EEG Power Spectra Changes and Forebrain Ischemia in Rats
Bibliographic record
Abstract
BACKGROUND: Several animal models of cerebral ischemia have been developed to investigate both pathophysiology and pharmacological treatment. The aim of this study was to verify the prognostic value of EEG power spectra analysis in a two-vessel plus hypotension rat model of transient global ischemia. METHODS: Spontaneously hypertensive rats (SHRs) and Wistar Kyoto rats (WKYs) were subjected to 20 min bilateral common carotid artery occlusion plus hypotension by sodium nitroprusside followed by reperfusion for seven days. Sham-operated animals served as controls. The changes after ischemia in EEG power spectra, and their relations with neuronal damage and astrocytic response were investigated. RESULTS: The EEG analysis revealed that in SHRs and WKYs, ischemia produced a dramatic increase in delta activity and a decrease in theta, beta and alpha activities derived from both cortical and hippocampal areas. EEG activity reverted to normal values more quickly in WKYs than in SHRs which did not recover cortical and hippocampal alpha and beta activities even at six days of reperfusion. SHRs presented more severe damage and intense astrocytosis than WKYs in almost all the brain regions analyzed. In SHRs, hippocampal delta activity was positively correlated with the degree of neuronal necrosis and astrocytic activation, whereas theta, alpha and beta activities correlated negatively. No correlations were found in WKYs. CONCLUSIONS: These data indicate that the hippocampal bioelectrical activity recorded in SHRs from the beginning of reperfusion could be useful for predicting the ischemic outcome and evaluating the effects of pharmacological interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".