AIMC Topic: Diabetes Mellitus, Experimental

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Properties of AgNPs stabilized with polyvinylpyrrolidone relevant to antidiabetic agents.

Nanoscale
Type 2 diabetes mellitus (DM2) is a chronic metabolic disease. Silver nanoparticles (AgNPs) show promise in their treatment. This study assessed the potential of AgNPs as DM2 treatment agent using in vitro, in vivo, and machine learning approaches. M...

Tanshinone IIA ameliorates pancreatic injury in type 2 diabetic mice by modulating inflammation and endoplasmic reticulum stress via the IL-6/JAK2/STAT3 pathway.

Functional & integrative genomics
Type 2 diabetes mellitus (T2DM) is a severe metabolic disorder in which pancreatic injury plays a pivotal role in disease progression. Tanshinone IIA (TanIIA), a bioactive compound extracted from Salvia miltiorrhiza, has shown therapeutic potential i...

Machine Learning-Assisted Real-Time Inflammation Monitoring and Optimal Treatment of Diabetic Wounds Based on a Ratiometric Fluorescent Sensing Peptide Hydrogel.

Nano letters
Managing inflammation in diabetic chronic wounds remains a major clinical challenge, primarily due to the lack of real-time monitoring techniques. To address this issue, we developed a peptide hydrogel capable of simultaneously monitoring the inflamm...

FTIR spectroscopy imaging coupled with machine learning reveals biochemical changes in the brains of diabetic mice.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Diabetic encephalopathy is a progressive complication of type 2 diabetes, yet its region-specific biochemical changes remain unclear. In this study, we applied Fourier Transform Infrared Microspectroscopy (FTIRM) to assess metabolic alterations in th...

Integrating machine learning and bioinformatics approaches to identify novel diagnostic gene biomarkers for diabetic mice.

Scientific reports
Diabetes is a complex metabolic disorder, and its pathogenesis involves the interplay of genetic, environmental factors, and lifestyle choices. With the rising prevalence and increasing associated chronic complications, identifying and understanding ...

Deciphering the Pharmacological Potential of Kouqiangjie Formula for the Treatment of Diabetic Periodontitis Based on Network Pharmacology, Machine Learning, Molecular Dynamics, and Animal Experiments.

Drug design, development and therapy
BACKGROUND: Periodontitis (PD) and type 2 diabetes mellitus (T2DM) represent interlinked global health burdens, commonly causing significant clinical complications when coincident. Therefore, managing both conditions (T2DM with periodontitis, DP) sim...

Actuation-Mediated Compression of a Mechanoresponsive Hydrogel by Soft Robotics to Control Release of Therapeutic Proteins.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Therapeutic proteins, the fastest growing class of pharmaceuticals, are subject to rapid proteolytic degradation in vivo, rendering them inactive. Sophisticated drug delivery systems that maintain protein stability, prolong therapeutic effects, and r...

Artificial intelligence derived categorizations significantly improve HOMA IR/β indicators: Combating diabetes through cross-interacting drugs.

Computers in biology and medicine
Improvements in the homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of beta-cell function (HOMA-β) significantly reduce the risk of disabling diabetic pathies. Nanoparticle (AuNP-AgNP)-metformin are conce...

Diagnostic application in streptozotocin-induced diabetic retinopathy rats: A study based on Raman spectroscopy and machine learning.

Journal of biophotonics
Vision impairment caused by diabetic retinopathy (DR) is often irreversible, making early-stage diagnosis imperative. Raman spectroscopy emerges as a powerful tool, capable of providing molecular fingerprints of tissues. This study employs RS to dete...