Proteomic Analysis of Pharmacological Preconditioning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ischemic preconditioning is characterized by resistance to ischemia reperfusion injury in response to previous short ischemic episodes, a protective effect that can be mimicked pharmacologically. The underlying mechanism of protection remains controversial and requires greater understanding before it can be fully exploited therapeutically. To investigate the overall effect of preconditioning on the myocardial proteome, isolated rabbit ventricular myocytes were treated with drugs known to induce preconditioning, adenosine or diazoxide (each at 100 micromol/L for 60 minutes). Their protein profiles were then compared with vehicle-treated controls (n=4 animals per treatment) using a multitiered 2D gel electrophoresis approach. Of 28 significantly altered protein spots, 19 nonredundant proteins were identified (5 spots remained unidentified). The majority of these proteins are involved in mitochondrial energetics, including subunits of tricarboxylic acid cycle enzymes and oxidative phosphorylation complexes. These changes were not indiscriminate, with only a small number of enzymes or complex subunits altered, indicating a very specific and targeted affect of these 2 preconditioning mimetics. Among the changes were shifts in the extent of posttranslational modification of 4 proteins. One of these, the adenosine-induced phosphorylation of the ATP synthase beta subunit, was fully characterized with the identification of 5 novel phosphorylation sites. This proteomics approach provides an overall assessment of the cellular response to pharmacological treatment with adenosine and diazoxide and identifies a distinct subset of enzymes and protein complex subunit that may underlie the preconditioned phenotype.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it