Neuronal and glial cell populations in the piriform cortex distinguished by using an approximation of q-space imaging after status epilepticus.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Temporal lobe epilepsy produces an injury cascade that includes neuronal loss and gliosis. The pilocarpine model reliably reproduces the symptoms of temporal lobe epilepsy and the resulting neuronal glial changes can be accurately depicted on diffusion-weighted images. The judicious choice of diffusion-encoding gradients can isolate multiple apparently isochromatic diffusing populations, but the assignment of these populations to specific tissue characteristics has been difficult. We sought to distinguish neuronal tissue from glial cell-infiltrated tissue by using signatures from unique spin populations obtained from an approximation of q-space imaging. METHODS: Ten male Sprague-Dawley rats received pilocarpine injections to induce seizures. All animals underwent diffusion-weighted imaging at 12 hours, 24 hours, and 7 days. At least two animals were selected for histologic analysis at each imaging time point. RESULTS: The results indicated that seizure-induced neurologic dysfunction may have been reflected in the emergence of new spin populations. In the piriform cortex-amygdala region of interest, the mean free diffusion path increased from 12 to 20 microm within 12 hours of seizure onset and persisted for at least 7 days. These results were temporally correlated with histologic evidence of necrotic changes. CONCLUSION: Our results suggest that even incomplete sampling of q space can provide useful physiologic information.
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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) | 0.000 | 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".