Altered placental immune cell composition and gene expression with isolated fetal spina bifida
Bibliographic record
Abstract
Abstract Problem Maternal B vitamin deficiency increases the risk of fetal spina bifida (SB) and placental maldevelopment. It is unclear whether placental processes involving folate are altered in fetuses with SB in a contemporary cohort. We hypothesised that fetal SB would associate with reduced expression of key folate transporters (folate receptor-α [FRα], proton coupled folate receptor [PCFT], and reduced folate carrier [RFC]), and an increase in Hofbauer cell (HBC) abundance and folate receptor- β ( FRβ) expression by HBCs. Method of Study FRα, PCFT, and RFC protein localisation and expression (immunohistochemistry) and HBC phenotypes (RNA in situ hybridization) were assessed in placentae from fetuses with SB (cases; n=12) and with no congenital anomalies (controls; n=22). Results Cases (vs. gestational age [GA]-matched controls) had a higher proportion of placental villous cells that were HBCs (6.9% vs. 2.4%, p=0.0001) and higher average FRβ expression by HBCs (3.2 mRNA molecules per HBC vs. 2.3, p=0.03). HBCs in cases were largely polarised to a regulatory phenotype (median 92.1% of HBCs). In sex-stratified analyses, male, but not female, cases had higher HBC levels and FRβ expression by HBCs 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 immunolabelling. Conclusions HBC abundance and FRβ expression by HBCs are increased in placentae of fetuses with isolated SB, suggesting immune-mediated dysregulation in placental development and function, and could contribute to SB-associated comorbidities, such as poor fetal growth.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".