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Probiotics and prebiotics in gastrointestinal disorders

2004· article· en· W2066494092 on OpenAlexafffund
Richard N. Fedorak, Karen Madsen

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMedicineGastroenterologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review summarizes the clinical efficacy of probiotics and prebiotics in gastrointestinal disorders and examines the mechanisms of action related to their therapeutic effect. RECENT FINDINGS: The demonstration that immune and epithelial cells can discriminate between different microbial species has extended the known mechanism(s) of action of probiotics beyond simple barrier and antimicrobial effects. It has also confirmed that probiotic bacteria modulate mucosal and systemic immune activity and epithelial function. The progressive unraveling of these mechanisms of action has led to new credence for the use of probiotics and prebiotics in clinical medicine. Level I evidence now exists for the therapeutic use of probiotics in infectious diarrhea in children, recurrent Clostridium difficile-induced infections and postoperative pouchitis. Level II evidence is emerging for the use of probiotics in other gastrointestinal infections, prevention of postoperative bacterial translocation, irritable bowel syndrome, and in both ulcerative colitis and Crohn disease. Nevertheless, one consistent feature has emerged over the past year: Not all probiotic bacteria have similar therapeutic effects. Future clinical trials will need to incorporate this fact into trial planning and design. SUMMARY: The use of probiotics and prebiotics as therapeutic agents for gastrointestinal disorders is rapidly moving into the "mainstream." Mechanisms of action explain the therapeutic effects and randomized; controlled trials provide the necessary evidence for their incorporation into the therapeutic armamentarium.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.023
GPT teacher head0.258
Teacher spread0.235 · 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

Citations150
Published2004
Admission routes2
Has abstractyes

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