Crystal structure of HPPD inhibitor sensitive protein from Oryza sativa.

4-hydroxyphenylpyruvate dioxygenase (HPPD) Inhibitor Sensitive 1 (HIS1) is an endogenous gene of rice, conferring broad-spectrum resistance to ß-triketone herbicides. Similar genes, known as HIS1-like genes (HSLs), exhibit analogous functions and can complement the herbicide-resistant characteristics endowed by HIS1. The identification of HIS1 and HSLs represents a valuable asset, as the intentional pairing of herbicides with resistance genes emerges as an effective strategy for crop breeding. Encoded by HIS1 is a Fe(II)/2-oxoglutarate-dependent oxygenase responsible for detoxifying ß-triketone herbicides through hydroxylation. However, the precise structure supporting this function remains unclear. This work, which determined the crystal structure of HIS1, reveals a conserved core motif of Fe(II)/2-oxoglutarate-dependent oxygenase and pinpoints the crucial residue dictating substrate preference between HIS1 and HSL.

Crystal structure of an aspartate aminotransferase Lpg0070 from Legionella pneumophila.

Legionella pneumophila aspartate aminotransferase (Lpg0070) is a member of the transaminase and belongs to the pyridoxal 5'-phosphate (PLP)-dependent superfamily. It is responsible for the transfer of α-amino between aspartate and α-ketoglutarate to form glutamate and oxaloacetate. Here, we report the crystal structure of Lpg0070 at the resolution of 2.14 Å and 1.7 Å, in apo-form and PLP-bound, respectively. Our structural analysis revealed the specific residues involved in the PLP binding and free form against PLP-bound supported conformational changes before substrate recognition. In vitro enzyme activity proves that the absence of the N-terminal arm reduces the enzyme activity of Lpg0070. These data provide further evidence to support the N-terminal arm plays a crucial role in catalytic activity.

A novel ribociclib derivative WXJ-103 exerts anti-breast cancer effect through CDK4/6.

The triple-negative breast cancer (TNBC) subtype is the most aggressive type of breast cancer with a low survival prognosis and high recurrence rate. There is currently no effective treatment to improve it. In this work, we explored the effect of a synthetic compound named WXJ-103 on several aspects of TNBC biology. The human breast cancer cell lines MDA-MB-231 and MCF-7 were used in the experiments, and the cell viability was detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide method, and the cell migration and invasion abilities were detected by wound healing assay and Transwell invasion assay. Cell cycle and apoptosis experiments were analyzed by flow cytometry, and protein levels related to cyclin-dependent kinase (CDK) 4/6-cyclin D-Rb-E2F pathway were analyzed by western blotting. Then, in-vivo experiments were performed to determine the clinical significance and functional role of WXJ-103. The results show that WXJ-103 can inhibit the adhesion, proliferation, migration, and invasion of TNBC cells, and can arrest the cell cycle in G1 phase. The levels of CDK4/6-cyclin D-Rb-E2F pathway-related proteins such as CDK6 and pRb decreased in a dose-dependent manner. Therefore, the antitumor activity of WXJ-103 may depend on the inhibition of CDK4/6-cyclin D1-Rb-E2F pathway. This research shows that WXJ-103 may be a new promising antitumor drug, which can play an antitumor effect on TNBC and provide new ideas for the treatment of TNBC.

Structural Characterization of an N-Acetyl Sugar Amidotransferase Involved in the Lipopolysaccharide Biosynthesis in Bacteria.

N-acetyl sugar amidotransferase (NASAT) is involved in the lipopolysaccharide (LPS) biosynthesis pathway that catalyzes the formation of the acetamido moiety (sugar-NC(=NH)CH3) on the O-chain. So far, little is known about its structural and functional properties. Here, we report the crystal structure of an N-acetyl sugar amidotransferase from Legionella pneumophila (LpNASAT) at 2.33 Å resolution. LpNASAT folds into a compact basin-shaped architecture with an unusually wide and open putative substrate-binding pocket and a conserved zinc ion-binding tetracysteine motif. The pocket contains a Rossmann-like fold with a PP-loop, suggesting that the NASAT-catalyzed amidotransfer reaction probably requires the conversion of ATP to AMP and PPi. Our data provide structural insights into the NASAT family of proteins, and allow us to possibly identify its functionally important regions.

SOX9-mediated UGT8 expression promotes glycolysis and maintains the malignancy of non-small cell lung cancer.

UDP-glycosyltransferases (UGTs) catalyze the covalent addition of sugars to small lipophilic chemicals and are associated with a wide range of diseases including cancer. The human genome contains 22 UGT genes which could be classified into four families: UGT1, UGT2, UGT3, and UGT8. The UGT8 family contains only one member which utilizes UDP galactose to galactosidate ceramide. Although higher UGT8 mRNA was observed in some types of cancer, its pathological significances remain elusive. Here, by integrating the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the Genotype-Tissue Expression (GTEx) databases, we showed that UGT8 was selectively highly expressed in non-small cell lung cancer (NSCLC) and associated with worse prognosis. The transcription factor SOX9 promoted UGT8 expression in NSCLC by recognizing two putative response elements localized on the promoter region of UGT8. Silencing UGT8 impaired glycolysis and reduced the malignancy of NSCLC cells both in vitro and in vivo. On the contrary, inhibition of glycolysis by 2-deoxy-d-glucose (2-DG) significantly impaired the pro-proliferation function of UGT8 in NSCLC cells. In conclusion, our results suggest that UGT8 maintains the malignancy of NSCLC mainly via enhanced glycolysis and provides a promising therapeutic target for NSCLC.

Gas-Responsive and Self-Powered Visual Composite Langmuir-Blodgett Films for Ultrathin Gas Sensors.

The complex and variable environments are challenging the development of related detection and analysis. Ammonia (NH3) and hydrogen chloride (HCl) gases are both commonly used in industry, but they are considered to be toxic and corrosive substances that can threaten human health and the environment. Therefore, it is necessary here to develop a convenient, sensitive, and reliable sensor device for acid-alkali gas detection. Herein, we propose the synthesis strategy of an ultrathin film gas sensor based on the pH-responsive, self-powered, and visible composite Langmuir-Blodgett (LB) films. In our work, the LB films with nanometric thicknesses are obtained based on the sensitive materials of two novel carbazole structural sensitizers (abbreviated as CS-35 and CS-37) and several dye molecules. The composite LB films are formed with Carbazole samples and dye molecules through hydrogen bonding, π-π stacking, synergistic electrostatic interactions, and hydrophobic interactions, existing as J-aggregate or H-aggregate. The formation of high-quality and uniform Langmuir films is confirmed with transmission electron microscope (TEM), UV-vis spectrum, atomic force microscopy (AFM), and other measurements. In addition, based on the simple protonation and deprotonation, the prepared LB films can be assembled into a visual sensor for the response of pH gases. The response is confirmed by the study of ultraviolet spectroscopy and electrical output in vertical contact separation mode, which potentially unlocks a sustainable future for the application of ultrathin self-powered gas sensors.

Structural basis for substrate binding and specificity of a sodium-alanine symporter AgcS.

The amino acid, polyamine, and organocation (APC) superfamily is the second largest superfamily of membrane proteins forming secondary transporters that move a range of organic molecules across the cell membrane. Each transporter in the APC superfamily is specific for a unique subset of substrates, even if they possess a similar structural fold. The mechanism of substrate selectivity remains, by and large, elusive. Here, we report two crystal structures of an APC member from Methanococcus maripaludis, the alanine or glycine:cation symporter (AgcS), with l- or d-alanine bound. Structural analysis combined with site-directed mutagenesis and functional studies inform on substrate binding, specificity, and modulation of the AgcS family and reveal key structural features that allow this transporter to accommodate glycine and alanine while excluding all other amino acids. Mutation of key residues in the substrate binding site expand the selectivity to include valine and leucine. These studies provide initial insights into substrate selectivity in AgcS symporters.

A Novel Approach for UAV Image Crack Detection.

Cracks are the most significant pre-disaster of a road, and are also important indicators for evaluating the damage level of a road. At present, road crack detection mainly depends on manual detection and road detection vehicles, with which the safety of detection workers is not guaranteed and the detection efficiency is low. A road detection vehicle can speed up the efficiency to a certain extent, but the automation level is low and it is easy to block the traffic. Unmanned Aerial Vehicles (UAV) have the characteristics of low energy consumption and easy control. If UAV technology can be applied to road crack detection, it will greatly improve the detection efficiency and produce huge economic benefits. In order to find a way to apply UAV to road crack detection, we developed a new technique for road crack detection based on UAV pictures, called DenxiDeepCrack, which is a trainable deep convolutional neural network for automatic crack detection which utilises learning high-level features for crack representation. In addition, we create a new dataset based on drone images called UCrack 11 to enrich the crack database of drone images for future crack detection research.

MAFF-Net: Multi-Attention Guided Feature Fusion Network for Change Detection in Remote Sensing Images.

One of the most important tasks in remote sensing image analysis is remote sensing image Change Detection (CD), and CD is the key to helping people obtain more accurate information about changes on the Earth's surface. A Multi-Attention Guided Feature Fusion Network (MAFF-Net) for CD tasks has been designed. The network enhances feature extraction and feature fusion by building different blocks. First, a Feature Enhancement Module (FEM) is proposed. The FEM introduces Coordinate Attention (CA). The CA block embeds the position information into the channel attention to obtain the accurate position information and channel relationships of the remote sensing images. An updated feature map is obtained by using an element-wise summation of the input of the FEM and the output of the CA. The FEM enhances the feature representation in the network. Then, an attention-based Feature Fusion Module (FFM) is designed. It changes the previous idea of layer-by-layer fusion and chooses cross-layer aggregation. The FFM is to compensate for some semantic information missing as the number of layers increases. FFM plays an important role in the communication of feature maps at different scales. To further refine the feature representation, a Refinement Residual Block (RRB) is proposed. The RRB changes the number of channels of the aggregated features and uses convolutional blocks to further refine the feature representation. Compared with all compared methods, MAFF-Net improves the F1-Score scores by 4.9%, 3.2%, and 1.7% on three publicly available benchmark datasets, the CDD, LEVIR-CD, and WHU-CD datasets, respectively. The experimental results show that MAFF-Net achieves state-of-the-art (SOTA) CD performance on these three challenging datasets.

Lightweight Hot-Spot Fault Detection Model of Photovoltaic Panels in UAV Remote-Sensing Image.

Photovoltaic panels exposed to harsh environments such as mountains and deserts (e.g., the Gobi desert) for a long time are prone to hot-spot failures, which can affect power generation efficiency and even cause fires. The existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both detection accuracy and speed is proposed. In this paper, the feature extraction part of YOLOv5 is replaced by the more lightweight Focus structure and the basic unit of ShuffleNetv2, and then the original feature fusion method is simplified. Considering that there is no publicly available infrared photovoltaic panel image dataset, this paper generates an infrared photovoltaic image dataset through frame extraction processing and manual annotation of a publicly available video. Consequently, the number of parameters of the model was 3.71 M, mAP was 98.1%, and detection speed was 49 f/s. A comprehensive comparison of the accuracy, detection speed, and model parameters of each model showed that the indicators of the new model are superior to other detection models; thus, the new model is more suitable to be deployed on the UAV platform for real-time photovoltaic panel hot-spot fault detection.

3D Object Detection Based on Attention and Multi-Scale Feature Fusion.

Three-dimensional object detection in the point cloud can provide more accurate object data for autonomous driving. In this paper, we propose a method named MA-MFFC that uses an attention mechanism and a multi-scale feature fusion network with ConvNeXt module to improve the accuracy of object detection. The multi-attention (MA) module contains point-channel attention and voxel attention, which are used in voxelization and 3D backbone. By considering the point-wise and channel-wise, the attention mechanism enhances the information of key points in voxels, suppresses background point clouds in voxelization, and improves the robustness of the network. The voxel attention module is used in the 3D backbone to obtain more robust and discriminative voxel features. The MFFC module contains the multi-scale feature fusion network and the ConvNeXt module; the multi-scale feature fusion network can extract rich feature information and improve the detection accuracy, and the convolutional layer is replaced with the ConvNeXt module to enhance the feature extraction capability of the network. The experimental results show that the average accuracy is 64.60% for pedestrians and 80.92% for cyclists on the KITTI dataset, which is 1.33% and 2.1% higher, respectively, compared with the baseline network, enabling more accurate detection and localization of more difficult objects.

The effect of information-driven resource allocation on the propagation of epidemic with incubation period.

In the pandemic of COVID-19, there are exposed individuals who are infected but lack distinct clinical symptoms. In addition, the diffusion of related information drives aware individuals to spontaneously seek resources for protection. The special spreading characteristic and coevolution of different processes may induce unexpected spreading phenomena. Thus we construct a three-layered network framework to explore how information-driven resource allocation affects SEIS (susceptible-exposed-infected-susceptible) epidemic spreading. The analyses utilizing microscopic Markov chain approach reveal that the epidemic threshold depends on the topology structure of epidemic network and the processes of information diffusion and resource allocation. Conducting extensive Monte Carlo simulations, we find some crucial phenomena in the coevolution of information diffusion, resource allocation and epidemic spreading. Firstly, when E-state (exposed state, without symptoms) individuals are infectious, long incubation period results in more E-state individuals than I-state (infected state, with obvious symptoms) individuals. Besides, when E-state individuals have strong or weak infectious capacity, increasing incubation period has an opposite effect on epidemic propagation. Secondly, the short incubation period induces the first-order phase transition. But enhancing the efficacy of resources would convert the phase transition to a second-order type. Finally, comparing the coevolution in networks with different topologies, we find setting the epidemic layer as scale-free network can inhibit the spreading of the epidemic.

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology.

Crystal structure of a hypothetical T2SS effector Lpg0189 from Legionella pneumophila reveals a novel protein fold.

Lpg0189 is a type II secretion system-dependent extracellular protein with unknown function from Legionella pneumophila. Herein, we determined the crystal structure of Lpg0189 at 1.98 Šresolution by using single-wavelength anomalous diffraction (SAD). Lpg0189 folds into a novel chair-shaped architecture, with two sheets roughly perpendicular to each other. Bioinformatics analysis suggests Lpg0189 and its homologues are unique to Legionellales and evolved divergently. The interlinking structural and bioinformatics studies provide a better understanding of this hypothetical protein.

Finite element analysis comparing short-segment instrumentation with conventional pedicle screws and the Schanz pedicle screw in lumbar 1 fractures.

Previous finite element studies of thoracolumbar fractures were mostly based on simulation analysis of one single object, which was difficult to objectively evaluate the differences between conventional pedicle screws and Schanz pedicle screws. The aim of this study was to evaluate the stress of screw and injured vertebrae displacement using the finite element model of conventional pedicle screw and Schanz pedicle screw instrumentation for the treatment of lumbar 1 fractures. Data of eight healthy volunteers were used to simulate the finite element model. The instrumentation models were divided into four groups: moderate fracture conventional (MC), moderate fracture Schanz (MS), unstable/severe fracture conventional (UC), and unstable/severe fracture Schanz (US) pedicle screw groups. The maximum screw stress and lumbar 1 displacement/micro-motion in each group increased with the increase of torque and/or load. Under the same fracture, maximum von Mises stress of conventional pedicle screw (MC/UC) was larger than Schanz pedicle screw (MS/US) (P < 0.05) and lumbar 1 displacement/micro-motion of Schanz pedicle screw (MS/US) was larger than conventional pedicle screw (MC/UC) (P < 0.05). Under the same screws, the maximum von Mises stress and displacement/micro-motion of unstable fracture (UC/US) were larger than moderate fracture (MC/MS) (P < 0.05). Posterior short-segment instrumentation with Schanz pedicle screws were recommended for unstable fractures. The compression displacement/micro-motion of bony defect during flexion may lead to the postoperative re-collapse of injured vertebrae.

Relationship Between IL-10 Gene Polymorphism and Spinal Tuberculosis.

BACKGROUND To investigate the relation between interleukin-10 (IL-10) gene rs1800871 (A/G) polymorphism and spinal tuberculosis. MATERIAL AND METHODS A total of 129 patients with spinal tuberculosis (spinal tuberculosis group) and 106 healthy subjects receiving physical examination (control group) were enrolled in this study. The general data of these subjects were collected, and the C-reactive protein, erythrocyte sedimentation rate (ESR) and baseline hematologic function were examined. The rs1800871 (A/G) polymorphism in IL-10 gene was detected by TaqMan-MGB probe method. RESULTS The C-reactive protein, ESR, white blood cell count, absolute neutrophil count and relative neutrophil count in spinal tuberculosis group were higher than those in control group, while the absolute lymphocyte count and relative lymphocyte count were lower than those in control group (p<0.05). Compared with AA genotype, GG and AG+GG genotypes showed statistically significant difference in distribution frequency (p<0.05), but no significant difference was detected between AG genotype and AA genotype (p>0.05). In spinal tuberculosis group, the frequency of G allele was higher than that of A allele (p<0.01). The C-reactive protein, ESR, white blood cell count and relative neutrophil count in GG genotype were increased compared with those in AG+GG genotype (p<0.05). CONCLUSIONS The rs1800871 (A/G) polymorphism in IL-10 gene is related to the susceptibility to spinal tuberculosis. Moreover, carrying G allele increases the risk of spinal tuberculosis.

Chemokines play a role in nerve damage and neuroprotection in vascular dementia.

Various Chemotactic Factors (FCs) play different roles in neuronal injury in vascular dementia. CXCL5 and CCL11 exacerbate neurological injury by promoting inflammatory responses. CXCL12/SDF-1 and CX3CL1 play neuroprotective roles.CXCL13, XCL-1 and CCL2/ MCP-1 exacerbate neurological injury in the early stage, while exerting neuronal regeneration and neuroprotective effects in the chronic progressive phase. Chemokines often play an important role in the course of vascular dementia by regulating inflammatory responses, oxidative stress, and autophagy. Activation of microglia plays an important role in the regression of vascular dementia. Activated microglia M1 causes neuronal damage through the release of chemokines. And microglia M2 has anti-inflammatory effects and is involved in the repair of brain damage. Therefore, dynamic monitoring of various related FCs and understanding the relationship between FCs and microglia can help to understand and regulate the disease course progression of vascular dementia.At present, many scholars have confirmed in basic research that different subgroups of chemokines are closely related to vascular dementia. In clinical research, new immunotherapy methods that upregulate XCL-1 and drugs that regulate the activity of CCL2/CCR2 signaling pathways are being studied and promoted.

Double-sided microstructured flexible iontronic pressure sensor with wide linear sensing range.

Iontronic pressure sensors have garnered significant attention for their potential in wearable electronic devices. While simple microstructures can enhance sensor sensitivity, the majority of them predominantly amplify sensitivity at lower pressure ranges and fail to enhance sensitivity at higher pressure ranges, leading to nonlinearity. In the absence of linear sensitivity in a pressure sensor, users are unable to derive precise information from its output, necessitating further signal processing. Hence, crafting a linearity flexible pressure sensor through a straightforward approach remains a formidable task. Herein, a double-sided microstructured flexible iontronic pressure sensor is presented with wide linear sensing range. The ionic gel is made by 1-Ethyl-3-methylimidazolium bis(tri-fluoromethylsulfonyl)imide (EMIM:TFSI) into the matrix of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), which acts as active layer, featuring irregular microstructures (IMS) and pyramid microstructures (PMS) on both sides. Unlike previous complex methods, IMS and uniform PMS are easily and achieved through pattern transfer from a sandpaper mold and micro-pyramid template. The iontronic pressure sensor exhibits exceptional signal linearity with R2 values of 0.9975 and 0.9985, in the wide pressure range from 100 to 760 kPa and 760 kPa to 1000 kPa, respectively. This outstanding linearity and wide sensing range stem from a delicate balance between microstructure compression and mechanical alignment at the ionic gel interface. This study provides valuable insights into achieving linear responses by strategically designing microstructures in flexible pressure sensors, with potential applications in intelligent robots and health monitoring.

Structural basis for substrate recognition by a S-adenosylhomocysteine hydrolase Lpg2021 from Legionella pneumophila.

S-Adenosyl-l-homocysteine hydrolase (SAHH) is a crucial enzyme that governs S-adenosyl methionine (SAM)-dependent methylation reactions within cells and regulates the intracellular concentration of SAH. Legionella pneumophila, the causative pathogen of Legionnaires' disease, encodes Lpg2021, which is the first identified dimeric SAHH in bacteria and is a promising target for drug development. Here, we report the structure of Lpg2021 in its ligand-free state and in complexes with adenine (ADE), adenosine (ADO), and 3-Deazaneplanocin A (DZNep). X-ray crystallography, isothermal titration calorimetry (ITC), and molecular docking were used to elucidate the binding mechanisms of Lpg2021 to its substrates and inhibitors. Virtual screening was performed to identify potential Lpg2021 inhibitors. This study contributes a novel perspective to the understanding of SAHH evolution and establishes a structural framework for designing specific inhibitors targeting pathogenic Legionella pneumophila SAHH.