Elucidating the interaction between maternal physical activity and circulating myokines throughout gestation: A scoping review
Bibliographic record
Abstract
Physical activity (PA) during pregnancy provides both maternal and fetal health benefits. It has been theorized that myokines, peptides secreted by contracting skeletal muscle, may play an important mechanistic role in facilitating the health benefits obtained from prenatal exercise. The objective of this review was to synthesize the current literature on the relationship between maternal PA and myokine response. A search strategy was developed using the terms pregnancy, PA, IL-6, IL-10, IL-13, and TNF-α. A systematic search was completed in July 2020, in Medline, SPORTDiscus, EMBASE, CENTRAL, and in November 2020 for unpublished dissertations (grey literature; Proquest). Both human- and animal-based studies of any design were included, while commentaries and editorial articles were excluded. Data were extracted by two independent reviewers and summarized narratively. Data were thematically summarized based on the myokine and whether findings were from human or animal studies. Ten studies were included in this review. Findings from studies that examined IL-6, IL-10, and TNF-α suggest a trimester-specific interaction between PA and myokine levels; no studies evaluated IL-13. Future research should investigate the PA-myokine relationship throughout all stages of gestation.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".