Chronic intermittent hypobaric hypoxia attenuates ischemic limb injury by promoting angiogenesis in mice
Bibliographic record
Abstract
This study aimed to evaluate the protective effect of chronic intermittent hypobaric hypoxia (CIHH) against limb ischemic injury. C57BL/6 mice were randomly divided into three groups: limb ischemic injury group (Ischemia, induced by ligation and excision of the left femoral artery), limb ischemia following CIHH pretreatment group (CIHH+Ischemia, simulated a 5000 m altitude hypoxia, 6 h per day for 28 days, before induction of hind-limb ischemia), and sham group (Sham). The blood flow in the mouse models of hind-limb ischemia was examined using laser doppler imaging. The functional and morphological performance of ischemic muscle was evaluated using contraction force and hematoxylin–eosin and Masson’s trichrome staining. Angiogenesis was determined by immunohistochemistry staining of the endothelial markers CD31 and CD34. The protein expressions of angiogenesis-related genes were detected using Western blot assay. Chronic ischemia resulted in reduced blood perfusion, decreased contraction tension, and morphological destruction in gastrocnemius muscle. CIHH pretreatment increased the contractile force and muscle fiber diameter and decreased necrosis and fibrosis of the ischemic muscle. Also, CIHH significantly increased the density of CD31+ and CD34+ cells and promoted the expression of angiogenesis-related molecules in ischemic muscle. These data demonstrate that CIHH has a protective effect against chronic limb ischemia by promoting angiogenesis.
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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 | 0.001 |
| 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".