Observation of neonatal microvessels and status of myocardial cells after transmycardial laser revascularization
Bibliographic record
Abstract
Objective:To observe angiogenesis surrounding laser channel and status of myocardial cells in ischemia area after transmycardial laser revascularization Methods: the 18 dogs were randomly divided into 3 group ,six served as non transmural group(NTG), six as transmural group(TG), six as control group(CG) Left anterial decend artery(LAD) was ligated at about the junction of its proximal and medial thirds to induce myocardial ischemia The 10～15 channels were created with the neodymium laser in ischemic area two months later, the dogs were sacrificed Image analysis system was engaged to evaluate the content of interstitial collagen, density of microvessels and areameter of microvessels Electronic microscope was used to observe the changes of mitochondria Results: at two months ①the density of microvessels around the channels both in TG and NTG was higher( P 0 05) than that of the control group, the areameter of TG was greater than that of NTG ②amount of collagen in CG was 19 43±2 65% versus in NTG 9 31±1 02% ( P 0 05) and versus in TG 5 19±0 54%( P 0 05) ③Degree of mitochondrial injury was normal or slightly damaged in TG, but were irreversible damaged in CG Conclusion: Transmycardial laser revascularization results in significant improvement in myocardial perfusion and induces angiogenesis in ischemic myocardium
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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 | 0.000 |
| 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) | 0.002 | 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".