Sex Differences in a Mouse Model of Focal Ischemia : Biochemical and Elemental Imaging Using Synchrotron-Based Techniques
Bibliographic record
Abstract
Authors and affiliations:Huishu Hou,1 Nicole J. Sylvain,1 M. Jake Pushie,1 Julia Newton,2 and Michael E. Kelly1.1Department of Surgery, College of Medicine, University of Saskatchewan.2 Department of Anatomy and Cell Biology, University of SaskatchewanStroke is associated with age and occurs more frequently in men. Studies show both estrogen and progesterone have neuroprotective effects after a brain injury in females. Other studies using rodents as stroke models reported no significant difference between males and females in stroke recovery.Using synchrotron-based X-ray fluorescence imaging (XFI) and Fourier transform infrared (FTIR) spectroscopic imaging combined with immunohistochemistry, we identify previously unobserved changes in both the biochemical and elemental distribution in the female brain at different points of the estrus cycle, post-stroke. Vaginal secretions were collected twice daily to track female mouse estrus stages. Photothrombotic stroke surgeries were conducted either at the oestrus (high estrogen and progesterone levels) or diestrus (low hormone levels) estrus stage. Age-matched male mice also underwent stroke surgery for comparison. 24h post-stroke brain were collected and cryo-sectioned for all experiments.Our results reveal that females have larger infarct size compared to age-matched males. Both XFI and FTIR results show minor differences in biochemical and elemental distribution between females and males, but trends are matched. Studies of sex differences in animal models is vital to understanding the underlying mechanisms of clinically-associated physiological changes in stroke.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".