ArticleMetabolites2023
A Fecal-Microbial-Extracellular-Vesicles-Based Metabolomics Machine Learning Framework and Biomarker Discovery for Predicting Colorectal Cancer Patients.
Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- Colorectal neoplasia-specific amino acid profiles and their diagnostic potential: a systematic review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Pooled it
- Evidence of cancer: a systematic review of metabolomics in extracellular vesicles for cancer biomarker detection.Metabolomics : Official journal of the Metabolomic Society · 2025Pooled it
- ML-BUSMetab: Machine Learning-Based Metabolomic Profiling for Predicting Aspirin Response in Colorectal Cancer Chemoprevention: A Multi-Model Explainable Artificial Intelligence Approach with External Validation.Journal of clinical medicine · 2026Article
- Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.Journal of nanobiotechnology · 2026Review
- Examining the gene network and prognostic biomarkers in the onset of colorectal cancer in stool samples using machine learning.Discover oncology · 2026Article
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- The metabolome of fecal extracellular vesicles in patients with malignant solid tumors.Scientific reports · 2025Article
- The Enteric Microbiome in Early-Onset Colorectal Cancer: A Comprehensive Review of Its Role as a Biomarker of Disease.Clinical and translational gastroenterology · 2025Review
- Machine Learning-Driven Insights in Cancer Metabolomics: From Subtyping to Biomarker Discovery and Prognostic Modeling.Metabolites · 2025Review
- The power of microRNA regulation-insights into immunity and metabolism.FEBS letters · 2025Review
- Untargeted Lipidomic Biomarkers for Liver Cancer Diagnosis: A Tree-Based Machine Learning Model Enhanced by Explainable Artificial Intelligence.Medicina (Kaunas, Lithuania) · 2025Article
- Gut microbiome-derived bacterial extracellular vesicles in patients with solid tumours.Journal of advanced research · 2025Article
- Yiqi Huayu Jiedu Decoction reduces colorectal cancer liver metastasis by promoting N1 neutrophil chemotaxis.Frontiers in immunology · 2025Article
- Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis.Computational and structural biotechnology journal · 2025Review
- Advancing miRNA cancer research through artificial intelligence: from biomarker discovery to therapeutic targeting.Medical oncology (Northwood, London, England) · 2024Review
- Adaptive laboratory evolution of Lipomyces starkeyi for high production of lignin derivative alcohol and lipids with comparative untargeted metabolomics-based analysis.Microbial cell factories · 2024Article
- Extracellular Vesicle Preparation and Analysis: A State-of-the-Art Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Article
- Correlation between NGS panel-based mutation results and clinical information in colorectal cancer patients.Heliyon · 2024Article
- Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies.ACS pharmacology & translational science · 2024Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
Colorectal cancer (CRC) is one of the most common and lethal diseases among all types of cancer, and metabolites play a significant role in the development of this complex disease. This study aimed to identify potential biomarkers and targets in the diagnosis and treatment of CRC using high-throughput metabolomics. Metabolite data extracted from the feces of CRC patients and healthy volunteers were normalized with the median normalization and Pareto scale for multivariate analysis. Univariate ROC analysis, the
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.