Maternal inflammation during late pregnancy is lower in physically active compared with inactive obese women
Bibliographic record
Abstract
The primary purpose of this study was to compare maternal plasma inflammation between physically active and inactive obese women during late pregnancy. The secondary purpose was to examine the relationships between maternal plasma inflammation and lipid metabolism and maternal and neonatal metabolic health in these women. A cross-sectional, observational study design was performed in 16 obese-inactive (OBI; means ± SD; age, 25.0 ± 4.8 years; prepregnancy body mass index (BMI), 36.3 ± 4.3 kg/m(2); body fat percentage in late gestation, 37.7% ± 3.5%) and 16 obese-active (OBA; age, 28.9 ± 4.8 years; prepregnancy BMI, 34.0 ± 3.7 kg/m(2); body fat in late gestation, 36.6% ± 3.8%) women during the third trimester of pregnancy. Maternal plasma inflammation (C -reactive protein (CRP)) and insulin resistance (Homeostatic Model Assessment-Insulin Resistance) were measured at rest. Plasma lipid concentration and metabolism (lipid oxidation and lipolysis) were measured at rest, during a 30-min bout of low-intensity (40% peak oxygen uptake) exercise, and during a resting recovery period using indirect calorimetry. Umbilical cord blood was collected for measurement of neonatal plasma insulin resistance, inflammation, and lipid concentration. Neonatal body composition was measured via air displacement plethysmography. Maternal plasma CRP concentration was significantly higher in OBI compared with OBA women (9.1 ± 4.0 mg/L vs. 6.3 ± 2.5 mg/L, p = 0.02). Maternal plasma CRP concentration was significantly associated with maternal lipolysis (r = 0.43, p = 0.02), baseline lipid oxidation rate (r = 0.39, p = 0.03), and baseline plasma free fatty acid concentration (r = 0.36, p = 0.04). In conclusion, maternal physical activity may reduce inflammation during pregnancy in obese women. Maternal lipid metabolism is related to systemic inflammation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".