Intravital Microscopy of the Murine Urinary Bladder Microcirculation
Bibliographic record
Abstract
Catheter associated urinary tract infection (UTI) is one of the most common nosocomial infections. The objective of this study was to establish an in vivo mouse model of the urinary bladder microcirculation to study the inflammatory response to UTI. Female C57Bl/6 mice were challenged intravesically with 0.1, 0.5, 1, 5 or 7 mg/kg of Escherichia coli lipopolysaccharide (LPS) or saline. 3.5 hrs later, the right jugular vein was cannulated, a catheter was inserted into the bladder, the urine drained and 100 μl of warm saline injected. The bladder was gently exteriorized and the bladder microcirculation was recorded for the next hour. In some mice, leukocyte endothelial cell interactions were observed after exposure to anti‐P‐selectin or anti‐α 4 ‐integrin Ab. LPS at a dose of 5 and 7 mg/kg resulted in a significant increase in leukocyte adhesion and rolling. Leukocyte adhesion at 4 and 4.5 hrs post saline stimulation was 0.9±1.0 and 2.7±1.0 cells/field of view, respectively, and the flux of rolling leukocytes was 21±6.4 and 47±22 cells/min. Leukocyte adhesion at the two time points after 5 mg/kg of LPS stimulation was 17±7.8 and 21±8.0 cells/field of view, respectively, and the flux of rolling leukocytes was 74±17 and 116±56 cells/min. Blockage of α 4 ‐integrin had no effect on leukocyte rolling, whereas the use of a P‐selectin Ab significantly inhibited leukocyte rolling (54.0± 26.0 to 1.25±0.97 cells/min, p<0.05). These results demonstrate that baseline conditions are maintained within the first half‐hour of microcirculatory observations. Leukocyte rolling within the bladder microcirculation is P‐selectin dependent but α 4 ‐integrin independent. This model can be used to decipher the molecular mechanisms of leukocyte recruitment into the bladder as well as to examine in vivo responses to catheter materials and bacterial infection.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".