Examining the Effects of Gestational Physical Activity and Hofbauer Cell Polarization on Angiogenic Factors
Bibliographic record
Abstract
While gestational physical activity (PA) has demonstrated health benefits for both birthing parent and fetus, the mechanisms still need to be fully understood. Placental macrophages, or Hofbauer cells (HBCs), comprise a heterogenous population containing inflammatory (CD206-) and anti-inflammatory (CD206+) phenotypes. Similar to other tissue-resident macrophages (TRMs), HBCs are potential mediators of angiogenesis due to their secretion of both pro- and anti-angiogenic factors, including FGF2, VEGF, and SPRY2. While PA is associated with an increase in the proportion of VEGF- and FGF2-producing CD206+ macrophages in other tissues, the phenotypes producing FGF2, VEGF, and SPRY2 in the placenta and the associated relationships with gestational PA have not been studied. Using accelerometry, pregnant participants were classified as physically active or inactive in mid- and late-gestation. Term placenta tissue was collected at delivery and used for Western blotting and immunofluorescence to examine the protein expression of FGF2 and SPRY2, and to localize FGF2 in histological samples, respectively. Primary cultures of HBCs were used to examine the phenotypic differences in FGF2, SPRY2, and VEGF production. While no differences in the placental expression of SPRY2, total FGF2, or high-molecular-weight FGF2 were observed based on PA status, active individuals had significantly reduced levels of low-molecular-weight FGF2. Additionally, HBCs of all polarizations produce VEGF, FGF2, and SPRY2, and can form intercellular junctions and multinucleated giant cells. These findings suggest a possible relationship between PA and HBC-driven angiogenesis, providing an avenue for future exploration.
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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 | 0.000 |
| 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 | 0.001 |
| 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".