Intravital Microscopy of the Murine Urinary Bladder Microcirculation
Bibliographic record
Abstract
OBJECTIVE: To establish an in vivo mouse model of the urinary bladder microcirculation, and characterize the molecular mechanisms of endotoxin-induced leukocyte recruitment. METHODS: The murine model was adapted from a technique previously reported for the rat. Mouse bladder microcirculation was observed using intravital microscopy, four hours after intravesical challenge with lipopolysaccharide (LPS) and leukocyte-endothelial interactions were examined. Molecular mechanisms of leukocyte recruitment were identified using antibodies to adhesion molecules and chemokines. RESULTS: LPS from Escherichia coli administered intravesically resulted in a significant increase in leukocyte adhesion and rolling at four hours post stimulation. LPS from Pseudomonas aeruginosa administered at similar doses resulted in a significant, but lower increase in leukocyte adhesion after four hours compared with E. coli LPS. Leukocyte adhesion within the bladder microcirculation was dependent on α(4) -integrins and ICAM-1, whereas leukocyte rolling was P-selectin dependent, but α(4) -integrin independent. Blockade of MIP-2 and KC did not alter leukocyte-endothelial interactions. The bladder endothelium expressed P-selectin, ICAM-1, VCAM-1, MIP-2, and MCP-1. Only VCAM-1 endothelial expression was significantly increased after LPS stimulation. CONCLUSION: The mouse model of the urinary bladder microcirculation is suitable for the study of inflammatory responses during urinary tract infection (UTI) in vivo.
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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) | 0.002 | 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".