FAS A‐670G and Fas ligand IVS2nt A 124G polymorphisms are significantly increased in women with pre‐eclampsia and may contribute to HELLP syndrome: a case‐controlled study
Bibliographic record
Abstract
OBJECTIVE: We evaluated the association between the Fas-670A/G and the Fas ligand FasL IVS2nt 124 A/G polymorphisms and the risk of pre-eclampsia and its complications. DESIGN: A case-controlled study. SETTING: University Hospitals in most areas of Tunisia. POPULATION: We recruited 300 pregnant women who developed pre-eclampsia and 300 age-matched healthy pregnant women from the same hospital. METHODS: Genotyping of Fas-670A/G and the FasL IVS2nt 124A/G gene polymorphisms were conducted using polymerase chain reaction-restriction fragment length polymorphism among our cohort. MAIN OUTCOME MEASURES: Fisher's exact test was used to compare the statistical differences between groups for categorical variables and Student t tests were used for continuous variables. RESULTS: The frequency of the Fas-670G gene variant was significantly increased in women with pre-eclampsia (42%) compared with control women (30%; P < 0.001). Also, a statistically significant difference was obtained in the distribution of the FasL IVS2nt 124G gene variant when comparing women with pre-eclampsia (43%) with controls (30%; P < 0.001). Interestingly, we found that the carriage of Fas-670G was associated with increased liver enzymes, suggesting an increased prevalence of the haemolysis, elevated liver enzymes and low platelets (HELLP) syndrome, a pre-eclampsia complication. CONCLUSION: The Fas-670G and FasL IVS2nt 124G polymorphisms are associated with a higher risk of pre-eclampsia and its complications. TWEETABLE ABSTRACT: Polymorphisms in the Fas and FasL genes are associated with increased risk of pre-eclampsia and HELLP syndrome.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".