Seizures cause sustained microvascular constriction associated with astrocytic and vascular smooth muscle Ca <sup>2+</sup> recruitment
Bibliographic record
Abstract
Abstract Previously we showed that seizures result in a severe hypoperfusion/hypoxic attack that results in postictal memory and behavioral impairments (Farrell et al., 2016). However, neither postictal changes in microvasculature nor Ca 2+ changes in key cell-types controlling blood perfusion have been visualized in vivo , leaving essential components of the underlying cellular mechanisms unclear. Here we use two-photon microvascular and Ca 2+ imaging in awake mice to show that seizures result in a robust vasoconstriction of cortical penetrating arterioles, which temporally mirrors the prolonged postictal hypoxia. The vascular effect was dependent on cyclooxygenase-2, as pre-treatment with ibuprofen prevented postictal vasoconstriction. Seizures caused a rapid elevation in astrocyte endfoot Ca 2+ that was confined to the seizure period. Vascular smooth muscle cells displayed a significant increase in Ca 2+ both during and following seizures, lasting up to 75 minutes. The temporal activities of two cell-types within the neurovascular unit lead to seizure-induced hypoxia. Highlights Seizures lead to equivalent levels of postictal hypoxia in both male and female mice Calcium elevation in astrocyte endfeet is confined to the seizure Postictal vasoconstriction in awake mice is mediated by cyclooxygenase-2 Calcium elevation in vascular smooth muscle cells is enduring and correlates with vasoconstriction.
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 | 0.000 | 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) | 0.002 | 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".