AIMC Topic: Antigens, Bacterial

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Rapid screening for acute rheumatic fever using machine learning analysis of host tissue reactive antibodies.

Scientific reports
Acute Rheumatic Fever and Rheumatic Heart Disease (ARF/RHD) affect over 45 million people globally. ARF/RHD are autoimmune complications following group A streptococcal infections. Current diagnosis of ARF requires thorough medical examination, echoc...

The multiplexed single-tier InBios Lyme Detect Multiplex ELISA is more sensitive than standard two-tier tests in the early stages of Lyme disease.

Journal of clinical microbiology
UNLABELLED: There are nearly 500,000 cases of Lyme disease each year in the United States; 10%-20% of them result in the development of a debilitating chronic disease known as post-treatment Lyme disease. Existing standardized and modified two-tier t...

The potential to improve Lyme disease diagnostics through quantification of immunoglobulin class switching patterns.

Journal of clinical microbiology
N. Nair, A. Marques , E. J. Horn, G. Brown et al., J Clin Microbiol 63:e0034725, 2025, https://doi.org/10.1128/jcm.00347-25 present data to demonstrate that infection by , the primary causative agent of Lyme disease in the USA, leads to immunoglobuli...

Field-oriented assessment of bovine tuberculosis in Tunisian cattle: IDR, PCR and serological test prediction based on AI approaches.

World journal of microbiology & biotechnology
Bovine tuberculosis (bTB), caused by Mycobacterium bovis (M. bovis), remains a major zoonotic and economically burdensome disease worldwide. In Tunisia, where bTB has remained present for many years, Efforts to eliminate the disease have been slowed ...

Overcoming Immune Evasion in : Strategies for Rational Vaccine Design.

ACS infectious diseases
remains one of the most elusive targets in bacterial vaccinology, primarily due to its complex immune evasion strategies and the phenomenon of immune imprinting. Despite decades of research and numerous clinical trials, no vaccine has demonstrated p...

Investigating genetic, antigenic, and structural diversity in the outer membrane protein, PorB: implications for vaccine design.

mBio
UNLABELLED: Vaccines targeting are needed to reduce disease burden and help address the problem of antimicrobial resistance, with an understanding of relationships between gonococcal genetics and molecules influencing diversity, infection, and the i...

A descriptor-free machine learning framework to improve antigen discovery for bacterial pathogens.

PloS one
Identifying protective antigens (PAs), i.e., targets for bacterial vaccines, is challenging as conducting in-vivo tests at the proteome scale is impractical. Reverse Vaccinology (RV) aids in narrowing down the pool of candidates through computational...

SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.

Frontiers in cellular and infection microbiology
INTRODUCTION: Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial diseases, particularly for Salmonella infections which remain a significant global health challenge...

Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis.

International immunopharmacology
Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate cancer, and it is classified under the group of mycoplasmas. Improved management of mycoplasma infections is essential due to the frequent ineffectiven...

VacSol-ML(ESKAPE) Machine learning empowering vaccine antigen prediction for ESKAPE pathogens.

Vaccine
The ESKAPE family, comprising Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., poses a significant global threat due to their heightened virulence and extensiv...