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Synaptic plasticity relies on rapid, yet spatially precise signaling to alter synaptic strength. Arc is a brain enriched protein that is rapidly expressed during learning-related behaviors and is essential for regulating metabotropic glutamate receptor-mediated long-term depression (mGluR-LTD). We previously showed that disrupting the ubiquitination capacity of Arc enhances mGluR-LTD; however, the consequences of Arc ubiquitination on other mGluR-mediated signaling events is poorly characterized. Here we find that pharmacological activation of Group I mGluRs with S-3,5-dihydroxyphenylglycine (DHPG) increases Ca²⁺release from the endoplasmic reticulum (ER). Disrupting Arc ubiquitination on key amino acid residues enhances DHPG-induced ER-mediated Ca²⁺release. These alterations were observed in all neuronal subregions except secondary branchpoints. Deficits in Arc ubiquitination altered Arc self-assembly and enhanced its interaction with calcium/calmodulin-dependent protein kinase IIb (CaMKIIb) and constitutively active forms of CaMKII in HEK293 cells. Colocalization of Arc and CaMKII was altered in cultured hippocampal neurons, with the notable exception of secondary branchpoints. Finally, disruptions in Arc ubiquitination were found to increase Arc interaction with the integral ER protein Calnexin. These results suggest a previously unknown role for Arc ubiquitination in the fine tuning of ER-mediated Ca²⁺signaling that may support mGluR-LTD, which in turn, may regulate CaMKII and its interactions with Arc.

 

. Computed Tomography (CT) takes X-ray measurements on the subjects to reconstruct tomographic images. As X-ray is radioactive, it is desirable to control the total amount of dose of X-ray for safety concerns. Therefore, we can only select a limited number of measurement angles and assign each of them limited amount of dose. Traditional methods such as compressed sensing usually randomly select the angles and equally distribute the allowed dose on them. In most CT reconstruction models, the emphasize is on designing effective image representations, while much less emphasize is on improving the scanning strategy. The simple scanning strategy of random angle selection and equal dose distribution performs well in general, but they may not be ideal for each individual subject. It is more desirable to design a personalized scanning strategy for each subject to obtain better reconstruction result. In this paper, we propose to use Reinforcement Learning (RL) to learn a personalized scanning policy to select the angles and the dose at each chosen angle for each individual subject. We first formulate the CT scanning process as an Markov Decision Process (MDP), and then use modern deep RL methods to solve it. The learned personalized scanning strategy not only leads to better reconstruction results, but also shows strong generalization to be combined with different reconstruction algorithms.

 

Electrocatalytic water splitting to produce clean hydrogen is a promising technique for renewable energy conversion and storage in the future energy portfolio. Aiming at industrial hydrogen production, cost-effective electrocatalysts are expected to be competent in both hydrogen evolution reactions (HERs) and oxygen evolution reactions (OERs) to accomplish the overall water splitting. Limited by the low tolerance and/or poor activity of most 1st-row transition metal-based electrocatalysts in strongly acidic media, bifunctional electrocatalysts are currently advocated to work at high pH values. Herein, this review summarizes the recent progress of nonprecious bifunctional electrocatalysts for overall water splitting in alkaline media, including transition metal-based phosphides, chalcogenides, oxides, nitrides, carbides, borides, alloys, and metal-free materials. Besides, some prevalent modification strategies to optimize the activities of catalysts are briefly listed. Finally, the perspective on current challenges and future prospects for overall water splitting driven by advanced nonprecious electrocatalysts are briefly discussed. 

Nanoconfinement could dramatically change molecular transport and reaction kinetics in heterogeneous catalysis. Here we specifically design a core-shell nanocatalyst with aligned linear nanopores for single-molecule studies of the nanoconfinement effects. The quantitative single-molecule measurements reveal unusual lower adsorption strength and higher catalytic activity on the confined metal reaction centres within the nanoporous structure. More surprisingly, the nanoconfinement effects on enhanced catalytic activity are larger for catalysts with longer and narrower nanopores. Experimental evidences, including molecular orientation, activation energy, and intermediate reactive species, have been gathered to provide a molecular level explanation on how the nanoconfinement effects enhance the catalyst activity, which is essential for the rational design of highly-efficient catalysts.