"Comparative evaluation of different chemical agents induced Autism Spectrum Disorder in experimental Wistar rats".

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition with uncertain etiology and pathophysiology. Several studies revealed that the commonly used animal models like Valproic Acid (VPA) and Propionic Acid (PPA) do not precisely represent the disease as the human patient does. The current study was conducted on different chemically (VPA, PPA, Poly I:C, Dioxin (2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD)) & Chlorpyrifos (CPF)) induced ASD-like animal models and validated the best suitable experimental animal model, which would closely resemble with clinical features of the ASD. This validated model might help to explore the pathophysiology of ASD. This study included rat pups prenatally exposed to VPA, PPA, Poly I:C, Dioxin & CPF within GD9 to GD15 doses. The model groups were validated through developmental and behavioral parameters, Gene Expressions, Oxidative Stress, and Pro-inflammatory and Anti-inflammatory cytokines levels. Developmental and neurobehavioral parameters showed significant changes in model groups compared to the control. In oxidative stress parameters and neuro-inflammatory cytokines levels, model groups exhibited high oxidative stress and neuro-inflammation compared to control groups. Gene expression profile of ASD-related genes showed significant downregulation in model groups compared to the control group. Moreover, the Poly I:C group showed more significant results than other model groups. The comparison of available ASD-like experimental animal models showed that the Poly I:C induced model represented the exact pathophysiology of ASD as the human patient does. Poly I:C was reported in the maternal immune system activation via the inflammatory cytokines pathway, altering embryonic development and causing ASD in neonates.

Efficacy, safety, and dose-response effects of calcifediol supplementation on 25-hydroxyvitamin D, parathyroid hormone, and 1,25-dihydroxyvitamin D levels in healthy adults: An open-label, interventional pilot study.

BACKGROUND: Vitamin D deficiency (VDD) is highly prevalent across the globe. Cholecalciferol (Vitamin D3) fails to attain sufficient serum concentrations of 25-hydroxyvitamin D (25(OH)D) in a significant proportion of supplemented individuals. Calcifediol (25-hydroxyvitamin D3) is less studied in healthy adults and its effects on 25(OH)D, parathyroid hormone (PTH), and 1,25-dihydroxyvitamin D (1,25(OH)2D) at higher doses are not well known. MATERIALS AND METHODS: The study was an open-label, interventional trial recruiting consecutive participants with VDD who were allocated to receive either 2 capsules (50 µg-group) or 1 capsule (25 µg-group) daily doses of calcifediol. Baseline assessment included clinicodemographic parameters, dietary calcium, calcemic (calcium, inorganic phosphate, albumin, alkaline phosphatase, urine spot calcium/creatinine), and hormonal parameters (25(OH)D, PTH, and 1,25(OH)2D). Participants were followed up at 4 and 8 weeks with repeat assessments of calcemic and hormonal parameters. RESULTS: There were 64 participants, 35 (50 µg-group) and 29 (25 µg-group), without any significant difference in any of the baseline parameters. 97.1% participants in the 50 µg-group (at 4 and 8 weeks) and 93.1% (at 4 weeks) and 96.5% (at 8 weeks) in the 25 µg-group attained 25(OH)D sufficiency (≥30 ng/ml) with calcifediol. The mean serum 25(OH)D was 84.0 ± 27.7 ng/ml in the 50 µg-group and 58.0 ± 23.6 ng/ml in the 25 µg-group group at 4 weeks, which later rose to 94.3 ± 21.8 ng/ml and 76.0 ± 16.4 ng/ml, respectively, at 8 weeks. PTH levels decreased in both groups at both time points. 1,25(OH)2D rose significantly in both groups at 4 and 8 weeks but was not significantly different between both groups. There was no case of incident hypercalcemia or symptomatic nephrolithiasis. CONCLUSION: Calcifediol is a safe and efficacious alternative for oral Vitamin D supplementation in young adults. Increment in 25(OH)D levels is rapid and dose-dependent.

Histopathological Image Diagnosis for Breast Cancer Diagnosis Based on Deep Mutual Learning.

Every year, millions of women across the globe are diagnosed with breast cancer (BC), an illness that is both common and potentially fatal. To provide effective therapy and enhance patient outcomes, it is essential to make an accurate diagnosis as soon as possible. In recent years, deep-learning (DL) approaches have shown great effectiveness in a variety of medical imaging applications, including the processing of histopathological images. Using DL techniques, the objective of this study is to recover the detection of BC by merging qualitative and quantitative data. Using deep mutual learning (DML), the emphasis of this research was on BC. In addition, a wide variety of breast cancer imaging modalities were investigated to assess the distinction between aggressive and benign BC. Based on this, deep convolutional neural networks (DCNNs) have been established to assess histopathological images of BC. In terms of the Break His-200×, BACH, and PUIH datasets, the results of the trials indicate that the level of accuracy achieved by the DML model is 98.97%, 96.78, and 96.34, respectively. This indicates that the DML model outperforms and has the greatest value among the other methodologies. To be more specific, it improves the results of localization without compromising the performance of the classification, which is an indication of its increased utility. We intend to proceed with the development of the diagnostic model to make it more applicable to clinical settings.