A New Model for Determining the Influence of Age and Sex on Functional Recovery following Hypoxic-Ischemic Brain Damage
Bibliographic record
Abstract
Stroke is a disorder affecting the lives of all age groups, and particularly those at the opposite ends of the age spectrum. It is generally believed that the immature brain is more resistant to damage resulting from a hypoxic/ischemic injury, and that it is also more 'plastic' in terms of its ability to recover. Evidence from our laboratory, and a host of others, has indicated, however, that the developing brain may in fact be more sensitive to injury resulting from hypoxia-ischemia. The question remains, however, whether the immature brain has a greater capacity for recovery. In order to determine the relative capability for functional recovery between age groups, a stroke model of comparable injury is required. This paper describes a new rodent model of ischemic injury allowing for comparisons of behavioral recovery spanning the spectrum of ages between newborn and the elderly. Endothelin-1, a potent vasoconstrictor, was stereotactically injected into the brains of 10-, 63-, and 180-day-old Wistar rats, immediately adjacent to the middle cerebral artery. Regionally, the cortex, caudate, and thalamus were most significantly affected, with sparing of the hippocampus. Pathologic assessment indicated a similar degree of injury across age groups affecting the territorial distribution of the middle cerebral artery, with a predominance of damage in the anterior sections of the cortex and caudate (p < 0.05), compared to the posterior sections including the cortex and thalamus. There were no regional differences in the extent of damage between age groups. Interestingly, however, there were significant differences between males and females regarding the overall extent of brain damage (p < 0.05), with males showing greater damage than females. In addition, there were significant regional differences in the extent of damage between males and females, particularly regarding cortical damage (p < 0.05), both anteriorly and posteriorly, and the caudate anteriorly (p < 0.05). Our findings provide an important new model for comparison of brain damage among the entire spectrum of ages affected by stroke. Importantly, this will allow for further investigations regarding both functional recovery and gender difference comparisons. This may have important ramifications for the development of therapeutic interventions that are age and gender specific.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".