The effects of adenine nucleotide perfusion on interstitial adenosine production in rat skeletal muscle
Bibliographic record
Abstract
The purpose of the present study was to utilize the microdialysis technique in rat skeletal muscle to perfuse varying concentrations of AMP, ADP, and ATP into the interstitium to examine the effects that these adenine nucleotides have on the production of adenosine in the interstitial space. Interstitial adenosine production appears to be related to the type (ATP, ADP, or AMP) and concentration (2-60 μmol/L) of the adenine nucleotide perfused. Interstitial adenosine levels increased (P < 0.05) from baseline (0.18 ± 0.02 and 0.22 ± 0.02 μmol/L) to 0.23 ± 0.02 and 0.41 ± 0.05 μmol/L following 5 and 30 μmol/L AMP perfusion, respectively. Similarly, perfusion with 30 μmol/L ADP and 30, 40, and 60 μmol/L ATP resulted in an increase (P < 0.05) in interstitial adenosine concentration from baseline (0.25 ± 0.02, 0.26 ± 0.02, 0.19 ± 0.03, and 0.14 ± 0.02 μmol/L) to 0.30 ± 0.02, 0.32 ± 0.02, 0.36 ± 0.04, and 0.33 ± 0.04 μmol/L, respectively. Interestingly, the most prominent increase in interstitial adenosine production occurred during the perfusion of 60 μmol/L ATP (126% increase from baseline). These data strongly suggest that interstitial ATP may play a more potent role in stimulating interstitial adenosine production as compared with ADP or AMP. In addition, interstitial adenosine production can occur independent of muscle contraction (voluntary or involuntary) or hypoxia when adequate concentrations of adenine nucleotides are available.
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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 | 0.001 |
| 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".