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Abstract The escalating frequency of environmental pollution incidents has raised significant concerns regarding the potential health impacts of pollutant fluctuations. Consequently, a comprehensive study on the role of pollutants in the prevalence of viral hepatitis is indispensable for the advancement of innovative prevention strategies. Monthly incidence rates of viral hepatitis from 2005 to 2020 were sourced from the Chinese Center for Disease Control and Prevention Infectious Disease Surveillance Information System. Pollution data spanning 2014–2020 were obtained from the National Oceanic and Atmospheric Administration (NOAA), encompassing pollutants such as CO, NO2, and O3. Time series analysis models, including seasonal auto-regressive integrated moving average (SARIMA), Holt-Winters model, and Generalized Additive Model (GAM), were employed to explore prediction and synergistic effects related to viral hepatitis. Spearman correlation analysis was utilized to identify pollutants suitable for inclusion in these models. Concurrently, machine learning (ML) algorithms were leveraged to refine the prediction of environmental pollutant levels. Finally, a weighted quantile sum (WQS) regression framework was developed to evaluate the singular and combined impacts of pollutants on viral hepatitis cases across different demographics, age groups, and environmental strata. The incidence of viral hepatitis in Beijing exhibited a declining trend, primarily characterized by HBV and HCV types. In predicting hepatitis prevalence trends, the Holt-Winters additive seasonal model outperformed the SARIMA multiplicative model ((1,1,0) (2,1,0) [12]). In the prediction of environmental pollutants, the SVM model demonstrated superior performance over the GPR model, particularly with Polynomial and Besseldot kernel functions. The combined pollutant risk effect on viral hepatitis was quantified as βWQS (95% CI) = 0.066 (0.018, 0.114). Among different groups, PM2.5 emerged as the most sensitive risk factor, notably impacting patients with HCV and HEV, as well as individuals aged 35–64. CO predominantly affected HAV patients, showing a risk effect of βWQS (95% CI) = − 0.0355 (− 0.0695, − 0.0016). Lower levels of PM2.5 and PM10 were associated with heightened risk of viral hepatitis incidence with a lag of five months, whereas elevated levels of PM2.5 (100–120 μg/m3) and CO correlated with increased hepatitis incidence risk with a lag of six months. The Holt-Winters model outperformed the SARIMA model in predicting the incidence of viral hepatitis. Among machine learning algorithms, SVM and GPR models demonstrated superior performance for analyzing pollutant data. Patients infected with HAV and HEV were primarily influenced by PM10 and CO, whereas SO2 and PM2.5 significantly impacted others. Individuals aged 35–64 years appeared particularly susceptible to these pollutants. Mixed pollutant exposures were found to affect the development of viral hepatitis with a notable lag of 5–6 months. These findings underscore the importance of long-term monitoring of pollutants in relation to viral hepatitis incidence.

Gas therapy is currently popular in cancer treatment because of its controllability, effectiveness, and biosafety, as well as the fast development of carriers for gas delivery. Here, we introduce the various gas molecules with exact anticancer effects, including nitric oxide (NO), carbon monoxide (CO), oxygen (O2), hydrogen (H2), etc., and their anticancer mechanisms. Besides, recent advances in stimuli-responsive delivery systems for gas therapy are summarized. In terms of the various stimulation methods, the design of delivery systems for gases is introduced. In addition, the strategies of gas therapy combined with other therapeutic modalities, including chemotherapy, radiotherapy (RT), photodynamic therapy (PDT), photothermal therapy (PTT), etc., are described. Finally, the current challenges and prospects of delivery platforms for gases, and the future development and clinical translational value of gas therapy are also discussed.

Background Percutaneous intramyocardial septal radiofrequency ablation (PIMSRA) has been reported to be safe and effective at midterm follow‐up to treat drug‐refractory hypertrophic obstructive cardiomyopathy in a single center. However, data from other centers are lacking. This retrospective cohort study aimed to investigate the efficacy and safety of PIMSRA from another independent center. Methods and Results PIMSRA was performed in 76 patients with hypertrophic obstructive cardiomyopathy in our center from April 2020 to June 2023. The primary outcome was the reduction of left ventricular outflow tract gradient after 6 months or more post‐PIMSRA. Secondary outcomes were periprocedural major adverse clinical events. Sixty‐one patients returned to the hospital for follow‐up 6 to 30 (median, 14) months after the procedure. At the last follow‐up of the 61 patients, the maximum septal thickness decreased from a median of 23.6 (interquartile range, 20.5–26.4) to 19.1 (interquartile range, 16.0–22.1) mm (P

Climate science is an indispensable part of climate solutions, and an era of climate actions necessitates certain paradigm shifts of climate science to better support viable climate actions and solutions. Three paradigm shifts are exemplified, namely (1) transcending the boundaries between physical science basis, adaptation, and mitigation; (2) embracing the synergy between climate science and technical innovations for effective climate solutions; and (3) shifting the paradigm from equilibrium climate dynamics toward non-equilibrium dynamics of climate/Earth systems. Beyond the application-driven and solution-oriented studies, curiosity-driven theoretical research is emphasized in the shift toward non-equilibrium climate/Earth systems—tipping elements, abrupt climate changes, and extremes—which may open avenues for new discoveries not only within climate science but also in mathematics, physics, and complex systems science.

Abstract There is increasing evidence that miRNAs play an important role in the prognosis of HCC. There is currently a lack of acknowledged models that accurately predict patient prognosis. The aim of this study is to create a miRNA-based model to precisely forecast a patient’s prognosis and a miRNA–mRNA network to investigate the function of a targeted mRNA. TCGA miRNA dataset and survival data of HCC patients were downloaded for differential analysis. The outcomes of variance analysis were subjected to univariate and multivariate Cox regression analyses and LASSO analysis. We constructed and visualized prognosis-related models and subsequently used violin plots to probe the function of miRNAs in tumor cells. We predicted the target mRNAs added those to the String database, built PPI protein interaction networks, and screened those mRNA using Cytoscape. The hub mRNA was subjected to GO and KEGG analysis to determine its biological role. Six of them were associated with prognosis: hsa-miR-139-3p, hsa-miR-139-5p, hsa-miR-101-3p, hsa-miR-30d-5p, hsa-miR-5003-3p, and hsa-miR-6844. The prognostic model was highly predictive and consistently performs, with the C index exceeding 0.7 after 1, 3, and 5 years. The model estimated significant differences in the Kaplan–Meier plotter and the model could predict patient prognosis independently of clinical indicators. A relatively stable miRNA prognostic model for HCC patients was constructed, and the model was highly accurate in predicting patients with good stability over 5 years. The miRNA–mRNA network was constructed to explore the function of mRNA.

Abstract Background The selection of prophylactic antibiotics for preventing post-operative pulmonary infections in smoking patients undergoing video-assisted thoracoscopic lung surgery (VATLS) is not clear. Methods In this retrospective cohort study, the outcomes of 572 smoking patients undergoing VATLS with prophylactic cefazolin/cefuroxime or other antibiotics were analyzed. Patients were classified as cefazolin/cefuroxime group and the control group. A 1:1 propensity score matching was also performed. Results The primary outcome of the incidence of post-operative pulmonary infection did not differ significantly between the two groups (23.7% vs 30.5%, RR = 0.777, 95%CI 0.564 ~ 1.070 p = 0.113). Similarly, secondary outcomes including the incidence of post-operative fever, the white blood cell count and neutrophils on the 3rd day after the surgery, and time for blood routine test recovery were all found without significant difference between the two groups. In the multivariate logistic regression model, no association was found between prophylactic use of cefazolin/cefuroxime and post-operative pulmonary infections after controlling other possible confounding factors (OR = 0.685, 95%CI 0.441 ~ 1.065, p = 0.093). Conclusions Prophylactic use of cefazolin/cefuroxime was not associated with more adverse clinical outcomes among smoking populations undergoing VATLS when compared with broad-spectrum antibiotics and the two drugs are still feasible for peri-operative prophylactic use for smoking population before the surgery.

Malicious traffic has posed a significant threat to current 5G networks. In the upcoming 6G era, with the rapid development of the Internet of Things (IoT), defending against malicious traffic has become even more challenging due to the diverse nature and widespread distribution of IoT devices. This paper presents a new distributed framework for detecting malicious traffic on the access side of the IoT. This framework shifts the line of defense forward, and could alleviate the resource-bottleneck problem of traditional detectors that are usually deployed at the victim side. In particular, we devise a transformer-based neural network, which is tailored for distributed malicious traffic detection at multiple detection points. Additionally, we develop a personalized federated learning-based collaborative algorithm to enable horizontal collaboration among multiple detection points by sharing neural network parameters. Different from the traditional federated learning framework which trains a high-precision global model, our proposed framework fully considers the differences in the distribution of IoT traffic at the entrance, and uses local traffic data to train personalized models with better local detection performance on the basis of the global model. The experimental results demonstrate that our approach achieves an average detection accuracy of 99.2% and an F1-score of 99.2% for all detection points using the N-BaIoT dataset. In comparison to methods lacking collaboration, our approach exhibits significant improvements in terms of accuracy, precision, recall, and F1-score. Moreover, our detection performance is comparable to that of centralized learning frameworks, despite sharing only the model parameters.

Nasal drug delivery efficiency is highly dependent on the position in which the drug is deposited in the nasal cavity. However, no reliable method is currently available to assess its impact on delivery performance. In this study, a biomimetic nasal model based on three-dimensional (3D) reconstruction and three-dimensional printing (3DP) technology was developed for visualizing the deposition of drug powders in the nasal cavity. The results showed significant differences in cavity area and volume and powder distribution in the anterior part of the biomimetic nasal model of Chinese males and females. The nasal cavity model was modified with dimethicone and validated to be suitable for the deposition test. The experimental device produced the most satisfactory results with five spray times. Furthermore, particle sizes and spray angles were found to significantly affect the experimental device's performance and alter drug distribution, respectively. Additionally, mometasone furoate (MF) nasal spray (NS) distribution patterns were investigated in a goat nasal cavity model and three male goat noses, confirming the in vitro and in vivo correlation. In conclusion, the developed human nasal structure biomimetic device has the potential to be a valuable tool for assessing nasal drug delivery system deposition and distribution.

BackgroundThe immune system plays an important role in the development and treatment of thyroid cancer(THCA).However, the correlation between immune cells and THCA has not been systematically studied.MethodsThis study used a two-sample Mendelian randomization (MR) study to determine the causal relationship between immune cell characteristics and THCA. Based on a large sample of publicly available genetic data, we explored the causal relationship between 731 immune cell characteristics and THCA risk. The 731 immunophenotypes were divided into 7 groups, including B cell panel(n=190),cDC panel(n=64),Maturation stages of T cell panel(n=79),Monocyte panel(n=43),Myeloid cell panel(n=64),TBNK panel(n=124),and Treg panel(n=167). The sensitivity of the results was analyzed, and heterogeneity and horizontal pleiotropy were excluded.ResultsAfter FDR correction, the effect of immunophenotype on THCA was not statistically significant. It is worth mentioning, however, that there are some unadjusted low P-values phenotypes. The odds ratio (OR) of CD62L on monocyte on THCA risk was estimated to be 0.953 (95% CI=0.930~0.976, P=1.005×10−4),and which was estimated to be 0.975(95% CI=0.961–0.989, P=7.984×10−4) for Resting Treg%CD4 on THCA risk. Furthermore, THCA was associated with a reduced risk of 5 immunophenotype:CD25 on CD39+ CD4 on Treg (OR=0.871, 95% CI=0.812~0.935, P=1.274×10−4), activated Treg AC (OR=0.884, 95% CI=0.820~0.953, P=0.001), activated & resting Treg % CD4 Treg (OR=0.872, 95%CI=0.811~0.937,P=2.109×10−4),CD28- CD25++ CD8br AC(OR=0.867,95% CI=0.809~0.930,P=6.09×10−5),CD28-CD127-CD25++CD8brAC(OR=0.875,95%CI=0.814~0.942,P=3.619×10−4).THCA was associated with an increased risk of Secreting Treg % CD4 Treg (OR=1.143, 95% CI=1.064~1.229, P=2.779×10−4) and CD19 on IgD+ CD24+ (OR=1.118, 95% CI=1.041~1.120, P=0.002).ConclusionsThese findings suggest the causal associations between immune cells and THCA by genetic means. Our results may have the potential to provide guidance for future clinical research.

China has been continuously improving its monitoring methods and strategies to address key infectious diseases (KIDs). After the severe acute respiratory syndrome epidemic in 2003, China established a comprehensive reporting system for infectious diseases (IDs) and public health emergencies. The relatively lagging warning thresholds, limited warning information, and outdated warning technology are insufficient to meet the needs of comprehensive monitoring for modern KIDs. Strengthening early monitoring and warning capabilities to enhance the public health system has become a top priority, with increasing demand for early warning thresholds, information, and techniques, thanks to constant innovation and development in molecular biology, bioinformatics, artificial intelligence, and other identification and analysis technologies. A panel of 31 experts has recommended a fourth-generation comprehensive surveillance system targeting KIDs (41 notifiable diseases and emerging IDs). The aim of this surveillance system is to systematically monitor the epidemiology and causal pathogens of KIDs in hosts such as humans, animals, and vectors, along with associated environmental pathogens. By integrating factors influencing epidemic spread and risk assessment, the surveillance system can serve to detect, predict, and provide early warnings for the occurrence, development, variation, and spread of known or novel KIDs. Moreover, we recommend comprehensive ID monitoring based on the fourth-generation surveillance system, along with a data-integrated monitoring and early warning platform and a consortium pathogen detection technology system. This series of considerations is based on systematic and comprehensive monitoring across multiple sectors, dimensions, factors, and pathogens that is supported by data integration and connectivity. This expert consensus will provides an opportunity for collaboration in various fields and relies on interdisciplinary application to enhance comprehensive monitoring, prediction, and early warning capabilities for the next generation of ID surveillance. This expert consensus will serve as a reference for ID prevention and control as well as other related activities.

Abstract Background Cotton, being extensively cultivated, holds immense economic significance as one of the most prominent crops globally. The SET (Su(var), E, and Trithorax) domain-containing protein is of significant importance in plant development, growth, and response to abiotic stress by modifying the lysine methylation status of histone. However, the comprehensive identification of SET domain genes (SDG) have not been conducted in upland cotton (Gossypium hirsutum L.). Results A total of 229 SDGs were identified in four Gossypium species, including G. arboretum, G. raimondii, G. hirsutum, and G. barbadense. These genes could distinctly be divided into eight groups. The analysis of gene structure and protein motif revealed a high degree of conservation among the SDGs within the same group. Collinearity analysis suggested that the SDGs of Gossypium species and most of the other selected plants were mainly expanded by dispersed duplication events and whole genome duplication (WGD) events. The allopolyploidization event also has a significant impact on the expansion of SDGs in tetraploid Gossypium species. Furthermore, the characteristics of these genes have been relatively conserved during the evolution. Cis-element analysis revealed that GhSDGs play a role in resistance to abiotic stresses and growth development. Furthermore, the qRT-PCR results have indicated the ability of GhSDGs to respond to salt stress. Co-expression analysis revealed that GhSDG51 might co-express with genes associated with salt stress. In addition, the silencing of GhSDG51 in cotton by the virus-induced gene silencing (VIGS) method suggested a potential positive regulatory role of GhSDG51 in salt stress. Conclusions The results of this study comprehensively analyze the SDGs in cotton and provide a basis for understanding the biological role of SDGs in the stress resistance in upland cotton.

This paper comprehensively analyses the first-ever monkeypox outbreak in Shenzhen, China, encompassing clinical symptomatology, therapeutic approaches, epidemiological research, and comprehensive laboratory tests, aiming to establish a robust reference for future monkeypox mitigation and management strategies. The investigation involved a thorough investigation of all identified positive cases, including extensive molecular analysis by nucleic acid detection and whole-genome sequencing of the monkeypox virus. Contact tracing and containment of the infected individuals were also undertaken. Three distinct monkeypox cases were identified in this unique outbreak, exhibiting mild and atypical clinical manifestations, primarily fever and rash. All cases were associated with a single transmission chain, primarily facilitated through close contact and homosexual behavior, indicative of a high-risk factor for monkeypox transmission.

Cotton is one of the world’s most important economic crops. Verticillium wilt is a devastating cotton disease caused by Verticillium dahliae, significantly impacting cotton yield and quality. E3 ubiquitin ligases are essential components of the ubiquitin-mediated 26S proteasome system, responsible for recognizing ubiquitinated target proteins and promoting their degradation, which play a crucial regulatory role in plant immune responses. In this study, on the basis of the confirmation of differential expression of GhDIRP1, a RING-type E3 ubiquitin ligase encoding gene, in two cotton varieties resistant (Zhongzhimian 2) or susceptible (Jimian 11) to V. dahliae, we demonstrated that GhDIRP1 is a negative regulator of V. dahliae resistance because silencing GhDIRP1 in cotton and heterogeneously overexpressing the gene in Arabidopsis enhanced and compromised resistance to V. dahliae, respectively. The GhDIRP1-mediated immune response seemed to be realized through multiple physiological pathways, including hormone signaling, reactive oxygen species, and lignin biosynthesis. Based on the sequences of GhDIRP1 isolated from Zhongzhimian 2 and Jimian 11, we found that GhDIRP1 had identical coding but different promoter sequences in the two varieties, with the promoter of Zhongzhimian 2 being more active than that of Jimian 11 because the former drove a stronger expression of GUS and LUC reporter genes. The results link the ubiquitination pathway to multiple physiological pathways acting in the cotton immune response and provide a candidate gene for breeding cotton varieties resistant to V. dahliae.

Gastric cancer (GC) is a prevalent form of malignancy characterized by significant heterogeneity. The development of a specific prediction model is of utmost importance to improve therapy alternatives. The presence of H. pylori can elicit pyroptosis, a notable carcinogenic process. Furthermore, the administration of chemotherapeutic drugs is often employed as a therapeutic approach to addressing this condition. In the present investigation, it was observed that there were variations in the production of 17 pyroptosis-regulating proteins between stomach tissue with tumor development and GC cells. The predictive relevance of each gene associated with pyroptosis was assessed using the cohort from the cancer genome atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) was utilized to enhance the outcomes of the regression approach. Patients with gastric cancer GC in the cohort from the TCGA were categorized into low-risk or high-risk groups based on their gene expression profiles. Patients with a low risk of gastric cancer had a higher likelihood of survival compared to persons classified as high risk (P

This paper focuses on the grouping formation control problem of unmanned aerial vehicle (UAV) swarms in obstacle environments. A grouping formation and obstacle avoidance control algorithm based on synchronous distributed model predictive control (DMPC) is proposed. First, the UAV swarm is divided into several groups horizontally and into a leader layer and a follower layer vertically. Second, tracking is regarded as the objective, and collision avoidance and obstacle avoidance are considered as constraints. By combining the velocity obstacle method with synchronous DMPC and providing corresponding terminal components, a leader layer control law is designed. The control law can enable the UAV swarm to track the target while avoiding collisions and dynamic obstacles. Then, considering the formation maintenance term, based on different priorities, member-level obstacle avoidance and group-level obstacle avoidance strategies are proposed, and the corresponding follower layer control laws are provided. Furthermore, the stability of the UAV swarm system under the control algorithm is demonstrated based on the Lyapunov theory. Finally, the effectiveness of the designed algorithm and its superiority in obstacle avoidance are verified through simulations.

Objectives: The Omicron BA.2 variant is probably the main epidemic strain worldwide at present. Comparing the epidemiological characteristics, transmissibility, and influencing factors of SARS-CoV-2, the results obtained in this paper will help to provide theoretical support for disease control. Methods: This study was a historical information analysis, using the R programming language and SPSS 24.0 for statistical analysis. The Geoda and Arc GIS were used for spatial autocorrelation analysis. Results: Local spatial autocorrelations of the incidence rate were observed in Delta and Omicron BA.1 outbreaks, whereas Omicron BA.2 outbreaks showed a random distribution in incidence rate. The time-dependent reproduction number of Delta, Omicron BA.1, and Omicron BA.2 were 3.21, 4.29, and 2.96, respectively, and correspondingly, the mean serial interval were 4.29 days (95% confidence interval [CI]: 0.37-8.21), 3.84 days (95% CI: 0-8.37), and 2.77 days (95% CI: 0-5.83). The asymptomatic infection rate of cases in Delta, Omicron BA.1, and Omicron BA.2 outbreaks were 21.71%, 6.25%, and 4.35%, respectively. Conclusion: The Omicron BA.2 variant had the greatest serial interval, transmissibility, and transmission speed, followed by BA.1, and then Delta. Compared with Delta and Omicron BA.1 variants, the Omicron BA.2 variant may be less pathogenic and more difficult to control than Omicron BA.1 and Delta.

Abstract Background Phloem protein 2 (PP2) proteins play a vital role in the Phloem-based defense (PBD) and participate in many abiotic and biotic stress. However, research on PP2 proteins in cotton is still lacking. Results A total of 25, 23, 43, and 47 PP2 genes were comprehensively identified and characterized in G.arboretum, G.raimondii, G.barbadense, and G.hirsutum. The whole genome duplication (WGD) and allopolyploidization events play essential roles in the expansion of PP2 genes. The promoter regions of GhPP2 genes contain many cis-acting elements related to abiotic stress and the weighted gene co-expression network analysis (WGCNA) analysis displayed that GhPP2s could be related to salt stress. The qRT-PCR assays further confirmed that GhPP2-33 could be dramatically upregulated during the salt treatment. And the virus-induced gene silencing (VIGS) experiment proved that the silencing of GhPP2-33 could decrease salt tolerance. Conclusions The results in this study not only offer new perspectives for understanding the evolution of PP2 genes in cotton but also further explore their function under salt stress.

Objective . Three-dimensional (3D) printed porous titanium scaffolds serve as a bone tissue engineering technology that offers a promising solution for addressing bone defects. The scaffold’s pore structure offers structural support and facilitates the proliferation of bone cells. Therefore, investigating the aperture and pore shape is of crucial for the development of 3D printed porous titanium scaffolds. Methods . Ti6Al4V scaffolds with the specified structure were fabricated using selective laser melting (SLM) technology. The scaffolds comprised fifteen cylindrical models measuring 20 mm in diameter and 20 mm in height. These models featured five scaffold shapes: imitation diamond-60°, imitation diamond-90°, imitation diamond-120°, regular tetrahedron and regular hexahedron. Each of these structural shapes was characterized by three different aperture sizes (400 μ m, 600 μ m and 800 μ m). The porosity and mechanical properties of Ti6Al4V scaffolds were examined. Results . The measured porosity of Ti6Al4V scaffolds varied between 56.50% and 95.28%. The porosity increased with the size of the aperture. The mechanical properties tests revealed that, for identical apertures, the compressive strength and torsional strength were influenced by the configuration of the unit structure. Furthermore, the positive and lateral compressive strength as well as torsional strength of various unit structures exhibited distinct advantages and disadvantages. Within a uniform unit structure shape, the compressive strength and torsional strength were found to be correlated with the size of apertures, indicating that larger apertures result in decreased compressive and torsional strength. Conclusion . The configuration of the aperture and the shape of the pore were identified as significant factors that influenced the compressive strength. The compressive strength of Ti6Al4V scaffolds with various unit structure shapes exhibited both advantages and disadvantages when subjected to positive, lateral, and torsional forces. The enlarged aperture augmented the scaffold’s porosity while diminishing its compressive and torsional strength.

Abstract Nitric oxide (NO) has shown great potential in tumor therapy, and the development of a platform for precise and controllable NO release still needs to be explored. Herein, a microfluidic electrospray strategy is proposed for the fabrication of hydrogel microspheres encapsulating NO donors (S‐nitrosoglutathione, GSNO) together with black phosphorus (BP) and chemotherapeutic doxorubicin (DOX) as microcarriers for tumor therapy. Based on the excellent photothermal property of BP and thermal sensitivity of GSNO, the microcarriers exhibit a near‐infrared light (NIR)‐responsive NO release behavior. Besides, the photothermal performance of the microcarriers accelerates the release of DOX. All these contribute to the excellent tumor‐killing effect of the microcarriers by combining multiple therapeutic strategies including NO therapy, photothermal therapy, and chemotherapy. Moreover, it was demonstrated that the NIR‐responsive NO delivery microcarriers could significantly inhibit tumor growth without apparent side effects in vivo. Therefore, it is believed that the novel NIR‐responsive NO microcarriers are promising candidates in clinical tumor therapy applications.

Abstract The wave velocity analysis of rock medium is the main method used to explore the internal compositions in the crust and research seismic. In this paper, a compression–shear coupled nonlinear elastic constitutive relation is established, which is consistent with the mechanical properties of rock and mineral medium under high pressure. On this basis, numerical solutions of the wave equation and plane wave analytical solutions for the primary and secondary wave velocities are obtained. As is indicated by the comparison with the linear elastic constitutive theory, the results reflect the compression–shear coupling characteristics of the rock, including the stress path effect and the compression–shear coupling wave effect. With different parameter values, the velocity of the secondary wave changes from lower than that of the elastic shear wave, to higher than that of the elastic shear wave. The research results are expected to provide meaningful explanations for the physical mechanisms of the supershear wave and sub‐Rayleigh wave, and guidance for the detection of rock and soil composition and the observation of seismic waves.

After traumatic brain injury (TBI), early assessment of secondary injury severity is critically important for estimating prognosis and treatment stratification. Currently, secondary injury severity is difficult to estimate. The objective of this study was to investigate the capacity of non-invasive amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) techniques to assess TBI injury in different brain regions and predict long-term neurobehavior outcomes. Fifty-five male and female rats were subjected to a controlled cortical impact with one of three different impactor depths to produce different degrees of TBI. Multi-parameter MRI data were acquired on a 4.7-Tesla scanner at 1?h, 1 day, and 3 days. Immunofluorescence staining was used to detect activated microglia at 3 days, and neurobehavioral tests were performed to assess long-term outcomes after 28 days. The APTw signal in the injury core at 1 day correlated with deficits in sensorimotor function, the sucrose preference test (a test for anhedonia), and spatial memory function on the Barnes maze. The APTw signal in the perilesion ipsilateral cortex gradually increased after TBI, and the value at 3 days correlated with microglia density at 3 days and with spatial memory decline and anhedonia at 28 days. The correlation between APTw and activated microglia was also observed in the ipsilateral thalamus, and its correlation to memory deficit and depression was evident in other ipsilateral sites. These results suggest that APTw imaging can be used for detecting secondary injury and as a potential predictor of long-term outcomes from TBI.

BackgroundChlamydia psittaci is a small bacterium often found in birds, including poultry, and domesticated mammals, which causes psittacosis (or parrot fever) in humans. Different strains of C. psittaci respond variably to antibiotics, suggesting a possible risk of antibiotic resistance. In general, different genotypes of C. psittaci have relatively stable hosts and different pathogenicity.MethodsMacrogenomic sequencing was performed using nucleic acids extracted from psittacosis patients’ alveolar lavage fluid samples and analyzed for genetic variability and antibiotic resistance genes. Nucleic acid amplification sequences specific to the core coding region of the C. psittaci ompA gene were used, and a phylogenetic tree was constructed with C. psittaci genotypic sequences from other sources, including Chinese published sources. The C. psittaci found in each patient were genotyped by comparing ompA gene sequences. In addition, to better illustrate the relationship between genotype and host of C. psittaci, 60 bird fecal samples were collected from bird-selling stores for screening and C. psittaci typing.ResultsMacrogenomic sequence alignment revealed the presence of resistance genes in varying abundance in samples from all three patients, including C. psittaci resistance gene sequences from two patients that matched those previously published on NCBI. Based on ompA genotyping, two patients were infected with C. psittaci genotype A and one patient was infected with genotype B. All five C. psittaci-positive samples obtained from bird-selling stores were genotype A. Both genotypes are reported to be infectious to humans. The host origin of the samples and the previously reported main sources of each genotype suggested that all but one of the C. psittaci genotype A in this study were derived from parrots, while genotype B was probably derived from chickens.ConclusionThe presence of bacterial resistance genes in psittacosis patients may affect the efficacy of clinical antibiotic therapy. Focusing on the developmental progression of bacterial resistance genes and differences in the therapeutic efficacy may facilitate effective treatment of clinical bacterial infections. Pathogenicity genotypes (e.g., genotype A and genotype B) are not limited to one animal host, suggesting that monitoring the development and changes of C. psittaci may help prevent transmission to humans.

Cognitive computers (κC) are intelligent processors advanced from data and information processing to autonomous knowledge learning and intelligence generation. This work presents a retrospective and prospective review of the odyssey toward κC empowered by transdisciplinary basic research and engineering advances. A wide range of fundamental theories and innovative technologies for κC is explored, and a set of underpinning intelligent mathematics (IM) is created. The architectures of κC for cognitive computing and Autonomous Intelligence Generation (AIG) are designed as a brain-inspired cognitive engine. Applications of κC in autonomous AI (AAI) are demonstrated by pilot projects. This work reveals that AIG will no longer be a privilege restricted only to humans via the odyssey to κC toward training-free and self-inferencing computers.

Salt stress is a major abiotic stressor that can severely limit plant growth, distribution, and crop yield. DNA-binding with one finger (Dof) is a plant-specific transcription factor that plays a crucial role in plant growth, development, and stress response. In this study, the function of a Dof transcription factor, GhDof1.7, was investigated in upland cotton. The GhDof1.7 gene has a coding sequence length of 759 base pairs, encoding 252 amino acids, and is mainly expressed in roots, stems, leaves, and inflorescences. Salt and abscisic acid (ABA) treatments significantly induced the expression of GhDof1.7. The presence of GhDof1.7 in Arabidopsis may have resulted in potential improvements in salt tolerance, as suggested by a decrease in H2O2 content and an increase in catalase (CAT) and superoxide dismutase (SOD) activities. The GhDof1.7 protein was found to interact with GhCAR4 (C2-domain ABA-related 4), and the silencing of either GhDof1.7 or GhCAR4 resulted in reduced salt tolerance in cotton plants. These findings demonstrate that GhDof1.7 plays a crucial role in improving the salt tolerance of upland cotton and provide insight into the regulation of abiotic stress response by Dof transcription factors.

Abstract Rapid progress has been made in quantum secure direct communication in recent years. For practical application, it is important to improve the performances, such as the secure information rate and the communication distance. In this paper, we report an elaborate physical system design and protocol with much enhanced performance. This design increased the secrecy capacity greatly by achieving an ultra-low quantum bit error rate of

Abstract Objective: To describe the characteristics and find out risk factors of COVID-19 patients infected with different categories of bacteria. Design: Case-control. Methods: We conducted a retrospective study including 129 COVID-19 patients admitted to a tertiary hospital between October 13, 2022 and December 31, 2022. Patients’ data were collected from the hospital information system. Patients were classified as having or not having confirmed secondary bacterial infections, or gram-positive and gram-negative bacterial infections for analysis. Categories and sources of isolated bacteria, characteristics of the patients, and the risk factors for developing secondary bacterial infections were analyzed. Results: Gram-negative bacteria accounted for the majority of secondary bacterial infections of the included patients. Critical type of COVID-19 (OR = 12.98, 95%CI 3.43∼49.18, p < 0.001), invasive therapy (OR = 9.96, 95%CI 3.01∼32.95, p < 0.001), and previous antibiotics use (OR = 17.23, 95%CI 1.38∼215.69, p = 0.027) were independent risk factors of secondary bacterial infections in COVID-19 patients. Ceftriaxone/cefotaxime use (OR = 15.45, 95%CI 2.72∼87.79, p = 0.002) was associated with gram-positive bacterial infections while age over 70 (OR = 3.30, 95%CI 1.06∼10.26, p = 0.039), invasive therapy (OR = 4.68, 95%CI 1.22∼17.93, p = 0.024), and carbapenems use (OR = 8.48, 95%CI 2.17∼33.15, p = 0.002) were associated with gram-negative bacterial infections. Conclusions: Critical patients with invasive therapy and previous antibiotics use should be cautious with secondary bacterial infections. Third-generation cephalosporins and carbapenems should be used carefully because both are risk factors for gram-positive or gram-negative bacterial infections.

Abstract The de Winter electrocardiography (ECG) pattern is a sign that implies proximal left anterior descending coronary artery occlusion in patients with chest pain. We report a case of a 34‐year‐old man with a history of smoking who presented to the local emergency department with a 49 min history of chest pain. The first ECG of the patient indicated that ST‐segment elevation was noted in the lead V2–V4; 57 min later, a second ECG revealed a typical de Winter syndrome when the patient was transferred to the emergency chest pain centre of our hospital. A percutaneous coronary intervention (PCI) was performed approximately 8 h later because the patient initially refused the PCI. Acute coronary artery angiography showed that the proximal left anterior descending coronary artery was completely occluded. Our case suggests that ST‐segment elevation myocardial infarction may evolve in the direction of de Winter, which reflects a coronary thrombus in formation, so the de Winter ECG pattern should not be considered static.

Duzheng Ye (Tu-cheng Yeh) was an active member of Rossby’s Chicago School, one of the founders of modern meteorology in China since the 1950s, and a pioneer of global change science in China and over the world. His achievements have been central to the development of atmospheric and climate dynamics and global change studies in China, and many of them remain to be fundamental in the context of global climate change. In this review, his lifelong research career is divided into five periods: (1) the preparatory period (1935–1944); (2) the Chicago period (1945–1950); (3) the period of breaking ground (1950–1966); (4) the period of transition (1972–1983); and (5) the period of global change (1984–2013). The evolution of Yeh’s main achievements is described in the context of the historical background of both China and the world. These well-known achievements included the theory of energy dispersion in the atmosphere, the general circulation of the atmosphere (GCA) over East Asia and the globe, Qinghai–Tibetan Plateau meteorology, the scale-dependence theory of geostrophic adaptation (adjustment), and his pioneering ideas on global change. Special emphases are put on some of Yeh’s investigations that were well ahead of his time, such as his investigations on trade inversion, the GCA as an internally consistent whole, abrupt seasonal changes in the GCA, the physical mechanism of atmospheric blocking, and orderly human activities.

Tropical surface temperature (TST) and its connection with atmospheric heating, including tropical latent heating (TLH), is essential to the interannual variability of tropical atmospheric circulation and global teleconnection. Utilizing seasonally averaged satellite-based TRMM precipitation data as a proxy of TLH and ERA5-based TST data from 1998 to 2018, we reveal some new features in terms of cross-hemispheric connection in the TLH and TST variability by decomposing them into equatorially symmetric and antisymmetric components. We find surprisingly that the spatial patterns of TLH projected upon the first principal components (PC1) of symmetric and antisymmetric TSTs over the whole-tropics, are very similar to each other, seemingly at odds with the classic Mastuno–Gill theory. The similarity in the projected TLH patterns is mainly because the PC1s of symmetric and antisymmetric TSTs co-vary temporally with a very high correlation. We use the spatial pattern of local correlation between symmetric and antisymmetric components, for both TST and TLH to depict geographic dependence of the symmetric–antisymmetric connection. We suggest that a whole-tropics perspective, which takes the different but connected nature of equatorially symmetric and antisymmetric modes across the whole-tropics into consideration, may well be useful in understanding and predicting tropical climate variability because clarifying the puzzle raised in this research from such a perspective about the consistency between the observation and the classic Mastuno–Gill theory is directly related to the fundamental dynamics of tropical systems, such as Walker circulation, monsoons, and their relationship with underlying land and sea conditions.

Abstract Background B-BOX (BBX) proteins are zinc-finger transcription factors with one or two BBX domains and sometimes a CCT domain. These proteins play an essential role in regulating plant growth and development, as well as in resisting abiotic stress. So far, the BBX gene family has been widely studied in other crops. However, no one has systematically studied the BBX gene in cotton. Results In the present study, 17, 18, 37 and 33 BBX genes were detected in Gossypium arboreum, G. raimondii, G. hirsutum and G. barbadense, respectively, via genome-wide identification. Phylogenetic analysis showed that all BBX genes were divided into 5 main categories. The protein motifs and exon/intron structures showed that each group of BBX genes was highly conserved. Collinearity analysis revealed that the amplification of BBX gene family in Gossypium spp. was mainly through segmental replication. Nonsynonymous (Ka)/ synonymous (Ks) substitution ratios indicated that the BBX gene family had undergone purification selection throughout the long-term natural selection process. Moreover, transcriptomic data showed that some GhBBX genes were highly expressed in floral organs. The qRT-PCR results showed that there were significant differences in GhBBX genes in leaves and shoot apexes between early-maturing materials and late-maturing materials at most periods. Yeast two-hybrid results showed that GhBBX5/GhBBX23 and GhBBX8/GhBBX26 might interact with GhFT. Transcriptome data analysis and qRT-PCR verification showed that different GhBBX genes had different biological functions in abiotic stress and phytohormone response. Conclusions Our comprehensive analysis of BBX in G. hirsutum provided a basis for further study on the molecular role of GhBBXs in regulating flowering and cotton resistance to abiotic stress.

Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched the relevant studies on transmission dynamics modeling of infectious diseases, SARS, MERS, and COVID-19 as of March 1, 2021 based on PubMed. We compared the key health decision-making time points of SARS, MERS, and COVID-19 prevention and control, and the publication time points of modeling research, to reveal the collaboration between infectious disease modeling and public health decision-making in the context of the COVID-19 pandemic. Searching with infectious disease and mathematical model as keywords, there were 166, 81 and 1 289 studies on the modeling of infectious disease transmission dynamics of SARS, MERS, and COVID-19 were retrieved respectively. Based on the modeling application framework of public health practice proposed in the current study, the collaboration among modelers, epidemiologists and public health decision-makers should be strengthened in the future.

Abstract This letter considers the robust design of radar waveform with discrete phase codes under constant modulus constraint to enhance target detectability. To solve the resultant max‐min non‐convex optimization problem, a robust discrete phase coding algorithm via iterative technology (R‐DPCA‐IT) is developed which monotonically improves the worst‐case SNR and has an upper bound ensuring to converge a finite value. At each iteration, the original multidimensional quadratic optimization problem is turned into multiple one‐dimensional optimization problems solved globally via line search. Finally, the computational time and objective value of the proposed algorithm are assessed in comparison with the existing methods.

The CCCH zinc-finger protein contains a typical C3H-type motif widely existing in plants, and it plays an important role in plant growth, development, and stress responses. In this study, a CCCH zinc-finger gene, GhC3H20, was isolated and thoroughly characterized to regulate salt stress in cotton and Arabidopsis. The expression of GhC3H20 was up-regulated under salt, drought, and ABA treatments. GUS activity was detected in the root, stem, leaves, and flowers of ProGhC3H20::GUS transgenic Arabidopsis. Compared with the control, the GUS activity of ProGhC3H20::GUS transgenic Arabidopsis seedlings under NaCl treatment was stronger. Through the genetic transformation of Arabidopsis, three transgenic lines of 35S-GhC3H20 were obtained. Under NaCl and mannitol treatments, the roots of the transgenic lines were significantly longer than those of the wild-type (WT) Arabidopsis. The leaves of the WT turned yellow and wilted under high-concentration salt treatment at the seedling stage, while the leaves of the transgenic Arabidopsis lines did not. Further investigation showed that compared with the WT, the content of catalase (CAT) in the leaves of the transgenic lines was significantly higher. Therefore, compared with the WT, overexpression of GhC3H20 enhanced the salt stress tolerance of transgenic Arabidopsis. A virus-induced gene silencing (VIGS) experiment showed that compared with the control, the leaves of pYL156-GhC3H20 plants were wilted and dehydrated. The content of chlorophyll in pYL156-GhC3H20 leaves was significantly lower than those of the control. Therefore, silencing of GhC3H20 reduced salt stress tolerance in cotton. Two interacting proteins (GhPP2CA and GhHAB1) of GhC3H20 have been identified through a yeast two-hybrid assay. The expression levels of PP2CA and HAB1 in transgenic Arabidopsis were higher than those in the WT, and pYL156-GhC3H20 had expression levels lower than those in the control. GhPP2CA and GhHAB1 are the key genes involved in the ABA signaling pathway. Taken together, our findings demonstrate that GhC3H20 may interact with GhPP2CA and GhHAB1 to participate in the ABA signaling pathway to enhance salt stress tolerance in cotton.

Abstract Background Valine-glutamine (VQ) motif-containing proteins play important roles in plant growth, development and abiotic stress response. For many plant species, the VQ genes have been identified and their functions have been described. However, little is known about the origin, evolution, and functions (and underlying mechanisms) of the VQ family genes in cotton. Results In this study, we comprehensively analyzed the characteristics of 268 VQ genes from four Gossypium genomes and found that the VQ proteins evolved into 10 clades, and each clade had a similar structural and conservative motif. The expansion of the VQ gene was mainly through segmental duplication, followed by dispersal. Expression analysis revealed that many GhVQs might play important roles in response to salt and drought stress, and GhVQ18 and GhVQ84 were highly expressed under PEG and salt stress. Further analysis showed that GhVQs were co-expressed with GhWRKY transcription factors (TFs), and microRNAs (miRNAs) could hybridize to their cis-regulatory elements. Conclusions The results in this study broaden our understanding of the VQ gene family in plants, and the analysis of the structure, conserved elements, and expression patterns of the VQs provide a solid foundation for exploring their specific functions in cotton responding to abiotic stresses. Our study provides significant insight into the potential functions of VQ genes in cotton.

The caleosin (CLO) protein family displays calcium-binding properties and plays an important role in the abiotic stress response. Here, a total of 107 CLO genes were identified in 15 plant species, while no CLO genes were detected in two green algal species. Evolutionary analysis revealed that the CLO gene family may have evolved mainly in terrestrial plants and that biological functional differentiation between species and functional expansion within species have occurred. Of these, 56 CLO genes were identified in four cotton species. Collinearity analysis showed that CLO gene family expansion mainly occurred through segmental duplication and whole-genome duplication in cotton. Sequence alignment and phylogenetic analysis showed that the CLO proteins of the four cotton species were mainly divided into two types: H-caleosins (class I) and L-caleosins (class II). Cis-acting element analysis and quantitative RT–PCR (qRT–PCR) suggested that GhCLOs might be regulated by abscisic acid (ABA) and methyl jasmonate (MeJA). Moreover, transcriptome data and qRT–PCR results revealed that GhCLO genes responded to salt and drought stresses. Under salt stress, gene-silenced plants (TRV: GhCLO06) showed obvious yellowing and wilting, higher malondialdehyde (MDA) content accumulation, and significantly lower activities of superoxide dismutase (SOD) and peroxidase (POD), indicating that GhCLO06 plays a positive regulatory role in cotton salt tolerance. In gene-silenced plants (TRV: GhCLO06), ABA-related genes (GhABF2, GhABI5, and GhNAC4) were significantly upregulated after salt stress, suggesting that the regulation of salt tolerance may be related to the ABA signaling pathway. This research provides an important reference for further understanding and analyzing the molecular regulatory mechanism of CLOs for salt tolerance.

Summary: Background: The end plate plays an important role in intervertebral disc degeneration progression. The aim of the study was to examine the compositional and structural changes of the end plate with age and to investigate the correlation between end plate and disc degeneration by T1ρ and T2 map magnetic resonance imaging. Methods: There were 12 young monkeys (6-7 years old), 20 aged monkeys (14-17 years old) and 12 human participants (30-50 years old) in this study. T1ρ or T2 map values of the nucleus pulposus and end plate cartilage were analyzed according to Pfirrmann grades and age. Afterwards, micro computed tomography and histological analysis were used to confirm the end plate changes in monkeys. Pearson’s correlation was performed to investigate the relationship between end plate and disc degeneration. Results: In monkeys, T1ρ (r=-0.794, P

To satisfy the growing demand for broadband maritime communications, space-ground integrated maritime communication networks (MCNs) arise, which are envisioned to take full advantage of both satellites and terrestrial shore-based networks. In practice, due to the frequent beam hopping of satellites and the limited number of geographically available onshore base-station sites, the space-ground integrated MCN usually presents a highly non-cellular network structure, leading to both challenging blind zones and coverage areas with severe interference. In this paper, we optimize the coverage performance by exploiting the marine environment information. Particularly, the transmit antenna correlation is estimated using the location and mobility information of scatterers on the sea, such as lighthouses, reefs, islands, and vessels. The position and attitude information of satellites are also utilized for interference estimation. Based on that, we optimize the input covariance and precoding matrix to maximize the ergodic sum capacity for all mobile terminals within the coverage. It is a complicated non-convex problem, especially because the ergodic sum capacity is difficult to be expressed straightly without the expectation operator. We introduce an upper bound of the ergodic sum capacity using the path loss and the transmit antenna correlation estimated from the environment information, and then propose an iterative algorithm to solve the problem by solving a set of convex subproblems. The proposed environment-aware scheme is evaluated using the real-world geographic information of a coastal area of China. Simulation results demonstrate that the proposed scheme can greatly improve the ergodic sum capacity and the energy efficiency compared with existing approaches, and achieve dynamic coverage to match the non-cellular network structure.

The membrane attack complex/perforin (MACPF) domain-containing proteins are involved in the various developmental processes and in responding to diverse abiotic stress. The function and regulatory network of the MACPF genes are rarely reported in Gossypium spp. We study the detailed identification and partial functional verification of the members of the MACPF family. Totally, 100 putative MACPF proteins containing complete MACPF domain were identified from the four cotton species. They were classified into three phylogenetic groups and underwent multifold pressure indicating that selection produced new functional differentiation. Cotton MACPF gene family members expanded mainly through the whole-genome duplication (WGD)/segmental followed by the dispersed. Expression and cis-acting elements analysis revealed that MACPFs play a role in resistance to abiotic stresses, and some selected GhMACPFs were able to respond to the PEG and cold stresses. Co-expression analysis showed that GhMACPFs might interact with valine-glutamine (VQ), WRKY, and Apetala 2 (AP2)/ethylene responsive factor (ERF) domain-containing genes under cold stress. In addition, silencing endogenous GhMACPF26 in cotton by the virus-induced gene silencing (VIGS) method indicated that GhMACPF26 negatively regulates cold tolerance. Our data provided a comprehensive phylogenetic evolutionary view of Gossypium MACPFs. The MACPFs may work together with multiple transcriptional factors and play roles in acclimation to abiotic stress, especially cold stress in cotton.

Soil salinization conditions seriously restrict cotton yield and quality. Related studies have shown that the DUF4228 proteins are pivotal in plant resistance to abiotic stress. However, there has been no systematic identification and analysis of the DUF4228 gene family in cotton and their role in abiotic stress. In this study, a total of 308 DUF4228 genes were identified in four Gossypium species, which were divided into five subfamilies. Gene structure and protein motifs analysis showed that the GhDUF4228 proteins were conserved in each subfamily. In addition, whole genome duplication (WGD) events and allopolyploidization might play an essential role in the expansion of the DUF4228 genes. Besides, many stress-responsive (MYB, MYC) and hormone-responsive (ABA, MeJA) related cis-elements were detected in the promoters of the DUF4228 genes. The qRT-PCR results showed that GhDUF4228 genes might be involved in the response to abiotic stress. VIGS assays and the measurement of relative water content (RWC), Proline content, POD activity, and malondialdehyde (MDA) content indicated that GhDUF4228-67 might be a positive regulator of cotton response to salt stress. The results in this study systematically characterized the DUF4228s in Gossypium species and will provide helpful information to further research the role of DUF4228s in salt tolerance.

The early flowering 4 (ELF4) family members play multiple roles in the physiological development of plants. ELF4s participated in the plant biological clock’s regulation process, photoperiod, hypocotyl elongation, and flowering time. However, the function in the ELF4s gene is barely known. In this study, 11, 12, 21, and 22 ELF4 genes were identified from the genomes of Gossypium arboreum, Gossypium raimondii, Gossypium hirsutum, and Gossypium barbadense, respectively. There ELF4s genes were classified into four subfamilies, and members from the same subfamily show relatively conservative gene structures. The results of gene chromosome location and gene duplication revealed that segmental duplication promotes gene expansion, and the Ka/Ks indicated that the ELF4 gene family has undergone purification selection during long-term evolution. Spatio-temporal expression patterns and qRT-PCR showed that GhELF4 genes were mainly related to flower, leaf, and fiber development. Cis-acting elements analysis and qRT-PCR showed that GhELF4 genes might be involved in the regulation of abscisic acid (ABA) or light pathways. Silencing of GhELF4-1 and GhEFL3-6 significantly affected the height of cotton seedlings and reduced the resistance of cotton. The identification and functional analysis of ELF4 genes in upland cotton provide more candidate genes for genetic modification.

Glycerol-3-phosphate acyltransferases (GPATs), critical for multiple biological processes like male fertility, have been extensively characterized. However, their precise functions and underlying regulatory mechanism in cotton anther development are unclear. This research demonstrated the importance of GhGPAT12/25 (a paralogs pair on A12/D12 sub-chromosome of cotton) to regulate the degradation of tapetum, anther cuticle formation, and pollen exine development. GhGPAT12 and GhGPAT25 exhibited specifically detected transcripts in tapetum and pollen exine during the early anther developmental stages. GhGPAT12/25 are sn-2 glycerol-3-phosphate acyltransferases and can transfer the acyl group of palmitoyl-CoA to glycerol-3-phosphate (G3P). CRISPR/Cas9-mediated knockout identified the functional redundancy of GhGPAT12 and GhGPAT25. Knockout of both genes caused completely male sterility associated with abnormal anther cuticle, swollen tapetum, and inviable microspores with defective exine and irregular unrestricted shape. RNA-seq analysis showed that the loss of function of GhGPAT12/25 affects the processes of wax metabolic, glycerol monomer biosynthesis, and transport. Consistently, cuticular waxes were dramatically reduced in mutant anthers. Yeast one-hybrid system (Y1H), virus-induced gene silencing (VIGS), and dual-luciferase (LUC) assays illustrated that GhMYB80s are likely to directly activate the expression of GhGPAT12/25. This study provides important insights for revealing the regulatory mechanism underlying anther development in cotton.

In this paper, a class of spatially coupled generalized low-density parity-check (SC-GLDPC) codes with minimum coupling width is introduced to mitigate the Class-A impulsive noise. Codes with minimum coupling width are beneficial to simple code structure, short window decoding delay, and small rate-loss. The SC-GLDPC code is constructed by coupling the multiple identical generalized low-density parity-check (GLDPC) codes. Decoding thresholds over impulsive channels are derived by a recursive extrinsic information transfer function approach and are further estimated by the fast prediction approach. An edge spreading optimization method is proposed to design SC-GLDPC codes with minimum coupling width. The simulation results show that the optimized SC-GLDPC codes with minimum coupling width can show capacity-approaching property over impulsive channels. Benefitting from spatial coupling and generalized check nodes the SC-GLDPC codes show better bit error rate performance over impulsive channels, compared with GLDPC codes and spatially coupled low-density parity-check (SC-LDPC) codes.

Recent studies have greatly promoted the development of semantic segmentation. Most state-of-the-art methods adopt fully convolutional networks (FCNs) to accomplish this task, in which the fully connected layer is replaced with the convolution layer for dense prediction. However, standard convolution has limited ability in maintaining continuity between predicted labels as well as forcing local smooth. In this paper, we propose the dense convolution unit (DCU), which is more suitable for pixel-wise classification. The DCU adopts dense prediction instead of the center-prediction manner used in current convolution layers. The semantic label for every pixel is inferred from those overlapped center/off-center predictions from the perspective of probability. It helps to aggregate contexts and embeds connections between predictions, thus successfully generating accurate segmentation maps. DCU serves as the classification layer and is a better option than standard convolution in FCNs. This technique is applicable and beneficial to FCN-based state-of-the-art methods and works well in generating segmentation results. Ablation experiments on benchmark datasets validate the effectiveness and generalization ability of the proposed approach in semantic segmentation tasks.

Quality of experience (QoE), which directly relates to both technical evolvement and profit promotion, is a vital concern for mobile video services. However, the wireless network operators have long been troubled by the problem of lacking effective QoE monitoring approaches since the traditional evaluation methods of communication quality are objective metrics oriented. Considering that mobile terminals are the network elements closest to users, it is promising to realize a real-time QoE estimation for video services by fully utilizing the sensing capabilities of mobile terminals. As the first step, we specifically develop a mobile video testing application. With support from China Unicom, one of the three major wireless network operators in China, over 80 000 data records are collected under the real-world conditions. The collected data consist of four types of subjective scores and 13 objective parameters concerning video attributes, network performance, device capability, playback events, and external factors. After preprocessing the data set through correlation analysis, we establish the two QoE estimation models based on the C4.5 method and the gradient boosting decision tree (GBDT) method, respectively. The experimental results demonstrate that the proposed models can achieve remarkable estimation performances and outperform the baseline models. Specifically, the overall estimation accuracy of the GBDT-based model is approximately 80% for a five-level scale and approaches 90% when a more practical 3-level scale is adopted. Finally, we comprehensively discuss the estimation performances based on characteristics of the data and validate the feasibility of estimating QoE based on mobile terminals-the “peripheral sensors” of the mobile networks.

In this paper, the geometry-aware GAN, referred to as GAGAN, is proposed to address the issue of face attribute transfer with unpaired data. The source and target images are not aligned and come from different individuals. The key idea is to deform the source image according to the geometry features and generate a high-resolution image with the desired attribute. To address the problem of the unpaired training samples, the CycleGAN architecture is applied to form an attribute adding and removing cycle, where the bilateral mappings between the source and target domains are learned. The geometry flow and occlusion mask are learned by the warping sub-network to capture the geometric variation between the two domains. In the attribute adding process, the spatial transformer network (STN) warps the source face into the desired pose and shape according to the flow, and the transfer sub-network hallucinates new components on the warped image. In the attribute removing process, the recover sub-network and the STN reverts the sample back to the source domain. Experiments on the benchmarks CELEBA and CELEBA-HQ datasets demonstrate the advantages of our method compared to the baselines, in terms of both quantitative and qualitative evaluation.

With the popularity of handheld devices, the development of wireless communication technology and the proliferation of multimedia resources, mobile video has become the main business in LTE networks with explosive traffic demands. How to improve the quality of experience (QoE) of mobile video in the dynamic and complex network environment has become a research focus. Dynamic adaptive streaming over HTTP technology introduces adaptive bitrate (ABR) requests at the client side to improve video QoE and various rate adaptation algorithms are also constantly proposed. In view of the limitations of the existing heuristic or learning-based ABR methods, we propose redirecting enhanced Deep Q-learning toward DASH video QoE (RDQ), a QoE-oriented rate adaptation framework based on enhanced deep Q-learning. First, we establish a chunkwise subjective QoE model and utilize it as the reward function in reinforcement learning so that the strategy can converge toward the direction of maximizing the subjective QoE score. Then, we apply several effective improvements of deep Q-learning to the RDQ agent’s neural network architecture and learning mechanism to achieve faster convergence and higher average reward than other learning-based methods. The proposed RDQ agent has been thoroughly evaluated using trace-based simulation on the real-time LTE network data. For disparate network scenarios and different video contents, the RDQ agent can outperform the existing methods in terms of the QoE score. The breakdown analysis shows that RDQ can suppress the number and the duration of the stalling events to the minimum while maintaining high video bitrate, thus achieving better QoE performance than other methods.

As one of the most important factors in alternative splicing (AS) events, serine/arginine-rich (SR) proteins not only participate in the growth and development of plants but also play pivotal roles in abiotic stresses. However, the research about SR proteins in cotton is still lacking. In this study, we performed an extensive comparative analysis of SR proteins and determined their phylogeny in the plant lineage. A total of 169 SR family members were identified from four Gossypium species, and these genes could be divided into eight distinct subfamilies. The domain, motif distribution and gene structure of cotton SR proteins are conserved within each subfamily. The expansion of SR genes is mainly contributed by WGD and allopolyploidization events in cotton. The selection pressure analysis showed that all the paralogous gene pairs were under purifying selection pressure. Many cis-elements responding to abiotic stress and phytohormones were identified in the upstream sequences of the GhSR genes. Expression profiling suggested that some GhSR genes may involve in the pathways of plant resistance to abiotic stresses. The WGCNA analysis showed that GhSCL-8 co-expressed with many abiotic responding related genes in a salt-responding network. The Y2H assays showed that GhSCL-8 could interact with GhSRs in other subfamilies. The subcellular location analysis showed that GhSCL-8 is expressed in the nucleus. The further VIGS assays showed that the silencing of GhSCL-8 could decrease salt tolerance in cotton. These results expand our knowledge of the evolution of the SR gene family in plants, and they will also contribute to the elucidation of the biological functions of SR genes in the future.

The combination of chemotherapy and protein therapy holds immense promise for tumor treatment. However, conventional bolus formulation or simple co-administration fails to achieve maximized efficacy due to the distinct physiological and pharmacological properties of small molecular drugs and protein therapeutics. As such, developing a co-delivery system for optimal antitumor efficacy remains a great challenge. Herein, we achieve the synergistic co-delivery of human interferon-α2b (IFN) and doxorubicin (Dox) by the facile synthesis of a multifunctional and stimuli-responsive protein-drug-polymer (PDP) conjugate IFN-PolyDox-PEP. IFN-PolyDox-PEP is constituted of IFN, a polydisulfide tethering multiple copies of Dox (PolyDox), and a stealthy polypeptide (PEP) for long circulation. IFN-PolyDox-PEP self-assembles into nanoparticles of 122 nm in diameter and is able to release its therapeutic cargos in response to tumor microenvironment cues such as matrix metalloproteinase, acidic pH, and reducing glutathione. The in vivo synergistic effect of IFN-PolyDox-PEP is demonstrated by the superior antitumor efficacy as compared with the co-administration of IFN-polypeptide conjugate and free Dox. This work demonstrates the power of highly efficient chemistry in constructing well-defined PDP conjugates, which are promising hybrid macromolecules for various chemo-protein combination therapies.