Development of a High-Throughput Urosepsis Mouse Model
Bibliographic record
Abstract
Murine sepsis models are typically polymicrobial, and are associated with high mortality. We aimed to develop a high-throughput murine model that mimics a slow-paced, monomicrobial sepsis originating from the urinary tract. A total of 23 male C57Bl/6 mice underwent percutaneous insertion of a 4 mm catheter into the bladder using an ultrasound-guided method, previously developed by our group. The following day, Proteus mirabilis (PM) was introduced percutaneously in the bladder in three groups: g1—50 µL 1 × 108 CFU/mL solution (n = 10); g2—50 µL 1 × 107 CFU/mL solution (n = 10); and g3 (sham mice)—50 µL sterile saline (n = 3). On day 4, mice were sacrificed. The number of planktonic bacteria in urine, adherent to catheters, and adherent to/invaded into the bladder and spleen was assessed. Cell-free DNA, D-dimer, thrombin–antithrombin complex (TAT), and 32 pro-/anti-inflammatory cytokines/chemokines were quantified in the blood. All mice survived the 4 day postinterventional period. Mean weight loss was 11% in g1, 9% in g2, and 3% in the control mice. Mean urine CFU counts were highest in group 1. All catheters showed high catheter-adhered bacterial counts. Of the infected mice, 17/20 had CFU counts in the splenic tissue, indicating septicemia. Plasma levels of cell-free DNA, D-dimer, and the proinflammatory cytokines IFN-γ, IL-6, IP-10, MIG, and G-CSF were significantly elevated in infected mice versus controls. We present a reproducible, monomicrobial murine model of urosepsis that does not lead to rapid deterioration and death, and is useful for studying prolonged urosepsis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".