Prediction of metabolic subphenotypes of type 2 diabetes via continuous glucose monitoring and machine learning.

The classification of type 2 diabetes and prediabetes does not consider heterogeneity in the pathophysiology of glucose dysregulation. Here we show that prediabetes is characterized by metabolic heterogeneity, and that metabolic subphenotypes can be predicted by the shape of the glucose curve measured via a continuous glucose monitor (CGM) during standardized oral glucose-tolerance tests (OGTTs) performed in at-home settings. Gold-standard metabolic tests in 32 individuals with early glucose dysregulation revealed dominant or co-dominant subphenotypes (muscle or hepatic insulin-resistance phenotypes in 34% of the individuals, and β-cell-dysfunction or impaired-incretin-action phenotypes in 40% of them).

Habitat Suitability Modelling for the Red Dwarf Honeybee (Apis florea (Linnaeus)) and Its Distribution Prediction Using Machine Learning and Cloud Computing.

Apis florea bees were recently identified in Egypt, marking the second occurrence of this species on the African continent. The objective of this study was to track the distribution of A. florea in Egypt and evaluate its potential for invasive behaviour.

Silver nanoparticles loaded with pomegranate peel extract and hyaluronic acid mediate recovery of cutaneous wounds infected with .

Smart innovative nanocomposites based on active ingredients and metallic nanoparticles with effective wound healing and antifungal properties are efficient in overcoming the limitations of traditional therapeutic products. Open wounds provide an ideal niche for colonization by () which poses substantial global health issues owing to delayed wound healing and disordered healing mechanisms. Therefore, proficient innovative therapies that control infection and promote wound healing are of imperative importance for the management of wounds and prevention of infection and possible complications.

Utilizing post-stack seismic inversion for delineation of gas-bearing sand in a pleistocene reservoir, baltim gas field, nile delta, Egypt.

Given useful rock properties, gas sands generally appear as bright events on seismic data. Unfortunately, partially saturated gas sands tend to be of similar brightness to fully saturated gas sands so cannot be distinguished easily. Seismic inversion can sometimes help, given adequate seismic data and a robust understanding of rock physics.

Delineation of the reservoir petrophysical parameters from well logs validated by the core samples case study Sitra field, Western Desert, Egypt.

In the northern section of the Western Desert, there are many extremely profitable petroleum and natural gas deposits in the Abu EL-Gharadig Basin. This study aims to highlight the hydrocarbon potential of Abu Roash F Formation, which stands for high organic content unconventional tight reservoirs, and Abu Roash G Formation which stands for conventional sand reservoirs, in Sitra field located in the central-western part of the Abu EL-Gharadig Basin. The research employed well-log data from four wells to ascertain petrophysical properties combined with core samples of two wells for a comprehensive examination and description of lithology.