Altered placental immune cell composition and gene expression with isolated fetal spina bifida
Bibliographic record
Abstract
PROBLEM: Fetal spina bifida (SB) is more common in pregnant people with folate deficiency or anomalies of folate metabolism. It is also known that fetuses with SB have a higher risk of low birthweight, a condition that is typically placental-mediated. We therefore hypothesized that fetal SB would associate with altered expression of key placental folate transporters and an increase in Hofbauer cells (HBCs), which are folate-dependent placental macrophages. METHOD OF STUDY: Folate receptor-α (FRα), proton coupled folate receptor (PCFT), and reduced folate carrier (RFC) protein localization and expression (immunohistochemistry) and HBC phenotypes (HBC abundance and folate receptor-β [FRβ] expression; RNA in situ hybridization) were assessed in placentae from fetuses with SB (cases; n = 12) and in term (n = 10) and gestational age (GA) - and maternal body mass index - matched (n = 12) controls without congenital anomalies. RESULTS: Cases had a higher proportion of placental villous cells that were HBCs (6.9% vs. 2.4%, p = .0001) and higher average HBC FRβ expression (3.2 mRNA molecules per HBC vs. 2.3, p = .03) than GA-matched controls. HBCs in cases were largely polarized to a regulatory phenotype (median 92.1% of HBCs). In sex-stratified analyses, only male cases had higher HBC levels and HBC FRβ expression than GA-matched controls. There were no differences between groups in the total percent of syncytium and stromal cells that were positive for FRα, PCFT, or RFC protein immunolabeling. CONCLUSIONS: HBC abundance and FRβ expression by HBCs are increased in placentae of fetuses with SB, suggesting immune-mediated dysregulation in placental phenotype, and could contribute to SB-associated comorbidities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".