Oncology/Hematology

[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-surgery-chemotherapy" to a holistic eco-system centered on precision stratification and multidisciplinary collaboration. This review synthesizes the current landscape and future perspectives of this evolution across four key dimensions. First, in su...

[Exploration and clinical application of the "digital and intelligent surgery" diagnosis and treatment workflow for oral and maxillofacial tumors].

Tumors in the oral and maxillofacial region present significant clinical challenges due to anatomical complexity and high individual variability, with the traditional experience-dependent model often lacking three-dimensional visualization, precise intraoperative navigation, and quantitative postoperative assessment. This article comprehensively reviews over a decade of research and clinical advan...

[Robotic gastrectomy: Research progress and practical challenges].

Gastric cancer is one of the malignant tumors with high incidence and mortality rates globally, with China ranking among the top 5 in both case number...

[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...

Neural network reveals platelet age from fluorescence microscopy images.

Platelets are small, anucleate cells with a primary physiological role in vascular damage repair (hemostasis) and initiation of thrombus formation in ...

Accelerating real-world data collection using large language models in rare neoplasms: a bone sarcoma example.

BACKGROUND: Real-world data collection in oncology remains a challenge due to the complex and unstructured format of medical notes. Recently, large la...

Incorporating artificial intelligence into morphological diagnosis of acute leukemias: Current landscape, challenges and prospects (Review).

Acute leukemias (ALs) are a diverse group of hematological malignancies characterized by the abnormal proliferation of immature cells. Microscopic obs...

Novel therapeutic strategies for metastatic castration‑resistant prostate cancer: Beyond androgen receptor pathway inhibition (Review).

Metastatic castration‑resistant prostate cancer (mCRPC) remains a lethal disease due to universal resistance to androgen‑receptor pathway inhibitors (...

CAR-T Cells: Current Status, Challenges, and Future Prospects.

As chimeric antigen receptor (CAR)-T cell therapy has expanded rapidly to meet the growing global cancer burden; many challenges have emerged as a cri...

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 ...

Spatial proteomics of tertiary lymphoid structures reveals correlation with immunotherapy response in Merkel cell carcinoma.

BACKGROUND: Tertiary lymphoid structures (TLS) are ectopic lymphoid formations within or around tumours. They are emerging as important predictors of ...

Machine Learning-Driven Ensemble Screening of Multitarget Kinase Inhibitors for Tauopathy-Associated Neurodegeneration Using All-Atom and Steered MD Simulations.

Tauopathies arise when normal functions of the tau protein in axonal transport and neuronal maintenance are disrupted by an imbalance between kinases ...

DANCE: Deep Learning-Assisted Analysis of ProteiN Sequences Using Chaos Enhanced Kaleidoscopic Images.

Cancer is a complex disease characterized by uncontrolled cell growth and requires an accurate classification for effective treatment. T cell receptor...

Exploring the potential targets and mechanisms of malachite green induced lung adenocarcinoma through network toxicology and molecular docking.

Malachite green (MG), a synthetic dye, has turned into a major risk to human health, because of its toxicity of teratogenic, genotoxic, carcinogenic, ...

Promptable segmentation with region exploration enables minimal-effort expert-level prostate cancer delineation.

PURPOSE: Accurate segmentation of prostate cancer on magnetic resonance (MR) images is crucial for planning image-guided interventions such as targete...

Association between diagnostic history and cancer incidence within 5 years: a real-world observational analysis.

Cancer is associated with many pre-existing health conditions (PHCs), but accurately quantifying these links remains challenging. Although some studie...

Clustering by patients-related characteristics identifies specific phenotypes with different prognosis after resection of non-small cell lung cancer: a French nationwide study from the Epithor database.

INTRODUCTION: Lung cancer remains the leading cause of cancer mortality worldwide despite advances in treatment. Patient-related factors beyond tumour...

Identifying environmental factors associated with tetrodotoxin contamination in bivalve mollusks using eXplainable AI.

Since 2012, tetrodotoxin (TTX) has been found in seafoods such as bivalve mollusks in temperate European waters. TTX contamination leads to food safet...

Predicting primary resistance to third-generation EGFR-TKIs in lung adenocarcinoma using a multisource cross-modal transformer model.

The aim of this study was to investigate the utility of a multisource cross-modal Transformer (MC-Trans) model in predicting primary resistance to thi...