Evaluation of the PLAC8 Gene in Mexican Women With and Without Preeclampsia and Obesity
Bibliographic record
Abstract
Preeclampsia (PE) is a leading cause of maternal-fetal mortality worldwide, and obesity is an important risk factor. Genes associated with pathophysiological events common to preeclampsia and obesity, such as PLAC8, remain to be studied; therefore, the aim of the present study was to evaluate this gene in the placentas of women affected with preeclampsia and healthy pregnant women. This case-controlled study included 71 healthy and 64 preeclampsia pregnancies. Gene expression was evaluated in primary human cytotrophoblasts (PHCT) from six normal and six preeclampsia pregnancies, and protein expression was verified in placentas from five healthy and six preeclampsia pregnancies. The whole coding and 5′ regions of the PLAC8 gene were sequenced from healthy (n = 10) and preeclamptic (n = 10) pregnancies. The presence of the observed nucleotide variations was analyzed by RT-PCR in the total population. Statistical analyses were performed accordingly. Obesity was associated with severe preeclampsia (SPE) (OR = 3.34; CI 95% 1.3–8.2, p < 0.01). Significantly higher mRNA and protein expression was observed in preeclamptic vs. healthy placentas (p < 0.05). After sequencing, a single nucleotide variation was identified in 10 cases and one control (p < 0.01), which was then evaluated in the total population showing no association with preeclampsia. This preliminary study confirms the association of SPE with obesity and suggests higher expression of PLAC8 mRNA and protein in placentas from preeclampsia. No differences in nucleotide variations between cases and controls of the whole population were observed. Further research is required to evaluate the implications of higher gene/protein expression in preeclampsia and the causes of such variation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".