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C26H26N6O5, monoclinic, P21/c (no. 14), a = 10.9393(1) Å, b = 16.8724(2) Å, c = 13.5836(2) Å, β = 102.843(1)°, V = 2444.43(5) Å3, Z = 4, R gt(F) = 0.0318, wRref (F 2) = 0.0827, T = 173 K.

Abstract Background Predicting patient mortality risk facilitates early intervention in intensive care unit (ICU) patients at greater risk of disease progression. This study applies machine learning methods to multidimensional clinical data to dynamically predict mortality risk in ICU patients. Methods A total of 33,798 patients in the MIMIC-III database were collected. An integrated model NIMRF (Network Integrating Memory Module and Random Forest) based on multidimensional variables such as vital sign variables and laboratory variables was developed to predict the risk of death for ICU patients in four non overlapping time windows of 0–1 h, 1–3 h, 3–6 h, and 6–12 h. Mortality risk in four nonoverlapping time windows of 12 h was externally validated on data from 889 patients in the respiratory critical care unit of the Chinese PLA General Hospital and compared with LSTM, random forest and time-dependent cox regression model (survival analysis) methods. We also interpret the developed model to obtain important factors for predicting mortality risk across time windows. The code can be found in https://github.com/wyuexiao/NIMRF . Results The NIMRF model developed in this study could predict the risk of death in four nonoverlapping time windows (0–1 h, 1–3 h, 3–6 h, 6–12 h) after any time point in ICU patients, and in internal data validation, it is suggested that the model is more accurate than LSTM, random forest prediction and time-dependent cox regression model (area under receiver operating characteristic curve, or AUC, 0–1 h: 0.8015 [95% CI 0.7725–0.8304] vs. 0.7144 [95%] CI 0.6824–0.7464] vs. 0.7606 [95% CI 0.7300–0.7913] vs 0.3867 [95% CI 0.3573–0.4161]; 1–3 h: 0.7100 [95% CI 0.6777–0.7423] vs. 0.6389 [95% CI 0.6055–0.6723] vs. 0.6992 [95% CI 0.6667–0.7318] vs 0.3854 [95% CI 0.3559–0.4150]; 3–6 h: 0.6760 [95% CI 0.6425–0.7097] vs. 0.5964 [95% CI 0.5622–0.6306] vs. 0.6760 [95% CI 0.6427–0.7099] vs 0.3967 [95% CI 0.3662–0.4271]; 6–12 h: 0.6380 [0.6031–0.6729] vs. 0.6032 [0.5705–0.6406] vs. 0.6055 [0.5682–0.6383] vs 0.4023 [95% CI 0.3709–0.4337]). External validation was performed on the data of patients in the respiratory critical care unit of the Chinese PLA General Hospital. Compared with LSTM, random forest and time-dependent cox regression model, the NIMRF model was still the best, with an AUC of 0.9366 [95% CI 0.9157–0.9575 for predicting death risk in 0–1 h]. The corresponding AUCs of LSTM, random forest and time-dependent cox regression model were 0.9263 [95% CI 0.9039–0.9486], 0.7437 [95% CI 0.7083–0.7791] and 0.2447 [95% CI 0.2202–0.2692], respectively. Interpretation of the model revealed that vital signs (systolic blood pressure, heart rate, diastolic blood pressure, respiratory rate, and body temperature) were highly correlated with events of death. Conclusion Using the NIMRF model can integrate ICU multidimensional variable data, especially vital sign variable data, to accurately predict the death events of ICU patients. These predictions can assist clinicians in choosing more timely and precise treatment methods and interventions and, more importantly, can reduce invasive procedures and save medical costs.

Background: 8-oxoguanine DNA glycosylase can maintain genomic stability and integrity. However, it can interfere with the regular DNA damage repair process, possibly leading to the development of cancer and various other human diseases when its activity becomes abnormal. Current methods for detecting 8-oxoguanine DNA glycosylase activity often suffer from low sensitivity, time-consuming procedures, labor-intensive requirements, and the need for specialized equipment and trained professionals for execution. Consequently, there is an urgent need for a portable, user-friendly 8-oxoguanine DNA glycosylase assay that offers swift results and supports real-time testing. Results: We've developed a PERFUME method that combines primer exchange reaction and functionalized G-quadruplex/hemin DNAzyme for sensitive detection of Fpg, a typical 8-oxoguanine DNA glycosylase. Utilizing a single probe and T4 Polynucleotide Kinase (PNK) simplifies the experiment to a one-step reaction at 37 °C in 3 h, reducing sample consumption and improving sensitivity. We chose functionalized hemin cofactors, significantly improving catalytic efficiency and enhancing detection capability. This biosensor detects Fpg activity with a sensitivity as low as 0.11 U mL−1, displaying exceptional sensitivity, selectivity, and interference resistance in human serum and bacterial cell extracts under isothermal conditions. The biosensor demonstrates remarkable selectivity and ability for Fpg inhibitors screening. In addition, this biosensor enables reading the sample's RGB values using a smartphone, facilitating accurate quantification of Fpg activity without the necessity for specialized equipment. Significance: PERFUME simplifies Fpg detection by using a single hairpin and PNK in a one-step process. We utilize FUME to enhance catalytic efficiency, it surpassing the performance of traditional G-quadruplex/hemin DNAzyme methods. This approach excels in analyzing Fpg in human serum and bacterial extracts. It allows quantitative Fpg detection using UV–Vis and smartphones under isothermal conditions, making it valuable for clinical diagnosis.

Cotton, a vital textile raw material, is intricately linked to people’s livelihoods. Throughout the cotton cultivation process, various diseases threaten cotton crops, significantly impacting both cotton quality and yield. Deep learning has emerged as a crucial tool for detecting these diseases. However, deep learning models with high accuracy often come with redundant parameters, making them challenging to deploy on resource-constrained devices. Existing detection models struggle to strike the right balance between accuracy and speed, limiting their utility in this context. This study introduces the CDDLite-YOLO model, an innovation based on the YOLOv8 model, designed for detecting cotton diseases in natural field conditions. The C2f-Faster module replaces the Bottleneck structure in the C2f module within the backbone network, using partial convolution. The neck network adopts Slim-neck structure by replacing the C2f module with the GSConv and VoVGSCSP modules, based on GSConv. In the head, we introduce the MPDIoU loss function, addressing limitations in existing loss functions. Additionally, we designed the PCDetect detection head, integrating the PCD module and replacing some CBS modules with PCDetect. Our experimental results demonstrate the effectiveness of the CDDLite-YOLO model, achieving a remarkable mean average precision (mAP) of 90.6%. With a mere 1.8M parameters, 3.6G FLOPS, and a rapid detection speed of 222.22 FPS, it outperforms other models, showcasing its superiority. It successfully strikes a harmonious balance between detection speed, accuracy, and model size, positioning it as a promising candidate for deployment on an embedded GPU chip without sacrificing performance. Our model serves as a pivotal technical advancement, facilitating timely cotton disease detection and providing valuable insights for the design of detection models for agricultural inspection robots and other resource-constrained agricultural devices.

Corona Virus Disease 2019 (COVID-19) is a highly prevalent and potent infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Until now, the world is still endeavoring to develop new ways to diagnose and treat COVID-19. At present, the clinical prevention and treatment of COVID-19 mainly targets the spike protein on the surface of SRAS-CoV-2. However, with the continuous emergence of SARS-CoV-2 Variants of concern (VOC), targeting the spike protein therapy shows a high degree of limitation. The Nucleocapsid Protein (N protein) of SARS-CoV-2 is highly conserved in virus evolution and is involved in the key process of viral infection and assembly. It is the most expressed viral structural protein after SARS-CoV-2 infection in humans and has high immunogenicity. Therefore, N protein as the key factor of virus infection and replication in basic research and clinical application has great potential research value. This article reviews the research progress on the structure and biological function of SARS-CoV-2 N protein, the diagnosis and drug research of targeting N protein, in order to promote researchers’ further understanding of SARS-CoV-2 N protein, and lay a theoretical foundation for the possible outbreak of new and sudden coronavirus infectious diseases in the future.

ABSTRACTThe nucleocapsid protein of SARS-CoV-2 plays significant roles in viral assembly, immune evasion, and viral stability. Due to its immunogenicity, high expression levels during COVID-19, and conservation across viral strains, it represents an attractive target for antiviral treatment. In this study, we identified and characterized a single-stranded DNA aptamer, N-Apt17, which effectively disrupts the liquid-liquid phase separation (LLPS) mediated by the N protein. To enhance the aptamer’s stability, a circular bivalent form, cb-N-Apt17, was designed and evaluated. Our findings demonstrated that cb-N-Apt17 exhibited improved stability, enhanced binding affinity, and superior inhibition of N protein LLPS; thus, it has the potential inhibition ability on viral replication. These results provide valuable evidence supporting the potential of cb-N-Apt17 as a promising candidate for the development of antiviral therapies against COVID-19.IMPORTANCEVariants of SARS-CoV-2 pose a significant challenge to currently available COVID-19 vaccines and therapies due to the rapid epitope changes observed in the viral spike protein. However, the nucleocapsid (N) protein of SARS-CoV-2, a highly conserved structural protein, offers promising potential as a target for inhibiting viral replication. The N protein forms complexes with genomic RNA, interacts with other viral structural proteins during virion assembly, and plays a critical role in evading host innate immunity by impairing interferon production during viral infection. In this investigation, we discovered a single-stranded DNA aptamer, designated as N-Apt17, exhibiting remarkable affinity and specificity for the N protein. Notably, N-Apt17 disrupts the liquid-liquid phase separation (LLPS) of the N protein. To enhance the stability and molecular recognition capabilities of N-Apt17, we designed a circular bivalent DNA aptamer termed cb-N-Apt17. In both in vivo and in vitro experiments, cb-N-Apt17 exhibited increased stability, enhanced binding affinity, and superior LLPS disrupting ability. Thus, our study provides essential proof-of-principle evidence supporting the further development of cb-N-Apt17 as a therapeutic candidate for COVID-19.

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding of their impact on human health and socio-economic realms. This study delves into the anticipated implications of elevated global temperatures, specifically the 1.5 and 2.0 °C warming scenarios under the SSP2-4.5 and SSP5-8.5 pathways, on population and GDP exposure to heatwaves in China. We also evaluated the aggregated impacts of climate, population, and GDP and their interactions on future socio-economic exposure across China. We leveraged data sourced from the climatic output of Coupled Model Intercomparison Project Phase 6 (CMIP6) for heatwave analysis and integrated population and GDP projections under divergent Shared Socio-economic Pathways (SSPs), including SSP2-4.5 (low emission) and SSP5-8.5 (high-emission). Results indicate a drastic surge in the number of heatwave days under both warming scenarios, particularly in regions like Xinjiang (XJ), North China (NC), and South China (SC) subregions, with a notable disparity in the elevation of heatwave days among different levels. There is an alarming surge in population exposure, escalating approximately 7.94–8.70 times under the 1.5 °C warming scenario and markedly increasing by 14.48–14.75 times by the 2100s relative to the baseline (1985–2014) under the more extreme 2.0 °C warming level. Likewise, the study unveils a substantial elevation in GDP exposure, ranging from 40.65 to 47.21 times under the 1.5 °C warming level and surging dramatically by 110.85–113.99 times under the 2.0 °C warming level. Further analyses disclose that the climate effect predominantly influences changes in population exposure, constituting 72.55–79.10% of the total change. Meanwhile, the interaction effect notably shapes GDP exposure alterations, contributing 77.70–85.99% to the total change. The comprehensive investigation into alterations in population and GDP exposure under varying warming scenarios, coupled with the quantification of each contributing factor, holds paramount importance in mitigating the detrimental repercussions of heatwaves on both human life and socio-economic landscapes.

During the normal laying and operation of a three-core umbilical cable, AC current can easily lead to AC electrochemical corrosion on the outer surface of the steel tube. To explore the electrochemical corrosion mechanism and the factors affecting the three-core umbilical cable, this paper optimizes the internal induced potential calculation method for three-core umbilical cables. It analyzes the changes in the characteristics of the induced potential and explores the variations in the density of induced current under different conditions. The research results show that by optimizing the calculation method for the induction potential of the umbilical cable’s steel pipe, for the electromagnetic significance of the smallest repeating unit, the induction potential on the steel pipe’s surface exhibited a cyclic change. The peak part of the induction potential is most likely to experience electrochemical corrosion. Additionally, reducing the radius of the outer insulation aperture of the steel pipe and improving the conductivity of seawater will increase the density of the induced current in the insulation aperture, thereby increasing the risk of electrochemical corrosion. As the cable pitch and AC frequency increase, the current density in the steel pipe pores will also rise.

Annually, more than 15 million people worldwide suffer from stroke, a condition linked to high mortality and disability rates. This disease significantly affects daily life, impairing everyday functioning, executive function, and cognition. Moreover, stroke severely restricts patients’ ability to perform daily activities, diminishing their overall quality of life. Recent scientific studies have identified cuproptosis, a newly discovered form of cell death, as a key factor in stroke development. However, the role of cuproptosis in stroke remains unclear to researchers. Therefore, it is crucial to investigate the mechanisms of cuproptosis in stroke’s pathogenesis. This review examines the physiological role of copper, the characteristics and mechanisms of cuproptosis, the differences and similarities between cuproptosis and other cell death types, and the pathophysiology of cuproptosis in stroke, focusing on mitochondrial dysfunction and immune infiltration. Further research is necessary to understand the relationship between previous strokes and cuproptosis and to clarify the mechanisms behind these associations.

Abstract Background Gastric cardia adenocarcinoma (GCA) is classified as Siewert type II adenocarcinoma at the esophagogastric junction in Western countries. The majority of GCA patients do not exhibit early warning symptoms, leading to over 90% of diagnoses at an advanced stage, resulting in a grim prognosis, with less than a 20% 5‐year survival rate. Method Metabolic features of 276 GCA and 588 healthy controls were characterized through a widely‐targeted metabolomics by UPLC‐MS/MS analysis. This study encompasses a joint pathway analysis utilizing identified metabolites, survival analysis in both early and advanced stages, as well as high and negative and low expression of HER2 immunohistochemistry staining. Machine learning techniques and Cox regression models were employed to construct a diagnostic panel. Results A total of 25 differential metabolites were consistently identified in both discovery and validation sets based on criteria of p

The inhalation of zinc chloride (ZnCl2) smoke is one of common resources of lung injury, potentially resulting in severe pulmonary complications and even mortality. The influence of ZnCl2 smoke on lysine succinylation (Ksucc) in the lungs remains uncertain. In this study, we used a ZnCl2 smoke inhalation mouse model to perform global proteomic and lysine succinylome analyses. A total of 6781 Ksucc sites were identified in the lungs, with injured lungs demonstrating a reduction to approximately 2000 Ksucc sites, and 91 proteins exhibiting at least five differences in the number of Ksucc sites. Quantitative analysis revealed variations in expression of 384 proteins and 749 Ksucc sites. The analysis of protein-protein interactions was conducted for proteins displaying differential expression and differentially expressed lysine succinylation. Notably, proteins with altered Ksucc exhibited increased connectivity compared with that in differentially expressed proteins. Beyond metabolic pathways, these highly connected proteins were also involved in lung injury-associated pathological reactions, including processes such as focal adhesion, adherens junction, and complement and coagulation cascades. Collectively, our findings contribute to the understanding of the molecular mechanisms underlaying ZnCl2 smoke-induced lung injury with a specific emphasis on lysine succinylation. These findings could pave the way for targeted interventions and therapeutic strategies to mitigate severe pulmonary complications and mortality associated with such injuries in humans.

Water droplets containing the SARS-CoV-2 virus, responsible for coronavirus 2019 transmission, were introduced into a controlled-temperature and -humidity chamber. The SARS-CoV-2 virus with green fluorescent protein tag in droplets was used to infect Caco-2 cells, with viability assessed through flow cytometry and microscopic counting. Whereas temperature fluctuations within typical indoor ranges (20°C–30°C) had minimal impact, we observed a notable decrease in infection rate as the surrounding air’s relative humidity increased. By investigating humidity levels between 20% and 70%, we identified a threshold of ≥40% relative humidity as most effective in diminishing SARS-CoV-2 infectivity. We also found that damage of the viral proteins under high relative humidity may be responsible for the decrease in their activity. This outcome supports previous research demonstrating a rise in the concentration of reactive oxygen species within water droplets with elevated relative humidity.

During the compaction process of HMA pavement, it is common to spray cold water on the wheel of a road roller to prevent the mixture from sticking to the wheel, which might deteriorate the bonding strength between the asphalt binder and aggregate, and consequently lead to surface polishing of the pavement. This paper aims to demonstrate whether the water used during the compaction process affects the surface performance of HMA pavement. In this study, the black pixel ratio and mass loss ratio were used to evaluate the water effect on the surface performance of asphalt pavement, considering the water consumption, molding temperature and long-term ageing process. The test results indicated that the water used during the compaction process would increase the risk of surface polishing of HMA pavement. This adverse effect became more significant if the HMA samples were prepared using greater water consumption, a greater molding temperature and a long-term ageing process. Moreover, there exists a certain correlation between the black pixel ratio and mass loss ratio, and their relationships were demonstrated by the experimental results in this study. It is recommended that further research concentrates on the influencing mechanism and the treatment strategy for the adverse effect caused by the water used during the compaction process. The use of more types of asphalt binders, aggregate and methodologies is also recommended in further studies.

Regeneration agents play a critical role in modifying the mechanical properties and durability of RAP asphalt mixtures. This paper aimed to develop a castor oil-based asphalt regeneration agent. The effects of this regeneration agent on the pavement performance of laboratory-aged asphalt and an RAP asphalt mixture were comparatively studied by a series of laboratory tests. For the developed castor oil-based asphalt regeneration agent, the weight ratio of the castor oil to dibutyl phthalate was determined as 1:4. Moreover, the regeneration effectiveness of the castor oil-based regeneration agent was tested on three laboratory-aged asphalt binders and an RAP asphalt binder; the penetration, softening point and ductility of the RAP asphalt binder recovered to 83 dmm, 50.3 °C, and more than 100 cm, respectively. The optimum content of the regeneration agent was 5% by the weight of the aged asphalt binder. Furthermore, the castor oil-based regeneration agent could effectively restore the pavement performance of an RAP asphalt mixture. In this study, the RAP percentage can reach up to 60% by the weight of the HMA mixture using the castor oil-based asphalt regeneration agent according to the Chinese specification.

Abstract Background The teaching of critical care medicine is a very important task, especially during the COVID-19 pandemic. The understanding of critical care parameters is the foundation and core, which is conducive to the formation of clinical thinking. This study is to evaluate the training effect of teaching of critical care parameters based on an online platform, and explore the teaching methods of critical care medicine that can help to cultivate trainees’ clinical thinking and practical ability. Methods Questionnaires were released before and after the training through the official new media platform “Yisheng” application (APP) of China Medical Tribune involving 1109 participants. The trainees who filled in the questionnaire in APP and received training were randomly selected as the investigated population. Statistical description and analysis were carried out using SPSS 20.0 and Excel 2020. Results The trainees were mainly attending physicians in tertiary hospitals and above. Among all critical care parameters, trainees paid more attention to critical hemodynamics, respiratory mechanics, severity of illness scoring systems, critical ultrasound, and critical hemofiltration. The degree of satisfaction with the courses was high, especially the course of critical hemodynamics was scored the highest. The trainees believed that the course contents were of great help to clinical work. However, no significant difference was found in the trainees’ understanding or cognition of the connotation of the parameters before and after the training. Conclusion Teaching of critical care parameters based on an online platform is conducive to improving and consolidating the clinical care ability of trainees. However, it is still necessary to strengthen the cultivation of clinical thinking in critical care. In the future, the integration of theory with practice must be strengthened in clinical practice, ultimately achieving the homogeneous diagnosis and treatment of patients with critical illness.

Abstract Viral infection in respiratory tract usually leads to cell death, impairing respiratory function to cause severe disease. However, the diversity of clinical manifestations of SARS-CoV-2 infection increases the complexity and difficulty of viral infection prevention, and especially the high-frequency asymptomatic infection increases the risk of virus transmission. Studying how SARS-CoV-2 affects apoptotic pathway may help to understand the pathological process of its infection. Here, we uncovered SARS-CoV-2 imployed a distinct anti-apoptotic mechanism via its N protein. We found SARS-CoV-2 virus-like particles (trVLP) suppressed cell apoptosis, but the trVLP lacking N protein didn’t. Further study verified that N protein repressed cell apoptosis in cultured cells, human lung organoids and mice. Mechanistically, N protein specifically interacted with anti-apoptotic protein MCL-1, and recruited a deubiquitinating enzyme USP15 to remove the K63-linked ubiquitination of MCL-1, which stabilized this protein and promoted it to hijack Bak in mitochondria. Importantly, N protein promoted the replications of IAV, DENV and ZIKV, and exacerbated death of IAV-infected mice, all of which could be blocked by a MCL-1 specific inhibitor, S63845. Altogether, we identifed a distinct anti-apoptotic function of the N protein, through which it promoted viral replication. These may explain how SARS-CoV-2 effectively replicates in asymptomatic individuals without cuasing respiratory dysfunction, and indicate a risk of enhanced coinfection with other viruses. We anticipate that abrogating the N/MCL-1-dominated apoptosis repression is conducive to the treatments of SARS-CoV-2 infection as well as coinfections with other viruses.

This study aims to prepare the self-luminous pavement marking (SLPM) to enhance driving safety and reduce the risk of traffic accident. Firstly, the composition of the SLPM was determined by the mechanical properties and luminous performance tests. The optimal mass proportions of epoxy resin, toughening agent, curing agent, curing accelerator, luminous powder, reflective powder, glass bead and glass powder was 1.0:0.1:0.3:0.006:0.4:0.3:0.25:0.55. In addition, test results showed that the SLPM has satisfactory mechanical properties, durability and luminous performance, which met the engineering requirements for practical application. The afterglow time was more than 11 h at night in laboratory test. Moreover, it is feasible to prepare different colors of the SLPM according to the RGP principle. The afterglow color and luminous intensity of SLPM strongly depend on the luminous material and its proportions. Overall, this paper provides a reference for designing and applying SLPM materials in road engineering.

AbstractObjective To explore a machine learning model for the early prediction of acute kidney injury (AKI) and to screen the related factors affecting new-onset AKI in the ICU.Methods A retrospective analysis was performed used the MIMIC-III data source. New onset of AKI defined based on the serum creatinine changed. We included 19 variables for AKI assessment using four machine learning models: support vector machines, logistic regression, and random forest. and XGBoost, using accuracy, specificity, precision, recall, F1 score, and AUROC (area under the ROC curve) to evaluate model performance. The four models predicted new-onset AKI 3–6–9–12 h ahead. The SHapley Additive exPlanation (SHAP) value is used to evaluate the feature importance of the model.Results We finally respectively extracted 1130 AKI patients and non-AKI patients from the MIMIC-III database. With the extension of the early warning time, the prediction performance of each model showed a downward trend, but the relative performance was consistent. The prediction performance comparison of the four models showed that the XGBoost model performed the best in all evaluation indicators in all the time point at new-onset AKI 3–6–9–12 h ahead (accuracy 0.809 vs 0.78 vs 0.744 vs 0.741, specificity 0.856 vs 0.826 vs 0.797 vs 0.787, precision 0.842 vs 0.81 vs 0.775 vs 0.766, recall 0.759 vs 0.734 vs 0.692 vs 0.694, Fl score 0.799 vs 0.769 vs 0.731 vs 0.729, AUROC 0.892 vs 0.857 vs 0.827 vs 0.818). In the prediction of AKI 6, 9 and 12 h ahead, the importance of creatinine, platelets, and height was the most important based on SHapley.Conclusions The machine learning model described in this study can predict AKI 3–6–9–12 h before the new-onset of AKI in ICU. In particular, platelet plays an important role.Key messageThe new-onset of AKI in ICU is a common and important problem, which early be identified the risk of AKI can improve patients’ outcomes.We explored MIMIC-III and determined the exact time point of occurrence of AKI as the basis for the new-onset of AKI in ICU.XGBoost model performed the best prediction in all the time point at new-onset AKI 3–6–9–12 h ahead.For patients with the new-onset of AKI in ICU, platelets become an important factor associated with AKI.

Vermicompost is a promising amendment for immobilization of cadmium (Cd) in soils; however, its effectiveness can be influenced by rhizosphere environment conditions, such as pH and the presence of low-molecular-weight organic acids (LMWOAs). In this study, a batch experiment was conducted to examine the characteristics of Cd adsorption by vermicompost at different pH (pH = 3, 5, and 7) and after the addition of different LMWOAs (oxalic acid; citric acid; malic acid). Furthermore, a series of morphology and structural analyses were conducted to elucidate the mechanisms of observed effects. The results showed that the adsorption capacity of vermicompost for Cd increased as pH increased, and chemisorption dominated the adsorption process. Changes in pH altered adsorption performance by affecting the -OH groups of alcohol/phenol and the -CH2 groups of aliphatics. Further, the addition of oxalic acid promoted Cd adsorption, and the effect was concentration dependent. Modifying the verimicompost surface with more adsorption sites might be the main reason. Conversely, citric acid and malic acid showed the ability to inhibit Cd adsorption by vermicompost. Citric acid caused a blocking effect by covering flocculent substances on the vermicompost surface while reducing surface adsorption sites by dissolving mineral components such as iron oxides. However, the action of malic acid did not appear to be related to changes in morphology or the structure of vermicompost. Overall, the results of this study partially explain the limited effectiveness of Cd immobilization within the rhizosphere by vermicompost, and provide theoretical support for regulating rhizosphere environments to improve the effectiveness of vermicompost immobilization of Cd.

Wild rice, a natural gene pool for rice germplasm innovation and variety improvement, holds immense value in rice breeding due to its disease-resistance genes. Traditional disease resistance identification in wild rice heavily relies on labor-intensive and subjective manual methods, posing significant challenges for large-scale identification. The fusion of unmanned aerial vehicles (UAVs) and deep learning is emerging as a novel trend in intelligent disease resistance identification. Detecting diseases in field conditions is critical in intelligent disease resistance identification. In pursuit of detecting bacterial blight in wild rice within natural field conditions, this study presents the Xoo-YOLO model, a modification of the YOLOv8 model tailored for this purpose. The Xoo-YOLO model incorporates the Large Selective Kernel Network (LSKNet) into its backbone network, allowing for more effective disease detection from the perspective of UAVs. This is achieved by dynamically adjusting its large spatial receptive field. Concurrently, the neck network receives enhancements by integrating the GSConv hybrid convolution module. This addition serves to reduce both the amount of calculation and parameters. To tackle the issue of disease appearing elongated and rotated when viewed from a UAV perspective, we incorporated a rotational angle (theta dimension) into the head layer's output. This enhancement enables precise detection of bacterial blight in any direction in wild rice. The experimental results highlight the effectiveness of our proposed Xoo-YOLO model, boasting a remarkable mean average precision (mAP) of 94.95%. This outperforms other models, underscoring its superiority. Our model strikes a harmonious balance between accuracy and speed in disease detection. It is a technical cornerstone, facilitating the intelligent identification of disease resistance in wild rice on a large scale.

With the continuous development of space station construction, space ecosystem research has attracted increasing attention. However, the complicated responses of different candidate plants and algae to radiation stress remain unclear. The present study, using integrated physiologic and proteomic analyses, was carried out to reveal the molecular mechanism of Navicula sp. in response to ultraviolet (UV) irradiation stress. Under 12~24 h of high-dose UV irradiation conditions, the contents of chlorophyll and soluble proteins in Navicula sp. cells were significantly higher than those in the control and 4~8 h of low-dose UV irradiation groups. The activity of catalase (CAT) increased with the extension of irradiation time, and the activity of superoxide dismutase (SOD) decreased first and then increased. Furthermore, differential volcano plot analysis of the proteomic data of Navicula sp. samples found only one protein with a significant difference. Differential protein GO analysis unveiled that UV irradiation can activate the antioxidant system of Navicula sp. and further impact photosynthesis by affecting the photoreaction and chlorophyll synthesis of Navicula sp. The most significant differences in KEGG pathway analysis were also associated with photosynthesis. The above results indicate that Navicula sp. has good UV radiation resistance ability by regulating its photosynthetic pigment content, photosynthetic activity, and antioxidant system, making it a potential candidate for the future development of space ecosystems.

Acute Respiratory Distress Syndrome (ARDS) is a sudden onset of lung injury characterized by bilateral pulmonary edema, diffuse inflammation, hypoxemia, and a low P/F ratio. Epithelial injury and endothelial injury are notable in the development of ARDS, which is more severe under mechanical stress. This review explains the role of alveolar epithelial cells and endothelial cells under physiological and pathological conditions during the progression of ARDS. Mechanical injury not only causes ARDS but is also a side effect of ventilator-supporting treatment, which is difficult to model both in vitro and in vivo. The development of lung organoids has seen rapid progress in recent years, with numerous promising achievements made. Multiple types of cells and construction strategies are emerging in the lung organoid culture system. Additionally, the lung-on-a-chip system presents a new idea for simulating lung diseases. This review summarizes the basic features and critical problems in the research on ARDS, as well as the progress in lung organoids, particularly in the rapidly developing microfluidic system-based organoids. Overall, this review provides valuable insights into the three major factors that promote the progression of ARDS and how advances in lung organoid technology can be used to further understand ARDS.

NLRP3 inflammasome mainly controls interleukin-1β (IL-1β) secretion, leading to cell death called pyroptosis constituting a major antiviral host defense and inflammatory diseases upon viral infection. The RAF-MEK1/2-ERK1/2 cascade and downstream c-Jun/Fos and Activator protein-1 (AP1) signaling pathway control the degree of inflammatory response. Influenza A virus (IAV) infection is known to stimulate NLRP3 inflammasome activation and inflammatory responses. Nevertheless, the detailed mechanism by which IAV induces NLRP3 inflammasome activation involved in transcription of pro-IL-1β mRNA remains elusive. In our study, we found that IAV infection promotes pro-IL-1β mRNA transcription and activates NLRP3 inflammasome. Detailed studies reveal that type I interferon (IFN-α/IFN-β) as well as U0126 (a selective inhibitor of MEK-1 and MEK-2) typically inhibit IAV-mediated NLRP3 inflammasome activation via downregulating pro-IL-1β mRNA. Moreover, knock-down of c-Jun decreases pro-IL-1β mRNA and inhibits NLRP3 inflammasome activation upon IAV infection. Overall, the findings uncover that AP-1 signaling pathway promotes NLRP3 inflammasome activation upon IAV infection, which provides a new idea for the therapy of NLRP3 inflammasome-associated inflammatory diseases.

Smoke bombs are often used in military/fire training, which can produce a large amount of zinc chloride (ZnCl2) smoke. Inhalation of ZnCl2 smoke usually causes acute lung injury (ALI) that would likely develop to acute respiratory distress syndrome (ARDS). However, there is no effective prevention or treatment strategy for the smoke-induced ALI. Resveratrol (RES) is a natural polyphenol with good anti-inflammatory and anti-apoptotic activities, but its low solubility, stability, and bioavailability restrict its clinical application. In this study, an inhalable RES formulation composed of RES-β-cyclodextrin inclusion complexes (RES-β-CD) was prepared for the prevention of ZnCl2 smoke-induced ALI. RES-β-CD powders had a small mass median aerodynamic diameter of 3.61 μm and a high fine particle fraction of 38.84%, suitable for pulmonary inhalation. RES-β-CD exhibited low BEAS-2B cytotoxicity. Pulmonary delivery of RES-β-CD to mice remarkably prevented the smoke-induced ALI with downregulation of TNF-α, IL-1β, STAT3, and GATA3, and upregulation of T-bet and Foxp3. RES-β-CD protected the respiratory function, percutaneous oxygen saturation, physical activity, lung capillary integrity, and lung liquid balance, alleviating inflammation and apoptosis. Pulmonary delivery of the positive drug, budesonide (BUD), also alleviated the smoke-induced ALI by reduction of inflammation and cell apoptosis. RES-β-CD exhibited the regulation of the Th1/Th2 and Treg/Th17 balances, while BUD did not show any effect on immune balances. In conclusion, pulmonary delivery of RES-β-CD is a promising anti-inflammatory and anti-apoptosis strategy for the prevention of ZnCl2 smoke-induced ALI by direct lung drug distribution and regulation of immune balance.

Aiming at the problem that the puncture drag of the medical suture needle produced in the suture process will cause damage to the soft tissue,and the greater the puncture drag is,the higher the damage degree is,a biomimetic model of low-drag medical suture needle was proposed.The biomimetic prototype of low-drag medical suture needle was constructed,and its needle tip taper/radius and needle body curvature were designed based on the morphological/structural characteristics of the thorn in Ziziphus jujube,and vertical stripe grooves were set on the needle body,forming the biomimetic model of low-drag medical suture needles.LS-DYNA software and Coulomb friction model were used to simulate the process of biomimetic low-drag medical suture needle penetrating skin soft tissue.The results show that the needle body with vertical stripe grooves can reduce the puncture drag of low-drag medical suture needle with the thorn tip taper/radius and the thorn body curvature by 34.24%~58.48%,and can reduce the puncture drag of low-drag medical suture needle with the thorn tip taper/radius by 30.26%~49.86%.The biomimetic low-drag medical suture needles were fabricated and their puncture drag was experimentally tested.In the penetrating process,the puncture drag of biomimetic low-drag medical suture needle was reduced by 43.02%.The results reveal the influence mechanism of the morphological/structural characteristics of medical suture needle on its puncture drag,and provide a theoretical reference for the biomimetic design of low-drag medical suture needle.

Abstract This study proposes a novel network model for video action tube detection. This model is based on a location-interactive weakly supervised spatial–temporal attention mechanism driven by multiple loss functions. It is especially costly and time consuming to annotate every target location in video frames. Thus, we first propose a cross-domain weakly supervised learning method with a spatial–temporal attention mechanism for action tube detection. In source domain, we trained a newly designed multi-loss spatial–temporal attention–convolution network on the source data set, which has both object location and classification annotations. In target domain, we introduced internal tracking loss and neighbor-consistency loss; we trained the network with the pre-trained model on the target data set, which only has inaccurate action temporal positions. Although this is a location-unsupervised method, its performance outperforms typical weakly supervised methods, and even shows comparable results with some recent fully supervised methods. We also visualize the activation maps, which reveal the intrinsic reason behind the higher performance of the proposed method.

Numerous genetic variants associated with Alzheimer’s disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.

Allogeneic Hematopoietic stem cell transplantation (HSCT) offers a potential cure for patients with hematologic malignancies. Unfortunately, graft-versus-host disease (GVHD) remains a major obstacle to the greater success of this treatment. Despite intensive research efforts over the past several decades, GVHD is still a major cause of morbidity and mortality in patients receiving allogeneic HSCT. The genetic disparity between donor and recipient is the primary factor that dictates the extent of alloimmune response and the severity of acute GVHD (aGVHD). However, some nongenetic factors are also actively involved in GVHD pathogenesis. Thus, identifying host factors that can be readily modified to reduce GVHD risk is of important clinical significance. We are particularly interested in the potential role of nutrition, as a nongenetic factor, in the etiology and management of aGVHD. In this article, we summarize recent findings regarding how different routes of nutritional support and various dietary factors affect aGVHD. Since diet is one of the most important factors that shape gut microbiota, we also provide evidence for a potential link between certain nutrients and gut microbiota in recipients of allogeneic HSCT. We propose a shifting role of nutrition from support to therapy in GVHD by targeting gut microbiota.

Severe COVID-19 patients exhibit impaired IFN-I response due to decreased IFN-β production, allowing persistent viral load and exacerbated inflammation. While the SARS-CoV-2 nucleocapsid (N) protein has been implicated in inhibiting innate immunity by interfering with IFN-β signaling, the specific underlying mechanism still needs further investigation for a comprehensive understanding. This study reveals that the SARS-CoV-2 N protein enhances interaction between the human SUMO-conjugating enzyme UBC9 and MAVS. Increased MAVS-UBC9 interaction leads to enhanced SUMOylation of MAVS, inhibiting its ubiquitination, resulting in the inhibition of phosphorylation events involving IKKα, TBK1, and IRF3, thus disrupting IFN-β signaling. This study highlights the role of the N protein of SARS-CoV-2 in modulating the innate immune response by affecting the MAVS SUMOylation and ubiquitination processes, leading to inhibition of the IFN-β signaling pathway. These findings shed light on the complex mechanisms utilized by SARS-CoV-2 to manipulate the host’s antiviral defenses and provide potential insights for developing targeted therapeutic strategies against severe COVID-19.

BackgroundThis study was intended to construct a brand new prognostic nomogram after combine clinical and pathological characteristics to increases prognostic value in patients with esophageal squamous cell carcinoma.MethodsA total of 1,634 patients were included. Subsequently, the tumor tissues of all patients were prepared into tissue microarrays. AIPATHWELL software was employed to explore tissue microarrays and calculate the tumor-stroma ratio. X-tile was adopted to find the optimal cut-off value. Univariate and multivariate Cox analyses were used to screen out remarkable characteristics for constructing the nomogram in the total populations. A novel prognostic nomogram with clinical and pathological characteristics was constructed on the basis of the training cohort (n=1,144). What’s more performance was validated in the validation cohort (n=490). Clinical-pathological nomogram were assessed by concordance index, time-dependent receiver operating characteristic, calibration curve and decision curve analysis.ResultsThe patients can divide into two groups with cut-off value of 69.78 for the tumor-stroma ratio. It is noteworthy that the survival difference was noticeable (P

Objective: The present study was developed to explore the impact of acupuncture on the Th17/Treg balance in the brain and the periphery and associated changes in cognitive deficits in a rat model of vascular dementia (VD). Methods: Male Wistar rats (8 weeks old) were randomly assigned to sham-operated (Gs, n = 10), and operation (n = 30) groups. A VD model was established for all rats in the operation group via the permanent bilateral occlusion of the common carotid artery. Behavioral screening of these rats was conducted via a hidden platform trial at 2 months post-operation. These operation group rats were then further subdivided into impaired (Gi) and acupuncture (Ga) groups (n = 10/group). Acupuncture was performed over a 21-day period for rats in the Ga group. A Morris water maze (MWM) test was used to assess cognitive function for rats in all groups. Flow cytometry and fluorescent staining were used to detect Th17 and Treg cells in samples from these animals based on IL-17/FoxP3 or CD4+FoxP3+/CD4+RORγt+ staining profiles. Results: Relative to the Gs group, escape latency values for rats in the Gi group were significantly increased. Following treatment, rats in the Ga group exhibited significant reductions in escape latency values as compared to rats in the Gi group (P 0.05), whereas the frequency of Th17 cells in the peripheral blood and spleen of Ga group rats trended downward relative to the Gi group (P > 0.05). Significantly fewer CD4+RORγt+ and RORγt+ cells were detected in the Ga group relative to the Gi group, whereas CD4+FoxP3+ and FoxP3+ cell counts were increased (P

BackgroundThe antiviral activity and underlying mechanism of Patchouli alcohol remain unclear.MethodsThis study evaluated the cytotoxicity, optimal methods for drug administration, anti-influenza A activity of Patchouli alcohol. The antiviral mechanism of Patchouli alcohol was also assessed via qRT-PCR, western blot, hemagglutination inhibiting (HAI) assay, and hemolysis inhibiting assay.ResultsPatchouli alcohol was shown to have low cytotoxicity and its strongest antiviral effect was associated with premixed administration. Patchouli alcohol inhibited virus replication during the early lifecycle stages of influenza A virus infection and specifically prevented expression of the viral proteins, HA and NP. In both the HAI and hemolysis inhibiting assays, Patchouli alcohol was able to block HA2-mediated membrane fusion under low pH conditions. Patchouli alcohol had lower binding energy with HA2 than HA1.ConclusionThese findings suggest that Patchouli alcohol could be a promising membrane fusion inhibitor for the treatment of influenza A infection.

A compact and reliable thin-core fiber (TCF) based in-line Mach-Zehnder interferometric (MZI) sensor for refractive index (RI) measurement is proposed and experimentally demonstrated. A section of TCF is sandwiched between a multi-mode fiber (MMF) and a single-mode fiber (SMF) to form the sensing head. In addition, the use of the differential intensity demodulation method not only greatly reduces the system cost, but also solves the problem of power fluctuation in the RI interrogation system. Three samples with different sensing lengths have been made, and the maximum sensitivity of 59.9 dB/RIU has been obtained in the range of 1.332–1.411 RIU, which means the measurement resolution is about 1.669 × 10−4 RIU. Besides, the proposed MZI-based RI sensor is less sensitive to temperature, thus the cross-sensitivity effect can be greatly weakened.

Abstract Background In sepsis, vitamin D binding protein (VDBP) has been shown to be low-expressed. The current study examined the relationship between serum VDBP level and liver injury in sepsis patients, as well as in a mouse model for sepsis and in cultured liver epithelial cell line exposed to lipopolysaccharide (LPS). Methods The human study included 78 sepsis patients and 50 healthy volunteers. Sepsis patients were categorized into sepsis survivor group (n = 43) and sepsis non-survivor group (n = 35) based on 28-day mortality for data analysis. Adult male C57BL/6 mice were subjected to cecal ligation and puncture (CLP). Serum samples were collected on day 1, 3, 5 and 7 to determine the levels of VDBP, 25-hydroxyvitamin D [25(OH)D3], 1,25-dihydroxyvitamin D [1,25(OH)2D3], interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α). Potential protective effects of VDBP overexpression against LPS-induced liver damage were examined in cultured THLE2 cells. Results Serum levels of VDBP, 25(OH)D3, and 1,25(OH)2D3 were significantly lower in sepsis patients vs. the healthy control (P

It is with deep sorrow that we mourn the passing of the virologist Professor Jianguo Wu [...]

Utilizing brake pad waste (BPW) in asphalt mixture can not only reduce the consumption of natural mineral material, but also alleviate the environmental pollution problem caused by such solid waste. This paper concentrates on the feasibility and strategy of using BPW as aggregate in asphalt mixture. Firstly, BPW aggregate within five different particle sizes were separately used to replace the limestone aggregate or filler with different proportions (25%, 50%, 75% and 100%) in asphalt mixture by the volume control method. The corresponding optimum asphalt contents of 21 kinds of asphalt mixtures were determined by the Marshall design procedure. Due to its high asphalt-absorption, BPW aggregate would increase the optimum asphalt content of asphalt mixture, which depends on the particle size of BPW aggregate. To meet the Chinese Standard Specification for asphalt mixture, the maximum substitution proportions for the BPW aggregates of 0–0.075 mm, 0.075–2.36 mm, 2.36–4.75 mm, 4.75–9.5 mm, 9.5–16 mm were 75%, 50%, 25%, 100%, and 100%, respectively. On this basis, BPW mixture simultaneously using the BPW aggregate with different sizes and the corresponding maximum substitution proportions were prepared and evaluated by a series of laboratory tests as well. Results implied that BPW mixture (BPW-M) outperformed the limestone asphalt mixture (Control-M) in term of the moisture stability, the high-temperature performance, the low-temperature property, and the fatigue life. Furthermore, dynamic modulus test results indicated that BPW-M mixture was more stiffness at relative low frequency (high temperature) and more flexible at relative high frequency (low temperature). Overall, this study verifies the feasibility and provides a reference datum of using BPW materials as aggregate in asphalt mixture.

Human enterovirus 71 (EV71) is one of the major agents of the hand, foot, and mouth disease (HFMD), and occasionally causes severe neurological complications. There is clinical evidence that EV71 infection increases the exosomes in the serum of severe HFMD patients, suggesting a role of exosomes in EV71 pathogenesis. However, the relationship between exosomes and EV71 replication remains elusive. In this study, we initially found that EV71 infection elevated exosome biogenesis in the cultured cells. Among EV71 non-structural proteins, we identified EV71 3A, but not 3B, constitutively promoted exosome secretion. In detail, EV71 3A protein interacted with vacuolar protein sorting 25 (VPS25), while knock-down of VPS25 reduced EV71 3A protein- and EV71-induced exosome production. Further studies revealed VPS25 located on exosomes and its expression correlated to the exosome production. During EV71 infection, knock-down of VPS25 decreased exosome biogenesis to attenuate viral replication. Consistently, GW4869, an exosome inhibitor, exerted an obviously antiviral activity against EV71 replication companied with the decrease of exosome secretion or formation. These findings suggest the binding of EV71 3A and VPS25 benefited exosome biogenesis, thereby boosting viral replication. This study uncovers a novel mechanism underlying EV71-mediated exosomes in the regulation of viral replication, which provides potential anti-viral strategies against the EV71 infection and transmission in HFMD.

Abstract. Acute respiratory distress syndrome (ARDS) is one of the most common severe diseases seen in the clinical setting. With the continuous exploration of ARDS in recent decades, the understanding of ARDS has improved. ARDS is not a simple lung disease but a clinical syndrome with various etiologies and pathophysiological changes. However, in the intensive care unit, ARDS often occurs a few days after primary lung injury or after a few days of treatment for other severe extrapulmonary diseases. Under such conditions, ARDS often progresses rapidly to severe ARDS and is difficult to treat. The occurrence and development of ARDS in these circumstances are thus not related to primary lung injury; the real cause of ARDS may be the “second hit” caused by inappropriate treatment. In view of the limited effective treatments for ARDS, the strategic focus has shifted to identifying potential or high-risk ARDS patients during the early stages of the disease and implementing treatment strategies aimed at reducing ARDS and related organ failure. Future research should focus on the prevention of ARDS.

Abstract Cytokine storm induced by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a major pathological feature of Coronavirus Disease 2019 (COVID-19) and a crucial determinant in COVID-19 prognosis. Understanding the mechanism underlying the SARS-CoV-2-induced cytokine storm is critical for COVID-19 control. Here, we identify that SARS-CoV-2 ORF3a and host hypoxia-inducible factor-1α (HIF-1α) play key roles in the virus infection and pro-inflammatory responses. RNA sequencing shows that HIF-1α signaling, immune response, and metabolism pathways are dysregulated in COVID-19 patients. Clinical analyses indicate that HIF-1α production, inflammatory responses, and high mortalities occurr in elderly patients. HIF-1α and pro-inflammatory cytokines are elicited in patients and infected cells. Interestingly, SARS-CoV-2 ORF3a induces mitochondrial damage and Mito-ROS production to promote HIF-1α expression, which subsequently facilitates SARS-CoV-2 infection and cytokines production. Notably, HIF-1α also broadly promotes the infection of other viruses. Collectively, during SARS-CoV-2 infection, ORF3a induces HIF-1α, which in turn aggravates viral infection and inflammatory responses. Therefore, HIF-1α plays an important role in promoting SARS-CoV-2 infection and inducing pro-inflammatory responses to COVID-19.

A simple and efficient cross-coupling of aryl halides with different alkyl disulfides under mild conditions was developed. This C–S bond formation method was carried out in the absence of transition-metal and external photosensitizer under air. Excellent yields were obtained with a broad substrate scope under mild conditions, tolerating various functional groups.

SARS-CoV-2 infection has been shown to drive NLRP3 inflammasome activation and thereby cytokine storm, but how it does so is unclear. Here the authors show that the viral N protein can bind to NLRP3, resulting in enhanced interaction with ASC and thereby with the NLRP3 inflammasome.