Higher expression of HSP70 and LOX-1 in the placental tissues of pre-eclampsia pregnancies
Bibliographic record
Abstract
BACKGROUND: Pre-eclampsia, a hypertensive disorder of pregnancy is the main cause of fetal and maternal morbidity and mortality. Growing evidences suggest that placental oxidative stress involves in the pathogenesis of pre-eclampsia. The HSP70 is a novel marker of oxidative stress which binds with high avidity to LOX-1. The aim of this study was to evaluate the co-expression of HSP70 and LOX-1 in the placental tissues of normotensive and pre-eclamptic pregnancies. MATERIALS AND METHODS: The placental tissues were collected from 35 healthy women with normal pregnancies and 33 women with pre-eclampsia disorder. Expression of HSP70 and LOX-1 on the placental tissues was examined by using immunohistochemistry technique. The intensity of the molecules' expression was determined by semi-quantitative scoring. RESULTS: The 34.3% and 37.1% of the healthy women did not express the HSP70 and LOX-1 on their placenta, respectively. All pre-eclamptic patients expressed HSP70 and LOX-1 with various scores. Indeed, the majority of the pre-eclamptic subjects had ≥3+ scores of the expression of HSP70 and LOX-1 on their placenta (60.6% and 66.7%, respectively). The percentage of the ≥3+ scores of the expression of HSP70 and LOX-1 was significantly higher in patients than those in healthy women (p<0.0001 for both). Similarly, the majority of the pre-eclamptic subjects had ≥3+ scores of the co-expression of HSP70 and LOX-1 molecules (57.6%) which was significantly higher in patients than those in control group (p=0.0001). CONCLUSIONS: These results showed higher expression of HSP70 and LOX-1 in the placental tissues of pre-eclampsia patients which represent the possible contribution of these molecules in the disease pathogenesis. Further studies need to clarify their role in the pathogenesis of preeclampsia disorder.
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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) | 0.002 | 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".