LILAC pilot study: Effects of metformin on mTOR activation and HIV reservoir persistence during antiretroviral therapy
Bibliographic record
Abstract
Background Chronic inflammation and residual HIV transcription persist in people living with HIV (PLWH) receiving antiretroviral therapy (ART), thus increasing the risk of developing non-AIDS co-morbidities. The mechanistic target of rapamycin (mTOR) is a key regulator of cellular metabolism and HIV transcription, and therefore represents an interesting novel therapeutic target. Methods The LILAC pilot clinical trial, performed on non-diabetic ART-treated PLWH with CD4 + /CD8 + T-cell ratios <0.8, evaluated the effects of metformin (12 weeks oral administration; 500-850 mg twice daily), an indirect mTOR inhibitor, on the dynamics of immunological/virological markers and changes in mTOR activation/phosphorylation in blood collected at Baseline, Week 12, and 12 weeks after metformin discontinuation (Week 24) and sigmoid colon biopsies (SCB) collected at Baseline and Week 12. Findings CD4 + T-cell counts, CD4 + /CD8 + T-cell ratios, plasma markers of inflammation/gut damage, as well as levels of cell-associated integrated HIV-DNA and HIV-RNA, and transcriptionally-inducible HIV reservoirs, underwent minor variations in the blood in response to metformin. The highest levels of mTOR activation/phosphorylation were observed in SCB at Baseline. Consistently, metformin significantly decreased CD4 + T-cell infiltration in the colon, as well as mTOR activation/phosphorylation, especially in CD4 + T-cells expressing the Th17 marker CCR6. Also, metformin decreased the HIV-RNA/HIV-DNA ratios, a surrogate marker of viral transcription, in colon-infiltrating CD4 + T-cells of 8/13 participants. Interpretation These results are consistent with the fact that metformin preferentially acts on the intestine and that mTOR activation/phosphorylation selectively occurs in colon-infiltrating CCR6 + CD4 + T-cells. Future randomized clinical trials should evaluate the benefits of long-term metformin supplementation of ART.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".