Placental Mitochondrial Dysfunction in relation to preterm delivery in HIV pregnancy
Bibliographic record
Abstract
Background: Preterm birth (PTB) (<37 weeks of gestation), is the leading cause of mortality and morbidity among children, responsible for >1 million deaths in 2015 [1]. In North America, PTB occurs in 6–10% of births. However, among pregnant women living with HIV, the rates are higher (18-29%). To date, there is no generally accepted mechanism underlying such increased rates. One possible explanation is reduced maternal progesterone production during pregnancy, which may be related to HIV infection and/or antiretroviral (ARV) treatment. Synthesis of progesterone (hormone central to pregnancy maintenance), is dependent on placental mitochondrial function. Given that many ARVs can affect mitochondrial (mt) function, I investigated the possible effects of ARV on placental mtDNA content and progesterone levels. Methods: 136 HIV+ and 60 HIV- pregnant women were enrolled in the Canadian prospective study, the Children and women: Antiretroviral and Markers of Aging (CARMA) cohort. Placenta and blood specimens, as well as clinical and sociodemographic data, were collected. Placental and plasma progesterone levels, as well as placenta mtDNA content, were measured using ELISA and qPCR respectively. We extended these investigations of ARV effects to in vitro models on two human placental cell lines, JEG-3 and BeWo. Results: Within this cohort, HIV-exposed uninfected (HEU) infants were born at an earlier gestational age (p=0.017), with a lower birth weight (p=0.011) compared to controls. PTB showed no association with HIV status, placenta mtDNA or progesterone levels. However, higher mtDNA was associated with preeclampsia (p<0.001), which often leads to PTB.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".