A simple method for identifying latent spasticity following compressive spinal cord injury by provoking clonic contractions of the hindpaw- and back musculature in rats.

Authors

Milen Zamfirov, Svenja Rink-Notzon, Levent Sarikcioglu, Maria Eleni Manthou, Lyudmila Belenska-Todorova, Doychin N Angelov

Published in

Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft. Pages 153364. Aug 29, 2026. Epub Aug 29, 2026.

Abstract

Spasticity after spinal cord injury (SCI) encompasses increased muscle tone, exaggerated tendon reflexes, muscle spasms, and involuntary rhythmic contractions (clonus) elicited by rapid muscle stretch. It develops in about two thirds of all patients within the first-year post-injury and often causes severe functional impairments. In rodent models, however, post-SCI spasticity period is frequently subtle or overlooked due to overlapping with central neuropathic pain symptoms such as reduced locomotor activity and paresis. Here we describe a simple and reproducible method to reveal latent spasticity in rats with incomplete thoracic SCI, which we discovered during treatment with passive flexion and extension (PFE) of their hindpaws. These observations were correlated with electrophysiological and histological assessments. In about half of the treated animals PFE provoked 2-3 powerful clonic contractions of the back- and hindpaw musculature. These responses were robust and clearly distinguishable from voluntary movements. Histological analysis of the lumbar enlargement ("below level") in clonus-positive rats revealed a marked reduction in vesicular GABA transporter (VGAT) immunofluorescence intensity in the deep dorsal horn interneurons (DDHI) compared to non-reactive animals. This provocation-based approach provides a straightforward and reliable essay for identifying latent spasticity following SCI. It may serve as a valuable tool for investigating the underlying mechanisms of SCI-related spasticity and for evaluating therapeutic interventions in preclinical models. (212 words).

PMID:
42668126
Bibliographic data and abstract were imported from PubMed on 30 Aug 2026.

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