Quantitative Behavioral Method for Assessing Pharmacologically-Induced Episodes of Micturition in an Animal Model of Urinary Retention and Detrusor-Sphincter Dyssynergia
Bibliographic record
Abstract
No cure or acceptable treatment exists against bladder problems and urinary retention in spinal cord-injured (SCI) patients.Although some non-central nervous system (CNS)-acting drugs exist, as symptomatic treatment, most have been associated with significant side effects and deleterious complications.To ease basic research aimed at identifying new drug candidates against bladder control problems, we develop a standardized approach and corresponding assays for assessing quantitatively acute recovery of bladder expression and episodic urination elicited by CNS-acting compounds in paraplegic animals.Following a period of acclimation, a single systemic (s.c.) Short Communicationinjection of vehicle (sterile water) was performed in intact animals or in early chronic (7-10 days post-surgery) thoracically (Th9/10)-transected (Tx) mice.Observations were immediately conducted during 30 minutes using a transparent circular Plexiglas arena where timing (postinjection), frequency (number of episodes post-injection), incidences and total volumes (mg) of expulsed urine were assessed.In clear contrast, administration of quipazine, a 5-HT2/3 receptor agonist was shown here to elicit increased urine volume expressed within 30 min postadministration in Tx mice.Using this simple, straightforward and reliable method, it will become possible to conduct large scale drug screening experiments aimed at identifying potent and safe centrally acting-drugs (e.g., upon the Sacral/Spinal Micturition Center) for potent 'on-demand' facilitation of urination and voiding in patients with SCI.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".