Background And Purpose: Intracerebral hemorrhage (ICH) is a known risk factor for the development of seizures, but little is known about the pathophysiology of seizures in the acute phase post-ICH and their influence on functional outcome. With the use of an animal model, the underlying pathophysiology could be further unraveled. The aim of our study was to optimize the rat collagenase stroke model for the detection of acute symptomatic seizures using video-EEG monitoring.
Methods: Male Sprague-Dawley rats were implanted with scalp electrodes and a craniotomy was made for later injection of collagenase. After one week of baseline video-EEG recording, rats were injected with 0.6 U collagenase in 0.7 μL saline in left striatum, in close proximity of the piriform cortex, and immediately reconnected to the video-EEG setup for 7 days. Occurrence of clinical and electrographic seizures was assessed and functional deficits were evaluated on several time points using the cylinder test, Neurological Deficit Scale (NDS) and forelimb placing test. At day 7 post-ICH, animals were euthanized. The volume and cortical involvement of the hemorrhage were assessed by histological examination of the brain tissue, using Cresyl violet stain.
Results: Collagenase injection induced ICH in all animals with a mean volume of 27 mm³ (SEM 7 mm³, range 4-92 mm³). Functional deficits were present in all animals injected with collagenase (pre-ICH vs post-ICH, p < 0.001). Epileptic seizures occurred in 5/11 animals and started between 1 and 61 h after ICH induction. Behavioral changes were observed in 13/15 seizures.
Conclusions: Injecting rats with 0.6 U of collagenase is a useful model to study the occurrence of acute symptomatic seizures post-ICH as it results in ICH in all animals without mortality, 45% incidence of ICH-induced acute symptomatic seizures and measurable functional deficits.
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http://dx.doi.org/10.1016/j.eplepsyres.2020.106364 | DOI Listing |
World J Clin Cases
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JACC Case Rep
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Mathematical models of viral dynamics are crucial in understanding infection trajectories. However, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load data often includes limited sparse observations with significant heterogeneity. This study aims to: (1) understand the impact of patient characteristics in shaping the temporal viral load trajectory and (2) establish a data collection protocol (DCP) to reliably reconstruct individual viral load trajectories.
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