Maternal circulating interferon‐γ and interleukin‐6 as biomarkers of Th1/Th2 immune status throughout pregnancy
Bibliographic record
Abstract
AIM: T cells may be classified as T helper type 1 (Th1) cells, which synthesize cytokines inducing cellular immunity, or T helper type 2 (Th2), which synthesize cytokines inducing humoral immunity. According to the Th1/Th2 paradigm, it has been postulated that successful pregnancy induces an immune Th2 bias, but it is not yet clear how Th1 and Th2 systems vary simultaneously throughout the pregnancy. METHODS: Using maternal circulating interferon-gamma (IFN-gamma) and interleukin-6 (IL-6) as biomarkers of Th1 and Th2 cytokines, respectively, we examined the variation of circulating Th1/Th2 ratio in 35 healthy pregnant women from 10 to 40 weeks of pregnancy. RESULTS: With increasing gestational age, maternal circulating levels of IFN-gamma decrease, whereas those of IL-6 increase. The IFN-gamma/IL-6 ratio switches around the 19th week of pregnancy. CONCLUSIONS: Our results suggest that maternal systemic IFN-gamma and IL-6 concentrations may be biomarkers of Th1/Th2 immune status during pregnancy. Moreover, our findings showed that contrary to the Th1/Th2 paradigm, the Th1 bias may be prevailing at the beginning of pregnancy, balanced in the middle of pregnancy and supplanted by the Th2 bias at the end of pregnancy.
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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 | 0.002 |
| 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) | 0.000 | 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".