Cognitive function after transient forebrain ischemia: Preliminary assessment of reversal by darbepoetin alfa
Bibliographic record
Abstract
Stroke is the leading cause of disability in adults. Stroke survivors endure neurologic deficits including impairments in cognitive function. In the present study, we investigated the use of a novel therapeutic for improving cognitive deficits in the four vessel occlusion (4-VO) model of transient global cerebral ischemia, an animal model of stroke. The Barnes maze, a test of spatial memory, was used to assess cognition. In this test, rodents are motivated to find a hidden escape box using spatial cues. After several trials the rodent will inherently locate the escape box faster and with fewer errors if spatial memory is unaffected. Using immunohistochemistry for the neuronal marker NeuN and cresyl violet staining, we have shown that 12 minutes of global ischemia selectively kills greater than 90% of CA1 neurons in the dorsal hippocampus of adult rats. Furthermore, animals in which there was a bilateral loss of hippocampal CA1 neurons display more errors and longer escape latency in the Barnes maze compared to sham-operated controls. The erythropoietin analog, darbepoetin alfa, has been shown to improve cognitive deficits in animal models of schizophrenia and may be able to improve the memory deficits of 4-VO treated rats. Preliminary results regarding the ability of darbepoietin alfa to enhance the performance of 4-VO treated rats in the Barnes maze will be presented.
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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 | 0.000 | 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".