Rheumatoid Arthritis

Risk Prediction of Liver Injury in Pediatric Tuberculosis Treatment: Development of an Automated Machine Learning Model.

PURPOSE: Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactions related to first-line anti-tuberculosis drugs in pediatric tuberculosis patients. This study aims to develop an automatic machine learning (AutoML) model for predicting the risk of anti-tuberculosis drug-induced liver injury (ATB-DILI) in children.

Opioid growth factor receptor overexpression exerts anti-hepatocellular carcinoma effects by activating P16 and P21 to inhibit proliferation and migration of HepG2 cells.

INTRODUCTION: Hepatocellular carcinoma (HCC) is the sixth most common type of cancer and the second leading cause of cancer death worldwide [19]. Opioid growth factor (OGF) has been shown to exhibit antitumour potential, binding to OGF receptor (OGFr). Naltrexone (NTX), an OGFr antagonist, is considered as a potential anti-cancer agent. However, the specific mechanism of how OGFr acts on HCC cells...

A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors.

In recent years, machine learning has gained substantial attention for its ability to predict complex chemical and biological properties, including th...

Machine Learning-Driven Prediction, Preparation, and Evaluation of Functional Nanomedicines Via Drug-Drug Self-Assembly.

Small molecules as nanomedicine carriers offer advantages in drug loading and preparation. Selecting effective small molecules for stable nanomedicine...

Automated Quantification of HER2 Amplification Levels Using Deep Learning.

HER2 assessment is necessary for patient selection in anti-HER2 targeted treatment. However, manual assessment of HER2 amplification is time-costly, l...

Artificial intelligence-driven identification and mechanistic exploration of synergistic anti-breast cancer compound combinations from L.- Hand.-Mazz. herb pair.

INTRODUCTION: The L. (PVL) and Hand.-Mazz. (TH) herb pair, which is commonly used in traditional Chinese medicine (TCM), has been applied for the tr...

Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.

BACKGROUND: First-line treatment for advanced gastric adenocarcinoma (GAC) with human epidermal growth factor receptor 2 (HER2) is trastuzumab combine...

Anti-ceramide antibody and sphingosine-1-phosphate as potential biomarkers of unresectable non-small cell lung cancer.

OBJECTIVES: Spingosine-1-phosphate (S1P) and ceramides are bioactive sphingolipids that influence cancer cell fate. Anti-ceramide antibodies might inh...

Evaluating generalizability of oncology trial results to real-world patients using machine learning-based trial emulations.

Randomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive el...

A novel non-invasive murine model for rapidly testing drug activity via inhalation administration against .

The efficacy of many compounds against is often limited when administered via conventional oral or injection routes due to suboptimal pharmacokinetic...

Sulforaphane as a promising anti-caries agents: inhibitory effects on and caries control in a rat model.

Dental caries has been one of the most prevalent diseases globally over the last few decades, threatening human oral and general health. The most crit...

A hybrid artificial neural network and multi-objective genetic algorithm approach to optimize extraction conditions of Mentha longifolia and biological activities.

In this work, artificial neural network coupled with multi-objective genetic algorithm (ANN-NSGA-II) has been used to develop a model and optimize the...

Comparison of the composition, immunological activity and anti-fatigue effects of different parts in sika deer antler.

BACKGROUND: Sika deer (, 1838) antler is a highly esteemed tonic renowned for its abundant assortment of polypeptides, polysaccharides, amino acids, a...

Investigating the anti-obesity potential of leaf bioactive compounds through machine learning and computational biology methods.

Obesity, a growing global health concern, is linked to severe ailments such as cardiovascular diseases, type 2 diabetes, cancer, and neuropsychiatric ...

Machine Learning-Engineered Nanozyme System for Synergistic Anti-Tumor Ferroptosis/Apoptosis Therapy.

Nanozymes with multienzyme-like activity have sparked significant interest in anti-tumor therapy via responding to the tumor microenvironment (TME). H...

How accurate are machine learning models in predicting anti-seizure medication responses: A systematic review.

IMPORTANCE: Current epilepsy management protocols often depend on anti-seizure medication (ASM) trials and assessment of clinical response. This may d...

Functional MRGPRX2 expression on peripheral blood-derived human mast cells increases at low seeding density and is suppressed by interleukin-9 and fetal bovine serum.

Primary human mast cells (MC) obtained through culturing of blood-derived MC progenitors are the preferred model for the study of MRGPRX2- IgE-media...

Generative Adversarial Network-Based Augmentation With Noval 2-Step Authentication for Anti-Coronavirus Peptide Prediction.

The virus poses a longstanding and enduring danger to various forms of life. Despite the ongoing endeavors to combat viral diseases, there exists a ne...

Hyb_SEnc: An Antituberculosis Peptide Predictor Based on a Hybrid Feature Vector and Stacked Ensemble Learning.

Tuberculosis has plagued mankind since ancient times, and the struggle between humans and tuberculosis continues. Mycobacterium tuberculosis is the le...

Phytochemical profiling and fractionation of extract versus silver nanoparticle-modified extract: assessment of photoprotective, anti-hemolytic, antibacterial, and anti-inflammatory properties.

INTRODUCTION: This study investigates the synthesis of silver nanoparticles (Ag NPs) using Helianthemum lippii extract and evaluates their photoprotec...