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Record W7020017110

Investigating the Clinical Effects and Mechanistic Underpinnings of Probiotics on Major Depressive Disorder

2021· dissertation· en· W7020017110 on OpenAlexaff

Bibliographic record

VenueQSpace (Queen's University Library) · 2021
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsQueen's University
Fundersnot available
KeywordsProbioticMajor depressive disorderTolerabilityNocebo EffectRandomized controlled trialDepression (economics)MicrobiomeBifidobacterium longumLactobacillus helveticusPlacebo
DOInot available

Abstract

fetched live from OpenAlex

Background: Probiotics have been hypothesized to improve symptoms of Major Depressive Disorder (MDD). Evidence suggests that these outcomes may be driven by probiotics reducing inflammation and regulating neurotransmission through the gut-brain axis. Objectives: 1) Systematically review the current literature on the effects of probiotics in mental health in humans; 2) Examine the efficacy, safety, and tolerability of a probiotic supplement on depression in a pilot study; 3) Develop a protocol for a double-blind randomized placebo-controlled trial to examine the effects of a probiotic supplement on depression; 4) Compare the clinical effects of a probiotic supplement versus placebo on depression to determine whether probiotics may have a role in alleviating symptoms of depression; 5) Examine molecular and microbial activity for possible mechanistic underpinnings of the relationship between probiotics and depression. Methods: I started by systematically reviewing the literature to evaluate the current state of the evidence and identify areas for further examination. I then implemented an 8-week open-label pilot study examining the effects of a probiotic supplement containing Lactobacillus helveticus R0052 and Bifidobacterium longum R0175 on symptoms of depression in treatment-naïve adults diagnosed with MDD. Using data and knowledge acquired from the pilot work, I developed a protocol for a 16-week double-blinded randomized placebo-controlled trial (DBRCT) to further examine these effects and explore potential blood-based biomarkers and microbiome composition for response predictors and underlying mechanisms. Results: My systematic review of the literature revealed promising preliminary evidence for probiotics alleviating symptoms of depression but highlighted significant gaps and inconsistencies in the current literature. In our pilot work, we observed significant improvements in depressive symptoms following probiotic supplementation. However, findings from our DBRCT did not support the pilot findings. We found that probiotics were no superior to placebo in reducing depressive symptoms which was reflected in no significant group differences in blood-based biomarkers. However, building off our pilot work, analyses revealed potentially important differences in microbiome composition between probiotic responders and non-responders. Conclusions: These findings add to the growing body of research in this emerging field and provide crucial direction for developing future studies to examine the relationship between probiotics and MDD.

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)0.011
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.236
Teacher spread0.229 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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