Allergy

Translating Food Biosensing into Practice: Smart Packaging, On-Site Analytics, and AI Integration.

The global food system encounters increasing challenges from contamination threats, necessitating innovative monitoring technologies to guarantee safety and quality. This review investigates novel precision monitoring methodologies, emphasizing sophisticated biosensing technologies, intelligent packaging systems, molecular docking, and AI-integrated platforms. Biosensors utilize electrochemical, o...

Machine learning-based integrative analysis identifies CXCL13-driven tertiary lymphoid structures as favorable immune and prognostic features in osteosarcoma.

BACKGROUND: Osteosarcoma, an aggressive bone malignancy with limited response to immunotherapy, remains a major clinical challenge. Tertiary lymphoid structures (TLS), as organized ectopic lymphoid aggregates, play a pivotal role in modulating antitumor immune responses. However, their landscape, clinical significance, and molecular determinants in osteosarcoma remain largely unexplored. METHODS: ...

cGAS-STING pathway regulated by spatiotemporal heterogeneity of tumor microenvironment and precision therapy strategies in lung cancer.

The cGAS-STING pathway is a central regulator of innate immunity and exhibits a complex dual function in lung cancer: it can activate anti-tumor immun...

Prognostic Significance and Therapeutic Implications of Migrasome-related genes in Sorafenib Treatment for Primary Liver Cancer.

PURPOSE: This study aimed to reveal the mechanism and prognostic significance of migrasome-related genes (MGs) in primary liver cancer (PLC) treated w...

Advancing equity in endometrial cancer: A narrative synthesis using a cluster-informed framework for resource-stratified implementation.

Endometrial cancer incidence and mortality are rising globally, disproportionately affecting health systems facing diagnostic, therapeutic, and surviv...

Integrating spatial and single-cell transcriptomics via machine learning to characterize efferocytosis in hepatocellular carcinoma prognosis and immunotherapy.

BACKGROUND: The intratumoral heterogeneity and immunosuppressive microenvironment of hepatocellular carcinoma (HCC) significantly limit therapeutic ef...

Machine-Learning-Based Prediction of Long-Term Efficacy of Nemolizumab: Post Hoc Analysis of Pooled Data from Two Phase III Clinical Trials.

INTRODUCTION: Nemolizumab is a humanized monoclonal antibody that specifically inhibits the receptor for interleukin-31, the major pruritogen in atopi...

Micropeptides in Cancer and Immunity: Diagnostic, Therapeutic, and Synthetic Biology Frontiers.

Micropeptides are emerging as a previously hidden layer of the human proteome, redefining the long-standing separation between coding and noncoding ge...

Tetrahedral framework nucleic acids as a promising vehicle for small molecule drugs of traditional Chinese medicine: application to disease prevention and treatment.

The modernization of Traditional Chinese Medicine (TCM) faces considerable challenges, primarily due to the poor water solubility, low chemical stabil...

Droplet microfluidic profiling of NK cell cytotoxicity with machine learning-enabled target-cell death analysis.

Predicting the clinical efficacy of Natural Killer (NK) cell immunotherapies remains challenging due to functional heterogeneity within effector popul...

Canadian radiology: 2026 update.

Canadian radiology continues to produce scholarship that is technically sophisticated, clinically relevant, and increasingly attentive to the wider sy...

A predictive 14-gene signature and FLI1 inhibition overcome tumor-infiltrating lymphocyte dysfunction in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype lacking effective targeted therapies. Although immune checkpoint inhibitors such as pemb...

Quantitative sensory testing and classical pain model dataset in 127 healthy volunteers.

Experimental pain models are integral to human pain research and the development of analgesic drugs. Of many options available, it is possible to iden...

Three-dimensional modeling of sensory nerve architecture and eosinophil and mast cell interactions in eosinophilic gastrointestinal disease.

Increased sensory nerve density has been described in type II inflammatory conditions and is linked to eosinophil and mast cell infiltration and neuro...

Mechanism-Informed Machine Learning Enables Discovery of Oncolytic Peptides for Cancer Immunotherapy.

Oncolytic peptides (OPs) represent a promising class of cancer therapeutics capable of rapidly lysing tumor cells and activating antitumor immunity. H...

Identification of ribosomal stress related signature genes and immune microenvironment analysis in ovarian cancer based on multi-machine learning.

BACKGROUND: Ovarian cancer (OC) is a highly aggressive malignancy with poor prognosis and limited response to immunotherapy. Ribosomal stress, a cellu...

Artificial intelligence model predicts malignant transformation of oral leukoplakia and optimizes interventions.

PURPOSE: Oral leukoplakia (OL), the most common oral potentially malignant disorder (OPMD), poses a significant risk for transformation to oral squamo...

RNA-based cancer immunotherapy: Harnessing the power of RNA nanoparticles for melanoma treatment.

RNA-based cancer immunotherapy has emerged as a next-generation strategy in oncology, harnessing the versatile properties of RNA molecules to activate...

Integrating multi-omics analysis and machine learning to refine molecular subtypes and prognostic assessment of lower-grade glioma.

Lower-grade glioma (LGG) is a highly heterogeneous disease, making accurate prognosis prediction and the development of precise, personalized treatmen...

Recent progress in the effects and mechanisms of non-thermal technologies on alleviating food allergy.

Food allergy is a big concern in food safety. Thermal processing is an effective approach to tackle it, but the method might significantly diminish th...