Allergy

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apoptotic cell death and senescence pathways contribute to tumor evolution and immunosuppression, their integration into predictive models for multi-target drug design and immunotherapy optimization is underexplored. Machine learning was used to identify k...

Ai-enhanced clinical decision support reduces medication errors and adverse drug events in a multicenter teaching hospital network: A prospective randomized controlled trial.

BACKGROUND: Medication errors remain a leading source of preventable harm in hospitalized patients, contributing to adverse drug events (ADEs), prolonged hospital stay, and avoidable healthcare costs. Although clinical decision support systems (CDSS) integrated with electronic health records (EHRs) have demonstrated potential to reduce prescribing errors, rigorous multicenter randomized evidence f...

Reinventing miRNA cancer therapy through immunomodulation and AI.

Despite the rational therapeutic premise of microRNA (miRNA) replacement or inhibition for cancer treatment, its clinical translation remains signific...

A macrophage co-expression signature enables robust prognostic prediction in glioblastoma.

BACKGROUND: Glioblastoma (GBM) exhibits profound cellular heterogeneity and a highly immunosuppressive microenvironment in which tumor-associated macr...

3D-printed real-time biosensing system integrating deep learning for label-free in vitro T cell culture analysis.

Recent advances in T cell-based immunotherapies highlight the urgent need for precise and dynamic monitoring across the entire cell culture pipeline. ...

Gene-level gut microbiome signatures as predictive biomarkers for response to immune checkpoint inhibitors across multiple cancer types.

Targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with immune checkpoint inhibitors (ICIs) has...

Machine Learning-Based Prediction of Critical Deterioration in the PICU.

BACKGROUND: Existing PICU early warning systems lack sufficient accuracy and timeliness for effective preparation. Machine learning approaches may imp...

Transcriptome and single-cell RNA sequencing data identify and validate candidate biomarkers associated with lysosomal and ferroptosis in osteoarthritis.

BACKGROUND: Osteoarthritis (OA) represents the most common degenerative joint disease, with emerging evidence linking it to lysosomal dysfunction and ...

Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.

Radiotherapy (RT) remains a cornerstone of cancer management but is fundamentally constrained by normal tissue toxicity, intrinsic and acquired radior...

Crosstalk between immune and programmed cell death and their application in colorectal cancer risk stratification.

Programmed cell death (PCD) and cellular immunity play pivotal roles in colorectal cancer (CRC) progression; understanding their crosstalk and identif...

n-Type Polymer Radio Frequency Rectifiers Operating at 18.5 GHz.

As advancements in artificial intelligence, the Internet of Things (IoT), and telecommunication technologies continue to accelerate, the demand for ch...

Optimal treatment selection for hepatocellular carcinoma in the era of immunotherapy.

Immunotherapy has revolutionized hepatocellular carcinoma (HCC) management, necessitating personalized strategies in current guidelines. Despite curat...

Clinician-deployable deep hypergraph model integrating clinical and CT radiomics predicts immunotherapy outcomes in NSCLC.

Current image-based deep learning models that predict the benefits of immunotherapy in non-small cell lung cancer (NSCLC) require high-performance har...

A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention and Interception.

Advances in targeted therapies, immunotherapy, and early detection have revolutionized lung cancer treatment and extended survival. Nonetheless, lung ...

[Current status and future perspectives of precision treatment for locally advanced rectal cancer].

The treatment paradigm for locally advanced rectal cancer is undergoing a fundamental transformation from the traditional fixed triad of "radiotherapy...

[Research progress in clinical pathology and molecular mechanisms of pancreatic adenosquamous carcinoma].

Pancreatic adenosquamous carcinoma (PASC) is a rare exocrine malignancy of the pancreas with an increasing incidence, histologically defined by the co...

From evolution to rational design: AI-driven engineering of safe and highly efficient food enzymes.

As a representative area of industrial biocatalysis, food enzyme engineering plays a critical role in advancing the food industry. Recently, bioinform...

Beyond chemotherapy: The rise of nucleic acid nanoformulations in personalized lung cancer therapy.

Lung cancer remains the leading cause of cancer-related mortality worldwide, driven by complex crosstalk among genetic, molecular, and environmental f...

Macrophage polarization as a therapeutic target in lung diseases: From pathogenesis to precision intervention.

Macrophages serve as core effector cells of the innate immune system, exerting dual regulatory roles in pulmonary homeostasis maintenance and disease ...

A network-based deep learning model integrating subclonal architecture for therapy response prediction in cancer.

Predicting treatment response remains challenging in oncology, particularly given the growing diversity of therapeutic options. Despite efforts using ...