A Hybrid Deep Learning and Machine Learning Approach with Mobile-EfficientNet and Grey Wolf Optimizer for Lung and Colon Cancer Histopathology Classification.

Background: Lung and colon cancers are among the most prevalent and lethal malignancies worldwide, underscoring the urgent need for advanced diagnostic methodologies. This study aims to develop a hybrid deep learning and machine learning framework for the classification of Colon Adenocarcinoma, Colon Benign Tissue, Lung Adenocarcinoma, Lung Benign Tissue, and Lung Squamous Cell Carcinoma from histopathological images.

Methods: Current approaches primarily rely on the LC25000 dataset, which, due to image augmentation, lacks the generalizability required for real-time clinical applications.

Enhanced Diabetes Detection and Blood Glucose Prediction Using TinyML-Integrated E-Nose and Breath Analysis: A Novel Approach Combining Synthetic and Real-World Data.

Diabetes mellitus, a chronic condition affecting millions worldwide, necessitates continuous monitoring of blood glucose level (BGL). The increasing prevalence of diabetes has driven the development of non-invasive methods, such as electronic noses (e-noses), for analyzing exhaled breath and detecting biomarkers in volatile organic compounds (VOCs). Effective machine learning models require extensive patient data to ensure accurate BGL predictions, but previous studies have been limited by small sample sizes.

Quantification of human immunodeficiency virus type 2 (HIV-2) viral load in plasma: Comparison of three commercial assays.

Introduction: There are few validated commercially available HIV-2 assays for the measurement of viral load. Our aim was to compare three commercial assays for the quantification of HIV-2 viral load in plasma of patients with HIV-2 infection from our hospital.

Material And Methods: We conducted a retrospective study at our tertiary-care hospital, analyzing samples from patients with known HIV-2 infection collected between 2022 and 2023.

Effect of Postbiotic Supplementation on Nutrient Digestibility and Milk Yield during the Transition Period in Dairy Cows.

The metabolites secreted by probiotics or released after their lysis are called postbiotics. They provide physiological benefits to the host, preventing the colonisation of pathogens by improving the intestinal environment for beneficial commensal bacteria, which reduces the incidence of digestive disorders and improves the immune system. The aim of this work was to evaluate the addition of postbiotics to dairy cow rations during the transition period on nutrient digestibility, composition, and milk yield.

Development, Characterization, and Cellular Toxicity Evaluation of Solid Dispersion-Loaded Hydrogel Based on Indomethacin.

Indomethacin (IND) as a non-selective cyclooxygenase 1 and 2 inhibitor administered orally causes numerous adverse effects, mostly related to the gastrointestinal tract. Moreover, when applied exogenously in topical preparations, there are obstacles to its permeation through the stratum corneum due to its low water solubility and susceptibility to photodegradation. In this work, solid dispersions (SDs) of IND with low-substituted hydroxypropyl cellulose (LHPC) were developed.