Hepatitis

First-in-Human Study of a First-in-Class AI-Designed Monoclonal Antibody (GB-0669) Against the Conserved SARS-CoV-2 Spike S2 Stem Helix

Antibodies against the SARS-CoV-2 spike receptor-binding domain provided effective COVID-19 treatment until resistant variants emerged. GB-0669 is a half-life extended monoclonal antibody optimized using artificial intelligence, targeting the conserved spike S2 stem helix, a region with limited selective pressure from natural infection-or vaccine-induced antibody responses. Pre-clinical safety stu...

Systems Vaccinology Reveals Distinct Immune Signatures of Inhaled and Intramuscular SARS-CoV-2 Vaccination in Humans

Mucosal vaccines may reduce both infection and transmission by engaging local immunity, yet the immunological pathways they activate in humans remain poorly defined. Here, we present a comprehensive systems vaccinology analysis of a Modified Vaccinia virus Ankara (MVA)-based SARS-CoV-2 vaccine candidate tested in two distinct phase 1 clinical trials as a booster vaccination with either inhaled or ...

Microscale Multiplexed Antigen-Specific Antibody Fc Profiling for Point-of-Care Diagnosis of Tuberculosis

Accurate, affordable tuberculosis (TB) diagnostics that do not require sputum samples are urgently needed for TB control and elimination. Prior serolo...

A three-dose MVA-BN mpox vaccination series improves the quality of anti-monkeypox virus immunity

The 2022 global outbreak of clade IIb mpox represented a turning point in public health’s handling of poxviruses. The primary vaccine available for pr...

Comparison of local large language models for extraction of signs and symptoms data from electronic health records

Electronic health records (EHRs) provide a large source of data that can be used for research purposes. Extraction of information from unstructured cl...

Estrogen upregulates NF-κB and TNF signaling in B cells to cause sex and age differences in antibody responses to seasonal influenza vaccination

Sex differences in the humoral immune responses to the seasonal quadrivalent influenza vaccine (QIV) in young adults (YA; 18-49yo) or high dose QIV in...

Enterotype-stratified gut microbial signatures in MASLD and cirrhosis based on integrated microbiome data.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health challenge, characterized by significant vari...

Identification of hub immune-related genes and construction of predictive models for systemic lupus erythematosus by bioinformatics combined with machine learning.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that involves multiple systems. SLE is characterized by the production of autoantib...

Predicting in-hospital mortality in patients with alcoholic cirrhosis complicated by severe acute kidney injury: development and validation of an explainable machine learning model.

BACKGROUND: At present, there are no specialized models for predicting mortality risk in patients with alcoholic cirrhosis complicated by severe acute...

Artificial intelligence in vaccine research and development: an umbrella review.

BACKGROUND: The rapid development of COVID-19 vaccines highlighted the transformative potential of artificial intelligence (AI) in modern vaccinology,...

Identification of hub gene for the pathogenic mechanism and diagnosis of MASLD by enhanced bioinformatics analysis and machine learning.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a heterogeneous disease caused by multiple etiologies. It is characterized by exce...

Modeling protective meningococcal antibody responses and factors influencing antibody persistence following vaccination with MenAfriVac using machine learning.

Meningococcal meningitis poses a significant public health burden in the meningitis belt region of sub-Saharan Africa. The introduction of the meningo...

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe ac...

Analyzing Country-Level Vaccination Rates and Determinants of Practical Capacity to Administer COVID-19 Vaccines

The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Globa...

E2ED^2:Direct Mapping from Noise to Data for Enhanced Diffusion Models

Diffusion models have established themselves as the de facto primary paradigm in visual generative modeling, revolutionizing the field through remar...

AI-Driven Non-Invasive Detection and Staging of Steatosis in Fatty Liver Disease Using a Novel Cascade Model and Information Fusion Techniques

Non-alcoholic fatty liver disease (NAFLD) is one of the most widespread liver disorders on a global scale, posing a significant threat of progressin...

An Integrated Approach to Develop a Potent Vaccine Candidate Construct Against Prostate Cancer by Utilizing Machine Learning and Bioinformatics.

BACKGROUND: Prostate cancer is the most common malignancy among males. Prostaglandin G/H synthase (PGHS) is an essential enzyme in the synthesis of pr...

Deep Neural Network-Based Prediction of B-Cell Epitopes for SARS-CoV and SARS-CoV-2: Enhancing Vaccine Design through Machine Learning

The accurate prediction of B-cell epitopes is critical for guiding vaccine development against infectious diseases, including SARS and COVID-19. Thi...

Exploring the Sparsity-Quantization Interplay on a Novel Hybrid SNN Event-Driven Architecture

Spiking Neural Networks (SNNs) offer potential advantages in energy efficiency but currently trail Artificial Neural Networks (ANNs) in versatility,...

Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics.

Recent advances in single-cell RNA-Sequencing (scRNA-Seq) technologies have revolutionized our ability to gather molecular insights into different phe...