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Whole-brain analysis of single-neuron morphology is crucial for unraveling the complex structure of the brain. However, large-scale neuron reconstruction from terabyte and even petabyte data of mammalian brains generated by state-of-the-art light microscopy is a daunting task. Here, we developed ‘Gapr’ (Gapr accelerates projectome reconstruction) that streamlines deep learning-based automatic reconstruction, ‘automatic proofreading’ that reduces human workloads at high-confidence sites, and high-throughput collaborative proofreading by crowd users through the Internet. Furthermore, Gapr offers a seamless user interface that ensures high proofreading speed per annotator, on-demand conversion for handling large datasets, flexible workflows tailored to diverse datasets and rigorous error tracking for quality control. Finally, we demonstrated Gapr’s efficacy by reconstructing over 4,000 neurons in mouse brains, revealing the morphological diversity in cortical interneurons and hypothalamic neurons. Here, we present Gapr as a solution for large-scale single-neuron reconstruction projects.

Previous studies report an association between maternal diabetes mellitus (MDM) and attention-deficit/hyperactivity disorder (ADHD), often overlooking unmeasured confounders such as shared genetics and environmental factors. We therefore conducted a multinational cohort study with linked mother–child pairs data in Hong Kong, New Zealand, Taiwan, Finland, Iceland, Norway and Sweden to evaluate associations between different MDM (any MDM, gestational diabetes mellitus (GDM) and pregestational diabetes mellitus (PGDM)) and ADHD using Cox proportional hazards regression. We included over 3.6 million mother–child pairs between 2001 and 2014 with follow-up until 2020. Children who were born to mothers with any type of diabetes during pregnancy had a higher risk of ADHD than unexposed children (pooled hazard ratio (HR) = 1.16, 95% confidence interval (CI) = 1.08-1.24). Higher risks of ADHD were also observed for both GDM (pooled HR = 1.10, 95% CI = 1.04-1.17) and PGDM (pooled HR = 1.39, 95% CI = 1.25-1.55). However, siblings with discordant exposure to GDM in pregnancy had similar risks of ADHD (pooled HR = 1.05, 95% CI = 0.94-1.17), suggesting potential confounding by unmeasured, shared familial factors. Our findings indicate that there is a small-to-moderate association between MDM and ADHD, whereas the association between GDM and ADHD is unlikely to be causal. This finding contrast with previous studies, which reported substantially higher risk estimates, and underscores the need to reevaluate the precise roles of hyperglycemia and genetic factors in the relationship between MDM and ADHD.

The application of object detection technology has been used in people's daily lives widely, and it can be used accurately in traffic scenes is also crucial. Based on the YOLOX object detection model, a lightweight neural network for traffic object detection is proposed. First, we propose S-PANet (Simple Path Aggregation Network) structure based on the YOLOX_S baseline model. The purpose of the S-PANet structure is to reduce the parameters number of models and the amount of floating-point computation in training. Second, we propose to add CBAM (Convolutional Block Attention Module) to the network based on the S-PANet. Adding CBAM attention mechanism can improve the detection accuracy of models, but has less computation added. It is a compensation of the simplification on feature pyramid. Final, we carry out the lightweight experiments on three kinds of models, including S, Tiny, and Nano. The proposed methods are verified on KITTI and PASCAL VOC datasets. Our S model can achieve 92.9% mAP@0.5 and 21.33 FPS on KITTI dataset. The Tiny and Nano models can achieve 84.3%, 79.4% mAP@0.5 and 33.07, 41.67 FPS respectively. Compared with the baseline models, the detection accuracies mAP@0.5 have less difference and the parameters number of the models are reduced.

High-precision MEMS accelerometers with nano-g resolution are emergent instruments for geophysical applications and proved their competence in terms of functionality. The electromagnetic actuator, which serves as an auxiliary component in nano-g MEMS accelerometers for improving the dynamic response, faces the challenges of process incompatibility, temperature sensitivity, and large form factor. Thereby, this paper proposes an area-changed capacitive method for both displacement transducing and force balance in a nano-g MEMS accelerometer, aiming to address those posed challenges and provide favourable performance. Thanks to the allowed large displacement range in the sensitive direction of the proposed device, the area-changed capacitive mechanism is able to be integrated with a highly-sensitive quasi-zero stiffness spring-mass structure. As a result, the fabricated force-balance MEMS accelerometer attains a calibrated self-noise of 1.3 ng/ $\surd $ Hz, which is one of the most sensitive MEMS-based accelerometers reported to date. The settling time, on the other hand, is reduced to 0.5 s with the electrostatic closed-loop control featuring the proposed subject, compared to 15.7 s in the open-loop configuration. In addition, the critical acceleration input at the boundary of the “pull-in” is calculated as 5.4 g, which is adaptable to most geophysical applications. This work is of considerable potential in geophysical applications such as earthquake monitoring or gravity measurements, and promising a high-performance closed-loop MEMS accelerometer. [2023-0161]

Previous deep convolutional neural network research has made significant progress toward improving the speed and accuracy of object detection. However, despite these advancements, the inaccurate detection of multi-object (small objects) remains challenging in the traffic environments. In this article, we propose a new architecture called YOLOM, which is specifically designed to achieve enhanced multi-object (small objects) detection precision. YOLOM incorporates several innovative features: a multi-spatial pyramid (MSP), an optimized focal loss (OFLoss) function, and an objectness loss that incorporates effective intersection over union (EIoU) calculations. These features collectively yield enhanced accuracy and reduce the miss rate of small objects, particularly in the multi-object cases. According to the sizes of receptive field features with different spatial scales with pooling layers, we propose the MSP module. We optimize the focal loss as a classification function instead of the cross-entropy loss, which solves some class imbalance problems caused by anchor-free detection when encountering disparate datasets. Due to the superior performance of EIoU in confidence scoring, we use EIoU to participate in the objectness loss calculation of our work. Therefore, our method substitutes EIoU for YOLOX's objectness loss. The experimental results demonstrate that our strategies significantly outperform some end-to-end object detection methods.

Segmentation of blood vessels in retinal fundus images is crucial for detecting and diagnosing eye diseases. In recent years, the application of deep learning methods based on convolutional neural networks (CNNs) in retinal blood vessel segmentation has made significant progress in performance. However, the downsampling operation used by CNN to extract high-level contextual semantics will cause the loss of low-level blood vessel spatial details. Therefore, accurately segmenting retinal blood vessels remains challenging. In this article, we propose a hierarchical full-resolution fusion network (HFRF-Net) for accurate blood vessel segmentation from retinal fundus images. In HFRF-Net, we design spatial path and contextual path based on a hierarchical structure, which is used to extract rich spatial features and sufficient contextual semantics, respectively. In the contextual path, we propose a cross-scale attention (CSA) block to simulate the interaction at multiple scales in the vascular region. Then, to cope with the loss of spatial information, we propose a full-resolution learning strategy, which consists of a spatial detail enhancement (SDE) block and a full-resolution fusion (FRF) block. The SDE block performs fine-grained analysis and feature extraction of blood vessels by multiplexing the original fundus images in the spatial path. Meanwhile, the FRF block is proposed to guide the full-resolution information fusion of contextual path and spatial path, which preserves the microstructure of blood vessels to the greatest extent. In addition to the design of the network architecture, we also propose a topology-aware connectivity booster (TCB) to improve the connectivity of blood vessels in the segmentation map. We conducted extensive experiments on three mainstream retinal fundus image datasets (DRIVE, CHASE-DB1, and STARE). Compared to other state-of-the-art methods, the results demonstrate that our method achieves superior segmentation performance.

Although often intended for long-term treatment, discontinuation of medication for ADHD is common. However, cross-national estimates of discontinuation are missing due to the absence of standardised measures. The aim of this study was to determine the rate of ADHD treatment discontinuation across the lifespan and to describe similarities and differences across countries to guide clinical practice.

The structures of dendrites and axons form the basis for the connectivity of neural network, but their precise relationship at single-neuron level remains unclear. Here we report the complete dendrite and axon morphology of nearly 2,000 neurons in mouse prefrontal cortex (PFC). We identified morphological variations of somata, dendrites and axons across laminar layers and PFC subregions and the general rules of somatodendritic scaling with cytoarchitecture. We uncovered 24 morphologically distinguishable dendrite subtypes in 1,515 pyramidal projection neurons and 405 atypical pyramidal projection neurons and spiny stellate neurons with unique axon projection patterns. Furthermore, correspondence analysis among dendrites, local axons and long-range axons revealed coherent morphological changes associated with electrophysiological phenotypes. Finally, integrative dendrite–axon analysis uncovered the organization of potential intra-column, inter-hemispheric and inter-column connectivity among projection neuron types in PFC. Together, our study provides a comprehensive structural repertoire for the reconstruction and analysis of PFC neural network.

Single-atom catalysts (SACs) show expressively enhanced activity toward diverse reactions due to maximized atomic utilization of metal sites, while their facile, universal, and massive preparation remains a pronounced challenge. Here we report a facile strategy for the preparation of SACs by use of the inherent confined space between the template and silica walls in template-occupied mesoporous silica SBA-15 (TOS). Different transition metal precursors can be introduced into the confined space readily by grinding, and during succeeding calcination single atoms are constructed in the form of M–O–Si (M = Cu, Co, Ni, and Zn). In addition to the generality, the present strategy is easy to scale up and can allow the synthesis of 10 g of SACs in one pot through ball milling. The Cu SAC has been applied for CO2cycloaddition of epichlorohydrin, and the activity is obviously higher than the counterpart prepared without confined space and various reported Cu-containing catalysts.

The development of the DC distribution system (DCDS) has attracted increasing attention, due to its technological superiorities in integrating new energy sources and DC power loads more friendly and effectively. In this paper, a comprehensive evaluation method is proposed for the medium–low​ voltage DCDS to handle the voltage sag assessment problem. Firstly, the topology structure and control strategy of the DCDS are stated, and the pragmatic characteristics of DC voltage sag on the medium-voltage and low-voltage sides based on the dual active bridge (DAB) converter are analyzed. Then, considering the difference in the evaluation indexes of the low-voltage and medium-voltage sides of the DCDS, a comprehensive evaluation system is established. Further, the analytic hierarchy process (AHP) and criteria importance through intercriteria correlation (CRITIC) weighting method are applied to achieve comprehensive weighting, and the TOPSIS model is used to describe the severity of DC voltage sag. Using MATLAB, a 10 kV/ 750 V DCDS with the DAB is built, and comparative assessments are performed. The results show that the proposed method can reasonably evaluate the DC voltage sag of the low-voltage and medium-voltage sides. Compared to the evaluation schemes based on the single index, the proposed method can more effectively reflect the waveform features of the DC voltage sag, and it is very appropriate for the voltage dip evaluation of the medium–low voltage DCDS.

SiC-based composites have a wide range of applications in thermostructural filed. It is of great significance to accurately manufacture high-performance SiC whisker-reinforced SiC matrix composites (SiCw/SiC). Binder jetting (BJ) is an additive manufacturing method that can prepare complex-shaped whisker preforms in near-net-size. Reactive melt infiltration (RMI) method can prepare highly dense matrix without shrinkage of composites. Currently, the preparation technology of SiCw/SiC using the combination of BJ and RMI has the challenges of low whisker volume fraction, irrational whisker distribution, and high residual silicon content in matrix. A combination process of spray drying and chemical vapor infiltration (CVI) was developed to shape one-dimensional SiCwinto SiCwcomposites microspheres (SiCw-CMS), which significantly improves the volume fraction and flowability of SiCw. Based on the SiCw-CMS, a novel hierarchical structural SiCw/SiC was designed. Also, through constructing reasonable infiltration channels of liquid silicon, the content of residual silicon in SiCw/SiC was reduced to 5.2 vol%. As a result, the flexural strength and fracture toughness of the SiCw/SiC can reach 385 MPa and 5.93 MPa·m1/2, respectively. The SiCw/SiC also shows low coefficient of thermal expansion of 4.0–5.4 × 10−6K−1, high thermal conductivity of 110.4 W/(m·K), and appropriate resistivity (7.09 Ω·cm). The hierarchical structural SiCw/SiC is expected to be a candidate for future thermal structural materials.

Prefrontal cortex (PFC) is the cognitive center that integrates and regulates global brain activity. However, the whole-brain organization of PFC axon projections remains poorly understood. Using single-neuron reconstruction of 6,357 mouse PFC projection neurons, we identified 64 projectome-defined subtypes. Each of four previously known major cortico-cortical subnetworks was targeted by a distinct group of PFC subtypes defined by their first-order axon collaterals. Further analysis unraveled topographic rules of soma distribution within PFC, first-order collateral branch point-dependent target selection and terminal arbor distribution-dependent target subdivision. Furthermore, we obtained a high-precision hierarchical map within PFC and three distinct functionally related PFC modules, each enriched with internal recurrent connectivity. Finally, we showed that each transcriptome subtype corresponds to multiple projectome subtypes found in different PFC subregions. Thus, whole-brain single-neuron projectome analysis reveals organization principles of axon projections within and outside PFC and provides the essential basis for elucidating neuronal connectivity underlying diverse PFC functions.

The design of organometallic catalysts is crucial in the development of catalytic reactions. Herein, we describe a heterometallic [Os-Cu]complex with the characteristics of bimetallics, metallaaromatics, and pincer complexes. This complex serves as a highly effective catalyst for selective amino- and oxyselenation of unactivated alkenes. More than 80 examples including challenging substrates of unsymmetric aliphatic alkenes and amine-based nucleophiles in such reactions are provided. These reactions produce 1,2-difunctionalized products with good yields and high levels of chemo-, regio-, and stereoselectivity. Our studies revealed the following: (i) The usually inert osmium center activates the N- or O-centered nucleophiles. (ii) The copper–osmium bonding and its cooperative effects play essential roles in control the selectivity by bringing the reaction components into close proximity. (iii) The metallaaromatic moiety helps to stabilize the intermediate. These findings provide a versatile platform for catalyst design based on metal–metallaaromatic cooperative effects that have not been attained previously with bimetallic complexes.

Spatially resolved scRNA-seq (sp-scRNA-seq) technologies provide the potential to comprehensively profile gene expression patterns in tissue context. However, the development of computational methods lags behind the advances in these technologies, which limits the fulfillment of their potential. In this study, we develop a deep learning approach for clustering sp-scRNA-seq data, named Deep Spatially constrained Single-cell Clustering (DSSC). In this model, we integrate the spatial information of cells into the clustering process in two steps: (1) the spatial information is encoded by using a graphical neural network model, and (2) cell-to-cell constraints are built based on the spatial expression pattern of the marker genes and added in the model to guide the clustering process. Then, a deep embedding clustering is performed on the bottleneck layer of autoencoder by Kullback–Leibler (KL) divergence along with the learning of feature representation. DSSC is the first model that can use information from both spatial coordinates and marker genes to guide cell/spot clustering. Extensive experiments on both simulated and real data sets show that DSSC boosts clustering performance significantly compared with the state-of-the-art methods. It has robust performance across different data sets with various cell type/tissue organization and/or cell type/tissue spatial dependency. We conclude that DSSC is a promising tool for clustering sp-scRNA-seq data.

DC-DC CONVERTERS ARE SOLID-STATE DC "transformers" that convert one type of dc electricity into another via power electronic circuits. They have been used in a broad range of applications, from IT devices (such as a power supply to provide different dc voltage levels inside a personal computer or a data center server) to medical equipment (e.g., a solar charger for a cardiac pacemaker) and from consumer electronics (e.g., chargers for various smart mobile devices) to high-power industrial applications, which is the focused area of this article. As there has been exponential growth in transportation electrification since the beginning of the 21st century, dc-dc converters have become one of the core devices in electric and autonomous vehicles. Extensive research and development efforts have been made on the design and implementation of dc-dc converters, aiming at higher power density, higher efficiency, and more reduction in cost. In this article, various dc-dc converter topologies and control methodologies for transportation electrification are reviewed. The challenges and future development trends for creating the next-generation dc-dc power converters are also discussed.

In this work, the interconnected graphene scaffolds are prepared by three-dimensional (3D) printing for multifunctional gas detection with tunable sensitivity. The scaffolds with regularly aligned graphene conductive networks exhibit significant mechanical strength and high electrical stability to multi-direction deformation, which can be attributed to the typical core-shell structure of graphene and PVP. The resistance of the free-standing scaffolds can realize the real-time response to H 2 O and NO 2 , and the relative resistance change to 100 ppm H 2 O and 100 ppm NO 2 can reach 2% and 2.5 %, respectively. The charge doping of the oxidizing gases is considered to be the main reason for various response sensitivities of the scaffolds with different orthogonal layers, in which the interconnected conductive network can generate a large specific surface area and significantly improving the adsorption of the target gases and the transfer of charge. The controllable fabrication of regular structure has appropriately great potential for further optimizations and applications in gas detection. [ABSTRACT FROM AUTHOR]

Hollow nanomaterials have been used as an attractive platform for the integration of multiple bioactive components for effective anticancer therapy. Herein, we report a novel and facile strategy for the fabrication of hollow and monodispersed zeolitic imidazolate framework-8 (ZIF-8) by the self-template method with folic acid (FA) as a bioetcher. Gold nanocluster and folic acid were critical for the formation of the hollow ZIF-8 (thickness of 38 nm) during solvothermal synthesis. By integrating CuS nanoparticles (size of 4.9 nm), the resultant quadruple ZIF-8/Au/CuS/FA nanocomposites (denoted as FACZ) exhibited effective anticancer activities on FA receptor-positive MCF-7 and HepG-2 tumor cells but a weak killing effect on HCMEC/D3 cells. Folic acid molecules were conjugated to the external surface of FACZ, which simultaneously offered an excellent tumor-targeting ability and fluorescence imaging property. Although the photothermal therapy caused by CuS was not so obvious due to partial reduction, the nanosized FACZ after cellular uptake was able to release Cu(I) to enable chemodynamic therapy. This catalytically decomposed H2O2to produce highly reactive oxygen species via the Fenton-like reaction as determined by the extracellular and intracellular hydroxyl radical. Our work offers a simple route for the fabrication of hollow ZIF-8 nanocomposite with active and selective anticancer activity. This is envisaged to have great potentials in biomedical applications.

Screening infrared (IR) nonlinear optical (NLO) materials remains an urgent concern, owing to the lack of efficient IR frequency-conversion materials with good NLO response. The deepened cognition of how cations regulate the contribution of anions to the SHG response is necessary to guide the exploration of IR NLO materials. In this work, the typical NLO materials A2HgI4(A = Ag, Cu) were studied systematically by the first-principles method. It is shown that they exhibit excellent SHG responses d14= 23.09 pm/V for Ag2HgI4and d14= 29.50 pm/V for Cu2HgI4,which are about two times the IR benchmark AgGaS2. A2HgI4(A = Ag, Cu) also possess moderate band gaps of 2.38 and 2.04 eV. To analyze the regulation of A-site cation to the anions, two hypothetical compounds, α-Na2HgI4and β-Na2HgI4, were designed via atom substitution, which maintain strong NLO response about d14= 11.68 pm/V and d14= 14.43 pm/V and larger band gaps (3.36 eV for α-Na2HgI4, 3.13 eV for β-Na2HgI4), respectively. Interestingly, these four compounds show hierarchical properties for differences in the A-site cation. The real-space atom-cutting (RSAC) method and SHG-density method reveal that the difference is not obtained directly from the change of A-site metals. Via the analysis of the electronic density method and SHG-density method, the iodine anions display hierarchical contributions to SHG response under the unexpected regulation by the A-site metals. Our findings offer a strategy to explore new NLO materials with desirable performances.

Graphene has attracted increasing attention for strain sensing due to its unique electrical and mechanical properties by tailoring and assembling functional macrostructures with a well-defined configuration. Here a novel graphene-based planar network (GPN) with highly stretchable strain sensing is developed by direct ink writing. The integrated and regulated structure of GPN indicates an excellent response sensitivity and cyclic stability to various strain modes compared with the traditional graphene-based woven fabric (GWF) structure. An equivalent resistance network is introduced to analyze the resistance change mechanism and fracture failure mode of the network structures, in which the difference can be mainly attributed to the interfacial resistance at the crosspoints of the crossed ribbons. The tunable and interconnected GPN shows a significant difference in the response sensitivity under stretching strain in different directions, and the relative resistance change is up to 20 and 3 in horizontal and vertical directions after 1000 cycles for a 20% stretching strain, respectively, which can be explained by the transformation of the stretching mode from macro-structural stretching to micromaterial stretching. The controllable fabrication of GPN can be utilized not only for the detection of full-range human activities but monitoring external stress distribution in real-time by integration.

Uniaxial tensile tests and stress-controlled low-cycle fatigue (LCF) and creep–fatigue interaction (CFI) tests of Inconel 625 alloy manufactured by selective laser melting (SLM) were performed at 815 °C in air environments. The microstructure was characterized by optical microscopy and scanning electron microscopy after testing. The results confirmed that significant embrittlement and large scatter in LCF life are resulted from manufacturing defects. The CFI life is decreased sharply to approximately dozens of cycles with the accumulated creep strain; however, the selected dwell time (i.e., 60 s and 300 s) exhibits low sensitivity to the fracture time and elongation to failure. The embrittlement of SLM Inconel 625 was proposed to be due to the low grain uniformity and precipitation of carbides at the grain boundaries. Due to the quality of the SLM process, the accelerated initiation and propagation of fatigue crack are caused by the present unmelted powder particles, which result in the large dispersion of LCF life. Meanwhile, due to the accumulation of creep damage, cracks in the CFI test are initiated along the grain boundaries and then linked together, contributing to a significant decline in fatigue life.

The alkali-metal molybdate iodate Na3(MoO4)(IO3) (I) and mixed-alkali-metal fluoromolybdate Na3Cs(MoO2F4)2(II) were obtained via a mild hydrothermal reaction using a “Teflon-pouch” method. Icrystallizes in the triclinic space group P1, whose structure comprises a 3D backbone made up of isolated [IO3]−pyramids and [MoO4]2–tetrahedra connected via 5- and 6-fold coordinated sodium cations. IIcrystallizes in the monoclinic space group P21/cand comprises isolated [MoO2F4]2–octahedra with strong out-of-center distortions and the Na+as well as Cs+cations acting as interstitial ions. Both compounds have been characterized by infrared (IR) spectra and ultraviolet–visible–near-infrared (UV–vis–NIR) diffuse reflectance spectra. First-principles calculations respectively reveal that they exhibit birefringence values with Δn= 0.078 and 0.210 at 1064 nm for Iand II, and the origin of the birefringence is discussed.

Soybean mosaic virus (SMV) is one of the most destructive pathogens of soybean (Glycine max (L.) Merr.) worldwide. In this study, 184 F7:11 recombinant inbred line (RIL) populations derived from Kefeng No. 1 × Nannong 1138-2 were used to study the inheritance and linkage mapping of resistance genes against SMV strains SC7 and SC13 in Kefeng No. 1. Two independent dominant genes (designated Rsc7 and Rsc13) that control resistance to SC7 and SC13 were located on a molecular linkage group (MLG) of chromosome 2 (D1b). A mixed segregating population was developed by self-pollination of three heterozygous plants of residual heterozygous lines (RHL3-27, RHL3-30, RHL3-53) with five markers linked to the loci, and was used in fine-mapping of Rsc7 and Rsc13. In addition, Rsc7 was fine-mapped between BARCSOYSSR_02_0667 and BARCSOYSSR_02_0670 on MLG D1b. The genetic distance between the two closest markers was 0.7 cM and the physical distance of the interval was ~77 kb, which included one LRR gene and another gene containing an F-box region. Two SSR markers (BARCSOYSSR_02_0610 and BARCSOYSSR_02_0621) were closely linked to the SC13 resistance gene. The physical distance where Rsc13 was located was ~191 kb. Sequence analysis showed that there were two K-box region types of transcription factor genes; GmHSP40 and two serine/threonine protein kinase (STK) genes were the most likely candidate genes. These results will facilitate map-based cloning of the Rsc7 and Rsc13 genes and development of transgenic disease-resistant varieties, and will provide SMV-resistance breeding systems with excellent resistance germplasm.

Background: Calcium ions usually act as a second messenger in the signal transmission process and a major element required by plants. In Hevea, calcium ion could alleviate the negative effects of long-term ethylene application to a certain extent. However, the molecular mechanisms remain unclear. Methods: Two-dimensional electrophoresis was used to determine the pattern of protein changes in latex after treatments with calcium and/or ethylene. Quantitative real-time polymerase chain reaction and Western blotting were used to determine the expression levels of some proteins and genes. STRING software was used to determine the protein-protein interaction network of the identified proteins. Results: Comparative proteomics identified 145 differentially expressed proteins, which represented 103 unique proteins. The abundance change patterns of some proteins involved in signal transduction, rubber particle aggregation, and natural rubber biosynthesis were altered upon calcium stimulation. Quantitative real-time polymerase chain reaction analysis of 29 proteins showed that gene expression did not always maintain the same trend as protein expression. The increased enzyme activities of superoxide dismutase, ascorbate peroxidase, and glutathione reductase suggested that calcium can enhance the antistress ability of plants by increasing the activity of their antioxidant enzyme systems. Conclusion: These results supplement the rubber latex proteome, and provide evidence for investigating the molecular mechanisms by which calcium alleviates the negative effects of ethylene stimulation.

The morphology and spatial distribution of axon arbors and boutons are crucial for neuron presynaptic functions. However, the principles governing their whole-brain organization at the single-neuron level remain unclear. We developed a machine-learning method to separate axon arbors from passing axons in single-neuron reconstruction from fluorescence micro-optical sectioning tomography imaging data and obtained 62,374 axon arbors that displayed distinct morphology, spatial patterns, and scaling laws dependent on neuron types and targeted brain areas. Focusing on the axon arbors in the thalamus and cortex, we revealed the segregated spatial distributions and distinct morphology but shared topographic gradients between feedforward and feedback projections. Furthermore, we uncovered an association between arbor complexity and microglia density. Finally, we found that the boutons on terminal arbors show branch-specific clustering with a log-normal distribution that again differed between feedforward and feedback terminal arbors. Together, our study revealed distinct presynaptic structural organizations underlying diverse functional innervation of single projection neurons.

This research investigates the unique configuration of cobalt ferrite (Co1.5Fe1.5O4) anchored onto the surface of cerium dioxide (CeO2), which effectively activates peroxymonosulfate (PMS) to degrade trichloroethylene (TCE). Co1.5Fe1.5O4-CeO2/PMS was able to completely degrade 5mg/L of TCE by comparison between PMS and the components of the prepared composites. In addition, the Co1.5Fe1.5O4-CeO2/PMS system was highly adaptable to pH and aqueous substrates. Quenching experiments combined with ESR spectroscopy results demonstrated that ·OH, SO4·-, O2·-, and 1O2in the system play an important role in degrading TCE. The Co1.5Fe1.5O4-CeO2/PMS system can maintain 90% degradation efficiency for various pollutants (TCE, carbon tetrachloride (CT), dichloromethane (DCM), 2,4-dichlorophenoxyacetic acid (2,4-D)) as well as the actual wastewater, and the multiple cycling experiments have verified that the Co1.5Fe1.5O4-CeO2/PMS has a good stability. XPS comparisons before and after the reaction revealed that cobalt ferrite exhibited a unique transition from the radical pathway to the non-radical pathway during TCE degradation after the introduction of CeO2. This pathway shift can be attributed to the synergistic interaction between cobalt ferrite and CeO2,which adjusts the electronic structure, facilitates the activation of PMS, and generates more reactive oxygen species to decompose TCE. This research offers valuable insights into the design of efficient advanced oxidation catalysts for the removal of organic pollutants from water and the optimization of degradation pathways.

Soybean mosaic virus(SMV), an RNA virus, is the most common and destructive pathogenic virus in soybean fields. The newly developed CRISPR/Cas immune system has provided a novel strategy for improving plant resistance to viruses; hence, this study aimed to engineer SMV resistance in soybean using this system. Specifically, multiple sgRNAs were designed to target positive- and/or negative-sense strands of the SMV HC-Progene. Subsequently, the corresponding CRISPR/CasRx vectors were constructed and transformed into soybeans. After inoculation with SMV, 39.02%, 35.77%, and 18.70% of T1plants were confirmed to be highly resistant (HR), resistant (R), and mildly resistant (MR) to SMV, respectively, whereas only 6.50% were identified as susceptible (S). Additionally, qRT-PCR and DAS-ELISA showed that, both at 15 and 30 d post-inoculation (dpi), SMV accumulation significantly decreased or was even undetectable in HR and R plants, followed by MR and S plants. Additionally, the expression level of the CasRxgene varied in almost all T1plants with different resistance level, both at 15 and 30 dpi. Furthermore, when SMV resistance was evaluated in the T2generation, the results were similar to those recorded for the T1generation. These findings provide new insights into the application of the CRISPR/CasRx system for soybean improvement and offer a promising alternative strategy for breeding for resistance to biotic stress that will contribute to the development of SMV-immune soybean germplasm to accelerate progress towards greater soybean crop productivity

The practical application of rechargeable Zn-air batteries relies on the advance of low-cost and high-performance oxygen evolution/reduction reaction (OER/ORR) bifunctional electrocatalyst. Herein, a noble-metal-free bifunctional electrocatalyst is rationally designed by anchoring the nickel‑iron layered double hydroxide (NiFe-LDH) nanosheets on the Fe, N decorated carbon nanofibers (LDH/FeNCF). The resultant LDH/FeNCF exhibits remarkable bifunctional catalytic activities for OER/ORR, delivering a reversible oxygen electrode index (ΔE) of 0.70 V, significantly surpassing that of noble-metal-based Pt/C-RuO2benchmark (ΔE = 0.77 V) and those of most bifunctional electrocatalysts ever reported. Moreover, the primary Zn-air batteries based on LDH/FeNCF cathode behave robust stability once discharging at 5 and 10 mA cm−2for 150 h, and the as-assembled rechargeable Zn-air batteries can be durably cycled for 690 h, suggesting their promising applications in the field of rechargeable Zn-air batteries, especially in terms of the facile process and low cost.

The neutron capture cross sections (n,γ) of bromine were obtained using the time-of-flight technique at the Back-n facility of the China Spallation Neutron Source. Prompt γ-rays originating from neutron-induced capture events were detected using four C6D6detectors. The pulse-height weighting technique and double-bunch unfolding method based on Bayesian theory were used in the data analysis. Background deductions, normalization, and corrections were carefully considered to obtain reliable measurement results. The multilevel R-matrix Bayesian code SAMMY was used to extract the resonance parameters in the resolved resonance region (RRR). The average cross sections in the unresolved resonance region (URR) were obtained from 10 to 400 keV. The experimental results were compared with data from several evaluated libraries and previous experiments in the RRR and URR. The TALYS code was used to describe the average cross sections in the URR. The astrophysical Maxwell average cross sections (MACSs) of 79,81Br from kT= 5 to 100 keV were calculated over a sufficiently wide range of neutron energies. At a thermal energy of kT=30keV, the MACS value for 79Br 682±68 mb was in good agreement with the KADoNiS v1.0 recommended value. By contrast, the value of 293±29 mb for 81Br was substantially higher than that of the evaluated database and the KADoNiS v1.0 recommended value.

An efficient, environmentally benign and sustainable method for the synthesis of 2‐pyrrolidinones from 1,6‐enynes via an unusual regioselective azidation/cyclization is described. The products have been obtained in good yields without the assistance of any transition‐metal catalysts or ligands. To demonstrate the utility of this protocol, the azidation products are converted to a synthetically valuable amine or triazole. This azidation cyclization involves a radical process, allows a regioselective way toward the formation of one C−N bond and one C−C bond. From 1 to 6, like dice: An efficient, environmentally benign and sustainable method for the synthesis of 2‐pyrrolidinones from 1,6‐enynes via an unusual regioselective azidation cyclization is described. The products were obtained in good yields without the assistance of any transition‐metal catalysts or ligands. To demonstrate the utility of this protocol, the azidation products were converted to a synthetically valuable amine and triazole. This azidation cyclization involves a radical process, and allows a regioselective way toward the formation of one C−N bond and one C−C bond.

An active crowbar protective circuit is an effective and common approach for low voltage ride through (LVRT) of a doubly-fed induction generator (DFIG). The crowbar resistance value and its switching scheme both have crucial effects on safety recovery. The effects encountered are correlative dependence and interplay so that analyzing them from a single factor, as most existing LVRT control methods would do, obtains a partial optimal solution. This paper connects these two factors to analyze their coordination effects on the LVRT control, and to also investigate whether the global optimal performance of these factors can be achieved. The principles for resistance selection and the schemes for crowbar switching are discussed first. Next the coupling relationship is analyzed based on statistical sampling simulation data with different resistance values and various switching schemes. The results demonstrate that their coordination has critical influence on rotor peak current, DC-link voltage and reactive power. The optimal coordination will be different according to specific requirements. Hence the global optimal combination could be achieved when all requirements are taken into consideration.

Two novel thermally activated delayed fluorescence (TADF) emitters, 3-phenylquinolino[3,2,1-de]acridine-5,9-dione (3-PhQAD) and 7-phenylquinolino[3,2,1-de]acridine-5,9-dione (7-PhQAD), were designed and synthesized based on a rigid quinolino[3,2,1-de]acridine-5,9-dione (QAD) framework. With the effective superimposed resonance effect from electron-deficient carbonyls and electron-rich nitrogen atom, both emitters realize significant TADF characteristics with small ΔESTs of 0.18 and 0.19 eV, respectively. And, molecular relaxations were dramatically suppressed for both emitters because of their conjugated structure. In the devices, 3-PhQAD realizes superior performance with a maximum external quantum efficiency (EQE) of 19.1% and a narrow full width at half-maximum (FWHM) of 44 nm, whereas a maximum EQE of 18.7% and an extremely narrow FWHM of 34 nm are realized for 7-PhQAD. These superior results reveal that apart from nitrogen and boron-aromatic systems, QAD framework can also act as a TADF matrix with effective resonance effect, and QAD derivatives are ideal candidates to develop TADF emitters with narrow FWHMs for practical applications.

A metal‐free oxynitration of acrylamides with commercially available tert‐butyl nitrite and easily available air was achieved through a regioselective pathway. A wide range of 1,2‐nitro alcohols were thus efficiently synthesized in a novel route under mild conditions. The reaction involves a radical process, allows a highly regioselective strategy toward the formation of new C−N and C−O bonds in one step. A metal‐free oxynitration of acrylamides with commercially available tert‐butyl nitrite and easily available air was achieved through a regioselective pathway. A wide range of 1,2‐nitro alcohols were thus efficiently synthesized in a novel route under mild conditions. The reaction involves a radical process, allows a highly regioselective strategy toward the formation of new C−N and C−O bonds in one step.

Molecularly imprinted polymers (MIPs) have been attracting increasing attention and used in various applications due to their tailor-made and adjustable selectivity. By means of innovation of the imprinting methods, such as using winnowing templates based on the analytical targets, the selectivity of MIPs can either be narrowed down to one particular molecule (high specificity), or broadened up to one group of analogues (wide selectivity). Based on the recent finding that polyhedral oligomeric silsesquioxanes (POSS) can enhance the absorption capacity of separation media, a baicalin-imprinted POSS hybridized monolith was synthesized and systematically investigated in terms of the preparation conditions and running parameters when using the MIP monolith as a capture column in on-line in-tube SPME-HPLC. The resulting MIP could be utilized to enrich baicalin out of a complex matrix of Scutellaria baicalensisfor facile quantitative analysis. Furthermore, by means of off-line LC-MS/MS, wide selectivity for capturing analogues of baicalin was also qualitatively confirmed. This work provides a new perspective and method for controlling the wide selectivity of MIPs, and also a facile 2-dimensional HPLC system for the analysis of traditional Chinese medicine (TCM).

A novel and environmentally attractive C(sp3)–H azidation of 2-oxindoles involving the formation of a C–N bond was developed. This methodology achieved for the first time 3-azido-2-oxindole construction under metal-free conditions at room temperature via a radical strategy. PhI(OAc)2was used as the oxidant and Et3N was used as the additive in this transformation. Furthermore, the mechanistic study indicated that this azidation involved a radical process.