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Shaped charge liner (SCL) has been extensively applied in oil recovery and defense industries. Achieving superior penetration capability through optimizing SCL structures presents a substantial challenge due to intricate rate-dependent processes involving detonation-driven liner collapse, high-speed jet stretching, and penetration. This study introduces an innovative optimization strategy for SCL structures that employs jet penetration efficiency as the primary objective function. The strategy combines experimentally validated finite element method with machine learning (FEM-ML). We propose a novel jet penetration efficiency index derived from enhanced cutoff velocity and shape characteristics of the jet via machine learning. This index effectively evaluates the jet penetration performance. Furthermore, a multi-model fusion based on a machine learning optimization method, called XGBOOST-MFO, is put forward to optimize SCL structure over a large input space. The strategy's feasibility is demonstrated through the optimization of copper SCL implemented via the FEM-ML strategy. Finally, this strategy is extended to optimize the structure of the recently emerging CrMnFeCoNi high-entropy alloy conical liners and hemispherical copper liners. Therefore, the strategy can provide helpful guidance for the engineering design of SCL.

Abstract Background The cardiac toxicity of radiotherapy (RT) can affect cancer survival rates over the long term. This has been confirmed in patients with breast cancer and lymphoma. However, there are few studies utilizing the two-dimensional speckle-tracking echocardiography (2D-STE) to evaluate the risk factors affecting radiation induced heart disease (RIHD), and there is a lack of quantitative data. Therefore, we intend to explore the risk factors for RIHD and quantify them using 2D-STE technology. Methods We ultimately enrolled 40 patients who received RT for thoracic tumors. For each patient, 2D-STE was completed before, during, and after RT and in the follow up. We analyzed the sensitivity of 2D-STE in predicting RIHD and the relationship between RT parameters and cardiac systolic function decline. Results Left ventricle global longitudinal strain (LVGLS), LVGLS of the endocardium (LVGLS-Endo), LVGLS of the epicardium (LVGLS-Epi), and right ventricle free-wall longitudinal strain (RVFWLS) decreased mid- and post-treatment compared with pre-treatment, whereas traditional parameters such as left ventricular ejection fraction (LVEF), cardiac Tei index (Tei), and peak systolic velocity of the free wall of the tricuspid annulus (s’) did not show any changes. The decreases in the LVGLS and LVGLS-Endo values between post- and pre-treatment and the ratios of the decreases to the baseline values were linearly correlated with mean heart dose (MHD) (all P values < 0.05). The decreases in the LVGLS-Epi values between post- and pre-treatment and the ratios of the decreases to the baseline values were linearly correlated with the percentage of heart volume exposed to 5 Gy or more (V5) (P values < 0.05). The decrease in RVFWLS and the ratio of the decrease to the baseline value were linearly related to MHD and patient age (all P values < 0.05). Endpoint events occurred more frequently in the right side of the heart than in the left side. Patients over 56.5 years of age had a greater probability of developing right-heart endpoint events. The same was true for patients with MHD over 20.2 Gy in both the left and right sides of the heart. Conclusions 2D-STE could detect damages to the heart earlier and more sensitively than conventional echocardiography. MHD is an important prognostic parameter for LV systolic function, and V5 may also be an important prognostic parameter. MHD and age are important prognostic parameters for right ventricle systolic function.

Objective: To select novel strains that could degrade pectin at low temperature from marine sediment samples and discover pectinase with potential industrial value. Methods: Take pectin as the only carbon source, screening a high-yielding pectinase strain from sea mud in Bohai Bay, Dalian with the transparent circle method and the 3,5-dinitrosalicylic acid method (DNS method). It analyzed the morphological, physiological and biochemical characteristics, and determined the 16S rDNA sequence. After comparing BLAST homologous gene, it built up a phylogenetic tree, and further studied the enzymatic properties. Results: It screened the strain with high pectinase yield which was named LY-1. Then it analyzed the 16S rDNA sequence and determined that this strain was Streptomyces olivogriseus from the physiological and biochemical index. When strain LY-1 was cultured at 25 ℃ and 180 r/min for 24 hours, the enzyme activity of pectinase was 30.56 U/mL. It showed that the optimal enzyme pH was 8.0, and the optimal enzyme temperature was 20 ℃. Furthermore, the enzymatic activity could still be maintained more than 70% when it was incubated at 60 ℃ for 2 hours, and remained stable in the pH range of 7.0~9.0 with enzyme activity at over 90%. The metal ions Cu2+, Ba2+, Mg2+, Ca2+, K+, and Co2+ could promote the activity of this enzyme, while Mn2+, Zn2+, Hg2+, and Na+ would inhibit its activity. Conclusion: The pectinase produced by strain LY-1 would have the potential to be applied to industrial commercial pectinase.

Abstract Background Post-stroke cognitive impairment (PSCI) is the focus and difficulty of poststroke rehabilitation intervention with an incidence of up to 61%, which may be related to the deterioration of cerebrovascular function. Computer-aided cognitive training (CACT) can improve cognitive function through scientific training targeting activated brain regions, becoming a popular training method in recent years. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, can regulate the cerebral vascular nerve function, and has an effect on the rehabilitation of cognitive dysfunction after stroke. This study examined the effectiveness of both CACT and tDCS on cognitive and cerebrovascular function after stroke, and explored whether CACT combined with tDCS was more effective. Methods A total of 72 patients with PSCI were randomly divided into the conventional cognitive training (CCT) group (n = 18), tDCS group (n = 18), CACT group (n = 18), and CACT combined with tDCS group (n = 18). Patients in each group received corresponding 20-minute treatment 15 times a week for 3 consecutive weeks. Montreal Cognitive Assessment (MoCA) and the Instrumental Activities of Daily Living Scale (IADL) were used to assess patients’ cognitive function and the activities of daily living ability. Transcranial Doppler ultrasound (TCD) was used to assess cerebrovascular function, including cerebral blood flow velocity (CBFV), pulse index (PI), and breath holding index (BHI). These outcome measures were measured before and after treatment. Results Compared with those at baseline, both the MoCA and IADL scores significantly increased after treatment (P

Abstract Background Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths. GNN-based methods has the limitation of using the edge weight information directly, makes it difficult to aggregate the neighboring nodes' information more efficiently when representing node embedding. Results To address this challenge, we developed a novel graph attention network framework named MMGAT, which employs an attention mechanism to adjust the attention coefficients among different nodes. And then MMGAT finds multiple ATAC-seq motifs based on the attention coefficients of sequence nodes and k-mer nodes as well as the coexisting probability of k-mers. Our approach achieved better performance on the human ATAC-seq datasets compared to existing tools, as evidenced the highest scores on the precision, recall, F1_score, ACC, AUC, and PRC metrics, as well as finding 389 higher quality motifs. To validate the performance of MMGAT in predicting TFBSs and finding motifs on more datasets, we enlarged the number of the human ATAC-seq datasets to 180 and newly integrated 80 mouse ATAC-seq datasets for multi-species experimental validation. Specifically on the mouse ATAC-seq dataset, MMGAT also achieved the highest scores on six metrics and found 356 higher-quality motifs. To facilitate researchers in utilizing MMGAT, we have also developed a user-friendly web server named MMGAT-S that hosts the MMGAT method and ATAC-seq motif finding results. Conclusions The advanced methodology MMGAT provides a robust tool for finding ATAC-seq motifs, and the comprehensive server MMGAT-S makes a significant contribution to genomics research. The open-source code of MMGAT can be found at https://github.com/xiaotianr/MMGAT , and MMGAT-S is freely available at https://www.mmgraphws.com/MMGAT-S/ .

BackgroundCervical cancer, a severe threat to women’s health, is experiencing a global increase in incidence, notably among younger demographics. With artificial intelligence (AI) making strides, its integration into medical research is expanding, particularly in cervical cancer studies. This bibliometric study aims to evaluate AI’s role, highlighting research trends and potential future directions in the field.MethodsThis study systematically retrieved literature from the Web of Science Core Collection (WoSCC), employing VOSviewer and CiteSpace for analysis. This included examining collaborations and keyword co-occurrences, with a focus on the relationship between citing and cited journals and authors. A burst ranking analysis identified research hotspots based on citation frequency.ResultsThe study analyzed 927 articles from 2008 to 2024 by 5,299 authors across 81 regions. China, the U.S., and India were the top contributors, with key institutions like the Chinese Academy of Sciences and the NIH leading in publications. Schiffman, Mark, featured among the top authors, while Jemal, A, was the most cited. ‘Diagnostics’ and ‘IEEE Access’ stood out for publication volume and citation impact, respectively. Keywords such as ‘cervical cancer,’ ‘deep learning,’ ‘classification,’ and ‘machine learning’ were dominant. The most cited article was by Berner, ES; et al., published in 2008.ConclusionsAI’s application in cervical cancer research is expanding, with a growing scholarly community. The study suggests that AI, especially deep learning and machine learning, will remain a key research area, focusing on improving diagnostics and treatment. There is a need for increased international collaboration to maximize AI’s potential in advancing cervical cancer research and patient care.

Advances in understanding the pathological mechanisms of breast cancer have resulted in the emergence of novel therapeutic strategies. However, triple-negative breast cancer (TNBC), a molecular subtype of breast cancer with a poor prognosis, lacks classical and general therapeutic targets, hindering the clinical application of several therapies to breast cancer. As insights into the unique immunity and molecular mechanisms of TNBC have become more extensive, immunotherapy has gradually become a valuable complementary approach to classical radiotherapy and chemotherapy. CD8+ cells are significant actors in the tumor immunity cycle; thus, research on TNBC immunotherapy is increasingly focused in this direction. Recently, CD8+ tissue-resident memory (TRM) cells, a subpopulation of CD8+ cells, have been explored in relation to breast cancer and found to seemingly play an undeniably important role in tumor surveillance and lymphocytic infiltration. In this review, we summarize the recent advances in the mechanisms and relative targets of CD8+ T cells, and discuss the features and potential applications of CD8+ TRM cells in non-luminal breast cancer immunotherapy.

The photogenerated charge carrier separation and transportation of inside photocathodes can greatly influence the performance of photoelectrochemical (PEC) H2 production devices. Coupling TiO2 with p-type semiconductors to construct heterojunction structures is one of the most widely used strategies to facilitate charge separation and transportation. However, the band position of TiO2 could not perfectly match with all p-type semiconductors. Here, taking antimony selenide (Sb2Se3) as an example, a rational strategy was developed by introducing a viologen electron transfer mediator (ETM) containing polymeric film (poly-1,1′-dially-[4,4′-bipyridine]-1,1′-diium, denoted as PV2+) at the interface between Sb2Se3 and TiO2 to regulate the energy band alignment, which could inhibit the recombination of photogenerated charge carriers of interfaces. With Pt as a catalyst, the constructed Sb2Se3/PV2+/TiO2/Pt photocathode showed a superior PEC hydrogen generation activity with a photocurrent density of −18.6 mA cm−2 vs. a reversible hydrogen electrode (RHE) and a half-cell solar-to-hydrogen efficiency (HC-STH) of 1.54% at 0.17 V vs. RHE, which was much better than that of the related Sb2Se3/TiO2/Pt photocathode without PV2+ (−9.8 mA cm−2, 0.51% at 0.10 V vs. RHE).

Microwave dielectric ceramics should be improved to advance mobile communication technologies further. In this study, we prepared Sr1+xY2O4+x (x = 0–0.04) ceramics with nonstoichiometric Sr2+ ratios based on our previously reported SrY2O4 microwave dielectric ceramic, which has a low dielectric constant and an ultrahigh quality factor (Q value). The ceramic exhibited a 33.6% higher Q-by-frequency (Q×f) value (Q ≈ 12,500) at x = 0.02 than SrY2O4. All Sr1+xY2O4+x (x = 0–0.04) ceramics exhibited pure phase structures, although variations in crystal-plane spacings were observed. The ceramics are mainly composed of Sr–O, Y1–O, and Y2–O octahedra, with the temperature coefficient of the resonant frequency (τf) of the ceramic increasing with Y2–O octahedral distortion. The ceramic comprises uniform grains with a homogeneous elemental distribution, clear grain boundaries, and no obvious cavities at x = 0.02. The Sr1+xY2O4+x (x = 0–0.04) ceramics exhibited good microwave dielectric properties, with optimal performance observed at x = 0.02 (dielectric constant (εr) = 15.41, Q×f = 112,375 GHz, and τf = −17.44 ppm/℃). The τf value was reduced to meet the temperature-stability requirements of 5G/6G communication systems by adding CaTiO3, with Sr1.02Y2O4.02+2wt%CaTiO3 exhibiting εr = 16.14, Q×f = 51,004 GHz, and τf = 0 ppm/℃. A dielectric resonator antenna prepared using Sr1.02Y2O4.02+2wt%CaTiO3 exhibited a central frequency of 26.6 GHz, with a corresponding gain and efficiency of 3.66 dBi and 83.14%, respectively. Consequently, Sr1.02Y2O4.02-based dielectric resonator antennas are suitable for use in 5G millimeter-wave band (24.5–27.5 GHz) applications.

Abstract Human cerebellum encompasses numerous neurons, exhibiting a distinct developmental paradigm from cerebrum. Here we conducted scRNA-seq, scATAC-seq and spatial transcriptomic analyses of fetal samples from gestational week (GW) 13 to 18 to explore the emergence of cellular diversity and developmental programs in the developing human cerebellum. We identified transitory granule cell progenitors that are conserved across species. Special patterns in both granule cells and Purkinje cells were dissected multidimensionally. Species-specific gene expression patterns of cerebellar lobes were characterized and we found that PARM1 exhibited inconsistent distribution in human and mouse granule cells. A novel cluster of potential neuroepithelium at the rhombic lip was identified. We also resolved various subtypes of Purkinje cells and unipolar brush cells and revealed gene regulatory networks controlling their diversification. Therefore, our study offers a valuable multi-omics landscape of human fetal cerebellum and advances our understanding of development and spatial organization of human cerebellum.

Abstract Background Obesity is increasingly recognized as a grave public health concern globally. It is associated with prevalent diseases including coronary heart disease, fatty liver, type 2 diabetes, and dyslipidemia. Prior research has identified demographic, socioeconomic, lifestyle, and genetic factors as contributors to obesity. Nevertheless, the influence of occupational risk factors on obesity among workers remains under-explored. Investigating risk factors specific to steelworkers is crucial for early detection, prediction, and effective intervention, thereby safeguarding their health. Methods This research utilized a cohort study examining health impacts on workers in an iron and steel company in Hebei Province, China. The study involved 5469 participants. By univariate analysis, multifactor analysis, and review of relevant literature, predictor variables were found. Three predictive models—XG Boost, Support Vector Machine (SVM), and Random Forest (RF)—were employed. Results Univariate analysis and cox proportional hazard regression modeling identified age, gender, smoking and drinking habits, dietary score, physical activity, shift work, exposure to high temperatures, occupational stress, and carbon monoxide exposure as key factors in the development of obesity in steelworkers. Test results indicated accuracies of 0.819, 0.868, and 0.872 for XG Boost, SVM, and RF respectively. Precision rates were 0.571, 0.696, and 0.765, while recall rates were 0.333, 0.592, and 0.481. The models achieved AUCs of 0.849, 0.908, and 0.912, with Brier scores of 0.128, 0.105, and 0.104, log losses of 0.409, 0.349, and 0.345, and calibration-in-the-large of 0.058, 0.054, and 0.051, respectively. Among these, the Random Forest model demonstrated superior performance. Conclusions The research indicates that obesity in steelworkers results from a combination of occupational and lifestyle factors. Of the models tested, the Random Forest model exhibited superior predictive ability, highlighting its significant practical application.

IntroductionMultiple sclerosis (MS) and neuromyelitis optic spectrum disorder (NMOSD) are mimic autoimmune diseases of the central nervous system with a very high disability rate. Their clinical symptoms and imaging findings are similar, making it difficult to diagnose and differentiate. Existing research typically employs the T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) MRI imaging technique to focus on a single task in MS and NMOSD lesion segmentation or disease classification, while ignoring the collaboration between the tasks.MethodsTo make full use of the correlation between lesion segmentation and disease classification tasks of MS and NMOSD, so as to improve the accuracy and speed of the recognition and diagnosis of MS and NMOSD, a joint model is proposed in this study. The joint model primarily comprises three components: an information-sharing subnetwork, a lesion segmentation subnetwork, and a disease classification subnetwork. Among them, the information-sharing subnetwork adopts a dualbranch structure composed of a convolution module and a Swin Transformer module to extract local and global features, respectively. These features are then input into the lesion segmentation subnetwork and disease classification subnetwork to obtain results for both tasks simultaneously. In addition, to further enhance the mutual guidance between the tasks, this study proposes two information interaction methods: a lesion guidance module and a crosstask loss function. Furthermore, the lesion location maps provide interpretability for the diagnosis process of the deep learning model.ResultsThe joint model achieved a Dice similarity coefficient (DSC) of 74.87% on the lesion segmentation task and accuracy (ACC) of 92.36% on the disease classification task, demonstrating its superior performance. By setting up ablation experiments, the effectiveness of information sharing and interaction between tasks is verified.DiscussionThe results show that the joint model can effectively improve the performance of the two tasks.

Abstract Retinal ischemia‒reperfusion (I/R) injury can cause significant damage to human retinal neurons, greatly compromising their functions. Existing interventions have been proven to have little effect. Ferroptosis is a newly discovered type of programmed cell death that has been found to be involved in the process of ischemia‒reperfusion in multiple organs throughout the body. Studies have shown that it is also present in retinal ischemia‒reperfusion injury. A rat model of retinal ischemia‒reperfusion injury was constructed and treated with deferoxamine. In this study, we found the accumulation of Fe2+, reactive oxygen species (ROS), malondialdehyde (MDA), and the consumption of glutathione (GSH) via ELISA testing; increased expression of transferrin; and decreased expression of ferritin, SLC7A11, and GPX4 via Western blotting (WB) and real-time PCR testing. Structural signs of ferroptosis (mitochondrial shrinkage) were observed across multiple cell types, including retinal ganglion cells (RGCs), photoreceptor cells, and pigment epithelial cells. Changes in visual function were detected by F-VEP and ERG. The results showed that iron and oxidative stress were increased in the retinal ischemia‒reperfusion injury model, resulting in ferroptosis and tissue damage. Deferoxamine protects the structural and functional soundness of the retina by inhibiting ferroptosis through the simultaneous inhibition of hemochromatosis, the initiation of transferrin, and the degradation of ferritin and activating the antioxidant capacity of the System Xc-GSH-GPX4 pathway.

Abstract Background Chronic obstructive pulmonary disease (COPD) represents a prevalent ailment, progressively surging within the ranks of coal mine laborers. The current study endeavors to elucidate the effects of dust exposure and smoking on COPD incidence amongst coal mine workers, while concurrently devising preventive strategies for this affliction. Method A nested case–control study was conducted encompassing 1,416 participants aged ≥ 18 years, spanning the duration from (2017–2018) until 2020. A meticulous matching process yielded a cohort of 708 COPD patients, each paired with a control subject, forming a harmonious 1:1 ratio. Multiple logistic regression analysis was employed to scrutinize the associations between smoking, dust exposure with COPD among coal workers. Results The COPD prevalence within the cohort of coal workers under investigation amounted to 22.66%, with an accompanying incidence density of 0.09/person-year. Following meticulous adjustment for confounding variables, it was discerned that cumulative dust exposure within the range of 47.19 ~ (OR: 1.90, 95% CI: 1.05, 3.44), 101.27 ~ (OR: 1.99, 95% CI: 1.17, 3.39), as well as smoking indices of 72 ~ (OR: 1.85, 95% CI: 1.19, 2.88), 145 ~ (OR: 1.74, 95% CI: 1.17, 2.61), 310 ~ (OR: 1.85, 95% CI: 1.23, 2.77) engender an escalated vulnerability to COPD among coal workers. Furthermore, interaction analysis discerned an absence of both multiplicative and additive interactions between dust exposure, smoking, and COPD occurrence amidst coal workers. Conclusion Dust exposure and smoking were unequivocally identified as precipitating risk factors for COPD incidence within the population of coal workers, albeit devoid of any discernible interaction between these two causal agents.

Abstract In the post‐lithium‐ion battery era, calcium‐ion batteries (CIBs) have aroused extensive attention because of their strong cost competitiveness, low standard redox potentials, and high safety. However, the related research is progressing slowly due to the constraints of the development of electrode materials. The large ionic radius of Ca2+ especially increases the challenge to design cathode materials for reversible Ca2+ uptake/removal. Despite the inspiring achievements, various challenges still need to be further resolved. Here, this review systematically summarizes the recent advances in CIB cathode materials, including Prussian blue and its analogues, metal oxides, metal chalcogenides, polyanionic compounds, and organic materials. We first provide a brief introduction to CIBs and compare their advantages with other battery technologies. Then, preparation methods are introduced, and breakthrough investigations are highlighted. Finally, some possible research directions are discussed to promote the development of this emerging battery technology.

Abstract Analyzing highly individual-specific genomic data to understand genetic interactions in cancer development is still challenging, with significant implications for the discovery of individual biomarkers as well as personalized medicine. With the rapid development of deep learning, graph neural networks (GNNs) have been employed to analyze a wide range of biomolecular networks. However, many neural networks are limited to black box models, which are only capable of making predictions, and they are often challenged to provide reliable biological and clinical insights. In this research, for sample-specific networks, a novel end-to-end hierarchical graph neural network with interpretable modules is proposed, which learns structural features at multiple scales and incorporates a soft mask layer in extracting subgraphs that contribute to classification. The perturbations caused by the input graphs' deductions are used to evaluate key gene clusters, and the samples are then grouped into classes to produce both sample- and stage-level explanations. Experiments on four gene expression datasets from The Cancer Genome Atlas (TCGA) show that the proposed model not only rivals the advanced GNN methods in cancer staging but also identifies key gene clusters that have a great impact on classification confidence, providing potential targets for personalized medicine.

Abstract Electrocatalytic urea synthesis is an emerging alternative technology to the traditional energy-intensive industrial urea synthesis protocol. Novel strategies are urgently needed to promote the electrocatalytic C–N coupling process and inhibit the side reactions. Here, we report a CuWO4 catalyst with native bimetallic sites that achieves a high urea production rate (98.5 ± 3.2 μg h−1 mg−1 cat) for the co-reduction of CO2 and NO3 − with a high Faradaic efficiency (70.1 ± 2.4%) at −0.2 V versus the reversible hydrogen electrode. Mechanistic studies demonstrated that the combination of stable intermediates of *NO2 and *CO increases the probability of C–N coupling and reduces the potential barrier, resulting in high Faradaic efficiency and low overpotential. This study provides a new perspective on achieving efficient urea electrosynthesis by stabilizing the key reaction intermediates, which may guide the design of other electrochemical systems for high-value C–N bond-containing chemicals.

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

Terrestrial ecosystems play a pivotal role in the global carbon sequestration process, and their photosynthetic capacity is highly susceptible to fluctuations in climate conditions. In 2022, the Yangtze River Basin (YRB) in China experienced an extensive and severe compounded heat and drought event. Compared with the past two decades, our results revealed that the temperature increased by approximately 0.78 ± 0.45 °C and precipitation decreased by about 45.20 ± 30.10 mm from July to October 2022 over the whole YRB. Region I (west from the Sichuan Basin and east to the easternmost of the basin) experienced a more severe temperature increase (0.98 ± 0.35 °C) and precipitation decrease (−60.27 ± 23.75 mm) compared to the other regions in the YRB. Changes in temperature and precipitation resulted in an increase of 0.14 ± 0.06 kPa in vapor pressure deficit (VPD) and a decrease of 5.28 ± 2.09 m ^3 m ^−3 in soil moisture, ultimately leading to a total loss of 26.12 ± 16.09 Tg C (about −6.08% compared to the 2001–2021 mean) in gross primary productivity (GPP) of July to October in 2022. It is noteworthy that broadleaf forests, which comprise 12.03% of the natural vegetation in region I, contributed only 6.46% of the GPP loss between July and October compared to other vegetation types, showing greater resistance to this climate event. Our findings from multiple linear regressions highlight that high temperatures and reduced soil moisture together contribute up to 94% photosynthesis loss in July–October in natural vegetation in region I, while the contribution of reduced VPD is minimal. In the future, we will further explore the impacts of compound heat and drought events on the coupled carbon and water cycles across different ecosystems, in order to better understand the ecosystem response mechanisms to extreme climates.

In this study, we developed a novel wireless, passive pressure-sensing method functional at cryogenic temperatures (−196 °C). The currently used pressure sensors are inconvenient and complicated in cryogenic environments for their weak low-temperature tolerances and long wires for power supply and data transmission. We propose a novel pressure-sensing method for cryogenic applications by only using low-temperature-tolerant passive devices. By innovatively integrating a magnetoresistor (MR) on a backscattering antenna, the pressure inside a cryogenic environment is transferred to a wirelessly obtainable return loss. Wireless passive measurement is thus achieved using a backscattering method. In the measurement, the pressure causes a relative displacement between the MR and a magnet. The MR’s resistance changes with the varied magnetic field, thus modulating the antenna’s return loss. The experimental results indicate that our fabricated sensor successfully identified different pressures, with high sensitivities of 4.3 dB/MPa at room temperature (24 °C) and 1.3 dB/MPa at cryogenic temperature (−196 °C). Additionally, our method allows for simultaneous wireless readings of multi sensors via a single reading device by separating the frequency band of each sensor. Our method performs low-cost, simple, robust, passive, and wireless pressure measurement at −196 °C; thus, it is desirable for cryogenic applications.

Abstract Generally, long wavelength absorbed near‐infrared II (NIR‐II) dyes have a low fluorescence efficiency in aggregate states for aggregate‐caused quenching effect, simultaneously enhancing efficiency and extending absorption is a challenging issue for NIR‐II dyes. Here, three benzo[1,2‐c:4,5‐c']bis[1,2,5]thiadiazole (BBT) derivatives (TPA‐BBT, FT‐BBT, and BTBT‐BBT) are used to clarify fluorescence quenching mechanisms. When the BBT derivatives are doped into a small molecule matrix, they show quite different fluorescence behaviors. Structure‐distorted TPA‐BBT displays fluorescence quenching originating from short‐range exchange interaction, while FT‐BBT and BTBT‐BBT with a co‐planar‐conjugated backbone exhibit concentration‐dependent quenching processes, namely changing from long‐range dipole‐dipole interaction to exchange interaction, which could be majorly ascribed to large spectral overlap between absorption and emission. By precisely tuning doping concentration, both FT‐BBT and BTBT‐BBT nanoparticles (NPs) present the optimal NIR‐II fluorescence brightness at ∼2.5 wt% doping concentration. The doped NPs have good biocompatibility and could be served as fluorescence contrast agents for vascular imaging with a high resolution under 980‐nm laser excitation. Those paradigms evidence that molecular doping can promote fluorescence efficiency of long wavelength‐absorbed NIR‐II fluorophores via suppressing long‐range energy migration.

Dendrobium officinale polysaccharides (DOPs) are important active polysaccharides found in Dendrobium officinale, which is commonly used as a conventional food or herbal medicine and is well known in China. DOPs can influence the composition of the gut microbiota and the degradation capacity of these symbiotic bacteria, which in turn may determine the efficacy of dietary interventions. However, the necessary analysis of the relationship between DOPs and the gut microbiota is lacking. In this review, we summarize the extraction, structure, health benefits, and related mechanisms of DOPs, construct the DOPs-host axis, and propose that DOPs are potential prebiotics, mainly composed of 1,4-β-D-mannose, 1,4-β-D-glucose, and O-acetate groups, which induce an increase in the abundance of gut microbiota such as Lactobacillus, Bifidobacterium, Akkermansia, Bacteroides, and Prevotella. In addition, we found that when exposed to DOPs with different structural properties, the gut microbiota may exhibit different diversity and composition and provide health benefits, such as metabolism regulations, inflammation modulation, immunity moderation, and cancer intervention. This may contribute to facilitating the development of functional foods and health products to improve human health.

Organic photothermal materials excited by near‐infrared (NIR) light display promising applications in biomedicine, optoelectronic devices, water purification, and so on. However, the most NIR responsive organic photothermal materials are in the mire of laborious synthesis, high cost, and limited functions. The newly emerging charge‐transfer complexes (CTCs) are promising photothermal materials to solve the issues and are receiving much attention. Compared with traditional photothermal agents, CTCs possess strong NIR absorption, high photo‐to‐thermal conversion efficiency, simple synthesis, and function‐directed material design. Herein, the latest advances in NIR‐excited CTCs for photothermal agents are systematically summarized. First, the basic structure–performance relationships are introduced. Then, several important factors affecting the photothermal properties of the CTCs are discussed from the sight of photophysics, and a comprehensive comparison is made among the nanoparticle systems. Finally, organic photothermal CTCs are highlighted as a multifunctional platform for applications and the perspective is given.

Background. Pancreatic ductal adenocarcinoma (PDAC) is a devastating cancer, and the therapy options for PDAC remain restricted. The distinctive tumor immunological microenvironment (TIME) of PDAC, comprising a high number of stromal cells and a limited infiltration of cytotoxic T lymphocytes (CTLs), rendered immunotherapy ineffective. The protein level of ubiquitin-specific protease 43 (USP43) was a prognostic predictor in numerous cancers; however, its function in PDAC is limited. This article focuses on the influence of USP43 expression on PDAC prognosis and TIME alteration. Methods. Based on TCGA database and tissue microarray staining, the expression of USP43 in PDAC was evaluated. The association between USP43 and prognosis was then investigated using tissue samples and online databases. In PDAC tumor tissues, the correlation between USP43 expression and clinicopathological characteristics, immune cell infiltration, and prognosis was investigated. The expression of USP43 in PDAC cell lines was evaluated using quantitative polymerase chain reaction. Using a cell counting kit-8 (CCK-8) and a cell colony formation test, the viability of the cells was determined. On the basis of online databases and tissue samples, the link between USP43 and immune cell infiltration around PDAC was also examined. For statistical analyses, the software GraphPad, R, and SPSS 26.0 were utilized. Results. The expression of USP43 was considerably higher in PDAC compared to normal pancreatic tissue in both the TCGA database and the tissue microarrays of PDAC patients (P

Urban temperature increase brings a challenge to public health, so urban warming has been widely concerned. Within the central area of Shenyang, a 3 × 3 fishnet with nine grids was built to analyze land surface temperature (LST) and frontal area index (FAI) variations based on the local climate zone (LCZ) classification and to explore relationships among them to generate implications for using wind for urban cooling. The results indicate that LST in the 4# grid (central grid) was the highest (35.11 °C) among the nine grids. In general, a higher LST occurred in the grid with a larger building area and vice versa. LCZ-G underwent the largest temperature reduction among the 17 LCZ types. LCZ-2 had the highest LST, while the LCZ-1 had the lowest LST among the three high and intensive building types, except for the LST in the 2# and 4# grids. The FAI in Shenyang decreased from the center to the surroundings. The FAI value was greatest in the 4# grid and the lowest was in the 2# and 8# grids under the prevailing wind of summer and winter. The FAI variations suggested that prevailing SW, SSW, and S winds in summer were difficult to penetrate the central urban area, and the wind cooling effect could not perform. The prevailing NEN and EEN winds in winter could enter the central urban area, enhancing the wind cooling effect, while it was a disadvantage in winter. Overall, there was a significant positive relationship among LST, FAI, and area of LCZ-building.

In order to study the role of metal sodium in the spray pyrolysis of biomass tar, this paper designs a sodium-containing naphthalene pyrolysis system (NSS) and a pure naphthalene pyrolysis system (PNS) using naphthalene as the carbon source and sodium chloride as the sodium metal donor for comparison. This enables an exploration of the effect of sodium on the initial nucleation of carbon fumes formed by naphthalene pyrolysis using reaction molecular dynamics (ReaxFF MD). The simulation results show that NSS undergoes pyrolysis reactions earlier and faster than PNS at the same temperature. Simulated at 3250 K temperature for 2 ns, the naphthalene pyrolysis consumption rate of the NSS was faster than that of the PNS, and the addition of sodium atoms during the condensation process provided more active sites and accelerated the condensation of macromolecular products. Moreover, Na+ and carbon rings form a Na+-π structure to promote the bending of graphite lamellae to facilitate the formation of carbon nuclei. Molecular dynamics simulations were used to simulate the formation of carbon nuclei during the initial stage of naphthalene pyrolysis, revealing that the mechanism of sodium salt catalyzed the acceleration of organic matter pyrolysis from a microscopic visualization perspective.

The influence of urbanization on the frequent winter aerosol pollution events in Northeast China is not fully understood. The Weather Research and Forecasting Model with Chemistry (WRF–Chem) coupled with urban canopy (UC) models was used to simulate the impact of urbanization on an aerosol pollution process in the Central Liaoning city cluster (CLCC), China. To investigate the main mechanisms of urban expansion and UC on the winter atmospheric environment and the atmospheric diffusion capacity (ADC) in the CLCC, three simulation cases were designed using land-use datasets from different periods and different UC schemes. A comparative analysis of the simulation results showed that the land-use change (LU) and both LU and UC (LUUC) effects lead to higher surface temperature and lower relative humidity and wind speed in the CLCC by decreasing surface albedo, increasing sensible heat flux, and increasing surface roughness, with a spatial distribution similar to the distribution of LU. The thermal effect leads to an increase in atmospheric instability, an increase in boundary layer height and diffusion coefficient, and an increase in the ADC. The LU and LUUC effects lead to a significant decrease in near-surface PM2.5 concentrations in the CLCC due to changes in meteorological conditions and ADC within the boundary layer. The reduction in surface PM2.5 concentrations due to the LU effect is stronger at night than during daytime, while the LUUC effect leads to a greater reduction in surface PM2.5 concentrations during the day, mainly due to stronger diffusion and dilution caused by the effect of urban turbulence within different levels caused by the more complex UC scheme. In this study, the LU and LUUC effects result in greater thermal than dynamic effects, and both have a negative impact on surface PM2.5 concentrations, but redistribute pollutants from the lower urban troposphere to higher altitudes.

Abstract Yaks are typical plateau-adapted animals, however the microvascular changes and characteristics in their lungs after birth are still unclear. Pulmonary microvasculature characteristics and changes across age groups were analysed using morphological observation and molecular biology detection in yaks aged 1, 30 and 180 days old in addition to adults. Results: Our experiments demonstrated that yaks have fully developed pulmonary alveolar at birth but that interalveolar thickness increased with age. Immunofluorescence observations showed that microvessel density within the interalveolar septum in the yak gradually increased with age. In addition, transmission electron microscopy (TEM) results showed that the blood–air barrier of 1-day old and 30-days old yaks was significantly thicker than that observed at 180-days old and in adults (P

BackgroundCoronavirus disease 2019 (COVID-19) significantly impacts physical, psychological, and social functioning and reduces quality of life, which may persist for at least 6 months. Given the fact that COVID-19 is a highly infectious disease and therefore healthcare facilities may be sources of contagion, new methods avoiding face-to-face contact between healthcare workers and patients are urgently needed. Telerehabilitation is the provision of rehabilitation services to patients at a distance via information and communication technologies. However, high-quality evidence of the efficacy of telerehabilitation for COVID-19 is still lacking. This meta-analysis aimed to investigate the efficacy of telerehabilitation for patients with and survivors of COVID-19.MethodsWe searched the Cochrane Library, EMBASE, Medline (via PubMed), PEDro, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform from January 1st, 2020 to April 30th, 2022 for randomized controlled trials published in English, which aimed to evaluate the efficacy of telerehabilitation vs. face-to-face rehabilitation, usual care, or no treatment for COVID-19. Methodological quality and overall evidence quality of the included studies were assessed. The statistical reliability of the data was quantified using the trial sequential analysis.ResultsSeven randomized controlled trials with eight comparisons were included and all of them were used for meta-analysis. The meta-analyses of absolute values showed the superiority of telerehabilitation over no treatment or usual care for dyspnea (Borg scale: mean difference = −1.88, −2.37 to −1.39; Multidimensional dyspnea-12: mean difference = −3.70, −5.93 to −1.48), limb muscle strength (mean difference = 3.29; 2.12 to 4.47), ambulation capacity (standardized mean difference = 0.88; 0.62 to 1.14), and depression (mean difference = −5.68; −8.62 to −2.74). Significant improvement in these variables persisted in the meta-analyses of change scores. No significant difference was found in anxiety and quality of life. No severe adverse events were reported in any of the included studies.ConclusionsModerate- to very low-quality evidence demonstrates that telerehabilitation may be an effective and safe solution for patients with and survivors of COVID-19 in dyspnea, lower limb muscle strength, ambulation capacity, and depression. Further well-designed studies are required to evaluate the long-term effects, cost-effectiveness, and satisfaction in larger samples.

Ozone pollution has been growing in the recent decade, becoming a critical urban environmental issue in China. However, Shenyang’s near-surface ozone concentration (ground to 100 m altitude) is of grave concern. To obtain the ozone concentration and the corresponding meteorological conditions from 1 October 2018, to 30 September 2019, we built observatory sites at low (≈15 m) and high (≈90 m) layers in Shenyang, northeast China. Then, we analyzed the temporal variation of ozone concentration and discussed the relationship between ozone concentration and the meteorological factors at low and high layers. Compared with the high layer, the ozone concentration in the low layer is chartered with an earlier peak and higher diurnal range. The ozone concentration in all seasons first peaked at a low-layer height, in early in winter (15:00) and late summer (17:00). Then, the peak at high-layer height lagged for behind 1–2 h, generally occurring between 17:00 and 19:00. The variations in ozone concentration at low and high layers differed in daytime and nighttime. The diurnal ranges of ozone concentrations at the low layer were higher than those at the high layer in the four seasons examined. Overall, ozone concentration correlated significantly with air temperature, having correlation coefficients of 0.814 (p < 0.05) in the low layer and 0.731 (p < 0.05) in the high layer. Inversely, it showed a weak correlation with relative humidity: 0.310 (p < 0.05) and 0.351 (p < 0.05) in the low and high layers, respectively. Also, the correlation coefficients with wind speed were meager at both layers. Generally, ozone pollution is not severe in Shenyang.

Traditional business process-extraction models mainly rely on structured data such as logs, which are difficult to apply to unstructured data such as images and videos, making it impossible to perform process extractions in many data scenarios. Moreover, the generated process model lacks analysis consistency of the process model, resulting in a single understanding of the process model. To solve these two problems, a method of extracting process models from videos and analyzing the consistency of process models is proposed. Video data are widely used to capture the actual performance of business operations and are key sources of business data. Video data preprocessing, action placement and recognition, predetermined models, and conformance verification are all included in a method for extracting a process model from videos and analyzing the consistency between the process model and the predefined model. Finally, the similarity was calculated using graph edit distances and adjacency relationships (GED_NAR). The experimental results showed that the process model mined from the video was better in line with how the business was actually carried out than the process model derived from the noisy process logs.

Abstract An AlInN/GaN superjunction fin‐gate high electron mobility transistor (SJFin‐HEMT) is proposed in this work. A superjunction region with GaN/AlInN/GaN/AlInN/GaN structure is defined between the gate and drain, and two‐dimensional‐hole‐gas/two‐dimensional‐electron‐gas/two‐dimensional‐hole‐gas/two‐dimensional‐electron‐gas (2DHG/2DEG/2DHG/2DEG) are respectively induced due to the polarization charges at the heterojunction interfaces. The 2DHGs and 2DEGs compensate each other, resulting a charge balanced superjunction in the gate‐drain spacing, thus inducing a uniform electric field distribution under off‐state maximizing the breakdown voltage. Additionally, because the current flows through both the 2DEGs, higher output current and lower on‐state resistance are observed in contrast to the conventional Fin‐HEMT. Simulation results show breakdown voltage of 2957 V (VGS = –6 V) and on‐state resistance of 0.31 mΩ·cm2 (VDS = 0.1 V, VGS = 0 V) for the SJFin‐HEMT, comparing with that of 241 V and 0.36 mΩ·cm2 for the conventional Fin‐HEMT.

Protein arginine methyltransferase 1 (PRMT1) can catalyze the protein arginine methylation by transferring the methyl group from S-adenosyl-L-methionine (SAM) to the guanidyl nitrogen atom of protein arginine, which influences a variety of biological processes including epithelial–mesenchymal transition (EMT) and EMT-mediated mobility of cancer cells. The upregulation of PRMT1 is involved in a diverse range of cancer, such as lung cancer, and there is an urgent need to develop novel and potent PRMT1 inhibitors. In this article, a series of 2,5-substituted furan derivatives and 2,4-substituted thiazole derivatives were designed and synthesized by targeting at the substrate arginine-binding site on PRMT1, and 10 compounds demonstrated significant inhibitory effects against PRMT1. Among them, the most potent inhibitor, compound 1r (WCJ-394), significantly affected the expression of PRMT1-related proteins in A549 cells and downregulated the expression of mesenchymal markers, by which WCJ-394 inhibited the TGF-β1-induced EMT in A549 cells and prevented the cancer cell migration. The current study demonstrated that WCJ-394 was a potent PRMT1 inhibitor, which could be used as the leading compound for further drug discovery.

Textured calcium caseinate extrudates are considered promising candidates in producing fish substitutes. This study aimed to evaluate how the moisture content, extrusion temperature, screw speed, and cooling die unit temperature of the high-moisture extrusion process affect the structural and textural properties of calcium caseinate extrudates. With an increase in moisture content from 60% to 70%, there was a decrease in the cutting strength, hardness, and chewiness of the extrudate. Meanwhile, the fibrous degree increased considerably from 1.02 to 1.64. The hardness, springiness, and chewiness showed a downward trend with the rise in extrusion temperature from 50 °C to 90 °C, which contributed to the reduction in air bubbles in the extrudate. Screw speed showed a minor effect on fibrous structure and textural properties. A low temperature (30 °C) in all cooling die units led to damaged structure without mechanical anisotropy, which resulted from fast solidification. These results show that the fibrous structure and textural properties of calcium caseinate extrudates can be effectively manipulated by adjusting the moisture content, extrusion temperature, and cooling die unit temperature.

Nap deprivation is regarded as a sleep loss for habitual nappers. The beneficial effects of napping and moderate-intensity aerobic exercise on the reduction in planning ability following nighttime sleep deprivation have been proven. However, it is still unknown whether it can improve the performance decline caused by daytime nap deprivation in habitual nappers. Seventy-four healthy adults who had a long-term habit of taking naps were assigned to three interventions after receiving nap deprivation: (1) Control group (no intervention); (2) Nap group (15-min sitting naps); (3) Exercise group (15-min aerobic exercise), in which subjective alertness, mood, fatigue, and task performance in objective alertness (Psychomotor Vigilance Task, PVT) and planning ability (the Tower of London Task) were measured. Results showed that nap deprivation negatively influenced some performance on the psychomotor vigilance (i.e., response times and 10% slowest response time) and planning ability (i.e., planning time). And acute moderate-intensity aerobic exercise improved psychomotor alertness (i.e., response times) and planning ability (i.e., execution accuracy, execution time), a 15-min sitting naps only alleviated subjective fatigue, whereas some performance (i.e., response times) deteriorated when no intervention was used. These findings suggested that acute moderate-intensity aerobic exercise has a better restorative effect on the reduced planning ability and objective alertness due to nap deprivation compared to sitting naps.

Transcutaneous electrical nerve stimulation (TENS) is a non-invasive therapeutic intervention that is typically used for many years to treat chronic pain in patients who are refractory to pain medications. However, evidence of the efficacy of TENS treatment for neuropathic pain is lacking in humans. To further understand the efficacy of TENS under various intervention conditions and illuminate the current circumstance and future research directions, we systematically reviewed animal studies investigating the efficacy of TENS in relieving pain in neuropathic pain rodent models. We searched the Cochrane Library, EMBASE, MEDLINE (via PubMed), and Web of Science and identified 11 studies. Two meta-analyses were performed. The first meta-analysis showed that a single TENS treatment was capable of temporarily ameliorating neuropathic pain when compared to control groups with a significant effect (standardized mean difference: 1.54; 95% CI: 0.65, 2.42; p = 0.0007; I2 = 58%). Significant temporary alleviation in neuropathic pain intensity was also observed in the meta-analysis of repetitive TENS (standardized mean difference: 0.85; 95% CI: 0.31, 1.40; p = 0.002; I2 = 75%). Subgroup analysis showed no effect of the timing of the application of TENS (test for subgroup difference, p = 0.47). Leave-one-out sensitivity analyses suggested that no single study had an outsized effect on the pooled estimates, which may partly prove the robustness of these findings. Other stratified analyses were prevented by the insufficient number of included studies. Overall, current data suggest that TENS might be a promising therapy to ameliorate neuropathic pain. However, the high risk of bias in the included studies suggests that cautions must be considered when interpreting these findings and it is not reasonable to directly generalize the results obtained from animal studies to clinical practice. Future studies should pay more attention to improving the quality of study design and reporting, thereby facilitating the understanding of mechanisms underlying TENS treatment, reducing more potentially unsuccessful clinical trials, and optimizing the efficacy of TENS for people with neuropathic pain.

Infarct size is associated with stroke severity in clinical studies, so reducing it has become an important target and research hotspot in the treatment of ischemic stroke. Some preclinical studies have shown transcranial direct current stimulation (tDCS) reduced infarct size and improved neurological deficit, but others have not found beneficial effects. Besides, the optimal pattern of tDCS for ischemic stroke remains largely unknown. To shed light on the current circumstance and future research directions, the systematic review evaluated the effect of different tDCS paradigms in reducing infarct size and improving neurological deficit in rodent models of ischemic stroke and assessed the methodological quality of current literature. We searched the MEDLINE (via PubMed), EMBASE, Web of Science, and Scopus from their inception to August 18, 2021, to identify studies evaluating the effects of tDCS in rodent models of ischemic stroke. Eight studies were included, of which seven studies were included in the meta-analysis. The results showed cathodal tDCS, rather than anodal tDCS, reduced infarct size mainly measured by tetrazolium chloride and magnetic resonance imaging (standardized mean difference: −1.13; 95% CI: −1.72, −0.53; p = 0.0002) and improved neurological deficit assessed by a modified neurological severity score (standardized mean difference: −2.10; 95% CI: −3.78, −0.42; p = 0.01) in an early stage of focal ischemic stroke in rodent models. Subgroup analyses showed effects of cathodal tDCS on infarct size were not varied by ischemia duration (ischemia for 1, 1.5, and 2 h or permanent ischemia) and anesthesia (involving isoflurane and ketamine). The overall quality of studies included was low, thus the results must be interpreted cautiously. Published studies suggest that cathodal tDCS may be a promising avenue to explore for augmenting rehabilitation from focal ischemic stroke. Considering the methodological limitations, it is unreliable to blindly extrapolate the animal data to the clinical practice. Future research is needed to investigate the mechanism of tDCS in a randomized and blinded fashion in clinically relevant stroke models, such as elderly animals, female animals, and animals with comorbidities, to find an optimal treatment protocol.

As a major public health problem, the prevalence of Acinetobacter baumannii (A. baumannii) infections in hospitals due to the pathogen’s multiple-antibiotic resistance has attracted extensive attention. We previously reported a series of 1,3-diamino-7H-pyrrolo[3,2-f]quinazoline (PQZ) compounds, which were designed by targeting Escherichia coli dihydrofolate reductase (ecDHFR), and exhibited potent antibacterial activities. In the current study, based on our molecular-modeling study, it was proposed that PQZ compounds may function as potent A. baumannii DHFR (abDHFR)-inhibitors as well, which inspired us to consider their anti-A. baumannii abilities. We further found that three PQZ compounds, OYYF-171, -172, and -175, showed significant antibacterial activities against A. baumannii, including multidrug-resistant (MDR) strains, which are significantly stronger than the typical DHFR-inhibitor, trimethoprim (TMP), and superior to, or comparable to, the other tested antibacterial agents belonging to β-lactam, aminoglycoside, and quinolone. The significant synergistic effect between the representative compound OYYF-171 and the dihydropteroate synthase (DHPS)-inhibitor sulfamethoxazole (SMZ) was observed in both the microdilution-checkerboard assay and time-killing assay, which indicated that using SMZ in combination with PQZ compounds could help to reduce the required dosage and forestall resistance. Our study shows that PQZ is a promising scaffold for the further development of folate-metabolism inhibitors against MDR A. baumannii.

The zinc finger protein (ZFP) family is one of plants’ most diverse family of transcription factors. These proteins with finger-like structural domains have been shown to play a critical role in plant responses to abiotic stresses such as drought. This study aimed to systematically characterize Triticum aestivum ZFPs (TaZFPs) and understand their roles under drought stress. A total of 9 TaC2H2, 38 TaC3HC4, 79 TaCCCH, and 143 TaPHD were identified, which were divided into 4, 7, 12, and 14 distinct subgroups based on their phylogenetic relationships, respectively. Segmental duplication dominated the evolution of four subfamilies and made important contributions to the large-scale amplification of gene families. Syntenic relationships, gene duplications, and Ka/Ks result consistently indicate a potential strong purifying selection on TaZFPs. Additionally, TaZFPs have various abiotic stress-associated cis-acting regulatory elements and have tissue-specific expression patterns showing different responses to drought and heat stress. Therefore, these genes may play multiple functions in plant growth and stress resistance responses. This is the first comprehensive genome-wide analysis of ZFP gene families in T. aestivum to elucidate the basis of their function and resistance mechanisms, providing a reference for precise manipulation of genetic engineering for drought resistance in T. aestivum.

Nowadays, a growing number of web services are offered in API marketplaces browsed by service developers or third-party registries. Under this situation, API marketplaces' users greatly rely on a search engine to find suitable web services. However, due to the fact that functional attributes of web services are usually described in short texts, the search engine-based discovery approach suffers from the semantic sparsity problem, which hinders the effect of service discovery. To address this issue, we propose a novel web service discovery approach using word embedding and Gaussian latent Dirichlet allocation (Gaussian LDA). Unlike most existing service discovery approaches, our approach first uses context information generated by word embedding to enrich the semantics of service descriptions and users' queries. Then, the enriched service description is loaded into the Gaussian LDA model to acquire service description representation. Finally, the services are ranked by considering the relevance between the extended user's query and service description representation. The experiments conducted on a real-world web service dataset and the results demonstrate that the proposed approach achieves superior effectiveness on web service discovery.

It is challenging for robots to improve their ability to pass through unstructured environments while maximizing motion performance in cities and factories. This paper presents an omnidirectional deformable wheeled robot based on a heterogeneous sensing system. We presented a novel structure with dual swing arms and six wheels. Moreover, the heterogeneous sensing system can perceive critical environmental data, such as friction and temperature, to assist the robot in executing different functions. In addition, a top-down ‘Order–Decision–Behaviour’ overall motion strategy is proposed based on the data acquisition. The strategy combines the key condition parameters with a kinetic model to integrate the robot’s movement, overcoming of obstacles, and mode switching. The robot is flexible and fast in moving mode and can overcome obstacles safely, reliably, and simply. This study describes the robot’s design, strategy, simulation, and experiments. Motion performance and strategy were investigated and evaluated in field environments.

Water oxidation is a vital anodic reaction for renewable fuel generation via electrochemical- and photoelectrochemical-driven water splitting or CO2 reduction. Ruthenium complexes, such as Ru-bda family, have been shown as highly efficient water-oxidation catalysts (WOCs), particularly when they undergo a bimolecular O-O bond formation pathway. In this study, a novel Ru(pda)-type (pda2– =1,10-phenanthroline-2,9-dicarboxylate) molecular WOC with 4-vinylpyridine axial ligands was immobilized on the glassy carbon electrode surface by electrochemical polymerization. Electrochemical kinetic studies revealed that this homocoupling polymer catalyzes water oxidation through a bimolecular radical coupling pathway, where interaction between two Ru(pda)–oxyl moieties (I2M) forms the O-O bond. The calculated barrier of the I2M pathway by density-functional theory (DFT) is significantly lower than the barrier of a water nucleophilic attack (WNA) pathway. By using this polymerization strategy, the Ru centers are brought closer in the distance, and the O-O bond formation pathway by the Ru (pda) catalyst is switched from WNA in a homogeneous molecular catalytic system to I2M in the polymerized film, providing some deep insights into the importance of third coordination sphere engineering of the water oxidation catalyst.

Abstract Zika virus (ZIKV) has evolved into a global health threat because of its causal link to congenital Zika syndrome. ZIKV infection of pregnant women may cause a spectrum of abnormalities in children. In the studies in Brazil, a large cohort of children with perinatal exposure to ZIKV is followed, and a spectrum of neurodevelopmental abnormalities is identified. In parallel, it is demonstrated that infection of the mouse neonatal brain by a contemporary ZIKV strain instead of an Asian ancestral strain can cause microcephaly and various abnormal neurological functions. These include defects in social interaction and depression, impaired learning and memory, in addition to severe motor defects, which are present in adult mice as well as in the prospective cohort of children. Importantly, although mouse brains infected later after birth do not have apparent abnormal brain structure, those mice still show significant impairments of visual cortical functions, circuit organization, and experience‐dependent plasticity. Thus, the study suggests that special attention should be paid to all children born to ZIKV infected mothers for screening of abnormal behaviors and sensory function during childhood.

This study investigated monthly variations of surface urban heat island intensity (SUHII) and the applicability of the local climate zones (LCZ) scheme for land surface temperature (LST) differentiation within three spatial contexts, including urban, rural and their combination, in Shenyang, China, a city with a monsoon-influenced humid continental climate. The monthly SUHII and LST of Shenyang were obtained through 12 LST images, with one in each month (within the period between 2018 and 2020), retrieved from the Thermal InfraRed Sensor (TIRS) 10 in Landsat 8 based on a split window algorithm. Non-parametric analysis of Kruskal-Wallis H test and a multiple pairwise comparison were adopted to investigate the monthly LST differentiations with LCZs. Overall, the SUHII and the applicability of the LCZ scheme exhibited spatiotemporal variations. July and August were the two months when Shenyang underwent strong heat island effects. Shenyang underwent a longer period of cool than heat island effects, occurring from November to May. June and October were the transition months of cool–heat and heat–cool island phenomena, respectively. The SUHII analysis was dependent on the definition of urban and rural boundaries, where a smaller rural buffering zone resulted in a weaker SUHI or surface urban cool island (SUCI) phenomenon and a larger urban area corresponded to a weaker SUHI or SUCI phenomenon as well. The LST of LCZs did not follow a fixed order, where in July and August, the LCZ-10 (Heavy industry) had the highest mean LST, followed by LCZ-2 (Compact midrise) and then LCZ-7 (Lightweight low-rise). In comparison, LCZ-7, LCZ-8 (Large low-rise) and LCZ-9 (Sparsely built) had the highest LST from October to May. The LST of LCZs varied with urban and rural contexts, where LCZ-7, LCZ-8 and LCZ -10 were the three built LCZs that had the highest LST within urban context, while LCZ-2, LCZ-3 (Compact low-rise), LCZ-8, LCZ-9 and LCZ-10 were the five built LCZs that had the highest LST within rural context. The suitability of the LCZ scheme for temperature differentiation varied with the month, where from July to October, the LCZ scheme had the strongest capability and in May, it had the weakest capability. Urban context also made a difference to the suitability, where compared with the whole study area (the combination of urban and rural areas), the suitability of built LCZs in either urban or rural contexts weakened. Moreover, the built LCZs had a higher level of suitability in an urban context compared with a rural context, while the land-cover LCZs within rural had a higher level of suitability.

Air pollution is a critical urban environmental issue in China; however, the relationships between air pollutants and ecological functional zones in urban areas are poorly understood. Therefore, we analyzed the spatiotemporal characteristics of four major air pollutants (particulate matter less than or equal to 2.5 µm (PM2.5) and 10 µm (PM10) in diameter, SO2, and NO2) concentrations over five ecological functional zones in Shenyang, Liaoning Province, at hourly, seasonal, and annual scales using data collected from 11 monitoring stations over 2 years. We further assessed the relationships between these pollutants and meteorological conditions and land-use types at the local scale. Peaks in PM, SO2, and NO2 concentrations occurred at 08:00–09:00 and 23:00 in all five zones. Daytime PM concentrations were highest in the industrial zone, and those of SO2 and NO2 were highest in residential areas. All four air pollutants reached their highest concentrations in winter and lowest in summer. The highest mean seasonal PM concentrations were found in the industrial zone, and the highest SO2 and NO2 concentrations were found in residential areas. The mean annual PM and SO2 concentrations decreased in 2017 in all zones, while that of NO2 increased in all zones excluding the cultural zone. The natural reserve zone had the lowest concentrations of all pollutants at all temporal scales. Pollutant concentrations of PM2.5, PM10, SO2, and NO2 were correlated with visibility, and their correlation coefficients are 0.675, 0.579, 0.475, and 0.477. Land coverage with buildings and natural vegetation negatively and positively influence air pollutant concentrations, respectively.

Studies on urban ventilation indicate that urban ventilation performance is highly dependent on urban morphology. Some studies have linked local-scale urban ventilation performance with the local climate zone (LCZ) that is proposed for surface temperature studies. However, there is a lack of evidence-based studies showing LCZ ventilation performance and affirming the reliability of using the LCZ classification scheme to demonstrate local-scale urban ventilation performance. Therefore, this study aims to analyse LCZ ventilation performances in order to understand the suitability of using the LCZ classification scheme to indicate local-scale urban ventilation performance. This study was conducted in Shenyang, China, with wind information at 16 weather stations in 2018. The results indicate that the Shenyang weather station had an annual mean wind speed of 2.07 m/s, while the mean wind speed of the overall 16 stations was much lower, only 1.44 m/s in value. The mean wind speed at Shenyang weather station and the 16 stations varied with seasons, day and night and precipitation conditions. The spring diurnal mean wind was strong with the speeds of 3.56 m/s and 2.21 m/s at Shenyang weather station and the 16 stations, respectively. The wind speed (2.21 m/s at Shenyang weather station) under precipitation conditions was higher than that (1.75 m/s at Shenyang weather station) under no precipitation conditions. Downtown ventilation performance was weaker than the approaching wind background, where the relative mean wind speed in the downtown area was only 0.53, much less than 1.0. The downtown ventilation performance also varied with seasons, day and night and precipitation conditions, where spring diurnal downtown ventilation performance was the weakest and the winter nocturnal downtown ventilation performance was the strongest. Moreover, the annual mean wind speed of the 16 zones decreased from the sparse, open low-rise zones to the compact midrise zones, indicating the suitability of using LCZ classification scheme to indicate local-scale urban ventilation performance. The high spatial correlation coefficients under different seasons, day and night and precipitation conditions, ranging between 0.68 and 0.99, further affirmed that LCZ classification scheme is also suitable to indicate local-scale urban ventilation performance, despite without the consideration of street structure like precinct ventilation zone scheme.

A novel recyclable surface-enhanced Raman scattering (SERS)-based immunoassay was demonstrated and exhibited extremely high sensitivity toward prostate specific antigen (PSA). The immunoassay, which possessed a sandwich structure, was constructed of multifunctional Fe3O4@TiO2@Au nanocomposites as immune probe and Ag-coated sandpaper as immune substrate. First, by adjusting the density of outside Au seeds on Fe3O4@TiO2 core-shell nanoparticles (NPs), the structure-dependent SERS and photocatalytic performance of the samples was explored by monitoring and degradating 4-mercaptobenzonic acid (4MBA). Afterwards, the SERS enhancement capability of Ag-coated sandpaper with different meshes was investigated, and a limit of detection (LOD), as low as 0.014 mM, was achieved by utilizing the substrate. Subsequently, the recyclable feasibility of PSA detection was approved by zeta potential measurement, absorption spectra, and SEM images and, particularly, more than 80% of SERS intensity still existed after even six cycles of immunoassay. The ultralow LOD of the recyclable immunoassay was finally calculated to be 1.871 pg/mL. Therefore, the recyclable SERS-based immunoassay exhibits good application prospects for diagnosis of cancer in clinical measurements.

Peste des petits ruminants is a highly contagious acute or subacute disease of small ruminants caused by the peste des petits ruminants virus (PPRV), and it is responsible for significant economic losses in animal husbandry. Vaccination represents the most effective means of controlling this disease, with virus-like particle (VLP) vaccines offering promising vaccine candidates. In this study, a PPRV VLP-based vaccine was developed using a baculovirus expression system, allowing for the simultaneous expression of the PPRV matrix (M), hemagglutinin (H), fusion (F) and nucleocapsid (N) proteins in insect cells. Immunization of mice and goats with PPRV VLPs elicited a robust neutralization response and a potent cellular immune response. Mouse studies demonstrated that VLPs induced a more robust IFN-γ response in CD4+ and CD8+ T cells than PPRV Nigeria 75/1 and recruited and/or activated more B cells and dendritic cells in inguinal lymph nodes. In addition, PPRV VLPs induced a strong Th1 class response in mice, as indicated by a high IgG2a to IgG1 ratio. Goat studies demonstrated that PPRV VLPs can induce the production of antibodies specific for F and H proteins and can also stimulate the production of virus neutralizing antibodies to the same magnitude as the PPRV Nigeria 75/1 vaccine. Higher amounts of IFN-γ in VLP-immunized animal serum suggested that VLPs also elicited a cellular immune response in goats. These results demonstrated that VLPs elicit a potent immune response against PPRV infection in small ruminants, making PPRV VLPs a potential candidate for PPRV vaccine development.