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Record W2188868872 · doi:10.1097/mog.0000000000000233

The long-term functional consequences of acute infectious diarrhea

2015· review· en· W2188868872 on OpenAlexaff
Sila Cocciolillo, Stephen M. Collins

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2015
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsMcMaster University Medical CentreMcMaster University
Fundersnot available
KeywordsIrritable bowel syndromeDysbiosisGut floraGenetic predispositionImmune systemImmunologyDiarrheaMedicineBiologyBioinformaticsDiseaseInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The study reviews recent publications that build on previous studies showing that acute enteric infection can produce persistent dysfunction in the lower gut (postinfectious irritable bowel syndrome) and proximal gut (postinfectious functional dyspepsia). The review addresses risk factors, the pathophysiological basis of persistent gut dysfunction, and the factors that initiate and maintain it. RECENT FINDINGS: Recent work has identified several loci of host genetic predisposition to these syndromes that focus attention on host immune responses that may lead to gut dysfunction, including changes in intestinal barrier function and cytokine responses to the initial infection. Human and animal studies identify changes in the serotonergic and cannabinoid pathways regulating visceral pain responses and gut motility. Recent work has also focused attention on the putative role of the intestinal microbiota or dysbiosis in maintaining gut dysfunction and this is reviewed in depth. SUMMARY: The development of long-term consequences following an acute episode of gastroenteritis reflects a convergence of host factors that include genetic predisposition and psychological factors, as well as the development of intestinal dysbiosis. It is anticipated that future research will generate biomarkers of susceptibility as well as novel microbiota-directed preventive and therapeutic strategies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.805
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.106
GPT teacher head0.391
Teacher spread0.286 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2015
Admission routes1
Has abstractyes

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