Double-Blind Randomized Placebo Controlled Trial of a <i>Lactobacillus</i> Probiotic Blend in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Abstract Rationale The gut-lung axis describes the crosstalk between the gut and lung wherein microbiota in the gut modulate systemic anti-inflammatory and immune responses in the lungs. Objectives: We hypothesized that a blend of probiotic bacteria ( Lactobacilli ) combined with herbal extracts (resB®) could improve quality of life in COPD patients. Methods We conducted a randomized, double-blinded, placebo-controlled study ( NCT05523180 ) evaluating the safety and impact of resB® on quality of life in volunteers with COPD. Participants took two capsules of resB® or placebo orally daily for 12 weeks. The primary endpoint was quality of life changes by Saint George’s Respiratory Questionnaire (SGRQ). In addition to safety, exploratory endpoints included changes in serum and sputum biomarkers as well as sputum and stool microbiome. Measurements and Main Results resB® was well tolerated by all participants, with no related adverse events reported. Participants who received resB® had improvement in their SGRQ symptom scores from baseline to final visit (P<0.05), while the change in SGRQ symptom scores in those receiving placebo was not significant. Serum and sputum concentrations of matrix metalloproteinase 9, serum c-reactive protein, and serum interleukin 6 decreased (P<0.05) between baseline and final visit in the resB® group, corresponding with an increase in stool Lactobacilli abundance. Relative abundance of Veillonella also increased in stool and sputum in the resB® group. Conclusions Participants with COPD who received resB® improved in respiratory symptoms over a 12-week course. Serum and sputum biomarkers suggest administration of the probiotic and herbal blend reduces inflammation and may thereby attenuate symptoms.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".