Abstract 178: Angiogenesis is Triggered by Nutrient Deprivation via Gcn2/atf4-dependent Regulation of Vegf and H2s Production
Bibliographic record
Abstract
Objective: Angiogenesis is crucial to maintain tissue homeostasis under nutrient and oxygen deprivation (ischemia). Although considerable evidence supports that angiogenesis is regulated by hypoxia-HIF1α induction of vascular endothelial growth factor (VEGF), the role of nutrient deprivation in angiogenesis is poorly defined. Approach and Results: We report that nutrient deprivation in the form of dietary sulfur amino acid restriction (Methionine/cysteine Restriction; MR) promotes VEGF expression and functional growth of new capillaries in skeletal muscle of mice (Fig.1 A, B). This occurred independently of hypoxia or HIF1α, but instead required the amino acid-sensing eIF2α kinase GCN2 and the transcription factor ATF4 (Fig. 1C). In addition to increased VEGF, nutrient deprivation boosted production of the pro-angiogenic gas hydrogen sulfide (H 2 S) via increased GCN2/ATF4-dependent expression of the H 2 S-generating enzyme cystathionine-gamma-lyase (CGL). The genetic requirement for CGL in angiogenesis triggered by nutrient deprivation, exercise or local VEGF overexpression, as well as the ability of local CGL overexpression to promote angiogenesis in vivo, revealed the critical importance of CGL-derived H 2 S in angiogenesis (Fig. 1D). Finally, plasma H 2 S was reduced in patients with vascular disease (versus non-diseased age-matched controls), and correlated with 2-year survival following vascular surgery (Fig.1 E, F). Conclusions: These data reveal a nutrient-sensing pathway targetable by diet as a previously unrecognized central regulator of VEGF expression and angiogenesis independent of canonical hypoxic signaling. This discovery points to novel dietary interventions and GCN2/ATF4/CGL/H 2 S-based strategies to manipulate angiogenesis. Figure 1
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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) | 0.003 | 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".