Abstract 82: Angiogenesis Following Hind-Limb Ischemia in Mice Generates a Functionally Abnormal Microvasculature
Bibliographic record
Abstract
Extensive angiogenesis can occur in ischemic muscle. However, the extent to which newly formed microvessels regulate blood flow in ischemic and regenerating muscle remains unknown. To answer this, we developed an intravital video microscopy approach to red blood cell imaging in the extensor digitorum longus (EDL) muscle of mice following femoral artery excision. After surgery, blood flow ceased in the EDL microvasculature, followed by widespread muscle necrosis. However, 10 days later an extensive and highly branched network of flowing neovessels had regenerated. On day 14, branch pruning was evident, and vessel length density reached that of uninjured EDL. By day 28, the network grossly resembled that of the uninjured EDL, and complete arteriovenous units had developed. However, lumenal cross-sectional area of neocapillaries was 40% greater than uninjured capillaries (p<0.05). In addition, 47% of neoarterioles flowed directly into venules, bypassing capillaries. Mean red blood cell flow in neocapillaries was only 59% of uninjured capillary flow (p<0.05) and displayed reduced flow heterogeneity (p<0.05). To evaluate the functional responsiveness of the regenerated network, the EDL was subjected to local hypoxia (2% O 2 ) via a polydimethylsiloxane (PDMS) membrane. Red blood cell flow in neocapillaries increased to only 66% of that in uninjured EDL capillaries (54.6±9.0 vs 82.6±7.4 μm/sec increase, p<0.05). Furthermore, the ability to sustain a hypoxic flow response was profoundly reduced in neocapillaries (p<0.05). Conclusions: Despite robust angiogenesis, the regenerated network in skeletal muscle is characterized by enlarged capillaries, slow red blood cell transit, non-functional flow units, and impaired flow responsiveness. These findings suggest that: 1) capillary density and bulk flow are inadequate indicators of functional angiogenesis; and 2) strategies beyond stimulating angiogenesis are needed to optimize flow to ischemic tissues.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".