USP19 is a ubiquitin-specific protease regulated in rat skeletal muscle during catabolic states
Bibliographic record
Abstract
Ubiquitin-dependent proteolysis is activated in skeletal muscle atrophying in response to various catabolic stimuli. Previous studies have demonstrated activation of ubiquitin conjugation. Because ubiquitination can also be regulated by deubiquitinating enzymes, we used degenerate oligonucleotides derived from conserved sequences in the ubiquitin-specific protease (UBP) family of deubiquitinating enzymes in RT-PCR with skeletal muscle RNA to amplify putative deubiquitinating enzymes. We identified USP19, a 150-kDa deubiquitinating enzyme that is widely expressed in various tissues including skeletal muscle. Expression of USP19 mRNA increased by approximately 30-200% in rat skeletal muscle atrophying in response to fasting, streptozotocin-induced diabetes, dexamethasone treatment, and cancer. Increased mRNA levels during fasting returned to normal with refeeding, but 1 day later than the normalization of rates of proteolysis and coincided instead with recovery of muscle mass. Indeed, in all catabolic treatments, USP19 mRNA was inversely correlated with muscle mass and provided an index of muscle mass that may be useful in many pathological conditions, using small human muscle biopsies. The increased expression of this deubiquitinating enzyme under conditions of increased proteolysis suggests that it may play a role in regeneration of free ubiquitin either coincident with or after proteasome-mediated degradation of substrates. USP19 may also be involved in posttranslational processing of polyubiquitin produced de novo in response to induction of the polyubiquitin genes seen under these conditions. Deubiquitinating enzymes thus appear involved in muscle wasting and implicate a widening web of regulation of genes in the ubiquitin system in this process.
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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 | 0.001 | 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 | 0.001 |
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".