Modifications of proteins by 4-hydroxy-2-nonenal in the ventilatory muscles of rats
Bibliographic record
Abstract
Although 4-hydroxy-2-nonenal (HNE, a product of lipid peroxidation) is a major cause of oxidative damage inside skeletal muscles, the exact proteins modified by HNE are unknown. We used two-dimensional electrophoresis, immunoblotting, and mass spectrometry to identify selective proteins targeted by HNE inside the diaphragm of rats under two conditions: severe sepsis [induced by E. coli lipopolysaccharides (LPS)] and during strenuous muscle contractions elicited by severe inspiratory resistive loading (IRL). Diaphragm HNE-protein adduct formation (detected with a polyclonal antibody) increased significantly after 1 and 3 h of LPS injection with a return to baseline values thereafter. Similarly, HNE-protein adduct formation inside the diaphragm rose significantly after 6 but not 3 h of IRL. Mass spectrometry analysis of HNE-modified proteins revealed enolase 3b, aldolase and triosephosphate isomerase 1, creatine kinase, carbonic anyhdrase III, aconitase 2, dihydrolipoamide dehydrogenase, and electron transfer flavoprotein-beta. Measurements of in vitro enolase activity in the presence of pure HNE revealed that HNE significantly attenuated enolase activity in a dose-dependent fashion, suggesting that HNE-derived modifications have inhibitory effects on enzyme activity. We conclude that lipid peroxidation products may inhibit muscle contractile performance through selective targeting of enzymes involved in glycolysis, energy production as well as CO(2) hydration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".