Hepatitis

DeepHeptox: An Interpretable Deep Learning Model for Multi-Endpoint Hepatotoxicity Prediction of Chemical Compounds.

Hepatotoxicity represents a major adverse outcome of chemical exposure, as the liver plays a central role in xenobiotic metabolism and detoxification. Accurate prediction of hepatotoxicity is therefore essential for drug development and chemical safety assessment. Computational methods provide an efficient and ethical alternative for assessing hepatotoxicity before experimental validation. To addr...

Age-Related Brain Atrophy Mediates a Composite Outcome of One-Year Ischemic Stroke Recurrence and All-Cause Mortality Through YKL-40-Related Inflammatory Pathways: A Structural Equation Model.

Chronological age is a strong predictor of poor outcomes after ischemic stroke but may not fully capture underlying biological vulnerability. This study investigated whether age-related brain atrophy and plasma YKL-40, a marker of astroglial inflammation, mediate the association between age and the one-year risk of ischemic stroke recurrence or all-cause mortality. Data were obtained from 4,305 pa...

Bridging the Vaccine Gap: Scientific and Technological Advances for Diseases Lacking Effective Vaccines.

Despite remarkable achievements in infectious disease control, more than 20 major pathogens responsible for significant global morbidity and mortality...

DB-IRES: a deep learning model based on ensemble learning for predicting internal ribosome entry sites.

BACKGROUND: Internal ribosome entry sites (IRES) are cap-independent translation initiation elements present in specific viral and cellular mRNAs. The...

A combi-elasto ultrasound based deep learning model on liver fibrosis staging for suspected MASLD/MASH patients.

OBJECTIVES: Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) weakened the ...

Artificial Intelligence Across the Vaccine Clinical Trial Lifecycle: Evidence, Readiness, and Guardrails.

Artificial intelligence (AI) is increasingly being used to support clinical research, but its value in vaccine clinical trials requires careful eviden...

Electrically Coded Retinomorphic Spectrophotodetector.

Accurate color sensing is essential for applications ranging from materials analysis to autonomous vision, yet compact systems that can classify color...

Precision Medicine for Anticoagulation Strategies in the Cath Lab: Part 2.

PURPOSE OF REVIEW: Intraprocedural anticoagulation during percutaneous coronary intervention (PCI) remains particularly challenging in high-risk and u...

Development and validation of an interpretable machine learning model for predicting in-hospital mortality among critically ill patients with liver cirrhosis.

This study aimed to develop and validate an interpretable machine learning model for early prediction of in-hospital mortality in critically ill patie...

AI-assisted fragment-based drug discovery of SARS-CoV-2 macrodomain binders validated by NMR and X-ray crystallography.

Fragment-based drug discovery (FBDD) is an effective approach for exploring chemical space using small, low-affinity fragments as starting points to f...

Artificial intelligence powered decoding of Plasmodium falciparum sporozoite motility patterns.

Sporozoites (SPZ), the infective mosquito stage of Plasmodium falciparum malaria, are widely studied as therapeutic targets for antibodies either endo...

Cancer Vaccine Development: Toward Artificial Intelligence-Assisted Personalized Cell Membrane Nanovaccine.

Cancer vaccines are an attractive immunotherapeutic approach, and numerous clinical trials are ongoing. However, most candidates have not achieved sta...

From sites to structure to serology: a roadmap for structure-aware molecular evolution of antigenically evolving viruses.

The genomic deluge has pushed viral molecular evolution into a site-resolved era. For antigenically evolving viruses such as influenza and severe acut...

The Role of Artificial Intelligence and Machine Learning in Predictive Virology: Forecasting, Tracking, and Combating Viral Threats.

The escalating threat of viral pandemics, dramatically illustrated by the COVID-19 crisis, has exposed the critical shortcomings of conventional react...

Integrating CRISPR/Cas Biosensors with Advanced Platforms: A Holistic Path Toward Preamplification-free, Multiplexed, and Continuous Molecular Monitoring.

The paradigm of molecular diagnostics has been transformed by the repurposing of CRISPR-Cas systems from being gene-editing tools to nucleic acid dete...

A machine learning approach to non-invasive prediction of hepatic decompensation in compensated advanced chronic liver disease: the CIRI model.

BACKGROUND & AIMS: Hepatic venous pressure gradient (HVPG) is the gold standard for assessment of prognosis in compensated advanced chronic liver dise...

Reversing cancer cell behavior using AI-guided CRISPR and quantum nanobiology: a systems-based approach to epigenetic reprogramming.

Treatment effectiveness is hindered by the phenotypic plasticity of cancer and the genetic complexity of tumors. However, CRISPR-Cas-based medicines f...

Circulating multi-omic signature of disease severity and cholangiocarcinoma in primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease often associated with inflammatory bowel disease (IBD) that ca...

Integrated multi-omics and machine learning identify OGDHL as a key regulator of glioblastoma progression and antitumor immunity via glutamine metabolism and histone lactylation.

BACKGROUND: Glioblastoma (GBM) has an extremely poor prognosis, and its malignant progression is closely associated with glutamine metabolic reprogram...

Cellular hallmarks and aging clock of the human lung parenchyma.

Aging affects lung function, predisposing older adults to respiratory diseases; however, the cellular and molecular mechanisms of lung aging are not f...