Rheumatology

Using Deep Learning to Segment Retinal Vascular Leakage and Occlusion in Retinal Vasculitis.

PURPOSE: Retinal vasculitis (RV) is characterised by retinal vascular leakage, occlusion or both on fluorescein angiography (FA). There is no standard scheme available to segment RV features. We aimed to develop a deep learning model to segment both vascular leakage and occlusion in RV.

Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep learning-based feature extraction.

Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a promising therapeutic approach. Yet, fundamental questions concerning anti-angiogenic therapy remain unanswered, partly due to the scale and resolution gap between...

Prediction of hyperuricemia in people taking low-dose aspirin using a machine learning algorithm: a cross-sectional study of the National Health and Nutrition Examination Survey.

Hyperuricemia is a serious health problem related to not only gout but also cardiovascular diseases (CVDs). Low-dose aspirin was reported to inhibit ...

Machine Learning in Modeling Disease Trajectory and Treatment Outcomes: An Emerging Enabler for Model-Informed Precision Medicine.

The increasing breadth and depth of resolution in biological and clinical data, including -omics and real-world data, requires advanced analytical tec...

Using real-world data to inform dosing strategies of rituximab for pediatric patients with frequent-relapsing or steroid-dependent nephrotic syndrome: a prospective pharmacokinetic-pharmacodynamic study.

Rituximab is frequently used off-label for the treatment of frequent-relapsing/steroid-dependent nephrotic syndrome (FRNS/SDNS). However, the optimal...

Anti-ultraviolet, antibacterial, and biofilm eradication activities against of melanins and melanin derivatives from and .

and produced significant amounts of water-insoluble melanins, and our previous study successfully enhanced their water solubility by arginine modifi...

Using deep learning and molecular dynamics simulations to unravel the regulation mechanism of peptides as noncompetitive inhibitor of xanthine oxidase.

Xanthine oxidase (XO) is a crucial enzyme in the development of hyperuricemia and gout. This study focuses on LWM and ALPM, two food-derived inhibitor...

Serological and Molecular Characterization of Occult HBV Infection in Blood Donors from South Italy.

Despite good vaccine coverage and careful blood donor selection policies, hepatitis B virus (HBV) is still the most frequent viral infection among blo...

Preparation and Characterisation of Zinc Diethyldithiocarbamate-Cyclodextrin Inclusion Complexes for Potential Lung Cancer Treatment.

Zinc diethyldithiocarbamate (Zn (DDC)), a disulfiram metabolite (anti-alcoholism drug), has shown a strong anti-cancer activity in vitro. However, its...

Ct-based subregional radiomics using hand-crafted and deep learning features for prediction of therapeutic response to anti-PD1 therapy in NSCLC.

PURPOSE: To develop and externally validate subregional radiomics for predicting therapeutic response to anti-PD1 therapy in non-small-cell lung cance...

Prospective Antiviral Effect of Aqueous Extract against COVID-19 Infection.

Marine algal extracts exhibit a potent inhibitory effect against several enveloped and non-enveloped viruses. The infection of severe acute respirator...

A deep learning framework for predicting molecular property based on multi-type features fusion.

Extracting expressive molecular features is essential for molecular property prediction. Sequence-based representation is a common representation of m...

Anti-Staphylococcal, Anti-Candida, and Free-Radical Scavenging Potential of Soil Fungal Metabolites: A Study Supported by Phenolic Characterization and Molecular Docking Analysis.

and are recognized as causative agents in numerous diseases, and the rise of multidrug-resistant strains emphasizes the need to explore natural sour...

Anti-Dengue: A Machine Learning-Assisted Prediction of Small Molecule Antivirals against Dengue Virus and Implications in Drug Repurposing.

Dengue outbreaks persist in global tropical regions, lacking approved antivirals, necessitating critical therapeutic development against the virus. In...

Thyrotoxic Cardiomyopathy Unveiled: Insights From a Compelling Case Report.

Thyrotoxicosis is a clinical condition characterized by inappropriately elevated thyroid hormone levels in the bloodstream, leading to systemic effect...

Postbiotic Activities of : Impacts on Viability, Structural Integrity, and Cell Death Markers in Human Intestinal C2BBe1 Cells.

Acute diarrheal disease (ADD) caused by rotavirus (RV) contributes significantly to morbidity and mortality in children under five years of age. Curre...

The Potential for Genotoxicity, Mutagenicity and Endocrine Disruption in Triclosan and Triclocarban Assessed through a Combination of In Vitro Methods.

Triclosan and Triclocarban, preservatives widely used in cosmetics and other consumer products, underwent evaluation using a battery of new-approach m...

Non-invasive prediction of the chronic degree of lupus nephropathy based on ultrasound radiomics.

OBJECTIVE: Through machine learning (ML) analysis of the radiomics features of ultrasound extracted from patients with lupus nephritis (LN), this atte...

Validating the Health Benefits of Coffee Berry Pulp Extracts in Mice with High-Fat Diet-Induced Obesity and Diabetes.

The effects of coffee ( L.) berry pulp extracts (CBP extracts) on the improvement of diabetes, obesity, and non-alcoholic fatty liver disease (NAFLD) ...

Exploring the joint potential of inflammation, immunity, and receptor-based biomarkers for evaluating ME/CFS progression.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic condition with no identified diagnostic biomarkers t...