Colon Cancer

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 biomarker for early detection. However, effective ctDNA detection remains challenging due to low abundance and complex workflows. Herein, we present SPECTRAL (Smart Photonic-hydrogel Enhanced chip for Cancer Type Recognition and AnaLysis), a sequenc...

Characterization of telomere-related gene subtypes in lung adenocarcinoma and their implications for prognosis and treatment.

BACKGROUND: Telomeres, located at chromosome ends, regulate cell division and maintain genomic stability. Telomere-related genes (TRGs) play essential roles in tumorigenesis and immune escape, but their mechanisms in lung adenocarcinoma (LUAD) are not fully understood. METHODS: This study integrated genomics, transcriptomics and pathological images to analyze TRGs expression in LUAD. Univariate Co...

Single-cell and bulk omics uncover fibroblast heterogeneity and HSPH1 as a key driver in Barrett's esophagus to esophageal adenocarcinoma progression.

BACKGROUND: Esophageal adenocarcinoma (EAC) is a highly aggressive malignancy with poor prognosis, often evolving from Barrett's esophagus (BE). Under...

Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.

The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates tar...

Klf4-Tymp axis promotes inflammation-driven early tumorigenesis by enhancing kras mutation-induced acinar-to-ductal metaplasia through Pi3k/Akt and Mek/Erk pathways.

BACKGROUND: Acinar-to-ductal metaplasia (ADM) is a pivotal step in pancreatic tumorigenesis, reversible in normal contexts but progressing to PanIN an...

Pancreatic cancer.

Pancreatic ductal adenocarcinoma remains one of the deadliest malignancies, characterized by late diagnosis, aggressive biology and limited therapeuti...

Machine learning-based prognostic signature integrating mitochondrial function and programmed cell death patterns in pancreatic adenocarcinoma.

The interplay between mitochondria and programmed cell deaths (PCD) is associated with tumor pathogenesis. However, the specific roles of genes relate...

Pediatric lung ground glass nodules: a real-world, large-scale CT cohort analysis.

BACKGROUND: Increasing detection of pediatric ground-glass nodules (GGNs) presents a clinical dilemma lacking robust evidence and guidelines. We aimed...

Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale.

OBJECTIVES: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommen...

Modulation of tumor-derived exosomes and reprogramming of cancer-associated fibroblasts for colorectal cancer therapy.

Hypoxia is pervasive within the solid tumor microenvironment (TME), reshaping it through exosome release. As the main component of the tumor stroma, f...

Single-cell and spatial transcriptomic profiling of POU5F1 in Lung Adenocarcinoma: Dynamics, spatial niche, and prognosis via multi-algorithm ML.

BACKGROUND: POU5F1 (OCT4), a core regulator of pluripotency, plays an important role in tumor stemness and immune microenvironment remodeling, yet its...

A Modular and Scalable FPGA Platform for Intelligent, High-Throughput Image-Activated Cell Sorting.

Image-activated cell sorting (IACS) enables high-throughput cell classification by linking cellular morphology to physiology. While integrating advanc...

Automated Delineation of Couinaud Segments on CT for Future Liver Remnant Volumetry.

Purpose To develop a deep learning model that automatically delineates the eight liver Couinaud segments and the spleen on CT for future liver remnant...

Histology-defined activated cancer-associated fibroblasts are associated with poor survival in diffuse-type gastric adenocarcinoma.

Activated cancer-associated fibroblasts (aCAFs), characterized by distinct histological features including fibroblast proliferation and extensive desm...

CARES-Net: a channel-attention residual network for multi-disease classification in small-sample 1H NMR metabolomics data.

BACKGROUND: NMR-based metabolomics is widely used in disease diagnosis due to its non-destructive and quantitative advantages. However, its analytical...

A Machine-Learning Approach to Predicting Adenoma Detection and Surveillance Impact of Deeper Sections in Colorectal Polypectomy Specimens.

CONTEXT.—: In the routine practice of pathology, cutting deeper levels into paraffin blocks of colorectal polypectomy specimens that do not show a les...

Applying Artificial Intelligence Technologies to Detect Pancreatic Ductal Adenocarcinoma Using Routine Laboratory Tests: A Pilot Study with the Aid of Machine Learning Suitable for a Small Data Analysis.

Objective This study aimed to investigate whether artificial intelligence could identify pancreatic ductal adenocarcinoma (PDAC) in patients aged <70 ...

Development and validation of a machine learning model to predict recurrence in polypoidal choroidal vasculopathy: a multicentre prospective study.

AIM: This study aims to develop and validate machine learning models for predicting recurrence in polypoidal choroidal vasculopathy (PCV) patients usi...

Artificial intelligence-powered H&E-based quantification of spatial tumor-infiltrating lymphocyte distribution identifies prognostic immune niches in colorectal cancer.

PURPOSE: The prognostic significance of tumor-infiltrating lymphocytes (TILs) in colorectal cancer (CRC) is well established; however, existing approa...

CAD-SEL: A dual-modal colonoscopy dataset of subepithelial lesion.

Subepithelial lesions (SELs) of the gastrointestinal tract encompass a heterogeneous spectrum of histology, ranging from benign to malignant. Their de...