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Record W2154509583 · doi:10.1186/1757-4749-3-1

Acne vulgaris, probiotics and the gut-brain-skin axis - back to the future?

2011· article· en· W2154509583 on OpenAlexaff
Whitney P. Bowe, Alan Logan

Bibliographic record

VenueGut Pathogens · 2011
Typearticle
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsRegent Park Community Health Centre
Fundersnot available
KeywordsAcneMedicineGut–brain axisGut floraMoodAnxietyDermatologyImmunologyPsychiatry

Abstract

fetched live from OpenAlex

Over 70 years have passed since dermatologists John H. Stokes and Donald M. Pillsbury first proposed a gastrointestinal mechanism for the overlap between depression, anxiety and skin conditions such as acne. Stokes and Pillsbury hypothesized that emotional states might alter the normal intestinal microflora, increase intestinal permeability and contribute to systemic inflammation. Among the remedies advocated by Stokes and Pillsbury were Lactobacillus acidophilus cultures. Many aspects of this gut-brain-skin unifying theory have recently been validated. The ability of the gut microbiota and oral probiotics to influence systemic inflammation, oxidative stress, glycemic control, tissue lipid content and even mood itself, may have important implications in acne. The intestinal microflora may also provide a twist to the developing diet and acne research. Here we provide a historical perspective to the contemporary investigations and clinical implications of the gut-brain-skin connection in acne.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0000.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations291
Published2011
Admission routes1
Has abstractyes

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