Rheumatoid Arthritis

Uncovering the therapeutic potential of Si-Miao-Yong-An decoction in abdominal aortic aneurysm: An integrative study combining network pharmacology, machine learning, molecular docking and dynamics simulation.

Abdominal aortic aneurysm (AAA) is a progressive and life-threatening vascular disorder characterized by abnormal dilation of the abdominal aorta and a high risk of rupture. Current pharmacological interventions remain limited in efficacy, highlighting the need for alternative therapeutic strategies. Si-Miao-Yong-An Decoction (SMYAD), a classical formula in traditional Chinese medicine, has demons...

Artificial intelligence in age-related macular degeneration: Advancing diagnosis, prognosis, and treatment.

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in older adults. While anti-vascular endothelial growth factor (anti-VEGF) therapy and novel treatments for geographic atrophy have improved management, timely diagnosis and personalized intervention remain a challenge. Artificial intelligence (AI), such as machine learning and deep learning models, shows promise...

Nivolumab plus ipilimumab for potentially resectable hepatocellular carcinoma: Long-term efficacy and biomarker exploration.

BACKGROUND & AIMS: Immune checkpoint inhibitor-based combination therapy has demonstrated high objective response rates in patients with hepatocellula...

Comparison of ChatGPT-3.5, ChatGPT-4.0 and DeepSeek in generating dietary plans for patients with chronic kidney disease: A focus on nutritional accuracy and dietary inflammation.

BACKGROUND: Our previous research indicated that ChatGPT-3.5 was inadequate in generating nutritionally accurate dietary plans for patients with chron...

Elucidating anti-triple-negative breast cancer mechanisms and mitigating toxicity of Fritillaria thunbergii Miq.: A multi-omics and network pharmacology approach.

ETHNOPHARMACOLOGICAL RELEVANCE: Fritillaria thunbergii Miq. (Zhebeimu, ZBM) is traditionally recognized in Chinese medicine for its effects of clearin...

AIP-TranLAC: A Transformer-Based Method Integrating LSTM and Attention Mechanism for Predicting Anti-inflammatory Peptides.

Anti-inflammatory peptides (AIPs) have emerged as potential therapeutic candidates for managing various inflammatory disorders, but their computationa...

Microbiome-metabolome generated bile acids gatekeep infliximab efficacy in Crohn's disease by licensing M1 suppression and Treg dominance.

INTRODUCTION: Despite the effectiveness of infliximab in treating Crohn's disease (CD), up to 40 % of patients fail to respond adequately. OBJECTIVES:...

Emerging innovations in ophthalmic drug delivery for diabetic retinopathy: a translational perspective.

Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes and a leading cause of vision impairment worldwide. Despite advancem...

Machine-Learning-Driven Discovery of -Phenylbenzenesulfonamides as a Novel Chemotype for Lactate Dehydrogenase A Inhibition with Anti-Pancreatic Cancer Activity.

Lactate dehydrogenase A (LDHA) is a promising target for cancer therapy due to its crucial role in aerobic glycolysis. Despite extensive efforts, the ...

Organic dual-channel transistors for reconfigurable signal modulation and anti-counterfeiting.

The development of integrated circuits and artificial intelligence demands electronic devices with versatile functions. While unconventional transisto...

Artificial intelligence-driven discovery of YH395A: A novel TGFβR1 inhibitor with potent anti-tumor activity against triple-negative breast cancer.

Characterized by high malignancy and limited treatment efficacy, triple-negative breast cancer (TNBC) remains a clinically challenging subtype within ...

Electrophysiological-based automatic subgroups diagnosis of patients with chronic dysimmune polyneuropathies.

BACKGROUND: Chronic Dysimmune Polyneuropathies (CDP) encompass a group of conditions characterized by autoimmune etiology targeting myelin and/or axon...

Unlocking potent anti-tuberculosis natural products through structure-activity relationship analysis.

Tuberculosis (TB) remains a world health problem due to the high number of affected individuals, high mortality rates, prolonged treatment durations, ...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contri...

D-optimal candexch algorithm-enhanced machine learning UV-spectrophotometry for five-analyte determination in novel anti-glaucoma formulations and ocular fluids: four-color sustainability framework with NQS assessment and UN-SDG integration.

The novel anti-glaucoma ophthalmic preparation containing latanoprost, netarsudil, and benzalkonium chloride has posed a significant challenge due to ...

Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis.

Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment resp...

Driving Multifunctional Nanomedicine Design for Non-Inflammatory Tumor Therapy with Integrated Machine Learning and Density Functional Theory.

Due to the promotive role of inflammation in tumor progression, designing multifunctional nanomedicines that synergistically combine anti-tumor and an...

A genotype-to-drug diffusion model for generation of tailored anti-cancer small molecules.

Despite advances in precision oncology, developing effective cancer therapeutics remains a significant challenge due to tumor heterogeneity and the li...

The effects of robot anthropomorphic characteristics on employees' anti-robot sabotage.

Robot anthropomorphic characteristics have not only been widely manifested in production practices, but their positive effects on human-robot interact...

Predicting PLGA nanoparticle size and zeta potential in synthesis for application of drug delivery via machine learning analysis.

This study employed multiple machine learning (ML) methods to model and predict key attributes of PLGA nanoparticles, specifically particle size and z...