Experimental Cannabinoid 2 Receptor Inhibition in <scp>CNS</scp> Injury‐Induced Immunodeficiency Syndrome
Bibliographic record
Abstract
OBJECTIVE: Severe CNS injury, such as stroke, traumatic brain injury, or spinal cord injury, is known to increase susceptibility to infections. The increased susceptibility to infection is due to an impaired immune response and is referred to as CIDS. The CB2 receptor on immune cells presents a potential therapeutic target in CIDS as activation of this receptor has been shown to be involved in immunosuppression. The main purpose of this study was to determine the impact of CB2 receptor inhibition on leukocyte activation within the microcirculation following endotoxin challenge in an experimental stroke model. METHODS: Five experimental groups (male C57BL/6 mice, age: 6-8 weeks) were subjected to the following treatments: control; endotoxemia (LPS 5 mg/kg, i.v.); transient cerebral hypoxia-ischemia (HI) + endotoxemia; HI + endotoxemia + CB2 receptor antagonist (AM630 2.5 mg/kg, i.v.). HI was induced by unilateral carotid artery occlusion, followed by 50 minute exposure to a low oxygen atmosphere (8% O2 ). The CB2 receptor antagonist was given 15 min prior to LPS administration. Intravital microscopy (IVM) was carried out 2h after LPS administration. Brains were extracted and stained with tetrazolium chloride (TTC) to measure infarct volume. RESULTS: Compared to endotoxemic animals without CNS injury, mice subjected to HI displayed reduced leukocyte activation in intestinal submucosal venules indicative of CIDS. Administration of the CB2 receptor antagonist in animals with CIDS challenged with endotoxin restored peripheral leukocyte recruitment without a detrimental impact on infarct size. CONCLUSION: We conclude that the ECS is involved in the impaired immune response following CNS injury. Future studies should further explore the CB2 receptor pathway to develop novel therapies for CIDS.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".