Regulation of DJ-1 by glutaredoxin 1 \u3ci\u3ein vivo – implications for Parkinson’s disease\u3c/i\u3e

Parkinson’s disease (PD) is the second most common neurodegenerative disease worldwide, caused by the degeneration of the dopaminergic neurons in the substantia nigra. Mutations in PARK7 (DJ-1) result in early onset autosomal recessive PD, and oxidative modification of DJ-1 has been reported to regulate the protective activity of DJ-1 in vitro. Glutathionylation is a prevalent redox modification of proteins resulting from the disulfide adduction of the glutathione moiety to a reactive cysteine-SH; and glutathionylation of specific proteins has been implicated in regulation of cell viability. Glutaredoxin 1 (Grx1) is the principal deglutathionylating enzyme within cells, and it has been reported to mediate protection of dopaminergic neurons in C. elegans, however many of the functional downstream targets of Grx1 in vivo remain unknown. Previously, DJ-1 protein content was shown to decrease concomitantly with diminution of Grx1 protein content in cell culture of model neurons (SH-SY5Y and Neuro-2A lines). In the current study we aimed to investigate the regulation of DJ-1 by Grx1 in vivo and characterize its glutathionylation in vitro. Here, with Grx−/− mice we provide evidence that Grx1 regulates protein levels of DJ-1 in vivo. Furthermore, with model neuronal cells (SH-SY5Y) we observed decreased DJ-1 protein content in response to treatment with known glutathionylating agents; and with isolated DJ-1 we identified two distinct sites of glutathionylation. Finally, we found that overexpression of DJ-1 in the dopaminergic neurons partly compensates for the loss of the Grx1 homolog in a C. elegans in vivo model of PD. Therefore; our results reveal a novel redox modification of DJ-1 and suggest a novel regulatory mechanism for DJ-1 content in vivo

Heteroatoms Induce Localization of the Electric Field and Promote a Wide Potential-Window Selectivity Towards CO in the CO2 Electroreduction

Carbon dioxide electroreduction (CO2RR) is a sustainable way of producing carbon-neutral fuels. Product selectivity in CO2RR is regulated by the adsorption energy of reaction-intermediates. Here, we employ differential phase contrast-scanning transmission electron microscopy (DPC-STEM) to demonstrate that Sn heteroatoms on a Ag catalyst generate very strong and atomically localized electric fields. In situ attenuated total reflection infrared spectroscopy (ATR-IR) results verified that the localized electric field enhances the adsorption of *COOH, thus favoring the production of CO during CO2RR. The Ag/Sn catalyst exhibits an approximately 100 % CO selectivity at a very wide range of potentials (from -0.5 to -1.1 V, versus reversible hydrogen electrode), and with a remarkably high energy efficiency (EE) of 76.1 %

Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

Initialization of nanowire or cluster growth critically controlled by the effective V/III ratio at the early nucleation stage

For self-catalyzed nanowires (NWs), reports on how the catalytic droplet initiates successful NW growth are still lacking, making it difficult to control the yield and often accompanying a high density of clusters. Here, we have performed a systematic study on this issue, which reveals that the effective V/III ratio at the initial growth stage is a critical factor that governs the NW growth yield. To initiate NW growth, the ratio should be high enough to allow the nucleation to extend to the entire contact area between the droplet and substrate, which can elevate the droplet off of the substrate, but it should not be too high in order to keep the droplet. This study also reveals that the cluster growth between NWs is also initiated from large droplets. This study provides a new angle from the growth condition to explain the cluster formation mechanism, which can guide high-yield NW growth

Structural basis of PROTAC cooperative recognition for selective protein degradation

Inducing macromolecular interactions with small molecules to activate cellular signaling is a challenging goal. PROTACs (proteolysis-targeting chimeras) are bifunctional molecules that recruit a target protein in proximity to an E3 ubiquitin ligase to trigger protein degradation. Structural elucidation of the key ternary ligase-PROTAC-target species and its impact on target degradation selectivity remain elusive. We solved the crystal structure of Brd4 degrader MZ1 in complex with human VHL and the Brd4 bromodomain (Brd4BD2). The ligand folds into itself to allow formation of specific intermolecular interactions in the ternary complex. Isothermal titration calorimetry studies, supported by surface mutagenesis and proximity assays, are consistent with pronounced cooperative formation of ternary complexes with Brd4BD2. Structure-based-designed compound AT1 exhibits highly selective depletion of Brd4 in cells. Our results elucidate how PROTAC-induced de novo contacts dictate preferential recruitment of a target protein into a stable and cooperative complex with an E3 ligase for selective degradation

Sparse Haar-Like Feature and Image Similarity-Based Detection Algorithm for Circular Hole of Engine Cylinder Head

If the circular holes of an engine cylinder head are distorted, cracked, defective, etc., the normal running of the equipment will be affected. For detecting these faults with high accuracy, this paper proposes a detection method based on feature point matching, which can reduce the detection error caused by distortion and light interference. First, the effective and robust feature vectors of pixels are extracted based on improved sparse Haar-like features. Then we calculate the similarity and find the most similar matching point from the image. In order to improve the robustness to the illumination, this paper uses the method based on image similarity to map the original image, so that the same region under different illumination conditions has similar spatial distribution. The experiments show that the algorithm not only has high matching accuracy, but also has good robustness to the illumination

3D Pose Tracking With Multitemplate Warping And Sift Correspondences

Template warping is a popular technique in vision-based 3D motion tracking and 3D pose estimation due to its flexibility of being applicable to monocular video sequences. However, the method suffers from two major limitations that hamper its successful use in practice. First, it requires the camera to be calibrated prior to applying the method. Second, it may fail to provide good results if the inter-frame displacements are too large. To overcome the first problem, we propose to estimate the unknown focal length of the camera from several initial frames by an iterative optimization process. To alleviate the second problem, we propose a tracking method based on combining complementary information provided by dense optical flow and tracked scale-invariant feature transform (SIFT) features. While optical flow is good for small displacements and provides accurate local information, tracked SIFT features are better at handling larger displacements or global transformations. To combine these two pieces of complementary information, we introduce a forgetting factor to bootstrap the 3D pose estimates provided by SIFT features, and refine the final results using optical flow. Experiments are performed on three public databases, i.e., the Biwi Head Pose dataset, the BU dataset, and the McGill Faces datasets. The results illustrate that the proposed solution provides more accurate results than baseline methods that rely solely on either template warping or SIFT features. In addition, the approach can be applied in a larger variety of scenarios, due to circumventing the need for camera calibration, thus providing a more flexible solution to the problem than existing methods