Leukocyte Telomere Length in HIV-Infected Pregnant Women Treated With Antiretroviral Drugs During Pregnancy and Their Uninfected Infants
Bibliographic record
Abstract
OBJECTIVES: HIV disease can lead to accelerated telomere attrition, although certain drugs used as part of antiretroviral therapy (ART) can inhibit telomerase reverse transcriptase activity. This could in turn lead to shorter telomeres. We hypothesized that HIV and ART exposure would be associated with shorter leukocyte telomere length (TL) in exposed mother/infant pairs compared with controls. METHODS: In these retrospective and prospective observational cohort studies, TL was evaluated in peripheral blood leukocytes obtained from HIV-infected pregnant women treated with ART and their uninfected infants, and compared with HIV untreated (retrospective cohort) or HIV mothers and their infants (prospective cohort). RESULTS: In HIV-infected ART-exposed mothers, leukocyte TL was not significantly shorter than that in HIV untreated mothers or HIV controls, nor was their infants' TL significantly different. Cord blood of ART-exposed infants exhibited TL shorter than that from infants born to HIV-negative mothers. Placenta also showed evidence of shorter TL after adjustment for relevant covariates. Factors associated with shorter maternal and infant TL included smoking and the use of drugs of addiction in pregnancy. CONCLUSIONS: These results suggest that maternal HIV infection or exposure to ART has minimal effect on infant leukocyte TL, a reassuring finding. In contrast, tissues that express higher telomerase activity such as umbilical cord blood and placenta appear comparatively more affected by ART. Smoking and the use of drugs of addiction have a negative impact on maternal and infant leukocyte TL, possibly through oxidative telomere damage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".