Microglia/macrophages are ultrastructurally altered by their proximity to spinal cord injury in adult female mice
Bibliographic record
Abstract
Traumatic spinal cord injury can cause immediate physical damage to the spinal cord and result in severe neurological deficits. The primary, mechanical tissue damage triggers a variety of secondary damage mechanisms at the injury site which significantly contribute to a larger lesion size and increased functional damage. Inflammatory mechanisms which directly involve both microglia (MG) and monocyte-derived macrophages (MDM) play important roles in the post-injury processes, including inflammation and debris clearing. In the current study, we investigated changes in the structure and function of MG/MDM in the injured spinal cord of adult female mice, 7 days after a thoracic contusion SCI. With the use of chip mapping scanning electron microscopy, which allows to image large samples at the nanoscale, we performed an ultrastructural comparison of MG/MDM located near the lesion vs adjacent regions to provide novel insights into the mechanisms at play post-injury. We found that MG/MDM located near the lesion had more mitochondria overall, including mitochondria with and without morphological alterations, and had a higher proportion of altered mitochondria. MG/MDM near the lesion also showed an increased number of phagosomes, including phagosomes containing myelin and partiallydigested materials. MG/MDM near the injury interacted differently with the spinal cord parenchyma, as shown by their reduced number of direct contacts with synaptic elements, axon terminals and dendritic spines. In this study, we characterized the ultrastructural changes of MG/MDM in response to spinal cord tissue damage in mice, uncovering changes in phagocytic activity, mitochondrial ultrastructure, and inter-cellular interactions within the spinal cord parenchyma.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".