Infectious Disease

Vaccines

Latest AI and machine learning research in vaccines for healthcare professionals.

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Natural Language-Assisted Multi-modal Medication Recommendation

Combinatorial medication recommendation(CMR) is a fundamental task of healthcare, which offers opportunities for clinical physicians to provide more precise prescriptions for patients with intricate health conditions, particularly in the scenarios of long-term medical care. Previous research efforts have sought to extract meaningful information from electronic health records (EHRs) to facilitate...

An organotypic in vitro model of human papillomavirus-associated precancerous lesions allowing automated cell quantification for preclinical drug testing

A durable organotypic epithelial raft culture was established as a model of cervical precancer. Plausible time- and dose-dependent effects of cisplatin, 5-FU, and sinecatechins treatment were observed on keratinocytes and HPV-transformed cells. Treatment effects were reliably quantified using machine learning-based cell classification. This model may serve as a platform for preclinical investigati...

Language models learn to represent antigenic properties of human influenza A(H3) virus

Given that influenza vaccine effectiveness depends on a good antigenic match between the vaccine and circulating viruses, it is important to assess th...

CoV-UniBind: A Unified Antibody Binding Database for SARS-CoV-2

Since the emergence of SARS-CoV-2, numerous studies have investigated antibody interactions with viral variants in vitro, and several datasets have be...

DeepPROTECTNeo: A Deep learning-based Personalized and RV-guided Optimization tool leveraging TCR Epitope interaction using Context-aware Transformers

The development of personalized cancer vaccines relies heavily on accurately identifying neoepitopes capable of eliciting strong immune responses. T c...

Integrating Artificial Intelligence-Driven Digital Pathology and Genomics to Establish Patient-Derived Organoids as a Novel Alternative Model for Drug Response in Head and Neck Cancer

Patient-derived organoids (PDOs) are emerging as advanced 3D ex vivo novel alternative method (NAM) preclinical models, offering significant advantage...

Mapping antigenic evolution of influenza A virus using deep learning-based prediction of hemagglutination inhibition titers

Seasonal influenza remains a significant public health challenge through unpredictable antigenic drift, where accumulated mutations enable immune evas...

Reengineering the antigen optimization process for superior neoantigen vaccine design

Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, the vast sequence space (>109 possible peptides) a...

From sequence to scaffold: computational design of protein nanoparticle vaccines from AlphaFold2-predicted building blocks

Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibod...

APDeeM: A machine Learning strategy towards Effective Peptide Vaccine Candidates Identification against Different Types of Viruses

Viral infections pose significant global health challenges, underscoring the urgent need for improved medications. Nevertheless, traditional medicinal...

A structure-informed evolutionary model for predicting viral immune escape and evolution

Persistent emergence of viral variants capable of evading host immunity constitutes a significant threat to public health. This antigenic evolution fr...

T-cell receptor specificity landscape revealed through de novo peptide design

T-cells play a key role in adaptive immunity by mounting specific responses against diverse pathogens. An effective binding between T-cell receptors (...

T-SCAPE: T-cell Immunogenicity Scoring via Cross-domain Aided Predictive Engine

T-cell immunogenicity, the ability of peptide fragments to elicit T-cell responses, is a critical determinant of the safety and efficacy of protein th...

Hollow-fibre biomanufacturing and cell-free engineering of HEK293 extracellular vesicles

Extracellular vesicles (EVs) are lipid-delineated nanoparticles that are produced by most cell types. EVs contain complex molecular cargoes that can h...

MAP-PRS: Multi-Ancestry Portfolio-Based Polygenic Risk Scores

Polygenic Risk Scores (PRS) are emerging tools for predicting an individual’s genetic risk for complex diseases. However, their usefulness in clinical...

peleke-1: A Suite of Protein Language Models Fine-Tuned for Targeted Antibody Sequence Generation

The discovery of therapeutic antibodies is a traditionally arduous process. Today, the lab-based process of antibody discovery consists of several tim...

An Immuno-Linguistic Transformer for Multi-Scale Modeling of T-Cell Spatiotemporal Dynamics

Understanding the spatiotemporal dynamics of T-cell clones is a critical challenge in immunology and immunotherapy, with direct implications for cance...

A study on edge devices for image classification of the Tasmanian devil (Sarcophilus harrisii) for vaccine delivery

A target-specific bait dispenser is required for oral bait vaccination of the endangered Tasmanian devil (Sarcophilus harrisii) against the deadly dev...

CHIMERA-DDR: A Machine Learning Framework for Classifying Heterogeneous Mismatch-Repair and Homologous-Recombination Deficiency Patterns in Prostate Cancer

Current DNA damage repair (DDR) biomarkers employ binary classifications that fail to capture the molecular complexity of tumors with concurrent repai...

ppLM-CO:Pre-trained Protein Language Model for Codon Optimization

Messenger ribonucleic acid (mRNA) vaccines represent a major advancement in synthetic biology, yet their efficacy remains limited by how efficiently t...

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