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Background: The effect of amyloid‐b brain deposition on cognition is still debated, since it has been shown that its accumulation begins almost 15 years before cognitive symptoms' onset, then reaches a plateau while cognition continues to decline. We studied if there is a parallel between amyloid‐b deposition and cognitive performances in young‐onset Mild Cognitive Impairment (MCI) patients, and if it is associated to symptoms' duration. Method: Subjects with a diagnosis of MCI and symptoms' onset ≤ 65 years underwent neuropsychological assessment, Magnetic Resonance Imaging, and (18F)Flutemetamol‐PET (amy‐PET). FMRIB Software Library was used to assess voxel‐wise correlations between amyloid‐b deposition and cognitive performances, adjusted for age, sex, education, and degree of grey matter atrophy. Correlations were repeated grouping patients depending on whether the duration of their cognitive symptoms had been shorter or longer than the median of the entire group (34 months). Result: Among the 30 recruited individuals we found a statistically significant correlation between amyloid‐b burden and performance in attentional‐executive (i.e., Trail Making Test [TMT]‐A/B and Stroop Test) and memory (i.e., Free and Cued Selective Reminding Test [FCSRT]‐immediate and delayed free recall, Corsi Supraspan, and Rey‐Osterrieth Complex Figure‐delayed recall) tests. Patients with short disease duration (n = 15) had even more significant associations relative to patients with longer duration. More precisely, they showed significant linear correlations in widespread brain regions between amyloid‐b burden and cognition in attentional‐executive (i.e., Attentional Matrices, Raven's Coloured Progressive Matrices, TMT‐A/B) and memory (i.e., Babcock Short Tale‐immediate/delayed recall, FCSRT‐immediate free recall, and Corsi Supraspan) tests. Conclusion: In young‐onset MCI we found a linear relationship between amyloid‐b deposition and cognitive performance, which is more evident in patients with shorter disease duration. Our results contribute to identifying which cognitive tests are most sensitive to amyloid‐b deposition in the initial stages of dementing diseases. [ABSTRACT FROM AUTHOR]

Introduction Selenium is an essential mineral that occurs naturally in soil-grown foods, though motorized traffic, tobacco smoke, and drinking water are additional sources of exposure. (1) Selenium is also found [...]

The research aimed to determine whether and which radiomic features from breast dynamic contrast enhanced (DCE) MRI could predict the presence of BRCA1 mutation in patients with triple-negative breast cancer (TNBC). This retrospective study included consecutive patients histologically diagnosed with TNBC who underwent breast DCE-MRI in 2010–2021. Baseline DCE-MRIs were retrospectively reviewed; percentage maps of wash-in and wash-out were computed and breast lesions were manually segmented, drawing a 5 mm-Region of Interest (ROI) inside the tumor and another 5 mm-ROI inside the contralateral healthy gland. Features for each map and each ROI were extracted with Pyradiomics-3D Slicer and considered first separately (tumor and contralateral gland) and then together. In each analysis the more important features for BRCA1 status classification were selected with Maximum Relevance Minimum Redundancy algorithm and used to fit four classifiers. The population included 67 patients and 86 lesions (21 in BRCA1-mutated, 65 in non BRCA-carriers). The best classifiers for BRCA mutation were Support Vector Classifier and Logistic Regression in models fitted with both gland and tumor features, reaching an Area Under ROC Curve (AUC) of 0.80 (SD 0.21) and of 0.79 (SD 0.20), respectively. Three features were higher in BRCA1-mutated compared to non BRCA-mutated: Total Energy and Correlation from gray level cooccurrence matrix, both measured in contralateral gland in wash-out maps, and Root Mean Squared, selected from the wash-out map of the tumor. This study showed the feasibility of a radiomic study with breast DCE-MRI and the potential of radiomics in predicting BRCA1 mutational status. [ABSTRACT FROM AUTHOR]