The Effects of Microbial Ecosystem Therapeutic-2 on Sleep Disturbances in Individuals with Major Depressive Disorder
Bibliographic record
Abstract
Objective: The primary objective of this thesis is to evaluate the effects of microbial ecosystem therapeutic-2 (MET-2) in comparison to a placebo on sleep disturbances in individuals with major depressive disorder (MDD) during a 6-week treatment period, with follow-up assessments at 12- and 24-weeks post-treatment. The secondary objectives are to assess changes in mood at the same intervals and to assess any correlations between sleep and mood. Methods: Data from this thesis were derived from the METDA study, a phase 2 double-blind placebo-controlled trial that recruited individuals with MDD in the Kingston and Toronto areas. Participants were randomly assigned to receive either MET-2 or a placebo for 6 weeks. Longitudinal effects of MET-2 were explored in a follow-up sub-study at 12- and 24-weeks post-treatment. The Pittsburgh Sleep Quality Index (PSQI) and the Montgomery Åsberg Depression Rating Scale (MADRS) evaluated changes in sleep and mood, respectively, at each time point. Results: Among the 27 participants included in the analysis of this thesis, a two-way repeated measures ANOVA showed significant improvements in PSQI scores within the MET-2 group (n= 13) compared to the placebo group (n= 14) from baseline to week 6 (p= 0.044) and baseline to week 18 (p= 0.011), after adjusting for sex and age. Although MADRS scores did not display inter-group differences, intra-group trends revealed notable mood improvements in MET-2 recipients from baseline to week 6 (p<0.001) and baseline to week 12 (p= 0.003). Conclusion: This study is the first to examine the potential efficacy of MET-2 in mitigating sleep disturbances in individuals with MDD, suggesting the potential benefits in treating sleep-related symptoms in MDD. The results of this study contribute to a growing body of research on gut repopulation as a treatment method for a variety of psychiatric illnesses, offering new insights and directions for future investigations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".