COVID-19

Interpretable machine learning for predicting low-dose methylprednisolone effectiveness in long COVID.

Long COVID is a chronic, multisystem disease with limited response to conventional treatments. While low-dose methylprednisolone has shown effectiveness in some patients, individual responses vary, and accurate predictive tools are lacking. This retrospective study included 330 long COVID patients who received low-dose methylprednisolone treatment across three hospitals. Patients were divided into...

A chalcone-rich extract from licorice root inhibits liver steatosis and fibrosis via regulating PPARα and TGFβ signaling.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major liver disorder, which seriously affects human health globally. However, there are currently no satisfactory treatments for MASLD. The extraction of licorice root (Glycyrrhiza inflata Bat.) has multiple therapeutic effects, but it has not yet been fully explored for its therapeutic potential to liver steatosis a...

Sequential active learning for medium optimization in mAb production.

Monoclonal antibodies (mAbs) are key therapeutics for diseases like cancer and autoimmunity. The production of mAbs relies on cell culture, in which t...

Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.

Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic la...

Integrating molecular diagnostics and artificial intelligence in chronic microbial disease.

Chronic microbial diseases, often driven by biofilm formation, pose a persistent global health burden due to their complex diagnosis, resistance mecha...

Integrated assessment of total airway count and pneumonia volume on chest computed tomography as a prognostic biomarker for coronavirus disease.

OBJECTIVES: The clinical relevance of computed tomography (CT)-based airway tree structure is unclear. Herein, we used artificial intelligence to segm...

SPP1-CD44 signaling contributes to the mechanisms and therapeutic implications in intervertebral disc degeneration.

BACKGROUND: Intervertebral disc degeneration (IVDD) is a major pathological cause of chronic back pain and reduced mobility. Among emerging molecular ...

Wirelessly transmitted subthalamic nucleus signals decode endogenous pain levels in Parkinson's disease patients.

Pain is a prominent non-motor symptom of Parkinson's disease (PD); it may appear in various levels (elevated or diminished) during waking hours and su...

EvoZymePro-Cat: A Protein-Ligand-Aware Deep Learning Framework for Predicting Mutation Effects in Enzyme Function.

Enzymes are biological catalysts that speed up chemical reactions in an eco-friendly way. Precise enzyme design is hindered by vast sequence space and...

EGR1 promotes ferroptosis in endometriosis through transcriptional activation of HMOX1.

Endometriosis (EM) affects approximately 10% of women of reproductive age and remains a prevalent estrogen-dependent gynecological disorder with limit...

Multi-scale feature enhancement in multi-task learning for medical image analysis.

Traditional deep learning approaches in medical image analysis usually focus on either segmentation or classification, which limits their ability to e...

Evolution and design shape protein dynamics in LOV domains - spanning picoseconds to days.

Light-sensitive proteins allow organisms to perceive and respond to their environment, and have diversified over billions of years. Among these, Light...

Development of an Infectious Disease Vulnerability Index (IDVI) for dairy farms: A data-driven approach to assessing risk and informing biosecurity practices.

Dairy farms are vulnerable to a wide range of infectious diseases, which can have significant economic and public health consequences. However, there ...

Integrative analysis of transcriptomic data reveals a predictive gene signature for chemoradiotherapy response in rectal cancer.

Locally advanced rectal cancer (LARC) is treated with neoadjuvant chemoradiotherapy (nCRT), but only a minority of patients achieve a pathological com...

NLRP1 as a Novel Pyroptosis Biomarker in Irreversible Pulpitis: A Laboratory Investigation and Animal Model Study.

AIM: Irreversible pulpitis poses a significant clinical burden due to progressive inflammatory pulp damage. While inflammatory mechanisms are central ...

Analysis of PANoptosis-related genes in septic cardiomyopathy by bioinformatics, machine learning and experimental validation.

The mechanisms underlying the pathogenesis of septic cardiomyopathy (SCM) are intricate and incompletely understood. PANoptosis is a novel type of pro...

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

BACKGROUND: Multiple sclerosis (MS) and psoriasis are both immune-mediated inflammatory diseases. Previous studies have reported comorbidity between M...

Optimization of NIRS-based models for predicting quality and gas production traits of fresh alfalfa silage via machine learning.

Near-infrared spectroscopy (NIRS) prediction models offer an expeditious method for assessing the nutritional value of feedstuffs, however, developing...

A novel multimodal diagnostic framework integrating hyperspectral imaging and deep learning for predicting RET gene mutations in medullary thyroid carcinoma.

BACKGROUND AND OBJECTIVE: Medullary thyroid carcinoma (MTC) is an aggressive malignancy driven predominantly by activating mutations in the RET proto-...

Self-Driving Development of Perfusion Processes for Monoclonal Antibody Production.

The development of autonomous agents in bioprocess development is crucial for advancing biopharma innovation. Time and resources required to develop a...