Drakevalencia6552

Krüppel-like factors (KLFs) are zinc finger transcription factors implicated in diverse biological processes, including differentiation of neural cells. The ability of mammalian neurons to elongate axons decreases during postnatal development in parallel with a decrease in cAMP, and increase in expression of several Klf genes. The paralogous KLFs 9 and 13 inhibit neurite outgrowth, and we hypothesized that their actions are mediated through repression of cAMP signaling. M3814 To test this we used the adult mouse hippocampus-derived cell line HT22 engineered to control expression of Klf9 or Klf13 with doxycycline, or made deficient for these Klfs by CRISPR/Cas9 genome editing. We also used primary hippocampal cells isolated from wild type, Klf9-/- and Klf13-/- mice. Forced expression of Klf9 or Klf13 in HT22 changed the mRNA levels of several genes involved with cAMP signaling; the predominant action was gene repression, and KLF13 influenced ∼4 times more genes than KLF9. KLF9 and KLF13 repressed promoter activity of the protein kinase a catalytic subunit alpha gene in transfection-reporter assays; KLF13, but not KLF9 repressed the calmodulin 3 promoter. Forskolin activation of a cAMP-dependent promoter was reduced after forced expression of Klf9 or Klf13, but was enhanced in Klf gene knockout cells. Forced expression of Klf9 or Klf13 blocked cAMP-dependent neurite outgrowth in HT22 cells, and axon growth in primary hippocampal neurons, while Klf gene knockout enhanced the effect of elevated cAMP. Taken together, our findings show that KLF9 and KLF13 inhibit neurite/axon growth in hippocampal neurons, in part, by inhibiting the cAMP signaling pathway.Cell adhesion molecules (CAMs) mediate interactions of neurons with the extracellular environment by forming adhesive bonds with CAMs on adjacent membranes or via binding to proteins of the extracellular matrix. Binding of CAMs to their extracellular ligands results in the activation of intracellular signaling cascades, leading to changes in neuronal structure and the molecular composition and function of neuronal contacts. Ultimately, many of these changes depend on the synthesis of new proteins. In this review, we summarize the evidence showing that CAMs regulate protein synthesis by modulating the activity of transcription factors, gene expression, protein translation, and the structure and distribution of organelles involved in protein synthesis and transport.Progressive myoclonus epilepsy of Unverricht-Lundborg type (EPM1) is a neurodegenerative disorder caused by loss-of-function mutations in the cystatin B (CSTB) gene. Progression of the clinical symptoms in EPM1 patients, including stimulus-sensitive myoclonus, tonic-clonic seizures, and ataxia, are well described. However, the cellular dysfunction during the presymptomatic phase that precedes the disease onset is not understood. CSTB deficiency leads to alterations in GABAergic signaling, and causes early neuroinflammation followed by progressive neurodegeneration in brains of a mouse model, manifesting as progressive myoclonus and ataxia. Here, we report the first proteome atlas from cerebellar synaptosomes of presymptomatic Cstb-deficient mice, and propose that early mitochondrial dysfunction is important to the pathogenesis of altered synaptic function in EPM1. A decreased sodium- and chloride dependent GABA transporter 1 (GAT-1) abundance was noted in synaptosomes with CSTB deficiency, but no functional difference was seen between the two genotypes in electrophysiological experiments with pharmacological block of GAT-1. Collectively, our findings provide novel insights into the early onset and pathogenesis of CSTB deficiency, and reveal greater complexity to the molecular pathogenesis of EPM1.To tackle real-world challenges, deep and complex neural networks are generally used with a massive number of parameters, which require large memory size, extensive computational operations, and high energy consumption in neuromorphic hardware systems. In this work, we propose an unsupervised online adaptive weight pruning method that dynamically removes non-critical weights from a spiking neural network (SNN) to reduce network complexity and improve energy efficiency. The adaptive pruning method explores neural dynamics and firing activity of SNNs and adapts the pruning threshold over time and neurons during training. The proposed adaptation scheme allows the network to effectively identify critical weights associated with each neuron by changing the pruning threshold dynamically over time and neurons. It balances the connection strength of neurons with the previous layer with adaptive thresholds and prevents weak neurons from failure after pruning. We also evaluated improvement in the energy efficiency of SNNs with our method by computing synaptic operations (SOPs). Simulation results and detailed analyses have revealed that applying adaptation in the pruning threshold can significantly improve network performance and reduce the number of SOPs. The pruned SNN with 800 excitatory neurons can achieve a 30% reduction in SOPs during training and a 55% reduction during inference, with only 0.44% accuracy loss on MNIST dataset. Compared with a previously reported online soft pruning method, the proposed adaptive pruning method shows 3.33% higher classification accuracy and 67% more reduction in SOPs. The effectiveness of our method was confirmed on different datasets and for different network sizes. Our evaluation showed that the implementation overhead of the adaptive method regarding speed, area, and energy is negligible in the network. Therefore, this work offers a promising solution for effective network compression and building highly energy-efficient neuromorphic systems in real-time applications.The differential diagnosis between brain tumors recurrence and early neuroinflammation or late radionecrosis is still an unsolved problem. The new emerging magnetic resonance imaging, computed tomography, and positron emission tomography diagnostic modalities still lack sufficient accuracy. In the last years, a great effort has been made to develop radiotracers able to detect specific altered metabolic pathways or tumor receptor markers. Our research project aims to evaluate irradiation effects on radiopharmaceutical uptake and compare the kinetic of the fluorinate tracers. T98G glioblastoma cells were irradiated at doses of 2, 10, and 20 Gy with photons, and 18F-DOPA and 18F-FET tracer uptake was evaluated. Activity and cell viability at different incubation times were measured. 18F-FET and 18F-DOPA are accumulated via the LAT-1 transporter, but 18F-DOPA is further incorporated, whereas 18F-FET is not metabolized. Therefore, time-activity curves (TACs) tend to plateau with 18F-DOPA and to a rapid washout with 18F-FET.