Functional and anatomical evidence of cerebral tissue hypoxia in young sickle cell anemia mice
Bibliographic record
Abstract
Cerebral ischemia is a significant source of morbidity in children with sickle cell anemia; however, the mechanism of injury is poorly understood. Increased cerebral blood flow and low hemoglobin levels in children with sickle cell anemia are associated with increased stroke risk, suggesting that anemia-induced tissue hypoxia may be an important factor contributing to subsequent morbidity. To better understand the pathophysiology of brain injury, brain physiology and morphology were characterized in a transgenic mouse model, the Townes sickle cell model. Relative to age-matched controls, sickle cell anemia mice demonstrated: (1) decreased brain tissue pO 2 and increased expression of hypoxia signaling protein in the perivascular regions of the cerebral cortex; (2) elevated basal cerebral blood flow , consistent with adaptation to anemia-induced tissue hypoxia; (3) significant reduction in cerebrovascular blood flow reactivity to a hypercapnic challenge; (4) increased diameter of the carotid artery; and (5) significant volume changes in white and gray matter regions in the brain, as assessed by ex vivo magnetic resonance imaging. Collectively, these findings support the hypothesis that brain tissue hypoxia contributes to adaptive physiological and anatomic changes in Townes sickle cell mice. These findings may help define the pathophysiology for stroke in children with sickle cell anemia.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".