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Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.

Journal of medicinal chemistry
Peptide-based drug discovery has surged with the development of peptide hormone-derived analogs for the treatment of diabetes and obesity. Machine learning (ML)-enabled quantitative structure-activity relationship (QSAR) approaches have shown great p...

A deep-learning-based threshold-free method for automated analysis of rodent behavior in the forced swim test and tail suspension test.

Journal of neuroscience methods
BACKGROUND: The forced swim test (FST) and tail suspension test (TST) are widely used to assess depressive-like behaviors in animals. Immobility time is used as an important parameter in both FST and TST. Traditional methods for analyzing FST and TST...

Identification of immune-related genes and small-molecule drugs in hypertension-induced left ventricular hypertrophy based on machine learning algorithms and molecular docking.

Frontiers in immunology
BACKGROUND: Left ventricular hypertrophy (LVH) is a common consequence of hypertension and can lead to heart failure. The immune response plays an important role in hypertensive LVH; however, there is no comprehensive method to investigate the mechan...

Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidat...

Biohybrid microrobots regulate colonic cytokines and the epithelium barrier in inflammatory bowel disease.

Science robotics
Cytokines have been identified as key contributors to the development of inflammatory bowel disease (IBD), yet conventional treatments often prove inadequate and carry substantial side effects. Here, we present an innovative biohybrid robotic system,...

Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach.

International immunopharmacology
OBJECTIVES: This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury (AKI), including sepsis-associated AKI (SA-AKI), a frequent complication in critically ill sepsis patients.

Integrated biomarker profiling for predicting the response of type 2 diabetes to metformin.

Diabetes, obesity & metabolism
AIM: To explore biomarkers that can predict the response of type 2 diabetes (T2D) patients to metformin at an early stage to provide better treatment for T2D.

OrganoIDNet: a deep learning tool for identification of therapeutic effects in PDAC organoid-PBMC co-cultures from time-resolved imaging data.

Cellular oncology (Dordrecht, Netherlands)
PURPOSE: Pancreatic Ductal Adenocarcinoma (PDAC) remains a challenging disease due to its complex biology and aggressive behavior with an urgent need for efficient therapeutic strategies. To assess therapy response, pre-clinical PDAC organoid-based m...

3DVascNet: An Automated Software for Segmentation and Quantification of Mouse Vascular Networks in 3D.

Arteriosclerosis, thrombosis, and vascular biology
BACKGROUND: Analysis of vascular networks is an essential step to unravel the mechanisms regulating the physiological and pathological organization of blood vessels. So far, most of the analyses are performed using 2-dimensional projections of 3-dime...

Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning.

The Analyst
Radiation-induced lung injury (RILI) is a dose-limiting toxicity for cancer patients receiving thoracic radiotherapy. As such, it is important to characterize metabolic associations with the early and late stages of RILI, namely pneumonitis and pulmo...