Expression and activity of N‐myristoyl transferase in normal and inflamed lungs
Bibliographic record
Abstract
N‐myristoyl transferase (NMT) attaches a 14 carbon fatty acid, myristic acid, to the N‐terminal glycine residue of proteins. Myristoylated proteins play critical roles in protein‐protein interactions, cell signaling, cellular transformation and oncogenesis. Although expression of NMT has been described in colorectal carcinoma, its expression and roles in inflammation are largely unknown. Therefore, we investigated the expression and activity of NMT in lung inflammation induced with intratracheal instillation of M. hemolytica . Immunohistochemistry revealed mild staining for NMT in the septum, vascular endothelium and the epithelium in the lungs from control as well as infected calves. NMT expression was intense in some of the inflammatory cells especially neutrophils in the necrotic areas in the inflamed lungs. Immuno‐electron microscopy localized NMT in cytoplasm and nuclei of micro‐ and macrovascular endothelium, pulmonary intravascular macrophages and airway epithelium. Western blots revealed a band of approximately 48kDa for NMT in both the infected and control animals. Further, we examined enzyme activity of NMT and found it to be lower in inflamed lungs compared to the normal (P<0.05). Lastly, we identified a putative inhibitor of NMT in inflamed lungs. These are the first data to record expression of NMT in lungs and inhibition of NMT activity in inflamed lungs and may have implications for the prolonged lifespan of neutrophils. (Funding: NSERC, Canada)
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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 | 0.000 |
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".