Molecular Targets from VHL Studies into the Oxygen-Sensing Pathway
Bibliographic record
Abstract
Inheritance of a faulty von Hippel-Lindau (VHL) tumor suppressor gene is the cause of VHL disease, a rare multisystemic autosomal dominant disorder characterized by the development of hypervascular tumors in a number of organs, including the retina, brain, spine, pancreas, adrenal gland, and the kidney. Recent discoveries have demonstrated that the VHL gene product pVHL serves as a substrate-recognition component of an E3 ubiquitin ligase complex that targets hypoxia-inducible factor (HIF) transcription factor for polyubiquitination and subsequent degradation. Accordingly, tumor cells devoid of functional pVHL show an inappropriate accumulation of HIF, as well as downstream HIF-target genes, such as vascular endothelial growth factor (VEGF), a potent angiogenic factor. Furthermore, HIF has been found to be elevated in many human cancers further underscoring its common significance in oncogenesis. These and other related recent findings have shed significant insight into the mechanisms governing mammalian cellular oxygen homeostasis and how disruptions in this oxygen-sensing pathway can lead to tumorigenesis. Next generation anti-cancer drugs will undoubtedly emerge from our understanding of the molecular pathways governing normal cellular metabolism, growth and differentiation that have gone awry during neoplastic transformation, and studies in VHL disease will serve as one of the proving grounds for the efficacy of 'designer' anti-cancer drugs tailored against the VHL-HIF pathway.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".