Epigenetic impairment and blunted transcriptional response to <i>Mycobacterium tuberculosis</i> of alveolar macrophages from persons living with HIV
Bibliographic record
Abstract
Abstract Persons living with HIV (PLWH) are at increased risk of tuberculosis (TB). HIV-associated TB is often the result of recent infection with Mycobacterium tuberculosis ( Mtb ) followed by rapid progression to disease. Alveolar macrophages (AM) are the first cells of the innate immune system that engage Mtb , but how HIV and antiretroviral therapy (ART) impact on the anti-mycobacterial response of AM is not known. To investigate the impact of HIV and ART on the transcriptomic and epigenetic response of AM to Mtb , we obtained AM by bronchoalveolar lavage from 20 PLWH receiving ART, 16 control subjects who were HIV-free (HC), and 14 subjects who received ART as pre-exposure prophylaxis (PrEP) to prevent HIV infection. Following in-vitro challenge with Mtb , AM from each group displayed overlapping but distinct profiles of significantly up- and down-regulated genes in response to Mtb . Compared to HC subjects, AM isolated from PLWH and PrEP subjects presented a substantially weaker transcriptional response. Further investigation of chromatin structure revealed that AM from control subjects challenged with Mtb responded with pronounced accessibility changes in over ten thousand regions. In stark contrast, AM obtained from PLWH and PrEP subjects displayed no significant changes in their chromatin state in response to Mtb . Collectively, these results revealed a previously unknown adverse effect of ART on the epigenetic landscape and transcriptional responsiveness of AM.
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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 | 0.000 |
| 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".