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Transforming the latent value of big data into real value requires the great human intelligence and application of human-data scientists. Data scientists are expected to have a wide range of technical skills alongside being passionate self-directed people who are able to work easily with others and deliver high quality outputs under pressure. There are hundreds of university, commercial, and online courses in data science and related topics. Apart from people with breadth and depth of knowledge and experience in data science, we identify a new educational path to train “bridge persons” who combine knowledge of an organization’s business with sufficient knowledge and understanding of data science to “bridge” between non-technical people in the business with highly skilled data scientists who add value to the business. The increasing proliferation of big data and the great advances made in data science do not herald in an era where all problems can be solved by deep learning and artificial intelligence. Although data science opens up many commercial and social opportunities, data science must complement other science in the search for new theory and methods to understand and manage our complex world. info:eu-repo/semantics/publishedVersion

Pediatric obesity develops when a complex biological predisposition collides with an obesogenic environment. To further elucidate the role of genetics in obesity onset, we performed a candidate-gene association study in a young and sportive Italian population by testing the association of functional polymorphisms in ACE (rs4646994), FTO (rs9939609), MC4R (rs17782313) and PPARG (rs1801282) genes with body mass index (BMI) and waist-to-height ratio (WHtR). We also tested the combinations of identified risk genotypes and epistatic interactions among them to determine the existence of cumulative effects in predicting the predisposition to gain weight. Our results confirm a significant direct influence of MC4R rs17782313 and PPARG rs1801282 on body composition, that is, minor allele homozygotes showed significantly higher BMI (rs17782313, β = 1.258, P = 0.031; rs1801282, β = 6.689, P = 1.2 × 10

Changes in the homeostasis of metals and microelements have been demonstrated in Parkinson's disease, whose etiology includes both a genetic and environmental basis. We studied the difference of microelements in the hair of Parkinson's disease subjects (n = 46) compared with healthy controls (n = 24). Hair was chosen as a representative matrix to measure microelements, since it is a vehicle of substance excretion from the human body and it allows for long-term evaluation of metal exposure. An inductively coupled plasma mass spectrometry (ICP-MS) analysis of hair collected from 24 Parkinson's patients compared with their healthy relatives used as controls shows a significant decrease in Ca (U = 166, p = 0.012),), Mg (U = 187, p = 0.037), and Sr (U = 183, p = 0.030). Cd and Ca/Mg were decreased, and Cu was increased, in patients with respect to their healthy related controls at the limit of significance (p = 0.0501). Principal Component Analysis (PCA) of these microelements in hair shows a clustering into two groups according to gender, disease severity according to the Hoehn-Yahr scale, and pharmacological therapy. This pilot study represents a starting point for future investigations where a larger group of subjects will be involved to define other microelements useful when screening for early biomarkers of Parkinson's disease.

The number of children affected by Autism Spectrum Disorders (ASD) is dramatically increasing as well as the studies aimed at understanding the risk factors associated with the development of ASD. Since the etiology of ASD is partly genetic and partly environmental, factors (i.e., heavy metals, pesticides) as well as lifestyle seem to have a key role in the development of the disease. ASD and Control (CTR) children, aged 5–12 years, were compared. Gas chromatography coupled with trap mass detector was used to measure the level of 3-PBA, the main pyrethroid metabolite in urine in a group of ASD patients, while optical emission spectrometry analysis was employed to estimate the level of metals and microelements in hair in a different group of ASD children. The presence of 3-PBA in urine seems to be independent of age in ASD children, while a positive correlation between 3-PBA and age was observed in the control group of the same age range. Urine concentration of 3-BPA in ASD children had higher values than in the control group, which were marginally significant (p = 0.054). Mg results were significantly decreased in ASD with respect to controls, while V, S, Zn, and Ca/Mg were marginally increased, without reaching statistical significance. Results of Principal Component (PC) analysis of metals and microelements in hair were not associated with either age or health status. In conclusion, 3-PBA in urine and Mg in hair were changed in ASD children relative to control ones.