Hypoxia and Hypoxia-Inducible Factor-1 Target Genes in Central Nervous System Radiation Injury
Bibliographic record
Abstract
PURPOSE: Microvascular permeability changes and loss of blood-brain barrier integrity are important features of central nervous system (CNS) radiation injury. Expression of vascular endothelial growth factor (VEGF), an important determinant of microvascular permeability, was examined to assess its role in CNS radiation damage. Because hypoxia mediates VEGF up-regulation through hypoxia-inducible factor-1alpha (HIF1alpha) induction, we studied the relationships of hypoxia, HIF1alpha expression, and expression of VEGF in this damage pathway. EXPERIMENTAL DESIGN: Expression of HIF1alpha, VEGF, and another hypoxia-responsive gene, glucose transporter-1, was assessed in the irradiated rat spinal cord using immunohistochemistry and in situ hybridization. Hypoxic areas were identified using the nitroimidazole 2-(2-nitro-1H-imidazole-L-yl)-N-(2,2,3,3,3,-pentafluoropropyl) acetamide. To determine the causal importance of VEGF expression in radiation myelopathy, we studied the response of transgenic mice with greater (VEGF-A(hi/+)), reduced (VEGF-A(lo/+)), and wild-type VEGF activity to thoracolumbar irradiation. RESULTS: In rat spinal cord, the number of cells expressing HIF1alpha and VEGF increased rapidly from 16 to 20 weeks after radiation, before white matter necrosis and forelimb paralysis. A steep dose response was observed in expression of HIF1alpha and VEGF. HIF1alpha and VEGF expressing cells were identified as astrocytes. Hypoxia was present in regions where up-regulation of VEGF and glucose transporter-1 and increased permeability was observed. VEGF-A(lo/+) mice had a longer latency to development of hindlimb weakness and paralysis compared with wild-type or VEGF-A(hi/+) mice. CONCLUSIONS: VEGF expression appears to play an important role in CNS radiation injury. This focuses attention on VEGF and other genes induced in response to hypoxia as targets for therapy to reduce or prevent CNS radiation damage.
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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) | 0.001 | 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".