Allergy & Immunology

Virtual cell/virtual cell like: The key to unlocking a new era of HIV/AIDS treatment ?

Virtual Cell (VC) technology, as an interdisciplinary frontier at the intersection of systems biology and computational biology, aims to precisely simulate cellular biological behaviors through computer models. This paper systematically explores the potential applications of virtual cell technology in the study of Human Immunodeficiency Syndrome (AIDS), the current key challenges, and future devel...

Nanoparticle-based immunotherapeutic strategies to overcome cancer drug resistance: From biological barriers to artificial intelligence-driven design.

Although cancer immunotherapy has revolutionized oncology, its clinical efficacy remains substantially limited by both primary and acquired resistance. These resistance mechanisms are largely driven by complex biological barriers within the tumor microenvironment (TME) and insufficient tumor immunogenicity. Nanotechnology offers a promising strategy to overcome these barriers by enabling precise s...

AI-driven body composition atlas reveals its association with NSCLC immunotherapy outcome and molecular background: a multicenter study.

Although previous studies have linked body composition to immunotherapy efficacy, comprehensive multidimensional analyses with biological explanations...

Benchmarking Hybrid CNN-Transformer Versus Pure Transformer Architectures for Accelerated Hyperpolarized 129Xe MRI Reconstruction.

BACKGROUND: Hyperpolarized 129Xe MRI faces technical challenges including low signal-to-noise ratio and breath-hold constraints. Current literature fo...

A novel cuproptosis-related prognostic gene signature is identified by machine learning and integrative analyses in gliomas.

Recent studies have highlighted the impact of copper-induced cell death (cuproptosis) on cancer progression, prognosis, and treatment, but it remains ...

IGH::FENDRR and specific KRAS mutations define a novel B-ALL molecular subtype with poor chemotherapy response.

Large scale sequencing efforts have defined up to 27 diagnostic entities in B-ALL, leaving few samples without subtype assignment. Extended genomic an...

Identification of MHC ligands through allele-guided isolation combined with machine learning for improved MHC assignment using ARDisplay-I.

The isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immuno...

Etiologic diagnosis of seasonal allergic rhinitis supported by artificial intelligence: the @IT-2020 project.

BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...

Artificial Intelligence and Nasal Cytology: Toward a Comprehensive Cytological Endotyping of Rhinitis.

Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.

Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...

In-silico study of machine learning discovers de novo lipogenesis for predicting prognosis and immunotherapy responses in kidney renal clear cell carcinoma.

Multi-omics integration reveals ANXA6-high γδ T cell-endothelial communication as a potential link between periodontitis and MASLD.

Periodontitis (PD) and metabolic dysfunction-associated steatotic liver disease (MASLD) were highly prevalent inflammatory disorders that frequently c...

Biotechnology advances and the parasitology paradigm: From genomes to multi-omics and translation.

Parasitic diseases impose a substantial and often underestimated burden on human and animal health, food security and economic development. Over recen...

OptiSyn: an interpretable, multi-omics-driven graph convolutional network framework for synergy-oriented drug combination design in disease treatment.

BACKGROUND: Bioinformatics and large-scale computational modelling have emerged as essential research fields in modern biomedical science, enabling dr...

Harnessing the gut microbiota in extra-intestinal cancers: from causal evidence to immunotherapy strategies.

The gut microbiota (GM) has emerged as a key modulator of cancer development and therapeutic response beyond the gastrointestinal tract. In extra-inte...

Differential Factors Associated With the Presence of Persistent Symptoms in Individuals Diagnosed With Long COVID: Protocol for a Longitudinal Matched Case-Control Study.

BACKGROUND: Long COVID (postacute sequelae of SARS-CoV-2 infection) is a heterogeneous condition with persistent multisystem symptoms and substantial ...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

Machine learning derived ORC6 as a hub biomarker for predicting tumor microenvironment, prognoses, and therapeutic responses in lung adenocarcinoma.

The origin recognition complex (ORC) is a DNA-binding complex composed of six subunits involved in DNA replication in cancer cells. The prognostic and...

FTO-CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification.

BACKGROUND: Fat Mass and Obesity-Associated (FTO) is linked to multiple myeloma (MM) progression, but its action mechanisms are poorly understood. MET...

Artificial intelligence in atopic dermatitis: Current applications and future perspectives.

Atopic dermatitis (AD) is a prevalent and burdensome chronic skin disease, with profound effects on patient quality of life. Advancing its diagnosis a...