Cellular correlates of longitudinal diffusion tensor imaging of axonal degeneration following hypoxic–ischemic cerebral infarction in neonatal rats
Bibliographic record
Abstract
Ischemically damaged brain can be accompanied by secondary degeneration of associated axonal connections e.g. Wallerian degeneration. Diffusion tensor imaging (DTI) is widely used to investigate axonal injury but the cellular correlates of many of the degenerative changes remain speculative. We investigated the relationship of DTI of directly damaged cerebral cortex and secondary axonal degeneration in the cerebral peduncle with cellular alterations in pan-axonal neurofilament staining, myelination, reactive astrocytes, activation of microglia/macrophages and neuronal cell death. DTI measures (axial, radial and mean diffusivity, and fractional anisotropy (FA)) were acquired at hyperacute (3 h), acute (1 and 2 d) and chronic (1 and 4 week) times after transient cerebral hypoxia with unilateral ischemia in neonatal rats. The tissue pathology underlying ischemic and degenerative responses had a complex relationship with DTI parameters. DTI changes at hyperacute and subacute times were smaller in magnitude and tended to be transient and/or delayed in cerebral peduncle compared to cerebral cortex. In cerebral peduncle by 1 d post-insult, there were reductions in neurofilament staining corresponding with decreases in parallel diffusivity which were more sensitive than mean diffusivity in detecting axonal changes. Ipsilesional reductions in FA within cerebral peduncle were robust in detecting both early and chronic degenerative responses. At one or four weeks post-insult, radial diffusivity was increased ipsilaterally in the cerebral peduncle corresponding to pathological evidence of a lack of ontogenic myelination in this region. The detailed differences in progression and magnitude of DTI and histological changes reported provide a reference for identifying the potential contribution of various cellular responses to FA, and, parallel, radial, and mean diffusivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".