Purine level regulation during energy depletion associated with graded excitatory stimulation in brain
Bibliographic record
Abstract
OBJECTIVES: The formation and release of adenosine following graded excitatory stimulation of the brain may serve important physiological functions such as sleep regulation, as well as an early resistance mechanism against excitotoxicity. However, adenosine at high levels may reflect merely the results of obstructed energy metabolism. METHODS: We examined the extent to which levels of adenosine and adenylate energy charge are affected in vivo by graded excitatory stimulations of brain using unilateral intrastriatal injections of glutamatergic agents and head-focused high energy microwaving for accurate and precise measures of purines. RESULTS: Our results confirmed that adenosine levels rise when adenylate energy charge decreases and showed that these increases occurred in three distinct phases with the rate of adenosine formation in each phase increasing as tissue adenylate energy charge was further depleted. In addition, we observed that, in most cases, the effects of focal excitatory stimulation on changes in tissue purine levels were restricted spatially within the immediate vicinity of the injection site; however, when strongly depolarizing stimuli were used, changes in purine levels could be observed in adjacent and, occasionally, even in contralateral brain regions. DISCUSSION: These results provide new insight into purine regulation that occurs under physiologically relevant conditions, such as sleep and during the early stages of brain insults that induce excitotoxicity.
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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".