ArticleNeurourology and urodynamics2025
Increased Afferent Nerve Firing Is Correlated With the Detection of Bladder Wall Micromotion in a Perfused Ex-Vivo Porcine Model.
Article in Neurourology and urodynamics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
INTRODUCTION AND
objectiveObservable autonomous rhythmic changes in intravesical pressure, termed bladder wall micromotion, is a phenomenon that has been linked to urinary urgency, the key symptom in overactive bladder (OAB). However, the mechanism through which micromotion drives urinary urgency is poorly understood. In addition, micromotion is inherently difficult to study in human urodynamics due to challenges distinguishing it from normal cyclic physiologic processes such as pulse rate, breathing, rectal contractions, and ureteral jetting. Therefore, the goal of this study was to create a reproducible model of micromotion using an ex-vivo perfused porcine bladder, as well as to describe the relationship between micromotion and afferent nerve signaling.
methodsPorcine bladders were reanimated using ex-vivo perfusion with a physiologic buffer. The pelvic nerve adjacent to the bladder was dissected, grasped with micro-hook electrodes and electroneurogram (ENG) signals were recorded at 20 kHz. Bladders were catheterized and intravesical pressure measurements were taken using a Laborie XT Urodynamics system. Bladders were filled to a fixed volume of 300 mL and control measurements were recorded. The bladders were then washed with 0.001 M carbachol (CCh) solution and refilled to 300 mL to induce micromotion, which was detected as rhythmic changes in intravesical pressure. ENG amplitude was calculated in μV, and nerve firing rate was calculated as number of spikes above baseline threshold per minute.
resultsMicromotion was induced by carbachol in 12/25 (48.4%) of trials as rhythmic changes in intravesical pressure after the instillation of carbachol but not in any control period. A fast Fourier transform (FFT) algorithm showed average peak dominant frequency component amplitude was significantly higher during the carbachol period when compared to the control period (0.47 vs. 0.01 cm-H
conclusionsMicromotion can be induced using instillation of carbachol in a perfused ex-vivo porcine bladder. Increased afferent nerve firing is observed during periods of micromotion. Thus, micromotion may drive afferent nerve signaling and may potentially contribute to urinary urgency, detrusor overactivity, and OAB. The development of an experimental ex-vivo porcine model for micromotion provides a reproducible method to study bladder micromotion and its potential role in the pathophysiology of urinary urgency and voiding dysfunction.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.