Systemic Inflammation Is Associated with Ovarian Follicular Dynamics during the Human Menstrual Cycle
Bibliographic record
Abstract
BACKGROUND: Ovarian processes and the timing of ovulation are important predictors of both female fertility and reproductive pathology. Multiple waves of antral follicular development have been documented during the menstrual cycle in women. However, the mechanisms underlying the development of follicular waves and their clinical significance are not fully understood. The objective of this study was to examine the relationship between C-reactive protein (CRP) and follicular waves in healthy women. We wanted to determine whether follicular wave dynamics influence systemic inflammation, as ovarian activity increases local inflammatory processes and blood flow. We tested the hypothesis that women with 3 follicular waves would have higher CRP concentrations than those with 2 waves. We further hypothesized that a greater number of major waves (those with a dominant follicle) would be positively associated with CRP. METHODS/PRINCIPAL FINDINGS: Thirty-nine healthy women underwent daily transvaginal ultrasound examinations for one interovulatory interval, as part of an earlier study. Serum was collected every 3 days during the interovulatory interval (IOI). Enzyme-linked immunosorbent assays were conducted to quantify serum CRP concentrations. Women with 3 waves had higher average log CRP concentrations (n = 14, -0.43±0.35) over the IOI than those with 2 waves (n = 25, -0.82±0.47, p = 02). Average log CRP concentrations were greater in women with 3 (0.30±0.31) versus 1 (-0.71±0.55) or 2 (-0.91±0.47) major waves (p = 0.03). Greater average CRP over the IOI was attributed to greater CRP in the follicular, but not the luteal phase, of the IOI. CONCLUSIONS/SIGNIFICANCE: A greater number of total antral follicular waves, in particular major waves, corresponded to greater serum concentrations of CRP. These findings suggest that women with a greater number of follicular waves exhibit greater tissue remodeling and therefore greater local and systemic inflammation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".