Can Probiotics Reduce Inflammation and Enhance Gut Immune Health in People Living with HIV: Study Designs for the Probiotic Visbiome for Inflammation and Translocation (PROOV IT) Pilot Trials
Bibliographic record
Abstract
OBJECTIVES: Despite substantial improvements in HIV outcomes with combination antiretroviral therapy (cART), morbidity and mortality remain above population norms. The gut mucosal immune system is not completely restored by cART, and the resultant microbial translocation may contribute to chronic inflammation, inadequate CD4 T-cell recovery, and increased rates of serious non-AIDS events. Since the microbial environment surrounding a CD4 T cell may influence its development and function, we hypothesize that probiotics provided during cART might reduce inflammation and improve gut immune health in HIV-positive treatment-naïve individuals (PROOV IT I) and individuals with suboptimal CD4 recovery on cART (PROOV IT II). METHODS: These prospective, double-blinded, randomized, placebo-controlled, multicenter pilot studies will assess the impact of the probiotic Visbiome at 900 billion bacteria daily. Forty HIV positive cART-naïve men will be randomized in the PROOV IT I study, coincident with antiretroviral initiation, and be followed for 24 weeks. In PROOV IT II, 36 men on cART, but with a CD4 T-cell count below 350 cells/mm(3) will be followed for 48 weeks. The primary outcome for both studies is the comparison of blood CD8 T-cell immune activation. Secondary analyses will include comparison of blood inflammatory biomarkers, microbial translocation, blood and gut immunology and HIV levels, the bacterial community composition, diet, intestinal permeability, and the safety, adherence and tolerability of the study product. DISCUSSION: These studies will evaluate the ability of probiotics as a safe and tolerable therapeutic intervention to reduce systemic immune activation and to accelerate gut immune restoration in people living with HIV.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".