Non-invasive voiding assessment in conscious mice
Bibliographic record
Abstract
OBJECTIVE: To review available options of assessing murine bladder function and to evaluate a non-invasive technique suitable for long-term recording. METHODS: We reviewed previously described methods to record rodent bladder function. We used modified metabolic cages to capture novel recording tracings of mouse micturition. We evaluated our method in a pilot study with female mice undergoing partial bladder outlet obstruction or sham operation, respectively; half of the partial obstruction and sham group received treatment with an S6K-inhibitor, targeting the mTOR pathway, which is known to be implicated in bladder response to obstruction. RESULTS: Our non-invasive method using continuous urine weight recording reliably detected changes in murine bladder function resulting from partial bladder outlet obstruction or treatment with S6K-inhibitor. We found obstruction as well as treatment with S6K-inhibitor to correlate with a hyperactive voiding pattern. CONCLUSIONS: While invasive methods to assess murine bladder function largely disturb bladder histology and intrinsically render post-cystometry gene expression analysis of questionable value, continuous urine weight recording is a reliable, inexpensive, and critically non-invasive method to assess murine bladder function, suitable for a long-term application.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".