Utility of intestinal intravital microscopy for the study of CNS injury-induced immunodepression syndrome (CIDS)
Bibliographic record
Abstract
BACKGROUND: Stroke, traumatic brain injury, or other forms of central nervous system (CNS) injury initiate a local inflammatory response. Compensatory anti-inflammatory pathways are activated to limit secondary damage due to inflammation. The associated release of immunosuppressing neuromodulators can result in system-wide immune dysregulation (CNS injury-induced immune-depression syndrome -CIDS). OBJECTIVE: To establish an experimental stroke model where CIDS can be studied by intravital microscopy (IVM). METHODS: We used the photothrombotic stroke (PTS) model in C57BL/6 mice and studied its effects on peripheral immunity following challenge with lipopolysaccharide (LPS). Leukocyte activation, as well as capillary perfusion of the microcirculation, were assessed using intestinal intravital microscopy (IVM). RESULTS: PTS caused a significant reduction in the number of adhering leukocytes in submucosal venules of the terminal ileum of mice challenged with LPS compared to LPS-challenged animals without stroke. Leukocyte rolling was also impacted by PTS in the submucosal venules. Following stroke, we also observed decreased mucosal functional capillary density (FCD). CONCLUSIONS: Our results suggest that PTS with subsequent LPS challenge poses as a viable model to further study CIDS using intravital microscopy of the intestinal microcirculation.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".