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The Test of Mobile Phone Dependence (TMD) is a questionnaire designed for appraising the main dimensions of problematic smartphone use in adolescence. This study evaluates the factor structure and psychometric properties of the TMD on a sample of 813 Italian middle and high school students. The original three-factor model (Abstinence, Lack of Control, and Tolerance) of the TMD was tested through a Confirmatory Factor Analysis. The results of the goodness of fit indices indicated a satisfactory solution. The overall TMD score showed a good level of internal consistency and good construct validity with the duration of use, age of possession of the first mobile phone, perceived self-efficacy, gender, and participants' age. The relationship between TMD and Nomophobia was also explored. Overall, the results indicate that the TMD is a valid and reliable assessment tool in Italian culture. However, reliability issues emerged on the subfactor Lack of Control. This indicates that the scores on this subfactor should be treated with caution., Author(s): Michela Vezzoli [sup.1] , Aurora Colombo [sup.1] , Alessandra Marano [sup.1] , Giorgia Zoccatelli [sup.1] , Cristina Zogmaister [sup.1] Author Affiliations: (1) grid.7563.7, 0000 0001 2174 1754, Department of [...]

α-synuclein oligomers within synaptic terminals of autonomic fibers of the skin reliably discriminate Parkinson's disease (PD) patients from healthy controls. Nonetheless, the prognostic role of oligomers for disease progression is unknown. We explored whether α-synuclein oligomers evaluated as proximity ligation assay (PLA) score may predict the worsening of cognitive functions in patients with Parkinson's disease. Thirty-four patients with PD and thirty-four healthy controls (HC), matched 1:1 for age and sex, were enrolled. Patients with PD underwent baseline skin biopsy and an assessment of cognitive domains including Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Clock Drawing Test, and Frontal Assessment Battery. At the last follow-up visit available, patients were either cognitively stable (PD-CS) or cognitively deteriorated (PD-CD). α-synuclein oligomers were quantified as PLA scores. Differences between groups were assessed, controlling for potential confounders. The relationship between skin biopsy measures and cognitive changes was explored using correlation and multivariable regression analyses. The discrimination power of the PLA score was assessed via ROC curve. To elucidate the relationship between skin biopsy and longitudinal cognitive measures, we conducted multivariable regression analyses using delta scores of cognitive tests (Δ) as dependent variables. We found that PD-CD had higher baseline PLA scores than PD-CS (p = 0.0003), and they were correctly identified in the ROC curve analysis (AUC = 0.872, p = 0.0003). Furthermore, ANCOVA analysis with Bonferroni correction, considering all groups (PD-CS, PD-CD, and HC), showed significant differences between PD-CS and PD-CD (p = 0.003), PD-CS and HC (p = 0.002), and PD-CD and HC (p < 0.001). In the regression model using ΔMMSE as the dependent variable, the PLA score was found to be a significant predictor (β = −0.441, p = 0.016). Similar results were observed when evaluating the model with ΔMoCA (β = −0.378, p = 0.042). In conclusion, patients with Parkinson's disease with higher α-synuclein burden in the peripheral nervous system may be more susceptible to cognitive decline. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) patients have lower levels of serum 25-hydroxyvitamin D (25(OH)D) than the general population. Previous studies have suggested a negative association between 25(OH)D and clinical features of PD, but the data are inconsistent. We conducted a cross-sectional, observational study. Serum 25(OH)D, disease (Hoehn-Yahr stage [HY]) and clinical symptom (Unified Parkinson Disease Rating Scale [UPDRS]) severity and global cognitive functions (Mini-Mental State Examination [MMSE]) were studied in 500 consecutive PD patients not using vitamin D supplements. Information on sunlight exposure and dietary intakes (using a 66-item food frequency questionnaire) were also collected. A convenient sample of age and sex-matched community healthy controls (N = 100) was included as a control group. PD patients had lower 25(OH)D serum levels than controls. Deficiency status (<20 ng/mL) was found in 65.6% of patients. 25(OH)D levels were independently correlated to sunlight exposure (P =.002) and vitamin D intake (P =.009). In multivariate models, using a Mendelian randomization approach, lower serum 25(OH)D was associated with more severe disease (HY, P =.035), worse clinical symptoms (UPDRS Part-III total score [P =.006] and dopaminergic [P =.033] and non-dopaminergic subscores [P =.001]) and greater global cognitive function impairment (P =.041). Neither cognitive functions nor clinical features were associated with reduced intake of vitamin D and sunlight exposure. : Serum 25(OH)D was negatively correlated with disease and symptoms severity, as well as with global cognitive functions. Our study adds to the evidence that low 25(OH)D may affect the progression of PD negatively. Intervention studies in this area are required. [ABSTRACT FROM AUTHOR]

Precision medicine significantly enhances patients prognosis, offering personalized treatments. Particularly for metastatic cancer, incorporating primary tumor location into the diagnostic process greatly improves survival rates. However, traditional methods rely on human expertise, requiring substantial time and financial resources. To address this challenge, Machine Learning (ML) and Deep Learning (DL) have proven particularly effective. Yet, their application to medical data, especially genomic data, must consider and encompass privacy due to the highly sensitive nature of data. In this paper, we propose OGHE, a convolutional neural network-based approach for privacy-preserving cancer classification designed to exploit spatial patterns in genomic data, while maintaining confidentiality by means of Homomorphic Encryption (HE). This encryption scheme allows the processing directly on encrypted data, guaranteeing its confidentiality during the entire computation. The design of OGHE is specific for privacy-preserving applications, taking into account HE limitations from the outset, and introducing an efficient packing mechanism to minimize the computational overhead introduced by HE. Additionally, OGHE relies on a novel feature selection method, VarScout, designed to extract the most significant features through clustering and occurrence analysis, while preserving inherent spatial patterns. Coupled with VarScout, OGHE has been compared with existing privacy-preserving solutions for encrypted cancer classification on the iDash 2020 dataset, demonstrating their effectiveness in providing accurate privacy-preserving cancer classification, and reducing latency thanks to our packing mechanism. The code is released to the scientific community.

Medical practice is shifting towards the automation and standardization of the most repetitive procedures to speed up the time-to-diagnosis. Semantic segmentation repre-sents a critical stage in identifying a broad spectrum of regions of interest within medical images. Indeed, it identifies relevant objects by attributing to each image pixels a value representing pre-determined classes. Despite the relative ease of visually locating organs in the human body, automated multi-organ segmentation is hindered by the variety of shapes and dimensions of organs and computational resources. Within this context, we propose BIONET, a U-Net-based Fully Convolutional Net-work for efficiently semantically segmenting abdominal organs. BIONET deals with unbalanced data distribution related to the physiological conformation of the considered organs, reaching good accuracy for variable organs dimension with low variance, and a Weighted Global Dice Score score of 93.74 ± 1.1%, and an inference performance of 138 frames per second. Clinical Relevance - This work established a starting point for developing an automatic tool for semantic segmentation of variable-sized organs within the abdomen, reaching considerable accuracy on small and large organs with low variability, reaching a 93.74 ± 1.1 % of Weighted Global Dice Score.