Oncology/Hematology

Machine learning and multi-dimensional transcriptomics reveal the key molecular network of benzo(a)pyrene/NNK in promoting laryngeal cancer and develop prognostic models.

Benzo(a)pyrene (BaP) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), as typical environmental carcinogens, are widely present in tobacco smoke and air pollution. Their combined exposure is an important cause of high incidence of laryngeal cancer. However, the molecular mechanism of their synergistic carcinogenesis remains unclear. To fill this gap, this study employed an integrated strat...

Artificial intelligence, omics, and biomarkers: Redefining lung cancer early detection.

Lung cancer, the leading cause of death worldwide, claims millions of lives yearly, largely due to limited early interventions. Currently used lung cancer screening methods are still limited in their reach and accuracy due to invasiveness, radiation exposure, and low sensitivity, especially in early stages, necessitating the need for innovative technologies. This review examines emerging tools for...

AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology.

Spatial transcriptomics (ST) assays are transforming our understanding of tumor heterogeneity, but their high cost limits their application in large-s...

Electrochemical Biosensors for Hepatocellular Carcinoma: Advances, Analytical Performance, and Clinical Translation.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide due to the limited sensitivity of current surveillance an...

Artificial intelligence-assisted confocal laser endomicroscopy for predicting invasion depth of superficial esophageal mucosal lesions: a cohort study.

INTRODUCTION: Accurate assessment of invasion depth in esophageal squamous cell carcinoma (ESCC) is essential for optimal treatment. Probe-based confo...

Lineage Classification of Pituitary Neuroendocrine Tumors From Whole-Slide Images Using Attention-Guided Graph Representation Learning.

Pituitary neuroendocrine tumors (PitNETs) are common sellar neoplasms and represent a major component of routine pituitary pathology. In the 2022 Worl...

Integrative analysis of tumor-educated platelets for stage-specific diagnosis, prognosis, and therapy in ovarian cancer.

BACKGROUND: Ovarian cancer (OC) remains one of the most lethal gynecological cancers worldwide. Despite advances in diagnosis, OC is mostly detected a...

Oral squamous cell carcinoma diagnosis with time and frequency domain features from optical coherence tomography A-scan signals.

Optical coherence tomography (OCT) is extremely useful in the screening and detection of oral cancers. But various challenges, such as its subjectivit...

Generative chromoendoscopy for gastric neoplasms: A multicenter prospective study.

BACKGROUND AND STUDY AIMS: Generative indigo carmine chromoendoscopy (generative chromoendoscopy), produced using deep learning-based synthetic image ...

[Driver gene mutations predicted by pathology-foundation-model and their clinical associations in clear cell renal cell carcinoma].

Objective: To evaluate the performance of a deep learning framework based on the PathOrchestra pathology foundation model for predicting key driver ge...

Next-generation probiotics: an outlook into current applications and future developments.

The probiotics field, a historically popular yet scientifically debated discipline, is moving beyond a decades-long promotion of 'first-generation' fo...

Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) presents with variable clinical and pathological features, leading to inconsistent responses to standard treatme...

De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics.

Growth differentiation factor-15 (GDF15), a stress-responsive cytokine of the transforming growth factor-β superfamily, is elevated in cancer cachexia...

Couinaud segment-aware deep learning on point clouds for major liver resection planning.

PURPOSE: In this study, we address the problem of automatic liver resection planning for major surgical procedures, including hemi-hepatectomy and ext...

Multi-omics analysis of the mechanism by ATP13A2 regulates the tumor microenvironment and prognosis in hepatocellular carcinoma.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is a prevalent global cancer. Most patients with HCC are diagnosed at an advanced stage. Therefore...

Leveraging immune and clinicopathological profiles with machine learning to predict axillary lymph node metastasis in breast cancer patients.

BACKGROUND: Breast cancer is the leading cause of cancer-related death in women, with mortality increasing when tumor cells spread to nearby lymph nod...

ELOVL1 promotes the progression of intrahepatic cholangiocarcinoma by enhancing endoplasmic reticulum stress and the PI3K/AKT/mTOR signaling pathway.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy characterized by an adverse outcome attributed to delayed d...

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...

Emerging Therapeutic Paradigms in Tuberculosis: Nanocarriers, Host-Directed Strategies, and Translational Pharmacology.

TB remains a significant global health burden due to protracted therapeutic courses, poor patient compliance, and toxicities associated with drug trea...

Thrombosis at the crossroads of inflammation, coagulation, and vascular biology: Recent advances and emerging therapeutic strategies.

Thrombosis is a multifaceted pathological process involving intravascular clot formation that drives a range of cardiovascular and cerebrovascular dis...