Lupus

The Synergism of β-Cyclodextrin and Fe3+ Enabled Anti-Swelling Ion-Conductive Hydrogels for Multimodal Underwater Sensing Aided by Machine Learning Algorithms.

As the key sensing component of flexible sensors, conductive hydrogels are prone to mechanical property degradation and signal deterioration owing to water absorption and swelling in underwater environments. Herein, an anti-swelling ion-conducting hydrogels are designed by incorporating ferric chloride (FeCl3) and β-cyclodextrin (β-CD) into acrylamide-acrylic acid copolymer (MA) via a one-pot meth...

Computational modeling-assisted discovery of the structural effects of phenylpropanoid derivatives on intracellular anti-Trypanosoma cruzi activity.

Previous investigations have demonstrated that n-hexacosyl p-coumarate, a natural product isolated from the Brazilian plant Baccharis sphenophylla, exhibits activity against the extracellular (trypomastigote) forms of Trypanosoma cruzi. Structural modification of this compound led to the synthesis of the n-hexyl p-coumarate derivative, which showed significantly improved bioactivity, achieving an ...

Identifying systemic lupus erythematosus from serum proteomic profiles using machine learning and genetic risk stratification.

OBJECTIVES: Proteome-wide risk models for lupus remain underexplored. We developed classification models to identify lupus from serum proteomic profil...

Human microphysiological systems of aging recreate the in vivo process expediting evaluation of anti-geronic strategies.

The search for biological mechanisms of human aging is stalled by a lack of suitable models, and it remains unknown whether and to what degree rejuven...

Anti-Disturbance Proximal Neural Networks for Composite Resource Allocation.

Composite resource allocation problems with general constraints are studied in this article, which frequently arise in networked systems such as smart...

Ameliorative effect of Rhus verniciflua Stokes on high-fat diet-induced obesity and advanced analysis with machine learning and deep learning-based network pharmacology.

AIMS: Obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) arise from impaired redox and energy homeostasis, yet current thera...

A decoction-inspired genetic algorithm and PPO reinforcement learning for intelligent molecular discovery: Anti-colorectal cancer candidates from the tiao-pi AnChang formula.

BACKGROUND: Colorectal cancer (CRC) remains among the leading causes of cancer-related mortality worldwide. The TiaoPi AnChang Decoction (TPACD), a tr...

Integrating bioinformatics, machine learning and molecular biology to elucidate the anti-allergic mechanisms of ginkgo biloba leaves.

Allergic diseases, encompassing allergic asthma, atopic dermatitis, food allergies, have emerged as substantial global public health challenges, with ...

AI-driven design of antimicrobial peptide for combating resistance and infectious diseases.

The growing threat of antimicrobial resistance, coupled with the challenges of developing new antibiotics, demands innovative therapeutic solutions. A...

A Scoping Review of Machine Learning Applications for Diagnosis, Classification, and Prognosis in Lupus Nephritis.

BACKGROUND: Over the past decade, machine learning (ML) has transformed histopathology, yet its application in lupus nephritis (LN) remains underexplo...

Task-adaptive sparse graph structure learning with error-edge pruning and anti-smoothing mechanism.

Graph Structure Learning (GSL) optimizes graph topologies to enhance node representations. This study reveals a critical limitation: while GSL excels ...

Detection of sample swapping in anti-doping investigations using machine learning.

The substitution of a urine sample that may result in an adverse analytical finding with a previously collected, clean sample is strictly prohibited u...

Protective Effects of Riociguat Against Contrast-Induced Nephropathy: An Experimental and Machine Learning-Based Study in Rats.

Contrast-induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventi...

Ultrasonic-assisted extraction, purification, identification, and bioactivity evaluation of phlorotannins from Sargassum fusiforme: A comparative study of RSM and SVM-GA.

Sargassum fusiforme is a medicinal and edible species present in China, Korea, and Japan, and its phlorotannins are considered valuable bioactive comp...

DeepStackVEGF a stacking ensemble deep learning framework for vascular endothelial growth factor prediction.

Vascular Endothelial Growth Factor (VEGF) plays a central role in angiogenesis, regulating both physiological processes such as wound healing, tissue ...

Pinostrobin attenuates microglia-mediated neuroinflammation after subarachnoid hemorrhage through modulation of the MYC-CTSL signaling axis.

Subarachnoid hemorrhage (SAH) is a life-threatening neurological emergency associated with high mortality and poor functional outcomes. Early brain in...

Polysaccharide-driven quality control of Gastrodia elata Blume: A multidimensional strategy integrating LC-MS/MS-based quantitative analysis, machine learning, and anti-neuroinflammatory bioactivity.

Gastrodia elata Blume (GE), a highly regarded traditional Chinese medicinal herb, is widely recognized for its diverse pharmacological activities. Cur...

Assessment of quantum chemical predictors for anti-colorectal cancer agents using QSAR modeling.

Optimizing the prediction of anti-colorectal cancer agent activity is essential aspect in the identification and creation of medications. Machine lear...

[Plasma proteomics in age-related macular degeneration].

BACKGROUND: Neovascular age-related macular degeneration (nAMD) shows a heterogeneous treatment response to anti-vascular endothelial growth factor (V...

Precision immunotherapies for systemic lupus erythematosus: From pathogenic targets to translational horizons.

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder in which aberrant B-cell activation, persistent autoantibody production, and...