Rheumatology

Preliminary study on the application of deep learning system to diagnosis of Sjögren's syndrome on CT images.

OBJECTIVES: This study estimated the diagnostic performance of a deep learning system for detection of Sjögren's syndrome (SjS) on CT, and compared it with the performance of radiologists.

Anti-Synchronization in Fixed Time for Discontinuous Reaction-Diffusion Neural Networks With Time-Varying Coefficients and Time Delay.

This paper studies the fixed-time anti-synchronization (FTAS) of discontinuous reaction-diffusion neural networks (DRDNNs) with both time-varying coefficients and time delay. First, differential inclusion theory is used to deal with the influence caused by discontinuous activations. In addition, a new fixed-time convergence theorem is used to handle the time-varying coefficients. Second, a novel s...

Machine Learning Methods to Predict Social Media Disaster Rumor Refuters.

This research provides a general methodology for distinguishing disaster-related anti-rumor spreaders from a non-ignorant population base, with strong...

Serum Pyridinoline is Associated With Radiographic Joint Erosions in Rheumatoid Arthritis.

OBJECTIVES: This study aims to compare the serum pyridinoline (Pyd) levels between rheumatoid arthritis (RA) patients and healthy controls and to dete...

Building the drug-GO function network to screen significant candidate drugs for myasthenia gravis.

Myasthenia gravis (MG) is an autoimmune disease. In recent years, considerable evidence has indicated that Gene Ontology (GO) functions, especially GO...

Acute renal failure in systemic sclerosis revealing Goodpasture syndrome: "All that glitters is not scleroderma renal crisis".

The most common cause of acute renal failure in systemic sclerosis patients is scleroderma renal crisis but other etiologies have to be considered suc...

Quantification of apixaban in human plasma using ultra performance liquid chromatography coupled with tandem mass spectrometry.

Apixaban, an inhibitor of direct factor Xa, is used for the treatment of venous thromboembolic events or prevention of stroke. Unlike many other antic...

Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes.

OBJECTIVES: Juvenile idiopathic arthritis (JIA) is the most common class of childhood rheumatic diseases, with distinct disease subsets that may have ...

Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.

BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accor...

Synthesis of chitosan nanoparticles, chitosan-bulk, chitosan nanoparticles conjugated with glutaraldehyde with strong anti-cancer proliferative capabilities.

In recent years, natural and synthetic polymers have attracted much attention due to their great potentials in medical science. In the present study, ...

Synthesis, characterization, antimicrobial and antimetastatic activity of silver nanoparticles synthesized from Ficus ingens leaf.

Cancer incidence is still increasing due to inadequate responsive treatments. Inertness and biocompatibility of nanoparticles synthesized using plant ...

The Importance of G-protein Coupled Estrogen Receptor in Patients With Fibromyalgia.

OBJECTIVES: This study aims to analyze the G-protein coupled estrogen receptor (GPER/GPR30) activity in patients with fibromyalgia syndrome (FMS).

Enhanced Anti-tumor of Pep-1 Modified Superparamagnetic Iron Oxide/PTX Loaded Polymer Nanoparticles.

Superparamagnetic iron-oxide nanoparticle (SPION) has gained tremendous attention for drug delivery applications due to their unique properties. In th...

Simulation program of a cytotoxic compounding robot for monoclonal antibodies and anti-infectious sterile drug preparation.

The aim of this study was to develop a specific simulation program for the validation of a cytotoxic compounding robot, KIRO® Oncology, for the prepar...

Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning.

Techniques of data mining and machine learning were applied to a large database of medical and facility claims from commercially insured patients to d...

Fully automated detection of retinal disorders by image-based deep learning.

PURPOSE: With the aging population and the global diabetes epidemic, the prevalence of age-related macular degeneration (AMD) and diabetic macular ede...

Application of machine learning in rheumatic disease research.

Over the past decade, there has been a paradigm shift in how clinical data are collected, processed and utilized. Machine learning and artificial inte...

Anti-proliferative Effect of a Novel Anti-oxidative Peptide in Hanwoo Beef on Human Colorectal Carcinoma Cells.

The present study aimed to characterise anti-oxidant peptides from water-soluble protein extracts of Hanwoo beef and evaluate their anti-proliferative...

Isolation of a Strain Producing Anti-staphylococcal Bacteriocin.

Bacteriocin is ribosomally synthesized by bacteria and inhibits closely related species. In this study we aimed at isolating lactic acid bacteria prod...

BPA, BADGE and analogues: A new multi-analyte LC-ESI-MS/MS method for their determination and their in vitro (anti)estrogenic and (anti)androgenic properties.

Information on the occurrence and endocrine potencies of analogues of bisphenol A (BPA) and diglycidyl ester derivatives (BDGEs) of BPA and BPF is lim...