Reactivity of isolated human chorionic vessels: analysis of some influencing variables
Bibliographic record
Abstract
The aim of the study was to determine whether 24 h of cold storage of samples, mode of delivery, and gestational age influenced in vitro human chorionic vascular reactivity (35 arteries and 34 veins). The following groups were compared: (i) fresh versus 24-h cold-stored (4 degrees C in Krebs-Henseleit solution) chorionic vascular rings from normal term placentas, (ii) fresh chorionic vascular rings from normal term placentas obtained after vaginal delivery versus those obtained after elective caesarean section, and (iii) fresh chorionic vascular rings from normal term placentas versus those obtained from preterm deliveries. Isometric recording of the concentration-response curve to KCl (5-120 mM) was assessed in each group. In vitro human chorionic vascular reactivity was influenced negatively by the 24-h cold storage of samples, with only 30% of stored samples being weakly reactive to KCl. Human chorionic vascular reactivity to KCl was unaffected by the mode of delivery. However, the response to KCl was gestational-age dependent. Thus, preterm vascular rings exhibited a significantly (P<0.05) decreased response (Emax=9.8 +/- 0.0 mN; EC50=26.0 +/- 1.3 mM) compared with term samples (Emax=21.6 +/- 2 mN; EC50=13.9 +/- 1.6 mM). In conclusion, this study provides evidence that fresh term vascular rings are the tissues of choice for studying human chorionic vascular reactivity.
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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 | 0.001 |
| 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".