Autoantibodies from primary biliary cirrhosis patients with anti-p95c antibodies bind to recombinant p97/VCP and inhibit<i>in vitro</i>nuclear envelope assembly
Bibliographic record
Abstract
We have reported previously that p95c, a novel 95-kDa cytosolic protein, was the target of autoantibodies in sera of patients with autoimmune hepatic diseases. We studied 30 sera that were shown previously to immunoprecipitate a 95 kDa protein from [(35)S]-methionine-labelled HeLa lysates and had a specific precipitin band in immunodiffusion. Thirteen sera were available to test the ability of p95c antibodies to inhibit nuclear envelope assembly in an in vitro assay in which confocal fluorescence microscopy was also used to identify the stages at which nuclear assembly was inhibited. The percentage inhibition of nuclear envelope assembly of the 13 sera ranged from 7% to 99% and nuclear envelope assembly and the swelling of nucleus was inhibited at several stages. The percentage inhibition of nuclear assembly was correlated with the titre of anti-p95c as determined by immunodiffusion. To confirm the identity of this autoantigen, we used a full-length cDNA of the p97/valosin-containing protein (VCP) to produce a radiolabelled recombinant protein that was then used in an immunoprecipitation (IP) assay. Our study demonstrated that 12 of the 13 (93%) human sera with antibodies to p95c immunoprecipitated recombinant p97/VCP. Because p95c and p97 have similar molecular masses and cell localization, and because the majority of sera bind recombinant p97/VCP and anti-p95c antibodies inhibit nuclear assembly, this is compelling evidence that p95c and p97/VCP are identical.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".