Beyond the hypoxia-inducible factor-centric tumour suppressor model of von Hippel-Lindau
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide an overview of the recent advances in the understanding of the molecular mechanisms governing the tumour suppressor functions of the von Hippel-Lindau protein. RECENT FINDINGS: von Hippel-Lindau is a vital component of an E3 ubiquitin ligase complex involved in the oxygen-dependent targeting of hypoxia-inducible factor for ubiquitin-mediated destruction. Recent reports have linked von Hippel-Lindau to the regulation of diverse biological processes including cell adhesion, extracellular matrix assembly and ciliogenesis in a manner dependent and/or independent of hypoxia-inducible factor. SUMMARY: The tumour suppressor function of von Hippel-Lindau has remained hypoxia-inducible factor-centric since the discovery of von Hippel-Lindau as a bona fide negative regulator of the ubiquitous oxygen-sensing pathway. Emerging evidence supports this hypothesis with the elucidation of fundamental cellular processes deregulated upon the inactivation of the von Hippel-Lindau-hypoxia-inducible factor pathway, but has also proved compelling on the hypoxia-inducible factor-independent tumour suppressor role of von Hippel-Lindau. These and continuing studies into the molecular pathways and mechanisms governing the tumour suppressor functions of von Hippel-Lindau will ultimately afford new avenues for anticancer strategies for the improved treatment of a diverse array of cancers.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".