In vitro immuno‐prevention of nitration/dysfunction of myogenic stem cell activator <scp>HGF</scp>, towards developing a strategy for age‐related muscle atrophy
Bibliographic record
Abstract
Abstract In response to peroxynitrite (ONOO−) generation, myogenic stem satellite cell activator HGF (hepatocyte growth factor) undergoes nitration of tyrosine residues (Y198 and Y250) predominantly on fast IIa and IIx myofibers to lose its binding to the signaling receptor c‐met, thereby disturbing muscle homeostasis during aging. Here we show that rat anti‐HGF monoclonal antibody (mAb) 1H41C10, which was raised in‐house against a synthetic peptide FTSNPEVRnitroY198EV, a site well‐conserved in mammals, functions to confer resistance to nitration dysfunction on HGF. 1H41C10 was characterized by recognizing both nitrated and non‐nitrated HGF with different affinities as revealed by Western blotting, indicating that the paratope of 1H41C10 may bind to the immediate vicinity of Y198. Subsequent experiments showed that 1H41C10‐bound HGF resists peroxynitrite‐induced nitration of Y198. A companion mAb‐1H42F4 presented similar immuno‐reactivity, but did not protect Y198 nitration, and thus served as the control. Importantly, 1H41C10‐HGF also withstood Y250 nitration to retain c‐met binding and satellite cell activation functions in culture. The Fab region of 1H41C10 exerts resistivity to Y250 nitration possibly due to its localization in the immediate vicinity to Y250, as supported by an additional set of experiments showing that the 1H41C10‐Fab confers Y250‐nitration resistance which the Fc segment does not. Findings highlight the in vitro preventive impact of 1H41C10 on HGF nitration‐dysfunction that strongly impairs myogenic stem cell dynamics, potentially pioneering cogent strategies for counteracting or treating age‐related muscle atrophy with fibrosis (including sarcopenia and frailty) and the therapeutic application of investigational HGF drugs.
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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".