Sex differences in the mouse photothrombotic stroke model investigated with X-ray fluorescence microscopy and Fourier transform infrared spectroscopic imaging
Bibliographic record
Abstract
Stroke is a leading cause of death and disability around the world. To date, the majority of pre-clinical research has been performed using male lab animals and results are commonly generalized to both sexes. In clinical stoke cases females have a higher incidence of ischemic stroke and poorer outcomes, compared to males. Best practices for improving translatability of findings for stroke, encourage the use of both sexes in studies. Since estrogen and progesterone have recognized neuroprotective effects, it is important to compare the size, severity and biochemical composition of the brain tissue following stroke in female and male animal models. In this study a photothrombotic focal stroke was induced in male and female mice. Vaginal secretions were collected twice daily to track the stage of estrous. Mice were euthanized at 24 h post-stroke. Histological staining, Fourier transform infrared imaging and X-ray fluorescence imaging were performed to better define the size and metabolic markers in the infarct core and surrounding penumbra. Our results show while the female mice had a significantly lower body mass than males, the cross-sectional area of the brain and the size of infarct and penumbra were not significantly different between the groups. In addition to the general expected sex-linked differences of altered NADH levels between males and females, estrus females had significantly elevated glycogen in the penumbra compared with males and total phosphorus levels were noted to be higher in the penumbra of estrus females. Elevated glycogen reserves in the tissue bordering the infarct core in females may present alternatives for improved functional recovery in females in the early post-stroke phase.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".