Maternal plasma levels of follistatin‐related gene protein in the first trimester of pregnancies with Down syndrome
Bibliographic record
Abstract
OBJECTIVE: To determine maternal plasma levels of follistatin-related gene protein (FLRG) in the first trimester of pregnancy and assess its potential role as a marker for prenatal screening of Down syndrome. METHODS: Maternal plasma levels of FLRG were determined in 100 pregnant women with normal fetuses in their first trimester of pregnancy (i.e. 11th to 15th weeks). These results were compared with 20 cases with Down syndrome fetuses, taking into consideration clinical and demographic variables, such as maternal age, maternal weight, gestational age, smoking status and ethnicity. RESULTS: Maternal plasma median of FLRG in the normal population was 1.41 ng/mL with 95% confidence interval (CI) of 1.37-1.70 and interquartile range (IQR) of 0.88, during the 11th to 15th weeks of pregnancy. Maternal age and weight were the only variables significantly related to FLRG levels (p = 0.030 and 0.020, respectively). Only maternal and gestational ages were related to Down syndrome (p = 0.039 and 0.006, respectively). Maternal plasma levels of FLRG were not significantly different in the presence of Down syndrome fetuses compared to normal population (p = 0.63). CONCLUSION: FLRG can be successfully detected in maternal plasma in the first trimester of pregnancy. However, its levels are not significantly altered in the presence of Down syndrome fetuses.
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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 | 0.002 |
| 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 | 0.000 |
| 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".