Cycle‐phase dependent associations between <scp>CRP</scp>, leptin, and reproductive hormones in an urban, <scp>C</scp>anadian sample
Bibliographic record
Abstract
OBJECTIVES: To assess the relationships among reproductive hormones, follicular development, inflammation, and adiposity in a sample of urban, Canadian women. MATERIALS AND METHODS: Participants (n = 41) had blood collected every 3 days through one interovulatory interval (IOI) to measure estradiol, progesterone, LH, FSH, leptin, and C-reactive protein (CRP). Participants underwent daily transvaginal ultrasound examinations during the IOI to quantify all follicles > 2 mm. CRP and leptin tertiles were used to compare conditions of high and low inflammatory processes and adiposity, respectively. RESULTS: Luteal phase estradiol, luteal phase LH, and follicular phase progesterone were lower among individuals in the highest CRP tertile (adjusted r(2) = 0.63, 0.70, 0.76, respectively). Luteal and follicular phase follicle diameter was greatest in the high CRP tertile (adjusted r(2) = 0.68, 0.71). Follicular phase progesterone was lowest among individuals in the highest leptin tertile, and follicular phase FSH was lowest among individuals in the lowest leptin tertile (adjusted r(2) = 0.54, 0.45). Luteal phase follicle diameter was highest among those in the moderate leptin tertile (adjusted r(2) = 0.49). DISCUSSION: This study is a first comprehensive assessment of the relationship between multiple ovarian function components and inflammatory biomarkers. The results are interpreted to mean that inflammatory and energetic stressors produce differential effects depending on population, adiposity, and cycle phase. Am J Phys Anthropol 160:389-396, 2016. © 2016 Wiley Periodicals, Inc.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".