Liposome-mediated transfection of central nervous system cells

Disclosed are methods for use in transferring nucleic acids into central nervous system cells in vivo and in vitro and/or for stimulating central nervous system cells. Neurotrophic genes are shown to stimulate neurofilament cells and to promote nerve cell growth, repair and regeneration in vivo. Gene transfer protocols are disclosed for use in transferring various nucleic acid materials into central nervous system cells, as may be used in treating various pathologies of the brain and spinal cord.Board of Regents, University of Texas Syste

Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?

Supervised classification methods often assume the train and test data distributions are the same and that all classes in the test set are present in the training set. However, deployed classifiers often require the ability to recognize inputs from outside the training set as unknowns. This problem has been studied under multiple paradigms including out-of-distribution detection and open set recognition. For convolutional neural networks, there have been two major approaches: 1) inference methods to separate knowns from unknowns and 2) feature space regularization strategies to improve model robustness to outlier inputs. There has been little effort to explore the relationship between the two approaches and directly compare performance on anything other than small-scale datasets that have at most 100 categories. Using ImageNet-1K and Places-434, we identify novel combinations of regularization and specialized inference methods that perform best across multiple outlier detection problems of increasing difficulty level. We found that input perturbation and temperature scaling yield the best performance on large scale datasets regardless of the feature space regularization strategy. Improving the feature space by regularizing against a background class can be helpful if an appropriate background class can be found, but this is impractical for large scale image classification datasets

Changing experience with dual chamber (DDD) pacemakers

Dual chamber (DDD) or “universal” pacemakers have had a significant impact on the advancement of artificial pacemakers by providing a more physiologic approach to cardiac pacing. However, with the early generation of DDD pacemakers (pacemakers that sense and pace in both the atrium and the ventricle), a significant number of patients experienced pacemaker-mediated tachycardia because intact ventriculoatrial conduction was sensed in the atrium and a reentrant tachycardia was induced. Newer generation DDD pacemakers have provided longer atrial refractory periods, which should correct this problem.In this study the first and second years of a 2 year experience with DDD pacemakers were compared to determine if the newer generation devices have allowed maintenance of pacing in the DDD mode as opposed to reprogramming to some alternate mode because of pacemaker-mediated tachycardia or other pacing problems. The results showed a significant decrease in pacemaker-mediated tachycardia during the second year and continuation of pacing in the DDD mode in a higher percent of patients. This improvement is attributed to improvement in the pulse generator as well as better patient selection

SIESTA: Efficient Online Continual Learning with Sleep

In supervised continual learning, a deep neural network (DNN) is updated with an ever-growing data stream. Unlike the offline setting where data is shuffled, we cannot make any distributional assumptions about the data stream. Ideally, only one pass through the dataset is needed for computational efficiency. However, existing methods are inadequate and make many assumptions that cannot be made for real-world applications, while simultaneously failing to improve computational efficiency. In this paper, we propose a novel continual learning method, SIESTA based on wake/sleep framework for training, which is well aligned to the needs of on-device learning. The major goal of SIESTA is to advance compute efficient continual learning so that DNNs can be updated efficiently using far less time and energy. The principal innovations of SIESTA are: 1) rapid online updates using a rehearsal-free, backpropagation-free, and data-driven network update rule during its wake phase, and 2) expedited memory consolidation using a compute-restricted rehearsal policy during its sleep phase. For memory efficiency, SIESTA adapts latent rehearsal using memory indexing from REMIND. Compared to REMIND and prior arts, SIESTA is far more computationally efficient, enabling continual learning on ImageNet-1K in under 2 hours on a single GPU; moreover, in the augmentation-free setting it matches the performance of the offline learner, a milestone critical to driving adoption of continual learning in real-world applications.Comment: Accepted to TMLR 202

Dual vulnerability of tau to calpains and caspase-3 proteolysis under neurotoxic and neurodegenerative conditions

Axonally specific microtubule-associated protein tau is an important component of neurofibrillary tangles found in AD (Alzheimer's disease) and other tauopathy diseases such as CTE (chronic traumatic encephalopathy). Such tau aggregate is found to be hyperphosphorylated and often proteolytically fragmented. Similarly, tau is degraded following TBI (traumatic brain injury). In the present study, we examined the dual vulnerability of tau to calpain and caspase-3 under neurotoxic and neurodegenerative conditions. We first identified three novel calpain cleavage sites in rat tau (four-repeat isoform) as Ser130↓Lys131, Gly157↓Ala158 and Arg380↓Glu381. Fragment-specific antibodies to target the major calpain-mediated TauBDP-35K (35 kDa tau-breakdown product) and the caspase-mediated TauBDP-45K respectively were developed. In rat cerebrocortical cultures treated with excitotoxin [NMDA (N-methyl-d-aspartate)], tau is significantly degraded into multiple fragments, including a dominant signal of calpain-mediated TauBDP-35K with minimal caspase-mediated TauBDP-45K. Following apoptosis-inducing EDTA treatment, tau was truncated only to TauBDP-48K/45K-exclusively by caspase. Cultures treated with another apoptosis inducer STS (staurosporine), dual fragmentation by calpain (TauBDP-35K) and caspase-3 (TauBDP-45K) was observed. Tau was also fragmented in injured rat cortex following TBI in vivo to BDPs of 45–42 kDa (minor), 35 kDa and 15 kDa, followed by TauBDP-25K. Calpain-mediated TauBDP-35K-specific antibody confirmed robust signals in the injured cortex, while caspase-mediated TauBDP-45K-specific antibody only detected faint signals. Furthermore, intravenous administration of a calpain-specific inhibitor SNJ-1945 strongly suppressed the TauBDP-35K formation. Taken together, these results suggest that tau protein is dually vulnerable to calpain and caspase-3 proteolysis under different neurotoxic and injury conditions

Acute NMDA toxicity in cultured rat cerebellar granule neurons is accompanied by autophagy induction and late onset autophagic cell death phenotype

<p>Abstract</p> <p>Background</p> <p>Autophagy, an intracellular response to stress, is characterized by double membrane cytosolic vesicles called autophagosomes. Prolonged autophagy is known to result in autophagic (Type II) cell death. This study examined the potential role of an autophagic response in cultured cerebellar granule neurons challenged with excitotoxin N-methyl-D-aspartate (NMDA).</p> <p>Results</p> <p>NMDA exposure induced light chain-3 (LC-3)-immunopositive and monodansylcadaverine (MDC) fluorescent dye-labeled autophagosome formation in both cell bodies and neurites as early as 3 hours post-treatment. Elevated levels of Beclin-1 and the autophagosome-targeting LC3-II were also observed following NMDA exposure. Prolonged exposure of the cultures to NMDA (8-24 h) generated MDC-, LC3-positive autophagosomal bodies, concomitant with the neurodegenerative phase of NMDA challenge. Lysosomal inhibition studies also suggest that NMDA-treatment diverted the autophagosome-associated LC3-II from the normal lysosomal degradation pathway. Autophagy inhibitor 3-methyladenine significantly reduced NMDA-induced LC3-II/LC3-I ratio increase, accumulation of autophagosomes, and suppressed NMDA-mediated neuronal death. ATG7 siRNA studies also showed neuroprotective effects following NMDA treatment.</p> <p>Conclusions</p> <p>Collectively, this study shows that autophagy machinery is robustly induced in cultured neurons subjected to prolonged exposure to excitotoxin, while autophagosome clearance by lysosomal pathway might be impaired. Our data further show that prolonged autophagy contributes to cell death in NMDA-mediated excitotoxicity.</p