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000271972 1001_ $$00000-0001-6686-1880$$aSkrobot, Matej$$b0
000271972 245__ $$aRefined movement analysis in the staircase test reveals differential motor deficits in mouse models of stroke.
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000271972 520__ $$aAccurate assessment of post-stroke deficits is crucial in translational research. Recent advances in machine learning offer precise quantification of rodent motor behavior post-stroke, yet detecting lesion-specific upper extremity deficits remains unclear. Employing proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT) in mice, we assessed post-stroke impairments via the Staircase test. Lesion locations were identified using 7 T-MRI. Machine learning was applied to reconstruct forepaw kinematic trajectories and feature analysis was achieved with MouseReach, a new data-processing toolbox. Lesion reconstructions pinpointed ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval alterations were observed, but were unrelated to overall stroke volume. Instead, forepaw slips and relative reaching success correlated with increasing cortical lesion size in both models. Striatal lesion size after MCAO was associated with prolonged reach durations that occurred with delayed symptom onset. Further analysis on the impact of selective serotonin reuptake inhibitors in the PT model revealed no clear treatment effects but replicated strong effect sizes of slips for post-stroke deficit detection. In summary, refined movement analysis unveiled specific deficits in two widely-used mouse stroke models, emphasizing the value of deep behavioral profiling in preclinical stroke research to enhance model validity for clinical translation.
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000271972 650_7 $$2Other$$aMachine learning
000271972 650_7 $$2Other$$amotor deficits
000271972 650_7 $$2Other$$arodent models
000271972 650_7 $$2Other$$astroke
000271972 650_7 $$2Other$$atranslational research
000271972 650_2 $$2MeSH$$aAnimals
000271972 650_2 $$2MeSH$$aMice
000271972 650_2 $$2MeSH$$aDisease Models, Animal
000271972 650_2 $$2MeSH$$aMale
000271972 650_2 $$2MeSH$$aInfarction, Middle Cerebral Artery: diagnostic imaging
000271972 650_2 $$2MeSH$$aInfarction, Middle Cerebral Artery: physiopathology
000271972 650_2 $$2MeSH$$aInfarction, Middle Cerebral Artery: complications
000271972 650_2 $$2MeSH$$aStroke: physiopathology
000271972 650_2 $$2MeSH$$aStroke: diagnostic imaging
000271972 650_2 $$2MeSH$$aStroke: complications
000271972 650_2 $$2MeSH$$aMice, Inbred C57BL
000271972 650_2 $$2MeSH$$aMagnetic Resonance Imaging: methods
000271972 650_2 $$2MeSH$$aMachine Learning
000271972 650_2 $$2MeSH$$aMovement: physiology
000271972 7001_ $$aSa, Rafael De$$b1
000271972 7001_ $$aWalter, Josefine$$b2
000271972 7001_ $$00000-0003-0925-0308$$aVogt, Arend$$b3
000271972 7001_ $$aPaulat, Raik$$b4
000271972 7001_ $$aLips, Janet$$b5
000271972 7001_ $$aMosch, Larissa$$b6
000271972 7001_ $$00000-0001-8777-4823$$aMueller, Susanne$$b7
000271972 7001_ $$aDominiak, Sina$$b8
000271972 7001_ $$aSachdev, Robert$$b9
000271972 7001_ $$aBoehm-Sturm, Philipp$$b10
000271972 7001_ $$0P:(DE-2719)2810838$$aDirnagl, Ulrich$$b11$$udzne
000271972 7001_ $$0P:(DE-2719)2811033$$aEndres, Matthias$$b12$$udzne
000271972 7001_ $$00000-0002-2063-2860$$aHarms, Christoph$$b13
000271972 7001_ $$aWenger, Nikolaus$$b14
000271972 773__ $$0PERI:(DE-600)2039456-1$$a10.1177/0271678X241254718$$gVol. 44, no. 9, p. 0271678X241254718$$n9$$p1551 - 1564$$tJournal of cerebral blood flow & metabolism$$v44$$x0271-678X$$y2024
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