The von Hippel–Lindau tumour suppressor gene: uncovering the expression of the pVHL172 isoform
Bibliographic record
Abstract
BACKGROUND: The von Hippel-Lindau (VHL) gene encodes two mRNA variants. Variant 1 encodes two protein isoforms, pVHL213 and pVHL160, that have been extensively documented in the literature. Variant 2 is produced by alternative splicing of exon 2 and encodes a pVHL isoform of 172 amino acids with a theoretical molecular weight of 19 kDa (pVHL172), the expression of which has never been demonstrated so far due to the absence of suitable antibodies. METHODS: We have generated an anti-pVHL monoclonal antibody (JD-1956) using pVHL172 recombinant protein. We tested the antibody against exogenous or endogenous expressed proteins in different cell lines. We identified the pVHL172 using a silencing RNA strategy. The epitope of the antibody was mapped using a peptide array. RESULTS: We efficiently detected the three different isoforms of pVHL in cell lines and tumorigenic tissues by western blotting and immunohistochemistry and confirmed for the first time the endogenous expression of pVHL172. CONCLUSIONS: The endogenous expression of the three isoforms and particularly the pVHL172 has never been shown before due to a lack of a highly specific antibody since none of the available commercial antibodies distinguish the three isoforms of pVHL in cells or in both normal and cancerous human tissues. Evidence of pVHL172 expression emphasises the need to further study its implication in renal tumorigenesis and VHL disease.
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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".