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Salivary biomarkers of stress and inflammation in first graders in Côte d′Ivoire: Effects of a probiotic food intervention

2021· article· en· W3160619174 on OpenAlexaff
Bonnie E. Brett, Bruno K. Koko, Habib O. Y. Doumbia, Frédéric Kouadio Koffi, Savorgnan E. Assa, Kollet Yao Aimé Sylvère Zahé, H Faye-Ketté, Séraphin Kati-Coulibaly, Remco Kort, Wilbert Sybesma, Gregor Reid, Carolina de Weerth

Bibliographic record

VenuePsychoneuroendocrinology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsLawson Health Research InstituteWestern University
FundersJacobs FoundationNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsProbioticPlaceboCote d ivoireRandomized controlled trialSalivaDisadvantagedMedicineInternal medicineEnvironmental healthBiology

Abstract

fetched live from OpenAlex

This semi-randomized controlled trial examined the effects of a probiotic food supplement on cortisol and C-reactive protein (CRP) in a sample of 262 four-to seven-year-old children (56% girls) in two economically-disadvantaged schools in an urban setting in Côte d'Ivoire. For one semester, children in one school were randomized to receive a probiotic (N = 79) or placebo (N = 85) fermented dairy food each day they attended school; one child (due to medical reasons) and all children in the other school (N = 98) continued their diets as usual. Children provided two saliva samples at 11:30 on consecutive days at the end of the study. Analyses revealed that the probiotic group had lower cortisol than the placebo or diet-as-usual groups (p = .015); CRP levels were comparable across groups (p = .549). Exploratory analyses suggested that dose and regularity of consumption may impact the biomarkers as well. This study provides the first evidence that a probiotic milk product may lower cortisol in a sample of young, economically-disadvantaged children.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.499

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 head0.007
GPT teacher head0.247
Teacher spread0.240 · 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 designBench or experimental
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

Citations13
Published2021
Admission routes1
Has abstractyes

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