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Pre-Differentiation Of Human Neural Stem Cells Into Gabaergic Neurons Prior To Transplant Results In Greater Repopulation Of The Damaged Brain And Accelerates Functional Recovery After Transient Ischemic Stroke, Hima C. S Abeysinghe, Laita Bokhari, Anita F. Quigley, Mahesh A. Choolani, Jerry Chan, Gregory J. Dusting, Jeremy M. Crook, Nao R. Kobayashi, Carli Roulston
Pre-Differentiation Of Human Neural Stem Cells Into Gabaergic Neurons Prior To Transplant Results In Greater Repopulation Of The Damaged Brain And Accelerates Functional Recovery After Transient Ischemic Stroke, Hima C. S Abeysinghe, Laita Bokhari, Anita F. Quigley, Mahesh A. Choolani, Jerry Chan, Gregory J. Dusting, Jeremy M. Crook, Nao R. Kobayashi, Carli Roulston
Australian Institute for Innovative Materials - Papers
2015 Abeysinghe et al. Introduction: Despite attempts to prevent brain injury during the hyperacute phase of stroke, most sufferers end up with significant neuronal loss and functional deficits. The use of cell-based therapies to recover the injured brain offers new hope. In the current study, we employed human neural stem cells (hNSCs) isolated from subventricular zone (SVZ), and directed their differentiation into GABAergic neurons followed by transplantation to ischemic brain. Methods: Pre-differentiated GABAergic neurons, undifferentiated SVZ-hNSCs or media alone were stereotaxically transplanted into the rat brain (n=7/group) 7 days after endothelin-1 induced stroke. Neurological outcome was assessed by neurological deficit …
Functional Brain Network Classification With Compact Representation Of Sice Matrices, Jianjia Zhang, Luping Zhou, Lei Wang, Wanqing Li
Functional Brain Network Classification With Compact Representation Of Sice Matrices, Jianjia Zhang, Luping Zhou, Lei Wang, Wanqing Li
Faculty of Engineering and Information Sciences - Papers: Part A
Recently, sparse inverse covariance estimation (SICE) technique has been employed to model functional brain connectivity. The inverse covariance matrix (SICE matrix in short) estimated for each subject is used as a representation of brain connectivity to discriminate Alzheimers disease from normal controls. However, we observed that direct use of the SICE matrix does not necessarily give satisfying discrimination, due to its high dimensionality and the scarcity of training subjects. Looking into this problem, we argue that the intrinsic dimensionality of these SICE matrices shall be much lower, considering i) an SICE matrix resides on a Riemannian manifold of symmetric positive …