Pregnancy associates with alterations to the host and microbial proteome in vaginal mucosa
Bibliographic record
Abstract
PROBLEM: Pregnant women are at increased risk of HIV acquisition, but the biological mechanisms contributing to this observation are not well understood. METHOD OF STUDY: Here, we assessed host immune and microbiome differences in the vaginal mucosa of healthy pregnant and non-pregnant women using a metaproteomics approach. Cervicovaginal lavage (CVL) samples were collected from 23 pregnant and 25 non-pregnant women. RESULTS: Mass spectrometry analysis of CVL identified 550 human proteins and 376 bacterial proteins from 11 genera. Host proteome analysis indicated 56 human proteins (10%) were differentially abundant (P < .05) between pregnant and non-pregnant women, including proteins involved in angiogenesis (P = 3.36E-3), cell movement of phagocytes (P = 1.34E-6), and permeability of blood vessels (P = 1.27E-4). The major bacterial genera identified were Lactobacillus, Gardnerella, Prevotella, Megasphaera, and Atopobium. Pregnant women had higher levels of Lactobacillus species (P = .017) compared with non-pregnant women. Functional pathway analysis indicated that pregnancy associated with changes to bacterial metabolic pathway involved in energy metabolism, which were increased in pregnant women (P = .035). CONCLUSION: Overall, pregnant women showed differences in the cervicovaginal proteome and microbiome that may be important for HIV infection risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".