Colon Cancer

High-fidelity super-resolution CT radiomics for non-invasive EGFR mutation prediction in lung adenocarcinoma: a multi-center pooled analysis.

OBJECTIVE: To develop and validate a high-fidelity super-resolution (SR)-enhanced radiomics framework using a Residual Channel Attention Network (RCAN) for non-invasive EGFR mutation prediction in lung adenocarcinoma (LUAD). METHODS: This retrospective multi-center study included 373 patients, partitioned into training (n = 298) and testing (n = 75) sets. CT images were reconstructed to a 1024 × 1...

Advances in the management of pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs), the most common CNS tumors in children, are increasingly recognized as chronic diseases with prolonged courses and cumulative morbidity. Long-term survival is excellent. Management depends on tumor location and often requires repeated therapy, with risk of long-term functional and neurocognitive impairment. This review synthesizes recent advances in pLGG manage...

Meta-analysis reveals microbiome signatures for colorectal cancer that are universal across age groups and sequencing methods.

Numerous studies have linked gut microbiome alterations to colorectal cancer (CRC), but limited sample sizes and study heterogeneity have hampered cro...

Interpretable machine learning for preoperative prediction of ground-glass nodules invasiveness in lung adenocarcinoma: a multicenter study.

Accurate, noninvasive prediction of invasiveness in ground-glass nodules (GGNs) is important for surgical planning in lung adenocarcinoma. This multic...

Multi-omics investigation of per- and polyfluoroalkyl substances in lung adenocarcinoma: comprehensive network toxicology, machine learning and molecular docking experiments.

Growing concerns regarding per- and polyfluoroalkyl substances (PFAS) as pervasive environmental contaminants have prompted increasing scrutiny regard...

Metabolic pathway signatures define prognostic subtypes of lung adenocarcinoma.

Metabolic reprogramming is a core hallmark of cancer, yet how it contributes to the clinical heterogeneity of lung adenocarcinoma (LUAD) remains poorl...

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation.

PURPOSE: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing inter...

Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges.

PURPOSE OF REVIEW: Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complica...

Development and validation of a machine learning-based postoperative staging system for hilar cholangiocarcinoma: a retrospective single-center cohort study.

BACKGROUND: Hilar cholangiocarcinoma (HCCA) is a malignant tumor at the hepatic hilum with poor prognosis and survival despite surgical resection. Whi...

A highly interpretable machine learning model for predicting lung cancer bone metastasis: uncovering the synergistic effect of routine biochemical markers.

BACKGROUND: Bone metastasis (BM) significantly impairs lung cancer prognosis and patient quality of life. Conventional imaging modalities often face l...

Boundary-Aware Spectral and Morphological Guidance Method for Feature-Driven Colorectal Cancer Segmentation.

Precise segmentation of medical images plays a crucial role in modern clinical practice, providing important foundations for the quantitative analysis...

Expression of the High Affinity Neurotensin Receptor Defines an Immune‑cold, Poor‑prognosis Colorectal Cancer Subtype.

OBJECTIVE: We investigated neurotensin receptor 1 (NTSR1) as a potential mediator of the mechanical immune barrier that contributes to T-cell exclusio...

A HRH1-YAP1 feedback loop drives pancreatic cancer progression and predicts therapeutic response.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a dismal prognosis, characterized by an immunosuppressive tumor microenviro...

Decoding chromatin regulator-LAIR1+ M2 like macrophage patterns in atherosclerosis and clinical outcomes of Lung adenocarcinoma patients: evidence from artificial intelligence-driven multi omics and in vitro validation.

Atherosclerosis (AS) is a common complication of lung adenocarcinoma (LUAD), but its underlying mechanisms in LUAD remain unclear. This study aimed to...

Integrated network toxicology and experimental validation to investigate potential mechanisms associated with aspartame-induced malignant phenotypic changes in colorectal cancer.

To investigate the potential molecular mechanisms underlying aspartame (APM)-induced malignant phenotypic changes in colorectal cancer (CRC). Candidat...

FD-MSP: feature decoupling network with multi-scale prototypes for domain-adaptive polyp segmentation.

Polyp segmentation in colonoscopy images plays a critical role in the early detection and treatment of colorectal cancer. Although deep learning-based...

Pancreatic organoids and organoid-on-a-chip platforms: from disease modeling to precision therapy.

BACKGROUND: Pancreatic diseases, including diabetes, pancreatic ductal adenocarcinoma, pancreatitis, and cystic fibrosis, impose a substantial clinica...

A three-gene signature (ABCE1, ATAD5, FUT4) for colorectal cancer prognosis: integrative analysis of transcriptomic, single-cell, and machine learning data.

Colorectal cancer (CRC) remains a leading cause of cancer-related death, highlighting an unmet need for robust, mechanistically grounded prognostic bi...

Dual modal pathomics model for colorectal cancer early recurrence prediction and mutation landscape analysis.

Patients with stage II/III colorectal cancer remain at substantial risk of early postoperative recurrence, yet accurate risk stratification remains ch...

Differentiating sub-centimeter lung metastases in colorectal cancer by deep learning: a multicenter retrospective study.

BACKGROUND: Early diagnosis of sub-centimeter lung metastases is critical for timely decision-making and improved prognosis in patients with colorecta...