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评估动物模型下尿路功能的方法。

Methods for Assessing Lower Urinary Tract Function in Animal Models.

机构信息

Institute for Regenerative Medicine, University of Zürich, Zürich, Switzerland; Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland.

Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, Zürich, Switzerland.

出版信息

Eur Urol Focus. 2021 Jan;7(1):186-189. doi: 10.1016/j.euf.2019.12.004. Epub 2020 Jan 11.

DOI:10.1016/j.euf.2019.12.004
PMID:31937460
Abstract

Lower urinary tract dysfunction affects a multitude of patients. Current therapeutic approaches are limited and very little is known about the mechanisms in failure of bladder control. Thus, more basic research is clearly needed to elucidate the underlying pathological mechanisms and to develop novel treatment strategies in urology. Noninvasive tests such as the void-spot assay and the metabolic cage and more invasive urodynamics investigations are currently used to assess lower urinary tract function in animals, in particular rodents. The noninvasive tests give some insights into the functionality of the system, whereas urodynamics testing yields an objective evaluation that allows distinction of different pathologies and investigations of the underlying neuronal malfunctions. PATIENT SUMMARY: We briefly summarize methods currently used to assess impairments of bladder function in animal models. Both noninvasive and invasive methods are available and can be used to understand and improve human health. An accurate and detailed diagnosis is, however, possible only with urodynamics assessments.

摘要

下尿路功能障碍影响众多患者。目前的治疗方法有限,对膀胱控制失败的机制知之甚少。因此,显然需要更多的基础研究来阐明潜在的病理机制,并在泌尿科开发新的治疗策略。目前,非侵入性测试(如排空点测定和代谢笼)和更具侵入性的尿动力学研究用于评估动物,特别是啮齿动物的下尿路功能。非侵入性测试提供了对系统功能的一些了解,而尿动力学测试则提供了客观的评估,可以区分不同的病理,并研究潜在的神经功能障碍。

患者总结

我们简要总结了目前用于评估动物模型中膀胱功能障碍的方法。有非侵入性和侵入性方法可供选择,可用于了解和改善人类健康。然而,只有通过尿动力学评估才能进行准确和详细的诊断。

相似文献

1
Methods for Assessing Lower Urinary Tract Function in Animal Models.评估动物模型下尿路功能的方法。
Eur Urol Focus. 2021 Jan;7(1):186-189. doi: 10.1016/j.euf.2019.12.004. Epub 2020 Jan 11.
2
Void spot assay: recommendations on the use of a simple micturition assay for mice.排空点检测法:关于对小鼠使用一种简单排尿检测法的建议。
Am J Physiol Renal Physiol. 2018 Nov 1;315(5):F1422-F1429. doi: 10.1152/ajprenal.00350.2018. Epub 2018 Aug 29.
3
Urodynamic measurements reflect physiological bladder function in rats.尿动力学测量反映了大鼠的膀胱生理功能。
Neurourol Urodyn. 2018 Apr;37(4):1266-1271. doi: 10.1002/nau.23455. Epub 2017 Nov 15.
4
Dysfunctional voiding: the importance of non-invasive urodynamics in diagnosis and treatment.排尿功能障碍:非侵入性尿动力学在诊断和治疗中的重要性。
Pediatr Nephrol. 2018 Mar;33(3):381-394. doi: 10.1007/s00467-017-3679-3. Epub 2017 May 31.
5
Void spot assay procedural optimization and software for rapid and objective quantification of rodent voiding function, including overlapping urine spots.用于快速、客观地定量分析啮齿动物排尿功能(包括重叠尿斑)的空位分析程序优化和软件。
Am J Physiol Renal Physiol. 2018 Oct 1;315(4):F1067-F1080. doi: 10.1152/ajprenal.00245.2018. Epub 2018 Jul 4.
6
Urodynamics and lower urinary tract symptoms.尿动力学与下尿路症状
Acta Urol Belg. 1998 Oct;66(3):7-9.
7
Is Urodynamics Necessary when Assessing a Patient with Male Lower Urinary Tract Symptoms?评估男性下尿路症状患者时是否需要尿动力学检查?
Eur Urol Focus. 2018 Jan;4(1):54-56. doi: 10.1016/j.euf.2018.04.008. Epub 2018 Apr 26.
8
Lower Urinary Tract Dysfunction and Associated Pons Volume in Patients with Wolfram Syndrome.沃尔弗拉姆综合征患者的下尿路功能障碍与桥脑体积相关。
J Urol. 2018 Nov;200(5):1107-1113. doi: 10.1016/j.juro.2018.06.002. Epub 2018 Jun 5.
9
An update on sacral neuromodulation: where do we stand with this in the management of lower urinary tract dysfunction in 2010?骶神经调节最新进展:2010年在治疗下尿路功能障碍方面我们处于什么水平?
BJU Int. 2010 Nov;106(10):1432-42. doi: 10.1111/j.1464-410X.2010.09702.x.
10
Traces: making sense of urodynamics testing--Part 8: Evaluating sensations of bladder filling.探索:理解尿动力学检查——第8部分:评估膀胱充盈感觉
Urol Nurs. 2011 Nov-Dec;31(6):369-74.

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Research and progress on the mechanism of lower urinary tract neuromodulation: a literature review.下尿路神经调节机制的研究进展:文献综述。
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Automated identification and segmentation of urine spots based on deep-learning.基于深度学习的尿斑自动识别与分割。
PeerJ. 2024 Jul 18;12:e17398. doi: 10.7717/peerj.17398. eCollection 2024.
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PeerJ. 2023 May 23;11:e15420. doi: 10.7717/peerj.15420. eCollection 2023.
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Tissue-engineered autologous peritoneal grafts for bladder reconstruction in a porcine model.用于猪模型膀胱重建的组织工程自体腹膜移植物
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