Identification and Characterization of a Membrane Receptor for Proteolysis-Inducing Factor on Skeletal Muscle
Bibliographic record
Abstract
Proteolysis-inducing factor (PIF) is a sulfated glycoprotein produced by cachexia-inducing tumors, which induces atrophy of skeletal muscle. PIF has been shown to bind specifically with high affinity (K(d), in nanomolar) to sarcolemma membranes from skeletal muscle of both the mouse and the pig, as well as murine myoblasts and a human muscle cell line. Ligand binding was abolished after enzymatic deglycosylation, suggesting that binding was mediated through the oligosaccharide chains in PIF. Chondroitin sulfate, but not heparan or dermatan sulfate, showed competitive inhibition (K(d), 1.1 x 10(-7) mol/L) of binding of PIF to the receptor, suggesting an interaction with the sulfated oligosaccharide chains. Ligand blotting of [(35)S]PIF to triton solublized membranes from C(2)C(12) cells provided evidence for a binding protein of apparent M(r) of approximately 40,000. Amino acid sequence analysis showed the PIF receptor to be a DING protein. Antisera reactive to a 19mer from the N-terminal amino acid residues of the binding protein attenuated protein degradation and activation of the ubiquitin-proteasome pathway induced by PIF in murine myotubes. In addition, the antisera was highly effective in attenuating the decrease in body weight in mice bearing the MAC16 tumor, with a significant increase in muscle wet weight due to an increase in the rate of protein synthesis, together with a reduction in protein degradation through attenuation of the increased proteasome expression and activity. These results confirm that the PIF binding protein has a functional role in muscle protein atrophy in cachexia and that it represents a potential new therapeutic target.
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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 | 0.001 |
| 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) | 0.002 | 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".