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Record W2914547283 · doi:10.1111/apt.15141

Comparison of the metabolomic profiles of irritable bowel syndrome patients with ulcerative colitis patients and healthy controls: new insights into pathophysiology and potential biomarkers

2019· article· en· W2914547283 on OpenAlexafffund
Ammar Hassanzadeh Keshteli, Karen Madsen, Rupasri Mandal, Guy E. Boeckxstaens, Přemysl Berčík, Giada De Palma, David E. Reed, David S. Wishart, Stephen Vanner, Levinus A. Dieleman

Bibliographic record

VenueAlimentary Pharmacology & Therapeutics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsQueen's UniversityMcMaster UniversityUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta Innovates Bio SolutionsAlberta Innovates - Health Solutions
KeywordsIrritable bowel syndromeMedicineUlcerative colitisGastroenterologyInternal medicinePathophysiologyUrinary systemMetabolomicsUrineMetabolomeDiseaseMetaboliteBioinformatics

Abstract

fetched live from OpenAlex

BACKGROUND: Evaluation of the metabolomic profile of patients with irritable bowel syndrome offers an opportunity to identify novel pathophysiological targets and biomarkers that could discriminate this disorder from related conditions. AIM: To identify potential urinary biomarkers that discriminate irritable bowel syndrome patients from ulcerative colitis patients in remission and healthy controls and to explore the pathophysiology of irritable bowel syndrome using a metabolomic approach. METHODS: Urine samples were collected from 39 irritable bowel syndrome patients, 53 ulcerative colitis patients in clinical remission and 21 healthy controls. Urinary metabolites were identified and quantified using direct infusion/liquid chromatography tandem mass spectrometry and gas-chromatography mass spectrometry. RESULTS: Patients with irritable bowel syndrome had a unique urinary metabolome that could separate them from ulcerative colitis patients with an area under the curve = 0.99 (95% confidence interval 0.95-1.00). The most important metabolites for this separation were a group of amino acids and organic acids. In addition, subjects with irritable bowel syndrome could be discriminated from healthy controls using their metabolic fingerprints. Irritable bowel syndrome patients had lower urinary Phosphatidyl choline acyl-alkyl C38:6, dopamine and p-hydroxybenzoic acid than healthy controls. Levels of some urinary metabolites including histamine correlated significantly with irritable bowel syndrome symptom severity scores. CONCLUSIONS: Irritable bowel syndrome patients have a unique urinary metabolomic profile compared to ulcerative colitis patients in clinical remission or healthy subjects. These data suggest that metabolomic profiling may provide important insights into pathophysiology and testable biomarkers to discriminate irritable bowel syndrome from other disorders that can mimic this condition and can be used to assess its severity and identify potential novel pathophysiological pathways.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.265
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2019
Admission routes2
Has abstractyes

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