Oncology/Hematology

Recent advances in the molecular interactions of anti-cancer peptides with cellular targets.

Anti-cancer peptides (ACPs) selectively kill tumor cells through membrane disruption, intracellular target engagement, and immune activation. Recent structural and computational advances have clarified structure-activity relationships, enabling rational engineering via cyclisation, D-amino acid incorporation, and nanoparticle delivery. This review integrates current understanding of ACP-cellular i...

Multi-omics precision diagnosis of brucellosis: Advances in biomarker discovery and clinical application.

Brucellosis, a neglected zoonosis caused by intracellular Brucella bacteria, remains a formidable global public health challenge, especially in developing regions. The notorious ability of Brucella to evade host immunity and establish chronic focal infections limits the utility of traditional diagnostic methods like bacterial culture and serology for early detection, therapeutic monitoring, and di...

Molecular Functions and Drug Prediction of MMP1 and TGFBR2 in Nasopharyngeal Carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is partially driven by epithelial-mesenchymal transition (EMT). We identified potential EMT-related biomark...

Integrative Bioinformatics, Experimental Validation, and Interpretable Machine Learning Reveal Oxyresveratrol-Mediated Protection Against Cadmium-Induced Lung Adenocarcinoma-Related Transcriptional Dysregulation.

Cadmium (Cd) is a toxic heavy metal strongly implicated in lung adenocarcinoma (LUAD) through mechanisms involving oxidative stress, epigenetic dysreg...

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...

The promise of artificial intelligence in diagnostic breast pathology.

Accurate pathology diagnosis has remained the most essential factor in providing optimal breast cancer care across the globe. Core needle biopsies acc...

Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal forms of cancer, with a five-year survival rate below 10% primarily due to late...

Single cell mechanodeformation signatures as early biomarkers for hematological malignancies.

Single-cell mechanical profiling of deformations has become a promising method of identifying a functional biomarker in patients with blood cancers. B...

Deciphering tumor metabolites: emerging technologies shaping clinical implications.

Metabolites exert pleiotropic effects that govern tumor progression. This review evaluates current platforms and technologies for metabolite detection...

Interpreting MALDI imaging data for rare types of ampullary cancer using machine learning.

Rare tumor diseases are difficult to diagnose and there is a lack of routine diagnostic procedures. Approaches must be found that allow comprehensive ...

Efficient deep learning models for oral squamous cell carcinoma classification in histopathological images.

Recent advances in deep learning have significantly improved the accuracy and efficiency of disease classification in digital pathology. Early diagnos...

Integrative bioinformatics analysis unveils neuro-cancer crosstalk-related genes and establishes prognostic risk model in Glioblastoma.

Neuro-cancer crosstalk plays an important role in the development and progression of Glioblastoma (GBM), but its specific mechanisms remain incomplete...

Exploring the utility of artificial intelligence in identifying progression of prostate cancer during active surveillance: A systematic review.

BACKGROUND: There is a recent surge in interest in the application of artificial intelligence (AI) in prostate cancer (PCa). When evaluating PSMA PET ...

Robot-assisted lumbar facet joint infiltration improves accuracy and reduces radiation exposure compared to the manual technique in a comparative phantom study.

Compact robotic systems offer new opportunities for spinal procedures outside the operating room, but their potential for small-scale interventions su...

Cross-cancer homologous recombination deficiency prediction from whole slide images using transfer learning.

Accurate prediction of Homologous Recombination Deficiency (HRD) is vital for personalized cancer therapy, yet genomic assays are often costly and com...

Plasma acylcarnitine dysregulation associated with CPT1-mediated metabolism contributes to oral carcinogenesis.

Growing evidence suggests that lipid metabolic reprogramming occurs in oral cancer (OC). We characterized circulating metabolic alterations associated...

Establishment of prognostic prediction model based on lipid metabolism related genes in esophageal squamous cell carcinoma by machine learning algorithms.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer-related mortality worldwide, with a high prevalence and poor prognosi...

The evolution of prostate cancer grading: from Gleason score to risk taxonomy and the artificial intelligence revolution.

Histopathological grading remains the cornerstone of risk stratification in prostate cancer, yet conventional Gleason-based assessment is limited by i...

Involved nodal versus elective neck radiotherapy (INVERT) for head and neck squamous cell carcinoma: a prospective phase II randomized controlled trial protocol.

BACKGROUND: Definitive chemoradiotherapy for head and neck squamous cell carcinomas (HNSCC) carries significant long-term toxicities, with elective ne...

SPECTRAL: An Intelligent and Ultra-Sensitive Photonic Hydrogel Platform for Biomarker-Based Cancer Prediction.

Point-of-care (POC) biosensing holds great promise for noninvasive cancer diagnostics, as circulating tumor DNA (ctDNA) serves as a minimally invasive...