Toll‐like receptors 2 and 4 and the cryopyrin inflammasome in normal pregnancy and pre‐eclampsia
Bibliographic record
Abstract
OBJECTIVE: Pre-eclampsia involves a maternal inflammatory response that differs from both normal pregnancy and normotensive intrauterine growth restriction (IUGR). Our objective was to examine neutrophil Toll-like receptor (TLR), cryopyrin, nuclear factor-kappaB (NF-kappaB) subunit and interleukin-1beta (IL-1beta), and inflammatory cytokine profiles in women with pre-eclampsia or normotensive IUGR, as well as in normal pregnancy and non-pregnancy controls. DESIGN AND METHOD: A case-control study was performed. We examined the messenger RNA (mRNA) and protein expressions of TLR4 and TLR2, mRNA levels of cryopyrin, IL-1beta, NF-kappaB subunits p50 and p65, as well as maternal serum inflammatory cytokine profiles (IL-2, IL-6, tumour necrosis factor-alpha [TNF-alpha], interferon-gamma [IFN-gamma] and IL-10) in women with and without pre-eclampsia using real-time reverse transcription polymerase chain reactions, flow cytometry and multiplex immunoassays. SETTING: A single tertiary maternity hospital in Vancouver, Canada. POPULATION: Women with early-onset pre-eclampsia (<34 weeks of gestation, n = 25), women with late-onset pre-eclampsia (>or=34(+0) weeks of gestation, n = 25), women with normotensive IUGR (n = 25), women with normal pregnancy (n = 75) and non-pregnancy (n = 25) controls. RESULTS: Women with pre-eclampsia (as a single combined group of early- and late-onset, and particularly in women with early-onset pre-eclampsia) had increased TLR2 and TLR4 mRNA and protein expressions elevated cryopyrin, NF-kappaB subunit, and IL-1beta mRNA expression, and TNF-alpha:IL-10 and IL-6:IL-10 ratios compared with other groups. CONCLUSIONS: These data suggest that TLRs and cryopyrin may modulate the innate immune response of the maternal syndrome of pre-eclampsia, and might also trigger the differential inflammatory response existing between early onset pre-eclampsia and normotensive IUGR.
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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".