Albumin Decrease Is Associated with Spontaneous Preterm Delivery within 48 h in Women with Threatened Preterm Labor
Bibliographic record
Abstract
Threatened preterm labor (TPTL) accounts for ∼30% of pregnancy-related hospital admissions. Maternal peripheral leukocytes can be used to monitor a variety of physiological processes occurring in the body. Two high-throughput mass spectrometry methodologies, SWATH and iTRAQ, were used to study differentially expressed peripheral blood leukocyte lysate proteins in symptomatic women admitted for TPTL who had a preterm birth within 48 h (n = 16) and those who did not (n = 24). The SWATH spectral library consisted of 783 proteins. SWATH methodology quantified 258 proteins (using ≥2 peptides) and 5 proteins (ALBU, ANXA6, HNRPK, HSP90A, and PDIA1) were differentially expressed (p < 0.05, Mann-Whitney U). iTRAQ workflow identified 765 proteins; 354 proteins were quantified and 14 proteins (MIF, UBIQ, HXK3, ALBU, HNRPD, ST1A2, RS15A, RAP1B, CAN1, IQGA2, ST1A1, COX5A, ADDA, and UBQL1) were significantly different between the two groups of women (p < 0.05, Mann-Whitney U). Albumin was the only common differentially expressed protein in both SWATH (28% decrease) and iTRAQ studies (45% decrease). This decrease in albumin was validated using ELISA (11% decrease, p < 0.05, Mann-Whitney U) in another 23 TPTL women. This work suggests that albumin is a broad indicator of leukocyte activation with impending preterm birth and provides new future work directions to understand the pathophysiology of TPTL.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".