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Accurate segmentation and classification of nuclei in histology images is critical but challenging due to nuclei heterogeneity, staining variations, and tissue complexity. Existing methods often struggle with limited dataset variability, with patches extracted from similar whole slide images (WSI), making models prone to falling into local optima. Here we propose a new framework to address this limitation and enable robust nuclear analysis. Our method leverages dual-level ensemble modeling to overcome issues stemming from limited dataset variation. Intra-ensembling applies diverse transformations to individual samples, while inter-ensembling combines networks of different scales. We also introduce enhancements to the HoVer-Net architecture, including updated encoders, nested dense decoding and model regularization strategy. We achieve state-of-the-art results on public benchmarks, including 1st place for nuclear composition prediction and 3rd place for segmentation/classification in the 2022 Colon Nuclei Identification and Counting (CoNIC) Challenge. This success validates our approach for accurate histological nuclei analysis. Extensive experiments and ablation studies provide insights into optimal network design choices and training techniques. In conclusion, this work proposes an improved framework advancing the state-of-the-art in nuclei analysis. We will release our code and models to serve as a toolkit for the community.

Artificial intelligence (AI) holds significant promise in transforming medical imaging, enhancing diagnostics, and refining treatment strategies. However, the reliance on extensive multicenter datasets for training AI models poses challenges due to privacy concerns. Federated learning provides a solution by facilitating collaborative model training across multiple centers without sharing raw data. This study introduces a federated attention-consistent learning (FACL) framework to address challenges associated with large-scale pathological images and data heterogeneity. FACL enhances model generalization by maximizing attention consistency between local clients and the server model. To ensure privacy and validate robustness, we incorporated differential privacy by introducing noise during parameter transfer. We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19,461 whole-slide images of prostate cancer from multiple centers. In the diagnosis task, FACL achieved an area under the curve (AUC) of 0.9718, outperforming seven centers with an average AUC of 0.9499 when categories are relatively balanced. For the Gleason grading task, FACL attained a Kappa score of 0.8463, surpassing the average Kappa score of 0.7379 from six centers. In conclusion, FACL offers a robust, accurate, and cost-effective AI training model for prostate cancer pathology while maintaining effective data safeguards.

ABSTRACT Following two human infections with the H10N3 avian influenza virus (AIV) in 2021 and 2022, a third case was discovered in Yunnan, China, in 2024, raising concerns about the potential for future pandemics. Recent studies have indicated that novel H10N3 viruses are highly pathogenic in mice and can be transmitted between guinea pigs via respiratory droplets without prior adaptation. However, the biological characteristics of novel H10N3 in poultry have not been fully elucidated. Our findings revealed that H10 subtype AIVs are predominantly prevalent in waterfowl. Notably, H10N8 and H10N3 viruses that have infected humans were primarily isolated from chickens. For the first time, double basic hemagglutinin cleavage sites (motif PEIKQGR↓GL) were identified in novel H10N3 AIVs, which exhibit enhanced replication in chickens, and can be transmitted between chickens through direct contact and respiratory droplets. Animal experimental studies demonstrated that ducks are also susceptible to H10N3 viruses and that the virus is transmissible through direct contact, suggesting a greater risk of transmission and recombination. Serological studies conducted among poultry workers suggest that while the human population was largely naïve to H10N3 infection, sporadic and undetected human infections did occur, indicating a potential increasing trend. These data further emphasize the growing threat to public health posed by zoonotic H10N3 subtype AIVs.IMPORTANCEExposure to poultry in live poultry markets (LPMs) is strongly associated with human infection with avian influenza viruses (AIVs), with chickens being the most common species found in these markets in China. The prevalence of AIVs in chickens, therefore, increases the risk of human infection. Notably, the main host of the novel H10N3 virus has shifted from waterfowl to chickens, and the virus can be transmitted between chickens via respiratory droplets, posing a potential risk of a pandemic within poultry populations. The novel H10N3 virus also remains sensitive to ducks and can be transmitted through direct contact, which means a greater risk of transmission and recombination. Significantly, the human population remains largely naïve to H10N3 infection, but sporadic seropositivity among poultry workers indicates previous exposure to H10 subtype AIVs. Therefore, a comprehensive surveillance of the novel H10N3 viruses in poultry is imperative. Effective control of the virus within poultry populations could significantly reduce the risk of emerging human infections.

Spatially resolved transcriptomics enable comprehensive measurement of gene expression at subcellular resolution while preserving the spatial context of the tissue microenvironment. While deep learning has shown promise in analyzing SCST datasets, most efforts have focused on sequence data and spatial localization, with limited emphasis on leveraging rich histopathological insights from staining images. We introduce GIST, a deep learning-enabled gene expression and histology integration for spatial cellular profiling. GIST employs histopathology foundation models pretrained on millions of histology images to enhance feature extraction and a hybrid graph transformer model to integrate them with transcriptome features. Validated with datasets from human lung, breast, and colorectal cancers, GIST effectively reveals spatial domains and substantially improves the accuracy of segmenting the microenvironment after denoising transcriptomics data. This enhancement enables more accurate gene expression analysis and aids in identifying prognostic marker genes, outperforming state-of-the-art deep learning methods with a total improvement of up to 49.72%. GIST provides a generalizable framework for integrating histology with spatial transcriptome analysis, revealing novel insights into spatial organization and functional dynamics.

Objectives The objective of this study is to explore the relationship between loneliness and socioeconomic status and social networks in older adults with activity of daily living (ADL) disabilities in China and investigate people who are more likely to feel lonely.Design Cross-sectional study.Setting This study was conducted in six districts of Nantong, Jiangsu, China.Participants A total of 880 older adults with ADL disabilities who participated in long-term care insurance and had an ADL score of less than 40 were investigated by the convenient sampling method.Primary outcome measures The UCLA Loneliness Scale (V.3) was used to assess loneliness.Results Among 880 participants, the mean age was 80.64 years (SD 10.29) and 59.43% were females. The mean score of loneliness was 44.70 (SD=10.01), and the majority suffered from moderate (39.89%) or moderate to severe (40.11%) loneliness. Regression showed that lower loneliness was associated with being females (β=−1.534, 95% CI: −2.841 to –0.228), married (β=−3.554, 95% CI: −4.959 to –2.149), often communicating with children (β=−3.213, 95% CI: −4.519 to –1.908), having more than two friends (β=−5.373, 95% CI: −6.939 to –3.808) and receiving home-based rehabilitation once a day (β=−3.692, 95% CI: −5.642 to –1.743). Participants who lived in rural areas (β=1.926, 95% CI: 0.658 to 3.193) and were unemployed before retirement (β=4.691, 95% CI: 1.485 to 7.898) experienced higher loneliness for older adults with ADL disability. The classification and regression tree model showed fewer friends and communication with children sometimes, and living in rural areas felt more lonely.Conclusions The poorer socioeconomic status and social network among older adults with ADL disability perceived more loneliness. Attention should be paid to the loneliness status of such vulnerable people, particularly those with ADL disabilities living in rural areas and having fewer social networks.

Vaccination is crucial for the prevention and mitigation of avian influenza infections in China. The inactivated H7N9 vaccine, when administered to poultry, significantly lowers the risk of infection among both poultry and humans, while also markedly decreasing the prevalence of H7N9 detections. Highly pathogenic (HP) H7N9 viruses occasionally appear, whereas their low pathogenicity (LP) counterparts have been scarcely detected since 2018. However, these contributing factors remain poorly understood. We conducted an exploratory investigation of the mechanics via the application of comprehensive bioinformatic approaches. We delineated the Yangtze River Delta (YRD) H7N9 lineage into 5 clades (YRD-A to E). Our findings highlight the emergence and peak occurrence of the LP H7N9-containing YRD-E clade during the 5th epidemic wave in China’s primary poultry farming areas. A more effective control of LP H7N9 through vaccination was observed compared to that of its HP H7N9 counterpart. YRD-E exhibited a tardy evolutionary trajectory, denoted by the conservation of its genetic and antigenic variation. Our analysis of YRD-E revealed only minimal amino acid substitutions along its phylogenetic tree and a few selective sweep mutations since 2016. In terms of epidemic fitness, the YRD-E was measured to be lower than that of the HP variants. Collectively, these findings underscore the conserved evolutionary patterns distinguishing the YRD-E. Given the conservation presented in its evolutionary patterns, the YRD-E LP H7N9 is hypothesized to be associated with a reduction following the mass vaccination in a relatively short period owing to its lower probability of antigenic variation that might affect vaccine efficiency.

Abstract Background Drought can result in yield losses, the application of plant growth regulators is an effective measure to improve drought resistance and yield. The objective of the study was to explore the application potential of mepiquat chloride (MC) in regulating soybean yield and drought resistance. Methods In this study, a three-year field experiment was designed and combined with drought experiments to measure the yield of popularized varieties during 2021–2022 and drought-resistant and drought-sensitive varieties were selected, and planted in the field in 2023. Results MC increased the yield of HN84 and HN87 for two consecutive years from 2021 to 2022 and improved their physiological characteristics under field conditions. Under M200 treatment, the yield of HN84 increased by 6.93% and 9.46%, and HN87 increased by 11.11% and 15.72%. Different concentrations of MC have different effects on soybeans. The maximum increase of SOD, POD and proline in HN84 under M400 treatment reached 71.92%, 63.26% and 71.54%, respectively; the maximum increase of SOD, POD and proline in HN87 under M200 treatment reached 21.96%, 93.49% and 40.45%, respectively. In 2023, the foliar application of MC improved the physiological characteristics of HN44 and HN65 under drought-stress conditions. On the eighth day of drought treatment, compared to the drought treatment, the leaf and root dry weight of HN44 under M100 treatment increased by 17.91% and 32.76%, respectively; the dry weight of leaves and roots of HN65 increased by 20.74% and 29.29% under M200 treatment, respectively. MC also reduced malondialdehyde (MDA) content, decreased antioxidant enzyme activity and proline content. In addition, different concentrations of MC increased the chlorophyll fluorescence parameters (Fs, Fv/Fm, YII, and SPAD). In the field, the plant height of the two varieties decreased significantly, the yield increased, the number of two-grain and three-grain pods increased, and the stem length at the bottom and middle decreased with MC induction. Conclusions The application of 100–200 mg/L MC effectively improved drought resistance and increased yield. This study provided support for the rational application of MC in soybean production.

Collaborative flight formations represent a promising operational model, but the integration of multi-source information in manned interfaces often results in cognitive overload and reduced situation awareness. This study evaluates the effectiveness of intelligent auxiliary information presentation modes in enhancing personnel capabilities. Using a simulation-based collaborative flight formation system, four presentation modes with varying levels of information and dynamics were experimentally tested and evaluated across subjective dimensions (cognitive workload, situation awareness, and interface design) and objective dimensions (design task flow information load and operational task flow information load). The results indicate that Level 3 and Level 4 modes significantly reduced mental workload and improved practical operational ability compared to the original mode. Level 3 achieved the highest interface evaluation scores, while Level 4 demonstrated the lowest design task flow information load. Both modes significantly enhanced situation awareness. Altogether, Level 3 and Level 4 resulted in the most significant improvements in personnel capabilities. These findings provide valuable insights for optimizing interface design and improving situation awareness in collaborative flight formation tasks.

West Lake holds a significant position internationally. This article studies the spatial distribution, historical development, functions, and the lake–city spatial relationship of 81 West Lakes (WLs), as well as their landscape characteristics. The results indicate the following: (1) The overall spatial distribution of WLs is related to China’s history of water conservancy development. (2) The evolution of and functional changes in WLs are influenced by multiple factors such as politics, economy, and culture during different historical periods and are directly related to the will of local administrators. (3) The initial functions of WLs can be categorized into three types, primarily related to urban infrastructure. (4) In terms of spatial relationships, there are four types of spatial relationships between WLs and their water sources and three types of spatial relationships between WLs and cities, forming a common pattern of “Mountains/Hills(–Water)–WL(–Water)–Cities(–Water, River, Sea)” or “WL(–Water)–Cities(–Water, River, Sea)”. (5) The scenery of WLs comprises six elements, including natural basements, water conservancy facilities, human settlements, secularization, landscape architecture, and animal and human activities, all imbued with poetic cultural connotations. Furthermore, this study summarizes three causes of WLs’ scenery; excavates the historical wisdom of WLs in terms of a holistic approach, ecological techniques, dynamic management, and landscape esthetics; and subsequently proposes recommendations for lake ecological governance and landscape construction.

IntroductionCrown width (CW) is a significant variable of tree growth, but measuring crown width is laborious and time-consuming. Diameter at breast height (D) is a commonly used growth variable in crown width prediction. Here, a CW-D model was developed to estimate the crown width of larch.MethodsThe data of 1,515 larch trees were collected in Guandi mountain, the northern China. We chose linear function, quadratic function, and other form of base functions to develop the CW models, and we introduced non-linear least squares techniques (NLS), non-linear mixed-effect (NLME), and Bayesian method in modeling process. Because the data was from different plot, we added a plot level random effect in NLME method to predict the effect from environment. For equally comparing the Bayesian method with the NLME, we also added the plot level random effect to the Bayesian MCMC procedure. We selected Akaike's information criterion and logarithm likelihood to evaluate NLS and NLME models, and chose deviance information criterion and stationary test to test Bayesian method. These methods had another three same indicators (the determination coefficient, root mean square error, and mean absolute deviation) in model evaluation.Results and discussionHeteroskedasticity wasn't occurred in this study. The model I.2 (quadratic formula) showed a best fitting effect in each method, and Bayesian method with random effect was slightly superior than other methods. Therefore, the selected final model was quadratic function by Bayesian method with plot level random effect, this combination had the highest prediction accuracy in the larch trees' crown width estimation of Guandi mountain.

Abstract Background Rural settlements are undergoing significant changes under the rapid urbanisation, and understanding their evolution characteristics and surrounding land use will provide a basis for land spatial planning. This study takes Pingnan County, Fujian Province, China as study area, reveals the characteristics of spatial–temporal evolution and surrounding land use transition of settlements during 1985–2020 through landscape metrics, spatial “hot spot” analysis, scale classification statistics, rank-size model, Gini index, land use transition matrix. Results The results show that: (1) Concerning the size and morphological characteristics, the settlements have witnessed a considerable increase in number and scale while remaining stable in shape. (2) Regarding spatial distribution characteristics, the settlements became more evenly spread, forming three main hotspot clusters. (3) Concerning scale structure characteristics, there are significant differences in scale, growth rates, and polarisation of settlements; the polarisation of large settlements shifted from a marked divergence before 2010 to a more balanced trend after 2010. (4) The land use transition around settlements differed in buffer zones and periods. During 1985–2010, settlement expansion heavily depended on cropland, depleting nearby resources, with an increase of woodland and grassland. During 2010–2020, expansion integrated cropland, woodland, and grassland, with cropland growth mainly encroaching on woodland and grassland. Conclusions The study's findings are significant for optimising rural settlement structure in mountains and promoting sustainable land resource use.

Abstract Organoid models have provided a powerful platform for mechanistic investigations into fundamental biological processes involved in the development and function of organs. Despite the potential for image-based phenotypic quantification of organoids, their complex 3D structure, and the time-consuming and labor-intensive nature of immunofluorescent staining present significant challenges. In this work, we developed a virtual painting system, PhaseFIT (phase-fluorescent image transformation) utilizing customized and morphologically rich 2.5D intestinal organoids, which generate virtual fluorescent images for phenotypic quantification via accessible and low-cost organoid phase images. This system is driven by a novel segmentation-informed deep generative model that specializes in segmenting overlap and proximity between objects. The model enables an annotation-free digital transformation from phase-contrast to multi-channel fluorescent images. The virtual painting results of nuclei, secretory cell markers, and stem cells demonstrate that PhaseFIT outperforms the existing deep learning-based stain transformation models by generating fine-grained visual content. We further validated the efficiency and accuracy of PhaseFIT to quantify the impacts of three compounds on crypt formation, cell population, and cell stemness. PhaseFIT is the first deep learning-enabled virtual painting system focused on live organoids, enabling large-scale, informative, and efficient organoid phenotypic quantification. PhaseFIT would enable the use of organoids in high-throughput drug screening applications.

Urban agglomerations with a high economic activity and population density are key areas for carbon emissions and pioneers in achieving carbon peaking and the Sustainable Development Goals (SDGs). This study combines machine learning with an extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model to uncover the mechanisms driving carbon peaking disparities within these regions. It forecasts carbon emissions under different scenarios and develops indices to assess peaking pressure, reduction potential, and driving forces. The findings show significant carbon emission disparities among cities in the Yangtze River Delta, with a fluctuating downward trend over time. Technological advancement, population size, affluence, and urbanization positively impact emissions, while the effects of industrial structure and foreign investment are weakening. Industrially optimized cities lead in peaking, while others—such as late-peaking and economically radiating cities—achieve peaking only under the ER scenario. Cities facing population loss and demonstration cities fail to peak by 2030 in any scenario. The study recommends differentiated carbon peaking pathways for cities, emphasizing tailored targets, pathway models, and improved supervision. This research offers theoretical and practical insights for global urban agglomerations aiming to achieve early carbon peaking.

Newcastle disease virus (NDV), known as avian paramyxovirus-1, poses a significant threat to poultry production worldwide. Vaccination currently stands as the most effective strategy for Newcastle disease control. However, the mesogenic vaccine strain Mukteswar has been observed to evolve into a velogenic variant JS/7/05/Ch during poultry immunization. Here, we aimed to explore the mechanisms underlying virulence enhancement of the two viruses. Pathogenically, JS/7/05/Ch mediated stronger virulence and pathogenicity in vivo compared to Mukteswar. Comparative transcriptome analysis revealed 834 differentially expressed genes (DEGs), comprising 339 up-regulated and 495 down-regulated genes, in the spleen, and 716 DEGs, with 313 up-regulated and 403 down-regulated genes, in the thymus. Gene Ontology (GO) analysis indicated that these candidate targets primarily participated in cell and biological development, extracellular part and membrane composition, as well as receptor and binding activity. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis unveiled a substantial portion of candidate genes predominantly involved in cellular processes, environmental information processing, metabolism, and organismal systems. Additionally, five DEGs (TRAT1, JUP, LPAR4, CYB561A3, and CXCR5) were randomly identified through RNA-seq analysis and subsequently confirmed via quantitative real-time polymerase chain reaction (qRT-PCR). The findings revealed a marked up-regulation in the expression levels of these DEGs induced by JS/7/05/Ch compared to Mukteswar, with CYB561A3 and CXCR5 exhibiting significant increases. The findings corroborated the sequencing accuracy, offering promising research directions. Taken together, we comprehensively evaluated transcriptomic alterations in chicken immune organs infected by NDV strains of diverse virulence. This study establishes a basis and direction for NDV virulence research.

Drought is an important agricultural problem worldwide, which seriously affects the growth and yield of crops. To explore the effects of different degrees of drought on the soluble sugar content of soybeans, this study measured the soluble sugar content of two soybean cultivars at three growth stages under four levels of drought stress. The results showed that drought stress significantly affected the soluble sugar content, and there were differences among different growth stages and cultivars. At the seedling and flowering stages, the sucrose content of both Heinong44 and Heinong65 showed an unimodal trend and reached the maximum value at moderate drought. The increase rate was the highest in the leaves at the flowering stage, which increased by 36.18% and 25.79% compared with CK, respectively. The fructose and glucose contents were the highest during severe drought, and the fructose content increased the most in the leaves at the seedling stage, which increased by 18.05% and 17.67% compared with CK, respectively. The glucose content increased the most in the petioles at the flowering stage, reaching 40.66% and 35.24%. At the pod-filling stage, the three sugar contents of both Heinong44 and Heinong65 were the lowest at severe drought, and the sucrose and fructose contents decreased the most in the petioles, which decreased by 21.66% and 23.94%, 12.58% and 13.49% compared with CK, respectively. The glucose content decreased the most in the stems, which decreased by 11.72% and 9.66%. In addition, at each growth stage and drought treatment, the ratio of the soluble sugar content of Heinong44 was higher than that of Heinong65.

[Introduction] In response to the pain points of the operation and maintenance of the converter station, the design methods of the three-dimensional digitization and intelligent operation system are proposed, and the actual application is performed in the project. [Method] Firstly, the overall architecture, technical architecture, data architecture and functional modules of the system were explained, and by using digital twin technology, operation and maintenance services such as intelligent inspection, intelligent operation, and intelligent security were realized. Then the key technologies of the system were studied, including converter station modeling and refined processing, model and data fusion technology, and panoramic visualization technology, which realized the centralized operation and control of the whole site in the three-dimensional scenarios. Finally, the system was deployed at the project site, which greatly improved operation and maintenance efficiency and experience. [Result] The application of the system shows that the manual replacement rate of daily intelligent inspection projects reaches more than 80%, the on-site operation time can be reduced by 60%, and the operating risk management and control capabilities and safety levels are improved, saving 65% of working hours. [Conclusion] The three-dimensional digitalization and intelligent operation system of the converter station can effectively improve the accurate management of the equipment, and realize the cost reduction and benefit increasing of the operation and maintenance business.

Drought stress is one of the most important abiotic stresses which causes many yield losses every year. This paper presents a comprehensive review of recent advances in international drought research. First, the main types of drought stress and the commonly used drought stress methods in the current experiment were introduced, and the advantages and disadvantages of each method were evaluated. Second, the response of plants to drought stress was reviewed from the aspects of morphology, physiology, biochemistry and molecular progression. Then, the potential methods to improve drought resistance and recent emerging technologies were introduced. Finally, the current research dilemma and future development direction were summarized. In summary, this review provides insights into drought stress research from different perspectives and provides a theoretical reference for scholars engaged in and about to engage in drought research.

Abstract As an important bioactive molecule, nitric oxide (NO) can effectively alleviate the effects of drought stress on crops. However, it is still unclear whether it can increase the stress resistance of soybean. Therefore, in this study, our objective was to explore the effect of exogenous NO application on the physiological characteristics of soybean seedlings under drought stress. As test material, two soybean varieties, HN65 and HN44, were used, while sodium nitroprusside (SNP) of 100 μmol L−1, 200 μmol L−1, 500 μmol L−1, 1000 μmol L−1 served as an exogenous NO donor, and PEG-6000 as an osmotic regulator to simulate drought stress. The effects of irrigation with different SNP concentrations for different days on the physiological characteristics of the soybean seedlings under drought conditions were then investigated. The results obtained showed that the activities of antioxidant enzymes, osmotic regulator contents, as well as the abscisic acid and salicylic acid contents of the plant leaves increased with increasing SNP concentration and treatment time. However, we observed that excessively high SNP concentrations decreased the activities of key nitrogen metabolism enzymes significantly. This study provides a theoretical basis for determining a suitable exogenous NO concentration and application duration. It also highlights strategies for exploring the mechanism by which exogenous NO regulates crop drought resistance.

Amid global industrialization and urbanization, mountainous rural settlements, especially those in metropolitan fringe area, are experiencing significant spatial changes in location and scale. This study takes Pingnan County, Fujian Province, China, as an example. Utilizing land use data and employing methods including standard deviation ellipse, average nearest neighbor index, kernel density estimation, spatial hotspot detection, binary logistic regression model, and Geodetector, this study aims to scientifically identify the spatial pattern characteristics and influencing factors of its settlements. The results show that: (1) The spatial distribution of settlements in Pingnan County is biased toward the southern part of the county; the center of settlement's spatial distribution is located south of the junction of Gufeng Town and Pingcheng Town; the spatial distribution trend of settlements is north-east-southwest. Settlements are generally aggregated, and the aggregation degree of Gufeng Town is obviously lower than that of other towns. (2) The density distribution of settlements presents a “core-periphery” structure and a “north-south linear” structure in space; the spatial pattern characteristics show high-density, large patches in Gufeng Town, high-density, small patches in Changqiao Town, Tangkou Town and Gantang Town, and medium-density or low-density, small patches in other towns. (3) Settlement location is mainly affected by the elevation, distance to cultivated land, and distance to main roads, while settlement scale is mainly affected by slope, relief degree of land surface, and distance to urban centers. The interaction between these factors exhibits enhancement effects, with natural terrain and location conditions exerting the most prominent influence. These findings underscore the strong constraints posed by natural topography on mountainous rural settlements in metropolitan fringe areas, coupled with a more pronounced influence from socio-economic factors. The study's results hold significant implications for optimizing the layout of such settlements, guiding land spatial planning, and promoting rural revitalization.

H9N2 avian influenza viruses (AIVs) pose an increasing threat to the poultry industry worldwide and have pandemic potential. Vaccination has been principal prevention strategy to control H9N2 in China since 1998, but vaccine effectiveness is persistently challenged by the emergence of the genetic and/or antigenic variants. Here, we analysed the genetic and antigenic characteristics of H9N2 viruses in China, including 70 HA sequences of H9N2 isolates from poultry, 7358 from online databases during 2010–2020, and 15 from the early reference strains. Bayesian analyses based on hemagglutinin (HA) gene revealed that a new designated clade16 emerged in April 2012, and was prevalent and co-circulated with clade 15 since 2013 in China. Clade 16 viruses exhibited decreased cross-reactivity with those from clade 15. Antigenic Cartography analyses showed represent strains were classified into three antigenic groups named as Group1, Group2 and Group3, and most of the strains in Group 3 (15/17, 88.2%) were from Clade 16 while most of the strains in Group2 (26/29, 89.7%) were from Clade 15. The mean distance between Group 3 and Group 2 was 4.079 (95%CI 3.605–4.554), revealing that major switches to antigenic properties were observed over the emergence of clade 16. Genetic analysis indicated that 11 coevolving amino acid substitutions primarily at antigenic sites were associated with the antigenic differences between clade 15 and clade 16. These data highlight complexities of the genetic evolution and provide a framework for the genetic basis and antigenic characterization of emerging clade 16 of H9N2 subtype avian influenza virus.

The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field. However, a persistent issue remains unsolved during experiments: the interferential technical noises caused by systematic errors (e.g., temperature, reagent concentration, and well location) are always mixed up with the real biological signals, leading to misinterpretation of any conclusion drawn. Here, we reported a mean teacher-based deep learning model (DeepNoise) that can disentangle biological signals from the experimental noises. Specifically, we aimed to classify the phenotypic impact of 1108 different genetic perturbations screened from 125,510 fluorescent microscopy images, which were totally unrecognizable by the human eye. We validated our model by participating in the Recursion Cellular Image Classification Challenge, and DeepNoise achieved an extremely high classification score (accuracy: 99.596%), ranking the 2nd place among 866 participating groups. This promising result indicates the successful separation of biological and technical factors, which might help decrease the cost of treatment development and expedite the drug discovery process. The source code of DeepNoise is available at https://github.com/Scu-sen/Recursion-Cellular-Image-Classification-Challenge.

IntroductionDrought stress has gradually become a limiting factor for plant growth. Soybean, a crop with a higher water demand than other plants, is particularly sensitive to water deficits.MethodTo explore the effect of drought stress on soybean protein expression, we used drought-tolerant soybean genotype HeiNong44 (HN44) and sensitive soybean genotype HeiNong65 (HN65) as experimental materials, PEG-6000 as an osmotic regulator, and tandem mass tag (TMT) technology to identify the differential expression of soybean proteins.ResultsWe identified that 48 upregulated and 38 downregulated proteins in HN44 and 55 upregulated and 13 downregulated proteins in HN65.DiscussionKEGG analysis showed that these differentially expressed proteins were involved in carbohydrate metabolism, signal transduction, amino acid metabolism, lipid metabolism, and programmed cell death. Drought stress usually caused an increase in the activity of plant antioxidant enzymes, the obstruction of photosynthetic synthesis, and a significant change in the content of plant hormones. We found that HN44 responds to drought stress mainly through sugar decomposition, increased antioxidant enzyme activity and lipid metabolism. HN65 responds to drought stress mainly through ABA synthesis, increased antioxidant enzyme activity and amino acid metabolism. Our study also found that differential proteins in the starch and sucrose metabolic pathway play a key role in supplying energy and regulating osmotic potential.

Abstract Background The soybean is an important food crop worldwide. Drought during the first pod stage significantly affects soybean yield, and understanding the metabolomic and physiological changes in soybeans under drought stress is crucial. This study identified the differential metabolites in initial pod stage soybean leaves under polyethylene glycol-simulated drought stress, using ultra performance liquid chromatography and tandem mass spectrometry, and the physiological indexes related to drought resistance. Results Physiologically, drought resistance also generates enzyme and antioxidant activity; levels of superoxide dismutase, peroxidase, and catalase first increased and subsequently decreased, while those of soluble sugar, soluble protein, malondialdehyde, and proline content increased in both varieties. The contents of CAT, proline and soluble sugar in Heinong 44 (HN44) were higher than those in Heinong 65 (HN65), and the contents of MDA were lower than those in HN65. In metabolomics, the OPLS-DA model was used to screen different metabolites. KEGG analysis showed that the two varieties resisted drought through different ways. Amino acid metabolism and lipid metabolism play a key role in drought resistance of the two varieties, respectively. TCA cycle was one of the core pathways of drought resistance in two varieties. Changes in the content of l-Asparagine and citric acid may be one of the reasons for the difference in drought resistance between the two varieties. Conclusions We think that the reasons of drought resistance among soybean varieties are as follows: the main metabolic pathways are different under drought stress; the contents of metabolites in these metabolic pathways are different; some physiological indexes are different, such as MDA, CAT, proline content and so on. Our study enhances the understanding of the metabolomic soybean drought stress response and provides a reference for soybean drought resistance breeding.

IntroductionSoybean is the world’s most important cultivated crop, and drought can affect their growth and, eventually, yields. Foliar application of mepiquat chloride (MC) can potentially alleviate the damage caused by drought stress in plants; however, the mechanism of MC regulation of soybean drought response has not been studied.MethodsThis study investigated the mechanism of soybean drought response regulation by mepiquat chloride in two varieties of soybean, sensitive Heinong 65 (HN65) and drought-tolerant Heinong44 (HN44), under three treatment scenarios, normal, drought stress, and drought stress + MC conditions.Results and discussionMC promoted dry matter accumulation under drought stress, reduced plant height, decreased antioxidant enzyme activity, and significantly decreased malondialdehyde content. The light capture processes, photosystems I and II, were inhibited; however, accumulation and upregulation of several amino acids and flavonoids by MC was observed. Multi-omics joint analysis indicated 2-oxocarboxylic acid metabolism and isoflavone biosynthetic pathways to be the core pathways by which MC regulated soybean drought response. Candidate genes such as LOC100816177, SOMT-2, LOC100784120, LOC100797504, LOC100794610, and LOC100819853 were identified to be crucial for the drought resistance of soybeans. Finally, a model was constructed to systematically describe the regulatory mechanism of MC application in soybean under drought stress. This study fills the research gap of MC in the field of soybean resistance.

Fiber reinforcement is the most common method for modifying polylactic acid (PLA). However, poor compatibility between fibers and PLA, especially at high cellulose contents, can promote cellulose agglomeration in the continuous phase, which damages the mechanical properties of composite materials. To address these issues, bagasse cellulose (BC) was used as a substrate and bifunctional glycidyl methacrylate (GMA) was used as a reactive monomer for graft modification. GMA-modified BC (BC-GMA)/PLA composite materials with different particle sizes were prepared using a blending grafting method, and the influence of the type and content of BC-GMA on the mechanical properties of the composite materials was explored. During the grafting modification of BC, a longer reaction time was found to result in smaller BC particles and a higher degree of grafting. For BC-GMA, the degree of grafting reached 27.02% with a maximum thermal decomposition temperature of 359.31°C. Furthermore, the BC-GMA/PLA composite material had a greater relative crystallinity of PLA, indicating that BC-GMA was evenly dispersed in the continuous phase. This study demonstrates that grafting modification can successfully achieve high cellulose loading in composite materials and thus reduce the production costs of PLA-based packaging materials.

Self-healing shape memory polymers (SMPs) have considerablepotential in advanced manufacturing and biomedical fields. Polypyrrole (PPy) exhibits excellent photoconversion properties, which may be utilized in SMP formulation; however, its application in this regard has not been explored. In this study, PPy-filled polymer nanocomposites were prepared to investigate their shape memory and self-healing characteristics. First, poly(lactic acid) (PLA) and polycaprolactone (PCL) were blendedto form PLA/PCL shape memory matrices. An 80:20 PLA/PCL blend showed excellent triple-shape memory performance with shape recovery rates (Rr1, Rr2, and Rr3 Rr) of 92%, 87%, and 93%, respectively PPy nanoparticles were then incorporated into the blend as photothermal conversion fillers to develop photoresponsive SMPs. SMPs. The resulting PLA/PCL/PPy nanocomposites exhibited elevated surface temperatures during near-infrared (NIR) irradiation, thus demonstrating the photoconversion effect. In addition, these nanocomposites showed reversible triple-shape change behavior and excellent self-healing efficiencies upon NIR exposure, owing to the controllable melting and recrystallization of the PLA and PCL phases. Furthermore, the material properties of severed nanocomposites were restored after self-healing. These results, in addition to the biocompatibility and simple fabrication process of these materials, therefore demonstrate the potential utility of PPy-filled SMPs in several applications, including soft robotics and biomedical devices.

In this study, the complete mitogenome of Grapsus albolineatus (Lamarck, 1818) (Crustacea: Grapsoidea) was sequenced. The mitogenome of G. albolineatus was a circular molecule with 15,578 bp length. Its nucleotide composition was 26.81% A, 16.37% G, 34.51% T, and 22.31% C. It comprised 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA), and two ribosomal RNA (rRNA). All PCGs were initiated by ATN codons, except for the atp8 and nad1 genes. Ten PCGs used a common stop codon of TAA or TAG, and the other three ended with a truncated stop codon (a single stop nucleotide T). Phylogenetic analysis revealed that G. albolineatus was closely related to species from the genera Pachygrapsus and Metopograpsus.

In the crowded metro station, it is important to forecast the changes of environmental parameters for the normal operation of metro and the safety of passengers in the future. Artificial Neural Network (ANN) has a good performance on processing time series data. In order to accurately predict environmental parameters, this paper uses ANN method to build the forecasting model of environmental parameters. The forecasting model uses the external environment parameters of the station as input variables. Finally, the accuracy of the model is verified by the field data collected from the metro station. The results show that the mean relative error of the proposed method is within 10%. The forecasting model based on ANN in this paper can accurately forecast the internal environment parameters of the metro station in the future period and is of great significance of emergency prevention and decision-making.

Soybeans are an important economic crop. As the most widely used growth regulator globally, the molecular mechanism of mepiquat chloride (DPC) in soybean remains unknown. In this study, RNA sequencing technology combined with ultra-performance liquid chromatography and tandem mass spectrometry were used to analyze the changes in the leaf transcriptome and metabolomics of soybean leaves at the seedling stage under DPC stress. The results showed that differentially expressed genes related to photosynthesis and cell wall synthesis were significantly downregulated at the transcriptional level. In addition, the syntheses of gibberellin, zeatin, brassinolide, and other plant hormones were inhibited in the signal transduction pathway of plant hormones, thereby inhibiting plant growth. In contrast, at the metabolic level, the expression levels of flavonoid differential metabolites were significantly increased, and the proportions of flavonoids in the two varieties were 61.5 and 66%, respectively. The combined analysis of transcriptome and metabolomics showed that the differential expressed genes and metabolites were mainly enriched in the isoflavonoid biosynthesis and flavonoid biosynthesis pathways. Principally, DPC inhibited plant growth but improved drought resistance. Our study is the first to report the molecular mechanism of DPC regulation in soybean, providing useful insights into the rational application of DPC in soybean.

Innate defense behaviours in animals in response to approaching threats are mostly studied in response to visual stimuli. Here, the authors show that looming sounds elicit stereotypical sequential defensive reactions that require the auditory cortex, superior colliculus and the striatum.

Abstract Background Pharyngeal fricative is one typical compensatory articulation error of cleft palate speech. It passively influences daily communication for people who suffer from it. The automatic detection of pharyngeal fricatives in cleft palate speech can provide information for clinical doctors and speech-language pathologists to aid in diagnosis. Results This paper proposes two features (CSIFs: correlation of signals in independent frequency bands; OSPP: octave spectrum prominent peak) to detect pharyngeal fricative speech. CSIFs feature is proposed to detect the distribution characteristics of frequency components in pharyngeal fricative speech caused by the changed place of articulation and movement of articulators. While OSPP is presented to reflect the concentration degree of prominent peak which is closely related to the place of articulation in pharyngeal fricative, both features are investigated to relate to the altered production process of pharyngeal fricative. To evaluate the capability of these two features to detect pharyngeal fricative, we collected a speech database covering all the types of initial consonants in which pharyngeal fricatives occur. In this detection task, the classifier used to discriminate pharyngeal fricative speech and normal speech is based on ensemble learning. Conclusion The detection accuracy obtained with CSIFs and OSPP features ranges from 83.5 to 84.5% and from 85 to 87%, respectively. When these two features are combined, the detection accuracy for pharyngeal fricative speech ranges from 88 to 89%, with an AUC (area under the receiver operating characteristic curve) value of 93%.

Subtype classification is critical in the treatment of gliomas because different subtypes lead to different treatment options and postoperative care. Although many radiological- or histological-based glioma classification algorithms have been developed, most of them focus on single-modality data. In this paper, we propose an innovative two-stage model to classify gliomas into three subtypes (i.e., glioblastoma, oligodendroglioma, and astrocytoma) based on radiology and histology data. In the first stage, our model classifies each image as having glioblastoma or not. Based on the obtained non-glioblastoma images, the second stage aims to accurately distinguish astrocytoma and oligodendroglioma. The radiological images and histological images pass through the two-stage design with 3D and 2D models, respectively. Then, an ensemble classification network is designed to automatically integrate the features of the two modalities. We have verified our method by participating in the MICCAI 2020 CPM-RadPath Challenge and won 1st place. Our proposed model achieves high performance on the validation set with a balanced accuracy of 0.889, Cohen’s Kappa of 0.903, and an F1-score of 0.943. Our model could advance multimodal-based glioma research and provide assistance to pathologists and neurologists in diagnosing glioma subtypes. The code has been publicly available online at https://github.com/Xiyue-Wang/1st-in-MICCAI2020-CPM.

Soybeans are the main sources of oil and protein for most of the global population. As the population grows, so does the demand for soybeans. However, drought is a major factor that limits soybean production. Regulating soybean response to drought stress using mepiquat chloride (MC) is a feasible method; however, its mechanism is still unclear. This study used PEG-6000 to simulate drought stress and quantitative proteomic techniques to reveal changes in Heinong44 (HN44) and Heinong65 (HN65) subjected to drought following the application of 100 mg/L of MC. The results showed that SOD in HN44 did not change significantly but decreased by 22.61% in HN65 after MC pretreatment, and MDA content decreased by 22.75% and 21.54% in HN44 and HN65, respectively. Furthermore, MC improved the GSH–ASA cycle and simultaneously promoted the Calvin cycle process to enable the plant to maintain a certain carbon assimilation rate under osmotic stress. In addition, MC upregulated some proteins during gluconeogenesis and starch metabolism and increased soluble sugar content by 8.41% in HN44. MC also reduced ribosomal protein abundance, affecting translation and amino acid metabolism. In summary, MC improved GSH–ASA cycle and Calvin cycle under stress to alleviate oxidative damage and maintain crop growth. Our study is the first to report the mechanism of MC regulation in soybean under osmotic stress, providing new insights for the rational application of MC in soybean.

Nitric oxide (NO) plays a significant role in plant drought resistance. However, the effects of the exogenous application of NO to crops under drought stress vary within and among species. In this study, we explored the influence of exogenous sodium nitroprusside (SNP) on the drought resistance of soybean leaves in the full flowering stage using two varieties: drought-tolerant HN44 and non-drought-tolerant HN65. Spraying SNP on soybean leaves at the full flowering period under drought stress improved the NO content in soybean leaves. The activities of nitrite reductase (NiR) and nitrate reductase (NR) in leaves were affected by NO inhibition. The activity of antioxidant enzymes in leaves increased with the extension of SNP application time. Contents of osmomodulatory substances, including proline (Pro), soluble sugar (SS), and soluble protein (SP) increased gradually with the extension of SNP application time. The malondialdehyde (MDA) content decreased as the NO content increased, thus reducing membrane system damage. Overall, spraying SNP reduced damage and improved the ability of soybean to cope with drought. This study explored the physiological changes of SNP soybean under drought stress and provided theoretical basis for improving drought-resistant cultivation of soybean.

Soybean is an important cash crop in the world, and drought is the main reason for the loss of soybean plants productivity, with drought stress during the most water-sensitive flowering period of soybeans. In this article, drought-tolerant variety Heinong 44 (HN44) and drought-sensitive variety Heinong 65 (HN65) were used as experimental materials. Drought treatment was carried out at the early flowering stage. The method of controlling soil moisture content was used to simulate different degrees of drought, and the physiological changes of these two varieties of soybean under different soil moisture contents were studied. The results showed that with a decrease in soil moisture content, the content of malondialdehyde (MDA) in soybean leaves increased significantly; the activities of peroxidase (POD), catalase (CAT), and ascorbic acid peroxidase (APX) increased first and then decreased; the content of proline, soluble sugar, and soluble protein increased; and the total antioxidant capacity (T-AOC) increased significantly. When the soil moisture content was 15.5%, the degree of membrane lipid peroxidation, osmotic regulatory substances, antioxidant enzyme activity, and T-AOC increased the most, and the decrease in drought-tolerant variety HN44 was significantly less than that of drought-sensitive variety HN65. Our research reveals the response law of soybean crops to physiological characteristics under water deficit and provides theoretical basis and guiding significance for drought-resistant cultivation and breeding of soybean.

Isoxazoles and isoxazolines are five-membered heterocyclic molecules containing nitrogen and oxygen. Isoxazole and isoxazoline are the most popular heterocyclic compounds for developing novel drug candidates. Over 80 molecules with a broad range of bioactivities, including antitumor, antibacterial, anti-inflammatory, antidiabetic, cardiovascular, and other activities, were reviewed. A review of recent studies on the use of isoxazoles and isoxazolines moiety derivative activities for natural products is presented here, focusing on the parameters that affect the bioactivity of these compounds.

To understand the pollution characteristics of volatile organic compounds (VOCs) in the glass deep-processing industry, samples were collected using polyvinyl fluoride bags and quickly transferred to summa tanks for GC/MS/FID analysis. The emission characteristics of VOCs, the ozone formation potential and the secondary aerosol formation potential were studied. The results showed that the VOCs emitted by the six enterprises were mainly aromatics and OVOCs, accounting for 35% to 97% of the emissions, with high emission loads of alkanes and halocarbons from individual enterprises. The stack emissions from Enterprise 2 were as high as 38 mg/m3, while the emissions from the remaining five enterprises were all in the range of 1.7~4.1 mg/m3, probably because the terminal treatment facilities were not updated in a timely manner, resulting in excessive stack emissions from Enterprise 2. The characteristic pollutants, including OVOCs, aromatics and alkanes, which are mainly derived from spray painting and gluing, were screened in the six enterprises. Aromatics and OVOCs contributed the most to the ozone formation potential in the six enterprises, with some enterprises having a high contribution from alkanes and alkenes. On the basis of the secondary aerosol formation potential, toluene, benzene, ethylbenzene, o-xylene and m/p-xylene account for 98% of the six enterprises’ emissions. Glass enterprises should prioritise the control of benzene and OVOCs emissions. The glass processing industry mainly emits aromatics, OVOCs and alkanes. Through a preliminary study on the emission characteristics of VOCs in the glass deep-processing industry, we provided basic data for the reduction and control of VOCs in the glass deep-processing industry in China.

MicroRNAs are involved in the regulation of the autophagy and proliferation in several diseases. This study aims to verify the role of miR-25-3p in the proliferation and autophagy of renal cells in polycystic kidney disease (PKD). We found that kidney to body weight and blood urea content were increased in PKD mice. Cystic dilations were increased in kidney tissue from PKD mice, and autophagy-related protein ULK1 and the ratio of LC3-II/LC3-I were decreased, indicating autophagy was inhibited in PKD mice. In addition, miR-25-3p was upregulated in PKD mice, and inhibition of miR-25-3p decreased cystic dilations in kidney tissues, increased ULK1 expression and the ratio of LC3-II/LC3-I, indicating inhibition of miR-25-3p enhanced the autophagy in PKD. Besides, inhibition of miR-25-3p suppressed the proliferation of renal cells and downregulated E2F-1 and PCNA expressions. Importantly, miR-25-3p targetedly suppressed ATG14 expression in PKD cells. Finally, silencing ATG14 abolished the inhibition effect of miR-25-3p inhibitor on renal cell proliferation, and reversed the inhibition effect of miR-25-3p inhibitor on E2F-1 and PCNA expressions in in vitro and in vivo experiments, which suggested that ATG14 was involved in the regulation of miR-25-3p-mediated kidney cell proliferation. Therefore, inhibition of miR-25-3p promoted cell autophagy and suppressed cell proliferation in PKD mice through regulating ATG14.

Cucumber seeds are the seeds of Cucumber (Cucumis sativus L.), which include a large number of essential fatty acids, plant sterols, glycosides, volatile oils, as well as Ca, Mg, and other inorganic elements. Cucumber seed oil has good UV absorption effect because it is rich in an unsaturated functional group structure. Plant sterol in cucumber seed oil shows strong permeability toward the skin, which promotes skin metabolism and inhibits skin inflammation. β-sitosterol in plant sterols can also effectively protect the peroxide of low-density lipoprotein, so they have an antioxidant effect. In this study, cucumber seed oil was extracted by the Soxhlet extraction method as plant-based sunscreen, in which cucumber seed oil was used as the main component, and an appropriate amount of titanium dioxide was used as an antioxidant. Taking the settling solvent ratio as the index, the orthogonal experiment was designed to determine the prescription composition of the pure matrix. Then the single factor experiments of cucumber seed oil, titanium dioxide, and vitamin E were carried out. The effects of three components on UV absorption were investigated by orthogonal experiments, and the optimum formula with cucumber seed oil as the main component was finally determined and verified. In conclusion, our plant sunscreen was produced by cucumber seed oil as raw material instead of hormone. There was no harm to the skin. It has the potential to develop plant-based sunscreen with cucumber seed oil and provides a reference for the development of plant sunscreen and skin care products.

Soybean is an important food crop in the world. Drought can seriously affect the yield and quality of soybean; however, studies on extreme drought—weak and strong—are absent. In this study, drought-tolerant soybean Heinong 44 (HN44) and sensitive soybean Heinong 65 (HN65) were used as the test varieties, and the effects of strong and weak droughts on the physiological stability of soybean were explored through the drought treatment of soybean at the early flowering stage. The results showed that the contents of malondialdehyde (MDA), hydrogen peroxide (H2O2), and superoxide anions (O2·−) increased with the increase in the degree of drought. The plant height and relative water content decreased, and photosynthesis was inhibited. The activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), and the total antioxidant capacity (T-AOC) showed a trend of first increasing and then decreasing. Through contribution analysis, CAT changed the most, and the role of SOD gradually increased with the aggravation of drought. With the aggravation of drought, the contents of soluble sugar (SSC) and proline (Pro) increased gradually, and the content of soluble protein (SP) increased initially and then decreased. According to contribution analysis, SSC had the highest contribution to osmotic adjustment. SSC and Pro showed an upward trend with the aggravation of drought, indicating that their role in drought was gradually enhanced.

Reassortment with the H9N2 virus gave rise to the zoonotic H7N9 avian influenza virus (AIV), which caused more than five outbreak waves in humans, with high mortality. The frequent exchange of genomic segments between H7N9 and H9N2 has been well-documented. However, the reassortment patterns have not been described and are not yet fully understood. Here, we used phylogenetic analyses to investigate the patterns of intersubtype and intrasubtype/intralineage reassortment across the eight viral segments. The H7N9 virus and its progeny frequently exchanged internal genes with the H9N2 virus but rarely with the other AIV subtypes. Before beginning the intrasubtype/intralineage reassortment analyses, five Yangtze River Delta (YRD A-E) and two Pearl River Delta (PRD A-B) clusters were divided according to the HA gene phylogeny. The seven reset segment genes were also nomenclatured consistently. As revealed by the tanglegram results, high intralineage reassortment rates were determined in waves 2–3 and 5. Additionally, the clusters of PB2 c05 and M c02 were the most dominant in wave 5, which could have contributed to the onset of the largest H7N9 outbreak in 2016–2017. Meanwhile, a portion of the YRD-C cluster (HP H7N9) inherited their PB2, PA, and M segments from the co-circulating YRD-E (LP H7N9) cluster during wave 5. Untanglegram results revealed that the reassortment rate between HA and NA was lower than HA with any of the other six segments. A multidimensional scaling plot revealed a robust genetic linkage between the PB2 and PA genes, indicating that they may share a co-evolutionary history. Furthermore, we observed relatively more robust positive selection pressure on HA, NA, M2, and NS1 proteins. Our findings demonstrate that frequent reassortment, particular reassorted patterns, and adaptive mutations shaped the H7N9 viral genetic diversity and evolution. Increased surveillance is required immediately to better understand the current state of the HP H7N9 AIV.

Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency medical attention, which is routinely diagnosed using non-contrast head CT imaging. The diagnostic accuracy of acute ICH on CT varies greatly among radiologists due to the difficulty of interpreting subtle findings and the time pressure associated with the ever-increasing workload. The use of artificial intelligence technology may help automate the process and assist radiologists for more prompt and better decision-making. In this work, we design a deep learning approach that mimics the interpretation process of radiologists, and combines a 2D CNN model and two sequence models to achieve accurate acute ICH detection and subtype classification. Being developed using the extensive 2019-RSNA Brain CT Hemorrhage Challenge dataset with over 25000 CT scans, our deep learning algorithm can accurately classify the acute ICH and its five subtypes with AUCs of 0.988 (ICH), 0.984 (EDH), 0.992 (IPH), 0.996 (IVH), 0.985 (SAH), and 0.983 (SDH), respectively, reaching the accuracy level of expert radiologists. Our method won 1st place among 1345 teams from 75 countries in the RSNA challenge. We have further evaluated our algorithm on two independent external validation datasets with 75 and 491 CT scans, respectively, and our method maintained high AUCs of 0.964 and 0.949 for acute ICH detection. These results have demonstrated the high performance and robust generalization ability of our proposed method, which makes it a useful second-read or triage tool that can facilitate routine clinical applications.

Zona incerta (ZI) is an inhibitory subthalamic nucleus with diverse connectivity yet its functional importance has not been extensively studied. Here the authors report that ZI receives mPFC input and can modulate both innate and learned defensive behaviors via its inhibitory projection to the PAG.

Highly pathogenic (HP) H7N9 avian influenza virus (AIV) emerged in China in 2016. HP H7N9 AIV caused at least 33 human infections and has been circulating in poultry farms continuously since wave 5. The genetic divergence, geographic patterns, and hemagglutinin adaptive and parallel molecular evolution of HP H7N9 AIV in China since 2017 are still unclear. Here, 10 new strains of HP H7N9 AIVs from October 2019 to April 2021 were sequenced. We found that HP H7N9 was primarily circulating in Northern China, particularly in the provinces surrounding the Bohai Sea (Liaoning, Hebei, and Shandong) since wave 6. Of note, HP H7N9 AIV phylogenies exhibit a geographical structure compatible with high levels of local transmission after unidirectional rapid geographical expansion towards the north of China in 2017. In addition, we showed that two major subclades were continually expanding with the viral population size undergoing a sharp increase after 2018 with an obvious seasonal tendency. Notably, the hemagglutinin gene showed signs of parallel evolution and positive selection. Our research sheds light on the current epidemiology, evolution, and diversity of HP H7N9 AIV that can help prevent and control the spreading of HP H7N9 AIV.

The ability to adjust defensive behavior is critical for animal survival in dynamic environments. However, neural circuits underlying the modulation of innate defensive behavior remain not well-understood. In particular, environmental threats are commonly associated with cues of multiple sensory modalities. It remains to be investigated how these modalities interact to shape defensive behavior. In this study, we report that auditory-induced defensive flight behavior can be facilitated by somatosensory input in mice. This cross-modality modulation of defensive behavior is mediated by the projection from the primary somatosensory cortex (SSp) to the ventral sector of zona incerta (ZIv). Parvalbumin (PV)-positive neurons in ZIv, receiving direct input from SSp, mediate the enhancement of the flight behavior via their projections to the medial posterior complex of thalamus (POm). Thus, defensive flight can be enhanced in a somatosensory context-dependent manner via recruiting PV neurons in ZIv, which may be important for increasing survival of prey animals.

This study presents a fluorescence method for detecting adenosine triphosphate (ATP) based on a label-free Ag nanocluster molecular beacon (MB) with high sensitivity. The sensor contains a hairpin-shaped MB, two short single-stranded DNA strands, and T4 DNA ligase. The MB consists of three parts, which are the template DNA sequence for synthesizing Ag nanoclusters at the 5′ end, the middle DNA with a hairpin-shaped structure, and the guanine base-rich DNA sequence at the 3′ end. The sensor exhibits high fluorescence intensity in the absence of ATP. However, when the probe is used for ATP detection, the two short DNA sequences in the sensor would form a long sequence by enzymatic ligation reaction; this long sequence opens the hairpin-shaped structure of the MB and decreases the fluorescence of the system. Under optimal analytical conditions, a clear linear relationship is observed between ATP concentration and fluorescence intensity in the range of 0.1–10 μM. The interference presented by other small molecules during ATP detection is evaluated, and results confirm the good selectivity of the proposed sensor. Compared with traditional methods, the sensor is label free, easy to operate, inexpensive, and highly sensitive.