thyroid function, glucose metabolism and obesity, puberty, fertility, and on carcinogenesis mainly through epigenetic mechanisms. This manuscript reviews the reports of a multidisciplinary national meeting on this topic. 

Titolo: Pregnancy risk factors related to autism: an Italian case-control study in mothers of children with ASD, their siblings and of typically developing children (2018)

Autore: Enzo Grossi, Lucia Migliore, Filippo Muratori

Info: Journal of Developmental Origins of Health and Disease, 23 April 2018


This study, carried out in two Italian Institutions, assesses the frequency of 27 potential autism risk factors related to pregnancy and peri- and postnatal periods by interviewing mothers who had children with autism, children with autism and one or two typically developing siblings, or only typically developing children. The clinical sample included three case groups: 73 children and adolescents with autism (Group A), 35 children and adolescents with autism (Group A1) having 45 siblings (Group B) and 96 typically developing children (Group C) matched for gender and age. Twenty-five out of 27 of risk factors presented a higher frequency in Group A in comparison with Group C and for nine of them a statistically significant difference was found. Twenty-one out of 27 of risk factors presented a higher frequency in Group A in comparison with Group B. A higher prevalence of environmental risk factors was observed in 11 risk factors in the Group A1 in comparison with Group B and for nine of them an odds ratio higher than 1.5 was found. For 13 factors there was a progressive increase in frequency going from Group C, B and A and a statistically higher prevalence of the mean number of stressful events per pregnancy was recorded in Group A when compared with Groups B and C. The results suggest that environmental, incidental phenomena and stressful life events can influence pregnancy outcome in predisposed subjects, pointing out a possible threshold effect in women who are predisposed to have suboptimal pregnancies.

Titolo: The role of carboxy-terminal cross-linking telopeptide of type I collagen, dual x-ray absorptiometry bone strain and Romberg test in a new osteoporotic fracture risk evaluation: A proposal from an observational study. (2018)

Autore: Fabio M Ulivieri, Luca P Piodi, Enzo Grossi, Luca Rinaudo, Carmelo Messina, Anna P Tassi, Marcello Filopanti, Anna Tirelli, Francesco Sardanelli

Info: Plos One January 5, 2018



The consolidated way of diagnosing and treating osteoporosis in order to prevent fragility fractures has recently been questioned by some papers, which complained of overdiagnosis and consequent overtreatment of this pathology with underestimating other causes of the fragility fractures, like falls. A new clinical approach is proposed for identifying the subgroup of patients prone to fragility fractures. This retrospective observational study was conducted from January to June 2015 at the Nuclear Medicine-Bone Metabolic Unit of the of the Fondazione IRCCS Ca' Granda, Milan, Italy. An Italian population of 125 consecutive postmenopausal women was investigated for bone quantity and bone quality. Patients with neurological diseases regarding balance and vestibular dysfunction, sarcopenia, past or current history of diseases and use of drugs known to affect bone metabolism were excluded. Dual X-ray absorptiometry was used to assess bone quantity (bone mineral density) and bone quality (trabecular bone score and bone strain). Biochemical markers of bone turnover (type I collagen carboxy-terminal telopeptide, alkaline phosphatase, vitamin D) have been measured. Morphometric fractures have been searched by spine radiography. Balance was evaluated by the Romberg test. The data were evaluated with the neural network analysis using the Auto Contractive Map algorithm. The resulting semantic map shows the Minimal Spanning Tree and the Maximally Regular Graph of the interrelations between bone status parameters, balance conditions and fractures of the studied population. A low fracture risk seems to be related to a low carboxy-terminal cross-linking telopeptide of type I collagen level, whereas a positive Romberg test, together with compromised bone trabecular microarchitecture DXA parameters, appears to be strictly connected with fragility fractures. A simple assessment of the risk of fragility fracture is proposed in order to identify those frail patients at risk for osteoporotic fractures, who may have the best benefit from a pharmacological and physiotherapeutic approach.

Titolo: The Role of Trabecular Bone Score and Hip Geometry in Thalassemia Major: A Neural Network Analysis (2017)

Autore: Marina Baldini, Enzo Grossi, Maria Domenica Cappellini, Carmelo Messina, Alessia Marcon, Elena Cassinerio, Lorena Airaghi, Giuseppe Guglielmi and Fabio Massimo Ulivieri*

Info: British Journal of Research ISSN 2394-3718


Osteopathy in thalassemia is a very heterogeneous condition; severity depends on multiple factors, interacting through nonlinear mechanisms. Classic statistics have limitations when applied to the study of such highly complex relationships. Currently, an alternative approach of analysis is represented by the artificial neural networks (ANNs), powerful mathematical tools, increasingly applied to analyze multifactorial databases, as considered more appropriate than classic statistics. We adopted this specialized mathematical method to 76 thalassemia major (TM) patients. In all of them dual energy X-ray absorptiometry (DXA) was performed to measure bone mineral density, and two recent developments were included: trabecular bone score, evaluating bone microarchitecture, and hip structural analysis, evaluating hip geometry. The relationships between bone status and endocrine, hematologic, and clinical parameters were investigated. Using a particular ANN (Auto Contractive Map algorithm), the strength of inter-variable association was defined and a connectivity map generated, visually representing the main connections among the entered variables. Iron status indices (ferritin, liver iron concentration) emerged as the most important variables, dividing the map into two sectors, with parameters indicating satisfactory bone condition in the upper, those indicating poor condition in the lower, near the variable “fractures”. The Auto Contractive Map highlighted the key role of bone quantity, bone geometry, and microarchitecture in defining thalassemic bone condition. Among numerous available indices, high femoral bone mineral density and low cross-sectional moment of inertia emerged as the gold standard to classify thalassemic patients for prognostic and therapeutic purposes.

Titolo: Role of the Human Breast Milk-Associated Microbiota on the Newborns’ Immune System: A Mini Review (2017)

Autore: Marco Toscano, Roberta De Grandi, Enzo Grossi and Lorenzo Drago*

Info: Frontiers in Microbiology, 25 October 2017



The human milk is a rich and complete nourishment that is essential for the correct development of the infant’s organism (Ballard and Morrow, 2013). The first milk produced by mothers after the delivery is called colostrum and it is biochemically and functionally different from the mature milk (Castellote et al., 2011). Colostrum, indeed, contains high concentration of lactoferrin, Immunoglobulin A (IgA), leukocytes and specific developmental factors, and a low amount of lactose, potassium and calcium, underlying its immunological functions rather than nutritional (Kulski and Hartmann, 1981; Pang and Hartmann, 2007). From 5 days to 2 weeks postpartum, there is the production of transitional milk which shares some characteristics of colostrum, although its main function is to support newborns at nutritional level (Henderson et al., 2008; Nommsen-Rivers et al., 2012). Finally, 2 weeks after the delivery the milk can be considered as mature and its composition tends to be stable over the time, even if slight variations can occur during lactation (Ballard and Morrow, 2013). The main components of human milk are: (i) macronutrients, such as protein, fat and lactose, which concentration depends on the stage of lactation and maternal characteristics; (ii) micronutrients, including vitamins A, B1, B2, B12 and D that vary in human milk in relation to maternal diet and body stores; (iii) growth factor, which are strongly active on the endocrine system, nervous system, vasculature and intestinal tract; (iv) immunological factors, which are essential to defend the newborn from inflammation and infection, and for this reason, the early milk is rich in immune components that can support infants in the first delicate stages of their life; (v) the microbiota, which comprises more than 200 different bacterial species with a pivotal role in the formation of the newborn’s first gut microbiota (Drago et al., 2017). The aim of the present Mini Review is to highlight the specific and fundamental role of human milk-associated bacteria in modulating and influencing the newborns’ immune system during their life.

Titolo: Impact of delivery mode on the colostrum microbiota composition (2017)

Autore: Marco Toscano, Roberta De Grandi, Diego Giampietro Peroni, Enzo Grossi, Valentina Facchin, Pasquale Comberiati and Lorenzo Drago.

Info: BMC Microbiology (2017) 17:205



Background Breast milk is a rich nutrient with a temporally dynamic nature. In particular, numerous alterations in the nutritional, immunological and microbiological content occur during the transition from colostrum to mature milk. The objective of our study was to evaluate the potential impact of delivery mode on the microbiota of colostrum, at both the quantitative and qualitative levels (bacterial abundance and microbiota network). Methods Twenty-nine Italian mothers (15 vaginal deliveries vs 14 Cesarean sections) were enrolled in the study. The microbiota of colostrum samples was analyzed by next generation sequencing (Ion Torrent Personal Genome Machine). The colostrum microbiota network associated with Cesarean section and vaginal delivery was evaluated by means of the Auto Contractive Map (AutoCM), a mathematical methodology based on Artificial Neural Network (ANN) architecture. Results Numerous differences between Cesarean section and vaginal delivery colostrum were observed. Vaginal delivery colostrum had a significant lower abundance of Pseudomonas spp., Staphylococcus spp. and Prevotella spp. when compared to Cesarean section colostrum samples. Furthermore, the mode of delivery had a strong influence on the microbiota network, as Cesarean section colostrum showed a higher number of bacterial hubs if compared to vaginal delivery, sharing only 5 hubs. Interestingly, the colostrum of mothers who had a Cesarean section was richer in environmental bacteria than mothers who underwent vaginal delivery. Finally, both Cesarean section and vaginal delivery colostrum contained a greater number of anaerobic bacteria genera. Conclusions The mode of delivery had a large impact on the microbiota composition of colostrum. Further studies are needed to better define the meaning of the differences we observed between Cesarean section and vaginal delivery colostrum microbiota.

Titolo: Effects of Improvisational Music Therapy vs Enhanced Standard Care on Symptom Severity Among Children With Autism Spectrum Disorder (2017)

Autore: Łucja Bieleninik (1), Monika Geretsegger (1), Karin Mössler (1), Jörg Assmus (1), Grace Thompson (2), Gustavo Gattino (3,4), Cochavit Elefant (5), Tali Gottfried (6), Roberta Igliozzi (7), Filippo Muratori (7,8), Ferdinando Suvini (7), Jinah Kim (9), Mike

Info: JAMA - The Journal of the American Medical Association, 2017; 318(6): 525-535



Importance Music therapy may facilitate skills in areas affected by autism spectrum disorder (ASD), such as social interaction and communication. Objective To evaluate effects of improvisational music therapy on generalized social communication skills of children with ASD. Design, Setting, and Participants Assessor-blinded, randomized clinical trial, conducted in 9 countries and enrolling children aged 4 to 7 years with ASD. Children were recruited from November 2011 to November 2015, with follow-up between January 2012 and November 2016. Interventions Enhanced standard care (n = 182) vs enhanced standard care plus improvisational music therapy (n = 182), allocated in a 1:1 ratio. Enhanced standard care consisted of usual care as locally available plus parent counseling to discuss parents’ concerns and provide information about ASD. In improvisational music therapy, trained music therapists sang or played music with each child, attuned and adapted to the child’s focus of attention, to help children develop affect sharing and joint attention. Main Outcomes and Measures The primary outcome was symptom severity over 5 months, based on the Autism Diagnostic Observation Schedule (ADOS), social affect domain (range, 0-27; higher scores indicate greater severity; minimal clinically important difference, 1). Prespecified secondary outcomes included parent-rated social responsiveness. All outcomes were also assessed at 2 and 12 months. Results Among 364 participants randomized (mean age, 5.4 years; 83% boys), 314 (86%) completed the primary end point and 290 (80%) completed the last end point. Over 5 months, participants assigned to music therapy received a median of 19 music therapy, 3 parent counseling, and 36 other therapy sessions, compared with 3 parent counseling and 45 other therapy sessions for those assigned to enhanced standard care. From baseline to 5 months, mean ADOS social affect scores estimated by linear mixed-effects models decreased from 14.08 to 13.23 in the music therapy group and from 13.49 to 12.58 in the standard care group (mean difference, 0.06 [95% CI, −0.70 to 0.81]; P = .88), with no significant difference in improvement. Of 20 exploratory secondary outcomes, 17 showed no significant difference. Conclusions and Relevance Among children with autism spectrum disorder, improvisational music therapy, compared with enhanced standard care, resulted in no significant difference in symptom severity based on the ADOS social affect domain over 5 months. These findings do not support the use of improvisational music therapy for symptom reduction in children with autism spectrum disorder. Trial Registration Identifier: ISRCTN78923965

Titolo: Diagnosis of autism through EEG processed by novel artificial adaptive systems: a proof of concept pilot study (2017)

Autore: Enzo Grossi, Chiara Olivieri & Massimo Buscema

Info: Computer Methods and Programs in Biomedicine 142 (2017) 73–79



Background MS-ROM/I-FAST is a new, complex algorithm used for blind classification of the original EEG tracing of each subject. This is accomplished by recording and analyzing a few minutes of their EEG without artifacts removing. A proof of concept study well equipped with cross-validation techniques previously published showed accuracy values ranging from 94%-98% in discerning subjects with Mild Cognitive Impairment and/or Alzheimer’s Disease from healthy elderly people. Since ASD is known to show deviant patterns in simple resting state EEG recordings, this supports the idea that the atypical organization of the cerebral cortex present in autism should result in an EEG signature open to detection through potent analytical systems like Artificial Neural networks (ANNs.) Aim of the study The aim of the study is to assess how effective this methodology distinguishes ADS subjects from typically developing ones. Methods Fifteen definite ASD subjects (13 males; 2 females; age range 7-14; mean value = 10.4) and ten typically developing subjects ( 4 males; 6 females; age range 7-12; mean value 9.2 ) were included in the study. Patients received independent Autism diagnoses according to DSM-V criteria, then subsequently confirmed by a qualified psychiatrist at Villa Santa Maria, where the patients reside, using the ADOS scale (overall severity score had a range from a minimum of 4 to a maximum of 10 points, average = 7.9). No autistic child was affected by genetic conditions and/or cerebral malformations documented by neuroimaging and epilepsy. A continuous segment of artefact-free EEG data lasting 60 s was used to compute multi-scale entropy values and for subsequent analyses. A Multi-scale ranked organizing map (MS-ROM), based on the self-organizing map (SOM) neural network, coupled with the TWIST system (an evolutionary system able to select predictive features) created an invariant features vector input of EEG on which supervised machine learning systems acted as blind classifiers. Results After MS-ROM/I-FAST preprocessing, the overall predictive capability of different machine learning systems in deciphering autistic cases from normal ones resulted extremely good reaching also perfect distinction with specific classifiers. These results were obtained at different times in separate experiments performed on the same training and testing subsets. The similarities among the ANN weight matrixes measured with apposite algorithms were not affected by the age of the subjects. This suggests that the ANNs do not read age-related EEG patterns, but rather invariant features related to the brain’s underlying disconnection signature. Conclusion This pilot study seems to open up new avenues for the development of non-invasive diagnostic testing for the early detection of ASD.rumors and disappointments at media level, while the third problem is specifically felt by Pharmaceutical Companies and Institutional Review Boards releasing the clearance for first in man trials.

Titolo: Assessment of presentation patterns, clinical severity and sensorial mechanism of tip-toe behavior in ASD children: a cohort observational study (2017)

Autore: Giulio Valagussa, Luca Trentin, Valeria Balatti, Enzo Grossi

Info: Autism Research 2017



We assessed presentation patterns, clinical severity and sensorial mechanism of tip-toe behavior (TTB ), more commonly known as toe walking , in a cohort of ASD subjects in two studies. The first study includes 69 consecutive ASD subjects (57 males, 12 females, mean age = 14 years – 3.7 SD) under observation at our institute. A therapist assessed the presence of TTB during standing, walking and running using direct observation and an interview of the main caregiver living with the children was conducted. The prevalence of TTB was 32%. We found three clinical presentation patterns of TTB: 1) present while standing, walking and running (45.5%), 2) present when walking and running (18.4%) or 3) present only when running (36.4%). TTB subjects were more frequently non-verbal than subjects without TTB (72.7% vs 44.6% - p= 0.03). On the other hand, no significant difference in ASD severity according to the ADOS scale was found between TTB and non-TTB subjects. In the second study, carried out in a subgroup of 14 ASD subjects (7 TTB and 7 non-TTB), we show that acting upon a soft floor surface (foam mats) made a substantial difference in reducing the phenomenon. TTB is a frequent phenomenon in individuals with ASD and may occur in three mutually exclusive modalities, which ultimately defines what is commonly known as toe walking. The presence of TTB seems correlated to the severity of language delay. Foot contact on soft surfaces reduces TTB both during static and/or dynamic tasks. Further evaluation is needed to clarify the potential pathophysiological implications of this phenomenon.

Titolo: Inequalities in access to biological treatments for psoriasis: Results from the Italian Psocare Registry (2016)

Autore: Luigi Naldi, Simone Cazzaniga, Marco Di Mercurio, Enzo Grossi, Antonio Addis

Info: British Journal of Dermatology Accepted manuscript online: 14 December 2016



Background: Limited evidence is available on the impact of socioeconomic factors in drug prescriptions for psoriasis. Objectives: To investigate factors influencing prescription of conventional versus biological treatment for psoriatic patients, based on the Psocare registry with a special focus on socioeconomic factors. Methods: This was a cross-sectional study evaluating the baseline data of patients included in the Italian Psocare Registry. All of the consecutive adult patients with a diagnosis of chronic plaque psoriasis (Ps) or psoriatic arthritis and who were prescribed a systemic treatment for Ps at the participating centres were included in this study. Univariate and multivariate analyses of the baseline factors associated with a biologics prescription were performed. Results: From September 2005 to September 2009, 12,838 patients were identified. A multivariate analysis revealed that, among other factors, completing a level of education higher than lower secondary school and being employed as a manager or a professional were independent factors associated with a biologics prescription at entry in the registry. Additional analyses on the association between these two variables and a severe Ps condition (i.e., psoriasis area and severity index [PASI] score > 20) revealed a significant increasing trend of severe disease towards lower educational attainment, while unemployed patients were more likely to have a more severe condition as compared to the other categories of workers. Conclusions: We documented inequalities of drug prescriptions for Ps in Italy, with a trend towards a higher frequency of prescription for more expensive biologics in higher socio-economic sectors of the population.

Titolo: Monitoring food selectivity in a group of children with autism spectrum disorders with direct observation: a comparative observational feasibility study (2016)

Autore: Enzo Grossi, Sara Melli, Marina Norsi

Info: Scientific Times Journal of Paediatrics, Volume 1 Issue 1



Food selectivity is a fairly common issue with children who have an autism spectrum disorder (ASD)’. Few studies based on direct observation of feeding behavior in youths with ASD are available in the literature.In this study we explore and monitor food selectivity by directly observing eating behaviors with a standardized protocol in a sample of10 children and adolescents with ASD residing at our rehabilitation institution comparing to 10 children and adolescents affected by mild-moderate mental retardation residing in the same institution. Carefully detailed food records for a 20 day period were analyzed.Subjects with ASD resulted significantly more selective than controls (lunch p = 0.016, dinner p = 0.042). Furthermore, the observed subjects with ASD had a bimodal distribution of weight percentiles ( 6 kids were < 25 % weight percentile. 2 kids > 75% weight percentile) while the control group revealed normal body weight distribution. We found a negative correlation between: food selectivity and duration of stay ( R = - 0.5848 ), as well as food selectivity and age ( R = - 0.6437 ), but a positive correlation between food refusal and disease severity measured with Autism Diagnostic Observation Scale (ADOS- 2) ( R = 0.4441 ). Our data confirm the feasibility of a direct observation monitoring protocol for feeding behavior importance of food selectivity in subjects affected by ASD. Younger children are more selective than older ones and the duration of institutional residency seems to positively impact this behavior pattern. Lastly, the severity of ASD symptoms resulted directly proportional to nutritional fixation severity

Titolo: SPSd - A New Rating Scale for Psychological Distress in Adolescence: a Validation Study on a Nationwide Italian Cohort Of 31,661 Adolescents (2016)

Autore: Enzo Grossi, Gabriele Manella, Giovanni Pieretti, Bruno Genetti, Milena Sperotto, Paolo Vian

Info: Psychological Distress, Nova Science Publishers Inc 2016



In this paper we present a new rating scale for adolescent psychological distress based on an Italian population study carried out in a cohort of 31,661 adolescents, and analyzed with Rasch Analysis in addition to the traditional tests. The Italian epidemiological survey on drug use in the school population was conducted by the Department of Anti Drug Policies in the first six months of 2014. It was based on a methodology of the European Monitoring Centre for Drugs and the Drug Addiction (EMCDDA - European School Survey Project on Alcohol and Other Drugs - ESPAD). The questionnaire and the survey procedures were taken from ESPAD and adjusted modified in order to address the specific characteristics of to the Italian school system. The total population sample consisted on 31,661 15-19 years old students who attended Italian public high schools. Among the items in the source scale we have selected nine items belonging to three dominions (Energy, Emotional Stability, Impulsivity and Risk-Taking) from which we expected the maximal indirect relation to wellbeing state and therefore as complement, to distress. To evaluate the psychometric properties of distress scale we carried out the homogeneity analysis or internal consistency of the scale, using the Cronbach's alpha coefficient, and analysis of the validity of the scale, using the Gamma coefficient of Goodman and Kruskal - index rank correlation. The data dimensionality was explored using Rasch Analysis and factor analysis. The Cronbach's alpha obtained considering all items was to 0.694, making it quite satisfactory and meeting the standards criteria of acceptability. Rasch analysis confirmed the items validity and that the items distribution remains in the area of the tolerance defined. A very good distribution emerges with a complete absorption of possible values along the scale range; neither ceiling or floor effect is observed. Whereas the level of distress measured by the scale is higher the lower the score detected, it is observed a significantly higher level of distress in females than in males (52.59 vs 59.61). For all psychotropic substances analyzed,significantly higher levels of distress in consumers than non-consumers have been found. In addition,the level of distress as measured by the scale appears to increase going from users of “soft” drugs to users of “hard” drugs: - 57.18 is the mean value obtained in the distress scale from the group of students who say they have never used any illegal drug; - 53.00 is the mean value obtained in the distress scale from the group of students who report use of cannabis at least once in their life; - 50.18 is the mean value obtained in the distress scale from the group of students who report use of cocaine at least once in their life; - 47.95 is the mean value obtained in the distress scale from the group of students who report use of heroin at least once in their life. This survey has detected several factors/conditions associated to the use of substances, which can be considered a reliable proxy of psychological distress: family background seems to be very important as well as the relationship with parents; this emerged as regards the presence of rules on behavior outside the home, the quality of relationships with prominent adult figures (particularly the father), their leadership role, and the family harmony.

Titolo: Psychological Interventions to Reduce Distress and Improve Quality of Life in Families with Autistic Children (2016)

Autore: Cristina Zarbo, Angelo Compare, Sara Melli, Enzo Grossi

Info: Psychological Distress, Nova Science Publishers Inc 2016



The experience of childbirth and becoming a parent can become particularly distressing when newborn has a severe chronic disability, like Autism Spectrum Disorder (ASD). Families with autistic children face an overload of their adaptive capacities and crisis situations that can in turn lead to various negative psychological consequences on each parent, the couple, children, and the whole family. Indeed, parents of autistic children show high incidence of psychological distress and mental disorders (e.g., anxiety disorders, depressive symptoms). Evidence suggests that parents of children with ASD may benefit of comprehensive and flexible psychological interventions to reduce parental distress and promote the wellbeing and improve the quality of life of the family.

Titolo: Mental Stress in Parents and Siblings of Autistic Children: Review of the Literature and Original Study of the Related Psychological Dimensions (2016)

Autore: Sara Melli, Enzo Grossi, Cristina Zarbo, Angelo Compare

Info: Psychological Distress, Nova Science Publishers Inc 2016



Parental mental stress is clinically common in families of autistic children and adversely affects the care of the child. Moreover, parents of autistic children frequently experience feelings of guilt, maladaptive coping styles, a lack of ability to forgive themselves and variations in mindfulness. However,it is unclear which of these dimensions is predominant in these families and their pattern of association with other components of this complex picture. While most notable in parents, this is also true of healthy siblings who intrinsically perceive more responsibility and often receive less attention than their afflicted brothers or sisters. The evidence available in the literature on the topic is quite controversial, revealing both positive and negative effects deriving from growing up with ASD siblings. Demographic and psychological information on mental stress, feelings of guilt, ability to forgive, mindfulness and coping styles were collected through clinical interviews and self-report questionnaires in parents and siblings of autistic children. Artificial Neural Networks (Auto-CM system) were applied to parents data to highlight the associations among the variables under investigation. Predominant dimensions in parents of autistic children indcluded low feelings of guilt, high levels of forgiveness and low levels of maladaptive coping responses. These three main dimensions were strictly related among themselves. While high parental mental stress was strictly related to high parental distress subscales, to high maladaptive coping styles, and to low self-forgiveness ability, conversely, low mental stress appeared to be marginal in relation to the other psychological dimensions. This behavior is typical of complex nonlinear systems. The severity of the ASD was not related to parental psychological dimensions. The ADOS scores, both low and high, were in fact marginal in the connectivity map in relation to the other dimensions. In siblings, the average distress scores level was extremely high irrespectively of ASD severity or family size. About one third of them were at risk of developing major depression. Distress appeared to be mainly related to difficulties in building a meaningful relationship with the ASD child and in managing the child’s behavioral problems. In conclusione the interplay of psychological factors related to stress in parents and siblings of ASD children is complex. Understanding these relationships is the starting point to activating and enhancing parental resources essential to the wellbeing of both children and caregivers.

Titolo: Artificial Neural Networks Link One-Carbon Metabolism to Gene-Promoter Methylation in Alzheimer's Disease (2016)

Autore: Enzo Grossi, Andrea Stoccoro, Pierpaola Tannorella, Lucia Migliore, Fabio Coppedè

Info: Journal Alzheimer Disease Jul 1;53(4):1517-22. doi: 10.3233/JAD-160210.



Background: There is increasing interest in DNA methylation studies in Alzheimer’s disease (AD), but little is still known concerning the relationship between gene-promoter methylation and circulating biomarkers of one-carbon metabolism in patients. Objective: To detect the connections among circulating folate, homocysteine (hcy) and vitamin B12 levels and promoter methylation levels of PSEN1, BACE1, DNMT1, DNMT3A, DNMT3B, and MTHFR genes in blood DNA. Methods:We applied a data mining system called Auto Contractive Map to an existing database of 100 AD and 100 control individuals. Results: Low vitamin B12 was linked to the AD condition, to low folates, and to high hcy. Low PSEN1 methylation was linked to low folate levels as well as to low promoter methylation of BACE1 and DNMTs genes. Low hcy was linked to controls, to high folates and vitamin B12, as well as to high methylation levels of most of the studied genes Conclusions: The present pilot study suggests that promoter methylation levels of the studied genes are linked to circulating levels of folates, hcy, and vitamin B12.

Titolo: Gut to brain interaction in Autism Spectrum Disorders. Role of probiotics on clinical, biochemical and neurophysiological parameters: a randomized controlled trial. (2016)

Autore: Elisa Santocchi, Letizia Guiducci, Francesca Fulceri, Lucia Billeci, Emma Buzzigoli, Fabio Apicella, Sara Calderoni, Enzo Grossi, Maria Aurora Morales, Filippo Muratori.

Info: BMC Psychiatry 16:183



Background A high prevalence of a variety of gastrointestinal (GI) symptoms is frequently reported in patients with Autism Spectrum Disorders (ASD). The GI disturbances in ASD might be linked to gut dysbiosis representing the observable phenotype of a “gut-brain axis” disruption. The exploitation of strategies which can restore normal gut microbiota and reduce the gut production and absorption of toxins, such as probiotics addition/supplementation in a diet, may represent a non-pharmacological option in the treatment of GI disturbances in ASD. The aim of this randomized controlled trial is to determine the effects of supplementation with a probiotic mixture (Vivomixx®) in ASD children not only on specific GI symptoms, but also on the core deficits of the disorder, on cognitive and language development, and on brain function and connectivity. An ancillary aim is to evaluate possible effects of probiotic supplementation on urinary concentrations of phthalates (chemical pollutants) which have been previously linked to ASD. Methods A group of 100 preschoolers with ASD will be classified as belonging to a GI group or to a Non-GI (NGI) group on the basis of a symptom severity index specific to GI disorders. In order to obtain four arms, subjects belonging to the two groups (GI and NGI) will be blind randomized 1:1 to regular diet with probiotics or with placebo for 6 months. All participants will be assessed at baseline, after three months and after six months from baseline in order to evaluate the possible changes in: GI symptoms; autism symptoms severity; affective and behavioral comorbid symptoms; plasmatic, urinary and fecal biomarkers related to abnormal intestinal function; neurophysiological patterns. Discussion The effects of treatments with probiotics on children with ASD need to be evaluated through rigorous controlled trials. Examining the impact of probiotics not only on clinical but also on neurophysiological patterns, the current trial sets out to provide new insights into the gut-brain connection in ASD patients. Moreover, results could add information to the relationship between phthalates levels, clinical features and neurophysiological patterns in ASD. Trial Registration: Identifier NCT02708901. Registered 4 March 2016. Key words Autism Spectrum Disorders (ASD), Gut-brain axis, endophenotype, probiotic Vivomixx®, quantitative electroencephalography (QEEG), phtalates.

Titolo: Microbiota Network and Mathematic Microbe Relation in Colostrum and Mature Milk of two different geographic areas: Italy versus Burundi (2016)

Autore: Lorenzo Drago, Marco Toscano, Roberta De Grandi, Enzo Grossi, Ezio Maria Padovani, Diego Peroni

Info: ISME Journal advance online publication 16 December 2016;



Human milk is essential for the initial development of newborns, as it provides all nutrients and vitamins, such as vitamin D, and it represents a great source of commensal bacteria. Here we explore the microbiota network of colostrum and mature milk of Italian and Burundian mothers. In both populations, by studying colostrum and mature milk microbiota with a new methodology based on an Artificial Neural Network (ANN) architecture, the Auto Contractive Map (AutoCM), it has been showed a different bacterial network, as diverse microbial hubs and central hubs have been observed in these samples. Interestingly, the Italian and Burundian mature milk showed a greater abundance of anaerobe intestinal bacteria if compared with colostrum samples, corroborating the hypothesis that intestinal microorganisms are able to reach the mammary glands by mean of dendritic cells and CD18+. In conclusion, the microbiota of human milk is a dynamic and complex ecosystem that not only differs between different populations, but it changes also during the transition from colostrum to mature milk. Finally, the association of complex mathematic systems such as ANN and AutoCM to metagenomics analysis represents an innovative approach to investigate in detail specific bacterial interactions in biological samples.

Titolo: Unexpected improvement in core autism symptoms after long term treatment with probiotics (2016)

Autore: Enzo Grossi, Delia Dunca, Sara Melli & Vittorio Terruzzi

Info: SAGE Open Medical Case Reports Volume 4: 1– 5



Background Many studies report the existence of so-called gut-brain axis: a physiological framework in which the gut microbiota communicates with the CNS and vice-versa through neural, endocrine and immune pathways. If this is true, then it is plausible to expect that the modulation gut microbiota may be a tractable strategy in developing novel therapeutics for complex CNS disorders. Autism is definitely one of these disorders. Objectives To report the case of a 12 year old boy with ASD and severe cognitive disability in which an unexpected improvement of autistic core symptoms was observed after four months of probiotic treatment. Method The case study refers to a 12 year old boy with ASD, severe cognitive disability and gastrointestinal disturbances attending the Villa Santa Maria Institute in resident care since 2009. The boy was first diagnosed with Pervasive Developmental Disorder (PDD) at the age of two. Later on ASD Diagnosis was made according to DSM-V criteria and was confirmed by the ADOS-2 assessment (Autism Diagnostic Observation Schedule). In February 2014, a probiotic treatment was prescribed to control gastrointestinal symptoms (VSL#3, a product with lyophilized Bifidobacteria, Lactobacilli and Streptococci), which lasted four months. The diet was consistently followed throughout the entire period and treatment compliance was ensured by a careful supervision. No other dietary supplements containing probiotics or prebiotics or antibiotics was administered during the treatment and follow-up period. The rehabilitation program already in place, based on behavior, communication, psychomotor therapy, individualized Education Plan/School Services and parents involvement, was regularly maintained. Improvement in ASD symptoms already became apparent and clinically evident from the few weeks after starting the probiotic treatment. The ADOS-2 assessment was repeated six times over the October 2013-March 2015 period (twice before starting the treatment, twice during (after month 1 and month 4) and twice after treatment interruption. Results The probiotic treatment reduced the severity of abdominal symptoms as expected. While the Restricted Repetitive Behaviors domain scores did not change, an unexpected improvement of the Autistic core symptoms did occur. The Social Affect Domain Score of ADOS improved, going from 20 to 18 after two months of treatment, with a further 1 point reduction during the following two months. The severity level 17 remained stable during the follow up period. Conclusions The appropriate use of probiotics merits further research, which hopefully will open new avenues in the fight against ASD.

Titolo: Predictors of Response to Long-Term Cholinesterase Inhibitors Treatment of Alzheimer Disease: Data Mining from Tredem Registry (2016)

Autore: Maurizio Gallucci , Pierpaolo Spagnolo, Maria Aricò, Enzo Grossi

Info: Journal Alzheimer Disease Vol. 50 969-979


Abstract. Background: the pharmacological treatment of Alzheimer Disease is based largely on cholinesterase inhibitors. Objective: to investigate whether or not some non-pharmacological and contextual factors measured prior to starting treatment such as past occupation, lifestyles, marital status, degree of autonomy and cognitive impairment, living alone or with others, the degree of brain atrophy are associated with a better response to cholinesterase inhibitors treatment. Methods: Eighty-four Alzheimer’s disease (AD) and six AD with cerebrovascular disease (AD + CVD) outpatients of Treviso Dementia (TREDEM) Registry, with an average cholinesterase inhibitors treatment length of four years, were considered. The outpatients had undergone a complete evaluation and some non-pharmacological and contextual factors were collected. We defined responder a patient with a delta score T0 – T1 equal or inferior to 2.0 points per year of MMSE and a non-responder a patient with a delta score T0 – T1 superior to 2.0 points per year. In order to identify hidden relationships between variables related to response and non-response, we use a special kind of artificial neural network called Auto-CM, able to create a semantic connectivity map of the variables considered in the study. Results: a higher cognitive profile, a previous intellectual work, healthier lifestyles, being married and not living alone, a higher degree of autonomy and lower degree of brain atrophy at baseline resulted to affect the response to long term ChEI therapy. Conclusion: non-pharmacological and contextual factors appear influence the effectiveness of treatment with ChEI in the long term.

Titolo: Pregnancy risk factors in autism: a pilot study with artificial neural networks (2016)

Autore: Enzo Grossi, Federica Veggo, Antonio Narzisi, Angelo Compare, Filippo Muratori

Info: Pediatric Research; Pediatr Res. 2016 Feb;79(2):339-47. doi: 10.1038/pr.2015.222. PubMed PMID: 26524714.


Background: Autism is a multi-factorial condition where a single risk factor can unlikely provide comprehensive explanation for the disease origin. Moreover, due to the complexity of risk factors interplay, traditional statistics is often unable to explain the core of the problem due to the strong inherent non-linearity of relationships. The aim of this study was to assess the frequency of twenty-seven potential risk factors related to pregnancy and peri-post natal period. Methods: The mothers of of forty-five autistic children and of 68 typical developing children completed a careful interview. 24 siblings of 19 autistic children formed an internal control group. Results: A higher prevalence of potential risk factors was observed in twenty-two and fifteen factors in external control and internal control group respectively. For six of them, the difference in prevalence was statistically significant. Specialized Artificial Neural Networks (ANNs) discriminated between autism and control subjects with 80.19% global accuracy. Conclusions: Pregnancy factors play an important role in autism development. ANNs are able to build up a predictive model, which could represent the basis for a diagnostic screening tool.

Titolo: Data Mining of Determinants of Intrauterine Growth Retardation Revisited Using Novel Algorithms Generating Semantic Maps and Prototypical Discriminating Variable Profiles (2015)

Autore: Massimo Buscema, Enzo Grossi, Luisa Montanini, Maria E. Street

Info: Plos One 7th July 2015



Objectives: Intra-uterine growth retardation is often of unknown origin, and is of great interest as a “FetalOrigin of Adult Disease” has been now well recognized. We built a benchmark based upon a previously analysed data set related to Intrauterine Growth Retardation with 46 subjectsdescribed by 14 variables, related with the insulin-like growth factor system and pro-inflammatorycytokines, namely interleukin -6 and tumor necrosis factor -α. Design and Methods: We used new algorithms for optimal information sorting based on the combination of twoneural network algorithms: Auto-contractive Map and Activation and Competition System. Auto-Contractive Map spatializes the relationships among variables or records by constructinga suitable embedding space where ‘closeness’ among variables or records reflects accurately their associations. The Activation and Competition System algorithm insteadworks as a dynamic non linear associative memory on the weight matrices of other algorithms, and is able to produce a prototypical variable profile of a given target. Results: Classical statistical analysis, proved to be unable to distinguish intrauterine growth retardationfrom appropriate-for-gestational age (AGA) subjects due to the high non-linearity of underlying functions. Auto-contractive map succeeded in clustering and differentiatingcompletely the conditions under study, while Activation and Competition System allowed to develop the profile of variables which discriminated the two conditions under study betterthan any other previous form of attempt. In particular, Activation and Competition System showed that ppropriateness for gestational age was explained by IGF-2 relative gene expression, and by IGFBP-2 and TNF-α placental contents. IUGR instead was explained by IGF-I, IGFBP-1, IGFBP-2 and IL-6 gene expression in placenta. Conclusions: This further analysis provided further insight into the placental key-players of fetal growthwithin the insulin-like growth factor and cytokine systems. Our previous published analysis could identify only which variables were predictive of fetal growth in general, and identified only some relationships.

Titolo: Networks in Coronary Heart Disease Genetics as a Step towards Systems Epidemiology. (2015)

Autore: Fotios Drenos, Enzo Grossi, Massimo Buscema, Steve E Humphries

Info: Plos One May 7, 2015



We present the use of innovative machine learning techniques in the understanding of Coronary Heart Disease (CHD) through intermediate traits, as an example of the use of this class of methods as a first step towards a systems epidemiology approach of complex diseases genetics. Using a sample of 252 middle-aged men, of which 102 had a CHD event in 10 years follow-up, we applied machine learning algorithms for the selection of CHD intermediate phenotypes, established markers, risk factors, and their previously associated genetic polymorphisms, and constructed a map of relationships between the selected variables. Of the 52 variables considered, 42 were retained after selection of the most informative variables for CHD. The constructed map suggests that most selected variables were related to CHD in a context dependent manner while only a small number of variables were related to a specific outcome. We also observed that loss of complexity in the network was linked to a future CHD event. We propose that novel, non-linear, and integrative epidemiological approaches are required to combine all available information, in order to truly translate the new advances in medical sciences to gains in preventive measures and patients care.

Titolo: Age-, Adiposity- and Insulin-Related Changes in Urinary Di-(2-Ethylhexyl) Phthalate Metabolites (2015)

Autore: Arianna Smerieri, Chiara Testa, Pietro Lazzeroni, Francesca Nuti, Enzo Grossi, Silvia Cesari, Luisa Montanini, Giuseppe Latini, Sergio Bernasconi, Anna Maria Papini, Maria E. Street.

Info: Plos One 10: 2. 02



Background and objectives: Phthalates might be implicated with obesity and insulin sensitivity. The aim of this study was to evaluate the levels of primary and secondary metabolites of DEHP in urine in obese and normal-weight subjects both before and during puberty, and to investigate their relationships with auxological parameters and indexes of insulin sensitivity. Methods: DEHP metabolites (MEHP, 6-OH-MEHP, 5-oxo-MEHP, 5-OH-MEHP, and 5-CX-MEHP), were measured in urine by RP-HPLC-ESI-MS. Traditional statistical analysis and a data mining analysis through the Auto-CM system, a fourth generation artificial neural network (ANN), were able to offer an insight of the complex biological connections between the studied variables. Results: The data showed changes in DEHP metabolites in urine, related with obesity, onset of puberty, and presence of insulin resistance. Changes in urine metabolites were related with age, height and weight, waist circumference and waist to height ratio, thus to fat distribution. In addition, clear relationships in both obese and normal-weight subjects were detected among MEHP, its products of oxidation and measurements of insulin sensitivity (insulin, fasting glucose to insulin ratio, HOMA-IR index, and whole body insulin sensitivity index). Conclusions: It remains to be elucidated whether exposure to phthalates per se is actually the risk factor or if the ability of the body to metabolize phthalates is actually the key point. Further studies that span from conception to elderly subjects besides further understanding of DEHP metabolism are warranted to clarify these aspects.

Titolo: Which are the better outcome predictors in preschoolers with autism who respond positively at the treatment as usual (TAU) ? Insights from an observational study using Artificial Neural Networks (2015)

Autore: Antonio Narzisi, Filippo Muratori, Massimo Buscema, Sara Calderoni, Enzo Grossi IRCCS Stella Maris Foundation - Department of Developmental Neuroscience, University of Pisa, Pisa, Italy, Semeion Research Center, Rome, Italy, 4Department of Mathematical



In Italy Treatment As Usual (TAU) for autism spectrum disorders (ASD) is composed of specific treatments performed by child neuropsychiatric services and of school inclusion with individual support teacher. The Artificial Neural Networks (ANNs) have never been used in order to study the effects of treatment in ASD. Auto Contractive Map (Auto-CM) is a special kind of ANNs able to find out consistent trends and associations among variables creating a semantic connectivity map. The matrix of connections, visualized through minimum spanning tree filter takes into account non linear associations among variables and captures connection schemes among clusters. Objectives: The main aim is to use Auto-CM in order to identify key variables to discriminate among responders versus no responders at TAU. Methods: 56 preschoolers with ASD aged between 24 and 48 months were recruited at different centers in Italy. They were evaluated by blind researchers at baseline and after six months using a multi-informant assessment protocol. All children were referred to community providers for available interventions. Results: At T1, the severity of autism measured through ADOS improved in 62% of involved children (Response) while it was the same or worse in 37% of 56 (No Response). The application of the the Semeion ANNs overcome the 85% of global accuracy (Sine–Net almost reaching 90%). Consequently, some of the tested algorithms were able to find a good correlation between some variables and TAU outcome. The semantic connectivity map obtained with the application of the Auto-CM system showed results that clearly indicated that ‘Response’ can be visually separated from the ‘No Response’ cases. Particularly it was possible to visualize a Response area characterized by’ Parents Involvement high’ and ‘MacArthur Expressive low’. No Response area resulted strongly connected only with ‘Parents Involvement low’. Conclusions: The ANN model that was used in this study appears to be a promising tool for the identification of the variables involved in the positive of negative response to TAU in autism.

Titolo: L'apporto dell'arte, della religione e della comunicazione nella "cura" delle persone con disturbi dello spettro autistico (2014)

Autore: Marina Norsi

Info: Dolentium Hominum n. 86



L'apporto della religione e dell'arte nella cura dei bambini autistici viene analizzata basandosi sui dati riportati nella letteratura e sull'esperienza degli ultimi 10 anni nelle strutture terapeutiche(nidi e asili) in Israele. L'influenza della religione nell'accettare la diagnosi ed affrontare la cura dell'autismo puo' essere positiva(accettazione della malattia come espressione della volonta' Divina) o negativa(malattia come punizione divina per i dubbi dei genitori nei confronti di Dio) . I dati riportati in letteratura confermano che il supporto delle organizzazioni religiose e dei ministri del culto sono di grande aiuto: diminuiscono lo stress e lo stato di ansia delle famiglie. L'arte terapia usata ormai in tutto il mondo come terapia complementare ha vantaggi rispetto alle terapie convenzionali:e' un mezzo di comunicazione non verbale, viene accettata dai bambini in modo positivo e non minaccioso,potenzia il contatto di sguardo, potenzia l'apprendimento di colori, forme geometriche, oggetti. Sono stati descritti in modo particolareggiato esempi concreti dell'uso dell'arte terapia e pratiche religiose nella stesura dei programmi cognitivi, educativi nelle strutture terapeutiche per bambini autistici.

Titolo: The Role of Intestinal Dysbiosis in the Pathogenesis of Autism: Minireview (2014)

Autore: Enzo Grossi & Vittorio Terruzzi

Info: International Journal of Microbiology & Advanced Immunology (IJMAI) 2: 201



Autism spectrum disorder is a complex neurodevelopmental disease where gastrointestinal disturbance is commonly reported. Here we review the evidence suggesting that gut microbota my play a role in this disease and summarize comparative studies we found in international literature on the topic. Discussion of results, methodology of the data collection, bias of selection and behavioral interferences lead to the conclusion that changes in the gut microbiota is a significant piece of autism spectrum disorder but further studies are needed to understand this pathogenetic role.

Titolo: Personality traits, cardiac risk factors, and their association with presence and severity of coronary artery plaque in people with no history of cardiovascular disease. (2014)

Autore: Angelo Compare, Paula M C Mommersteeg, Francesco Faletra, Enzo Grossi, Elena Pasotti, Tiziano Moccetti, Angelo Auricchio

pdf url


Coronary artery disease (CAD) is a complex, multifactorial disease in which personality seems to play a role but with no definition in combination with other risk factors. Objective: To explore the nonlinear and simultaneous pathways between traditional and personality traits risk factors and coronary stenosis by Artificial Neural Networks (ANN) data mining analysis. Method: Seventy-five subjectswere examined for traditional cardiac risk factors and personality traits.Analyseswere based on a new data mining method using a particular artificial adaptive system, the autocontractive map (AutoCM). Results: Several traditional Cardiovascular Risk Factors (CRF) present significant relations with coronary artery plaque (CAP) presence or severity. Moreover, anger turns out to be the main factor of personality for CAP in connection with numbers of traditional risk factors. Hidden connection map showed that anger, hostility, and the Type D personality subscale social inhibition are the core factors related to the traditional cardiovascular risk factors (CRF) specifically by hypertension. Discussion: This study shows a nonlinear and simultaneous pathway between traditional risk factors and personality traits associated with coronary stenosis in CAD patients without history of cardiovascular disease. In particular, anger seems to be the main personality factor for CAP in addition to traditional risk factors.

Titolo: PAHA study: Psychological Active and Healthy Aging: psychological wellbeing, proactive attitude and happiness effects of whole-body vibration versus Multicomponent Training in aged women: study protocol for a randomized controlled trial. (2014)

Autore: Angelo Compare, Cristina Zarbo, Elena Marín, Alessia Meloni, Jacobo A Rubio-Arias, Rosendo Berengüí, Enzo Grossi, Edo Shonin, Gianmaria Martini, Pedro E Alcaraz



Evidence demonstrates that physical exercise and psychological wellbeing are closely interlinked, particularly in older-aged women. However, research investigating how different forms of exercise influence mental health in older-aged women is underdeveloped. Methods/design: A randomized controlled trial (N = 300) will assess the relative effectiveness of two different exercise programs (whole-body vibration and Multicomponent Training) for improving psychological wellbeing in older-aged women. The following outcomes will be assessed at three time points (that is, pre, post, and follow-up): psychological wellbeing, proactive attitude, quality of life, and happiness.

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