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Our study showed that alteration in α-synuclein and γ-synuclein might be associated with ASD pathogenesis and could be an indicator of the severity of the disorder.

Energy consumption is a critical issue in resource-constrained wireless neural recording applications with limited data bandwidth. Compressed sensing (CS) has emerged as a powerful framework in addressing this issue owing to its highly efficient data compression procedure. selleck products In this paper, a CS-based approach termed Simultaneous Analysis Non-Convex Optimization (SANCO) is proposed for large-scale, multi-channel local field potentials (LFPs) recording.

The SANCO method consists of three parts (1) the analysis model is adopted to reinforce sparsity of the multi-channel LFPs, therefore overcoming the drawbacks of conventional synthesis models. (2) An optimal continuous order difference matrix is constructed as the analysis operator, enhancing the recovery performance while saving both computational resources and data storage space. (3) A non-convex optimizer that can by efficiently solved with alternating direction method of multipliers (ADMM) is developed for multi-channel LFPs reconstruction.

Experimental results on real datasets reveal that the proposed approach outperforms state-of-the-art CS methods in terms of both recovery quality and computational efficiency.

Energy efficiency of the SANCO make it an ideal candidate for resource-constrained, large scale wireless neural recording. Particularly, the proposed method ensures that the key features of LFPs had little degradation even when data are compressed by 16x, making it very suitable for long term wireless neural recording applications.

Energy efficiency of the SANCO make it an ideal candidate for resource-constrained, large scale wireless neural recording. Particularly, the proposed method ensures that the key features of LFPs had little degradation even when data are compressed by 16x, making it very suitable for long term wireless neural recording applications.Graphite/silicon (G/Si) composites are considered as possible alternative anode materials to commercial graphite anodes. However, the unstable solid electrolyte interphase (SEI) on G/Si particles results in rapid capacity decay, impeding practical applications. Herein, a facile and low-cost Al2O3 coating was developed to fabricate stable artificial SEI layers on G/Si composites. The amorphous Al2O3 coating with a thickness of 10-15 nm was synthesized by a simple sol-gel method followed by high-temperature annealing. The Al2O3 coated G/Si anode delivers an initial discharge capacity of 540 mAh g-1 at 25 °C and has improved Coulombic efficiency and cycling stability. After 100 cycles, the capacity retention is 76.4%, much higher than the 56.4% of the uncoated anode. Furthermore, the Al2O3 coating was found to be more effective at improving the stability of G/Si at a higher temperature (55 °C). This was explained by the Al2O3 coating suppressing the growth of SEI on Si/G and thus reducing the charge transfer resistance at the G/Si-electrolyte interface. It is expected that the Al2O3 coating prepared by the sol-gel process can be applied to other Si-based anodes in the manufacture of practical high-performance lithium-ion batteries.

Computational models of neural activity at the meso-scale suggest the involvement of discrete oscillatory bursts as constructs of cognitive processing during behavioral tasks. Classical signal processing techniques that attempt to infer neural correlates of behavior from meso-scale activity employ spectral representations of the signal, exploiting power spectral density techniques and time - frequency energy distributions to capture band power features. However, such analyses demand more specialized methods that incorporate explicitly the concepts of neurophysiological signal generation and time resolution in the tens of milliseconds. This paper focuses on working memory (WM), a complex cognitive process involved in encoding, storing and retrieving sensory information, which has been shown to be characterized by oscillatory bursts in the beta and gamma band. Employing a generative model for oscillatory dynamics, we present a Marked Point Process (MPP) representation of bursts during memory creation and reademployed time - frequency methods. Finally, our results underscore the novelty in interpreting oscillatory dynamics encompassed by the marked features of the point process.

An MPP representation of meso-scale activity not just enables a rich, high - resolution parameter space for analysis but also presents a novel tool for diverse neural applications.

An MPP representation of meso-scale activity not just enables a rich, high - resolution parameter space for analysis but also presents a novel tool for diverse neural applications.T-cell immunotherapy holds promise for the treatment of cancer, infection, and autoimmune diseases. Nevertheless, T-cell therapy is limited by low cell expansion efficiency ex vivo and functional deficits. Here we describe two 3D bioprinting systems made by different biomaterials that mimic the in vivo formation of natural lymph vessels and lymph nodes which modulate T-cell with distinct fates and functions. We observe that coaxial alginate fibers promote T-cell expansion, less exhausted and enable CD4+ T-cell differentiation into central memory-like phenotype (Tcm), CD8+ T-cells differentiation into effector memory subsets (Tem), while alginate-gelatin scaffolds bring T-cells into a relatively resting state. Both of the two bioprinting methods are strikingly different from a standard suspension system. The former bioprinting method yields a new system for T-cell therapy and the latter method can be useful for making an immune-chip to elucidate links between immune response and disease.We describe a radiation therapy treatment plan optimization method that explicitly considers the effects of interfraction organ motion through optimization on the clinical target volume (CTV), and investigate how it compares to conventional planning using a planning target volume (PTV). The method uses simulated treatment courses generated using patient images created by a deformable registration algorithm to replicate the effects of interfraction organ motion, and performs robust optimization aiming to achieve CTV coverage under all simulated treatment courses. The method was applied to photon-mediated treatments of three prostate cases and compared to conventional, PTV-based planning with margins selected to achieve similar CTV coverage as the robustly optimized plans. Clinical goals for the CTV and healthy tissue were used in comparison between the two types of plans. Out of the two clinical goals for overdosage of the CTV, the three robustly optimized plans violated respectively 2, 2, and 0 goals in the mean over the scenarios, whereas none of the PTV plans violated these goals.