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@ARTICLE{Skrobot:271972,
      author       = {Skrobot, Matej and Sa, Rafael De and Walter, Josefine and
                      Vogt, Arend and Paulat, Raik and Lips, Janet and Mosch,
                      Larissa and Mueller, Susanne and Dominiak, Sina and Sachdev,
                      Robert and Boehm-Sturm, Philipp and Dirnagl, Ulrich and
                      Endres, Matthias and Harms, Christoph and Wenger, Nikolaus},
      title        = {{R}efined movement analysis in the staircase test reveals
                      differential motor deficits in mouse models of stroke.},
      journal      = {Journal of cerebral blood flow $\&$ metabolism},
      volume       = {44},
      number       = {9},
      issn         = {0271-678X},
      address      = {London},
      publisher    = {Sage},
      reportid     = {DZNE-2024-01114},
      pages        = {1551 - 1564},
      year         = {2024},
      abstract     = {Accurate 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.},
      keywords     = {Animals / Mice / Disease Models, Animal / Male /
                      Infarction, Middle Cerebral Artery: diagnostic imaging /
                      Infarction, Middle Cerebral Artery: physiopathology /
                      Infarction, Middle Cerebral Artery: complications / Stroke:
                      physiopathology / Stroke: diagnostic imaging / Stroke:
                      complications / Mice, Inbred C57BL / Magnetic Resonance
                      Imaging: methods / Machine Learning / Movement: physiology /
                      Machine learning (Other) / motor deficits (Other) / rodent
                      models (Other) / stroke (Other) / translational research
                      (Other)},
      cin          = {AG Dirnagl / AG Endres},
      ddc          = {610},
      cid          = {I:(DE-2719)1810002 / I:(DE-2719)1811005},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)16},
      pmc          = {pmc:PMC11418716},
      pubmed       = {pmid:39234984},
      doi          = {10.1177/0271678X241254718},
      url          = {https://pub.dzne.de/record/271972},
}