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BackgroundEarly neurological deterioration (END) is a frequent complication in patients with perforating artery territory infarction (PAI), leading to poorer outcomes. Therefore, we aimed to apply machine learning (ML) algorithms to predict the occurrence of END in PAI and investigate related risk factors.MethodsThis retrospective study analyzed a cohort of PAI patients, excluding those with severe stenosis of the parent artery. We included demographic characteristics, clinical features, laboratory data, and imaging variables. Recursive feature elimination with cross-validation (RFECV) was performed to identify critical features. Seven ML algorithms, namely logistic regression, random forest, adaptive boosting, gradient boosting decision tree, histogram-based gradient boosting, extreme gradient boosting, and category boosting, were developed to predict END in PAI patients using these critical features. We compared the accuracy of these models in predicting outcomes. Additionally, SHapley Additive exPlanations (SHAP) values were introduced to interpret the optimal model and assess the significance of input features.ResultsThe study enrolled 1,020 PAI patients with a mean age of 60.46 (range 49.11–71.81) years. Of these, 30.39% were women, and 129 (12.65%) experienced END. RFECV selected 13 critical features, including blood urea nitrogen (BUN), total cholesterol (TC), low-density-lipoprotein cholesterol (LDL-C), apolipoprotein B (apoB), atrial fibrillation, loading dual antiplatelet therapy (DAPT), single antiplatelet therapy (SAPT), argatroban, the basal ganglia, the thalamus, the posterior choroidal arteries, maximal axial infarct diameter (measured at < 15 mm), and stroke subtype. The gradient-boosting decision tree had the highest area under the curve (0.914) among the seven ML algorithms. The SHAP analysis identified apoB as the most significant variable for END.ConclusionOur results suggest that ML algorithms, especially the gradient-boosting decision tree, are effective in predicting the occurrence of END in PAI patients.

Abstract Background Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored. Methods Four independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model. Results Patients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy. Conclusion Different immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG.

Abstract Background Antiviral intervention in hepatitis B virus (HBV)-infected pregnant women can effectively reduce mother-to-child transmission. However, the immunological characteristics of pregnant women with chronic HBV infection and the effects of antiviral intervention during pregnancy on maternal immune response remain unknown. We aimed to investigate these effects by comparing mothers who received antiviral intervention during pregnancy with those who did not. Methods Pregnant women positive for hepatitis B surface antigen and hepatitis B e-antigen (HBsAg+ HBeAg+) were enrolled at delivery, including 34 received prophylactic antiviral intervention during pregnancy (AVI mothers) and 15 did not (NAVI mothers). T lymphocyte phenotypes and functions were analysed using flow cytometry. Results At delivery, maternal regulatory T cell (Treg) frequency in AVI mothers was significantly higher than that in NAVI mothers (P

Sugar beet is one of the most important sugar crops in the world. It contributes greatly to the global sugar production, but salt stress negatively affects the crop yield. WD40 proteins play important roles in plant growth and response to abiotic stresses through their involvement in a variety of biological processes, such as signal transduction, histone modification, ubiquitination, and RNA processing. The WD40 protein family has been well-studied in Arabidopsis thaliana, rice and other plants, but the systematic analysis of the sugar beet WD40 proteins has not been reported. In this study, a total of 177 BvWD40 proteins were identified from the sugar beet genome, and their evolutionary characteristics, protein structure, gene structure, protein interaction network and gene ontology were systematically analyzed to understand their evolution and function. Meanwhile, the expression patterns of BvWD40s under salt stress were characterized, and a BvWD40-82 gene was hypothesized as a salt-tolerant candidate gene. Its function was further characterized using molecular and genetic methods. The result showed that BvWD40-82 enhanced salt stress tolerance in transgenic Arabidopsis seedlings by increasing the contents of osmolytes and antioxidant enzyme activities, maintaining intracellular ion homeostasis and increasing the expression of genes related to SOS and ABA pathways. The result has laid a foundation for further mechanistic study of the BvWD40 genes in sugar beet tolerance to salt stress, and it may inform biotechnological applications in improving crop stress resilience.

BackgroundBrain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions.MethodA total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the “Segment” tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions.ResultsOur findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (β = −0.428, p = 0.007) and density (β = −0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear.ConclusionThe morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.

A highly sensitive electrochemical sensor was successfully fabricated for the determination of niclosamide (NA) based on the chitosan (CTS) functionalized carbon nanotube@carbon black scaffolds (CNT@CBS) nanocomposite modified glassy carbon electrode (GCE). CNT@CBS with interconnected long- and short-range conductive network provided more efficient charge transfer channels and high electrochemical active surface area;CTS not only promoted the uniform dispersion of CNT@CBS but also possessed good biocompatibility, high adsorption capability, and excellent film-forming property. Benefitting from the synergistic effect of CNT@CBS and CTS, the CNT@CBS@CTS/GCE sensor showed a low limit of detection of 4.3 nM (Linear NA concentration: 0.01–10 μM). When applied for the NA detection in real samples, the fabricated sensor presented good practicability with satisfactory RSD values of 2.62%–4.35% and recoveries of 95.6–100.5%.

Abstract Background Salt stress is often associated with excessive production of reactive oxygen species (ROS). Oxidative stress caused by the accumulation of ROS is a major factor that negatively affects crop growth and yield. Root is the primary organ that senses and transmits the salt stress signal to the whole plant. How oxidative stress affect redox sensitive proteins in the roots is not known. Results In this study, the redox proteome of sugar beet M14 roots under salt stress was investigated. Using iTRAQ reporters, we determined that salt stress caused significant changes in the abundance of many proteins (2305 at 20 min salt stress and 2663 at 10 min salt stress). Using iodoTMT reporters, a total of 95 redox proteins were determined to be responsive to salt stress after normalizing again total protein level changes. Notably, most of the differential redox proteins were involved in metabolism, ROS homeostasis, and stress and defense, while a small number play a role in transport, biosynthesis, signal transduction, transcription and photosynthesis. Transcription levels of 14 genes encoding the identified redox proteins were analyzed using qRT-PCR. All the genes were induced by salt stress at the transcriptional level. Conclusions Based on the redox proteomics results, we construct a map of the regulatory network of M14 root redox proteins in response to salt stress. This study further refines the molecular mechanism of salt resistance at the level of protein redox regulation.

Abstract Background Salt stress is a major abiotic stress that limits plant growth, development and productivity. Studying the molecular mechanisms of salt stress tolerance may help to enhance crop productivity. Sugar beet monosomic addition line M14 exhibits tolerance to salt stress. Results In this work, the changes in the BvM14 proteome and redox proteome induced by salt stress were analyzed using a multiplex iodoTMTRAQ double labeling quantitative proteomics approach. A total of 80 proteins were differentially expressed under salt stress. Interestingly, A total of 48 redoxed peptides were identified for 42 potential redox-regulated proteins showed differential redox change under salt stress. A large proportion of the redox proteins were involved in photosynthesis, ROS homeostasis and other pathways. For example, ribulose bisphosphate carboxylase/oxygenase activase changed in its redox state after salt treatments. In addition, three redox proteins involved in regulation of ROS homeostasis were also changed in redox states. Transcription levels of eighteen differential proteins and redox proteins were profiled. (The proteomics data generated in this study have been submitted to the ProteomeXchange and can be accessed via username: reviewer_pxd027550@ebi.ac.uk, password: q9YNM1Pe and proteomeXchange# PXD027550.) Conclusions The results showed involvement of protein redox modifications in BvM14 salt stress response and revealed the short-term salt responsive mechanisms. The knowledge may inform marker-based breeding effort of sugar beet and other crops for stress resilience and high yield.

Multi-agent system has attracted extensive attention in the past two decades because of its potential applications in engineering, social science and natural science, etc.To achieving the consensus of multi-agent system, it is usually necessary to solve the correlation matrix equation to design the control protocol offline, which requires system model to be known accurately.However, the actual multi-agent system has the characteristics of large-scale, nonlinear coupling, and dynamic change of environment, which makes it very difficult to accurately model the system.This brings challenges to the design of model dependent multi-agent consensus protocol.Reinforcement learning is widely used to solve the optimal control and decision-making problems of complex systems because it can learn the optimal solution of control problems in real time by using the measurement data along the trajectory of the system.The existing theories and methods of online solving the optimal consensus of multi-agent system inreal-time by using reinforcement learning technology were summarized.The application of data-driven reinforcement learning technology in multi-agent system optimal consensus was introduced from the aspects of continuous and discrete, homogenous and heterogeneous, anti-interference robustness and so on.Finally, the future research direction of the optimal consensus problem of multi-agent system based on data-driven technology was discussed.

Science and technology innovation are crucial components underpinning agriculture. We constructed an evaluation framework including 4 pillars and 21 indicators, taking 31 provinces in China as examples to examine the level of agriculture science and technology development from a regional perspective. We found that there is an obvious gap between east and west nationwide, and that only about half of the provinces have reached the high and medium levels. It was worth noting that the innovation conditions in Shanghai and Beijing presented huge advantages, of vital importance to a first-class talent team, a complete innovation system, a stable and prosperous market, and active exchanges and cooperation. In addition, to maximize the transformation of agricultural science and technology achievements into real productivity, local government should also strengthen the construction of agricultural research and innovation platforms, technology transfer, and transformation of results. The findings advance understanding of the strengths and weaknesses of the evaluation subjects’ agricultural science and technology development from a regional perspective and are expected to provide some basis for the government and stakeholders to make relevant decisions.

Salt stress can cause cellular dehydration, which induces oxidative stress by increasing the production of reactive oxygen species (ROS) in plants. They may play signaling roles and cause structural damages to the cells. To overcome the negative impacts, the plant ROS scavenging system plays a vital role in maintaining the cellular redox homeostasis. The special sugar beet apomictic monosomic additional M14 line (BvM14) showed strong salt stress tolerance. Comparative proteomics revealed that six antioxidant enzymes (glycolate oxidase (GOX), peroxiredoxin (PrxR), thioredoxin (Trx), ascorbate peroxidase (APX), monodehydroascorbate reductase (MDHAR), and dehydroascorbate reductase3 (DHAR3)) in BvM14 were responsive to salt stress. In this work, the full-length cDNAs of genes encoding these enzymes in the redox system were cloned from the BvM14. Ectopic expression of the six genes reduced the oxidative damage of transgenic plants by regulating the contents of hydrogen peroxide (H2O2), malondialdehyde (MDA), ascorbic acid (AsA), and glutathione (GSH), and thus enhanced the tolerance of transgenic plants to salt stress. This work has charecterized the roles that the antioxidant enzymes play in the BvM14 response to salt stress and provided useful genetic resources for engineering and marker-based breeding of crops that are sensitive to salt stress.

Extreme climate change, rapid population growth and economic development drive a growing demand for resources, which lead to energy, food, water and their intertwined nexus becoming increasingly important. Agricultural decisions considering the interconnections among water, energy, and food are critical. The consumption of large amounts groundwater and non-renewable energy by the predominant traditional wheat-maize cropping system has caused a serious water shortage in the North China Plain (NCP), which is a large food production region in China. This situation has strained the relationship between water/energy consumption and food production. It is important to seek synergy in the water-energy-food nexus. This paper proposed a relative index of water-energy-food (WEFRI) based on different values of resource consumption and use efficiency between treatment systems and control system to analyze the synergy between water utilization, energy consumption and food supply in different cropping systems at the field scale. The goal is to seek a sustainable cropping system to balance crop production while reducing energy consumption and water depletion. In this case, different systems including monocropped maize (Zea mays) (MM), intercropped maize and soybean (Glycine max) (MS), relay cropped of maize with pea (Pisum sativum) (MP) and potato (Solanum tuberosum) (MO), rotation of maize with spinach (Spinacia oleracea) (MI) and ryegrass (Secale cereale) (MR), and using traditional wheat-maize (Triticum aestivum) (MW) as a control. MM, MS, MP and MO were the best systems within a particular range of food supply reduction. The WEFRI of the MM/MS system was the highest (2.96/2.78). Compared to the MW system, the groundwater consumption of MM/MS was reduced by 73.84%/73.84%, and non-renewable energy inputs were reduced by 48.01%/48.30%; however, the food supply decreased by 48.05%/51.70%. The WEFRI of the MP system was 1.98. In comparison with the MW system, the groundwater consumption of the MP system was reduced by 28.46%, and the non-renewable energy inputs were reduced by 42.68%. However, the food supply decreased by 37.13%. The WEFRI of MO system was 1.92. Compared to the MW system, the groundwater consumption of MO was reduced by 11.47%, non-renewable energy inputs were reduced by 32.14%, and the food supply only decreased by 26.27%. In conclusion, we theoretically proposed the following references for cropping systems in the NCP: MM and MS are implemented when the areas has extreme water shortages, MO is implemented when a less than 30% reduction in the food supply capacity is acceptable, and MP is recommended if a 30%–40% reduction in the food supply is acceptable.

BackgroundTo improve the quality of plan for the radiation treatment of advanced left breast cancer by introducing the auxiliary structures (ASs) which are used to spare the regions with no intact delineated structures adjacent to the target volume.MethodsCT data from 20 patients with left-sided advanced breast cancer were selected. An AS designated as A1 was created to spare the regions of the aorta, pulmonary artery, superior vena ava, and contralateral tissue of the upper chest and neck, and another, designated as A2, was created in the regions of the cardia and fundus of the stomach, left liver lobe, and splenic flexure of the colon. IMRT and VMAT plans were created for cases with and without the use of the AS dose constraints in plan optimization. Dosimetric parameters of the target and organs at risk (OARs) were compared between the separated groups.ResultsWith the use of AS dose constraints, both the IMRT and VMAT plans were clinically acceptable and deliverable, even showing a slight improvement in dose distribution of both the target and OARs compared with the AS-unused plans. The ASs significantly realized the dose sparing for the regions and brought a better conformity index (p < 0.05) and homogeneity index (p < 0.05) in VMAT plans. In addition, the volume receiving at least 20 Gy (V20) for the heart (p < 0.05), V40 for the left lung (p < 0.05), and V40 for the axillary-lateral thoracic vessel juncture region (p < 0.05) were all lower in VMAT plans.ConclusionThe use of the defined AS dose constraints in plan optimization was effective in sparing the indicated regions, improving the target dose distribution, and sparing OARs for advanced left breast cancer radiotherapy, especially those that utilize VMAT plans.

The agricultural sustainable development for human well-being considers food security and ecological health as well as people’s socio-economic conditions. Nowadays, most of the holistic assessments of agricultural sustainability, mainly focus on food production and ecological consequences, relatively lacking analysis from the socio-economic perspective. In this context, this study constructs an agricultural social life cycle assessment model based on the guidelines of UNEP to assess the social and economic impacts on the three major staple grain crops in China, including maize, rice and wheat. The assessment model aims to analyze effects of stakeholders containing farmer, agricultural value chain actors, consumer, rural areas, society, and impact categories including high-quality growth of agriculture, a comfortable life in rural areas, the prosperity of rural people. The data is mainly from national statistical databases and representative industry databases. The impact assessment adopts social risk and social impact as quantitative characterization methods, and Analytical Hierarchical Process to obtain weights. The results show that: among the three major grain crops, farmers are the most important factors for stakeholders, and agricultural industrial development has the greatest potential negative impacts on society; maize has the most positive impacts on agricultural sustainable development in China.

Lou onion (Allium fistulosum L. var. viviparum) is an abundant source of flavonols which provides additional health benefits to diseases. Genome-wide specific length amplified fragment (SLAF) sequencing method is a rapidly developed deep sequencing technologies used for selection and identification of genetic loci or markers. This study aimed to elucidate the genetic diversity of 122 onion accessions in China using the SLAF-seq method. A set of 122 onion accessions including 107 A.fistulosum L. var. viviparum Makino, 3 A.fistulosum L. var. gigantum Makino, 3 A.mongolicum Regel and 9 A.cepa L. accessions (3 whites, 3 reds and 3 yellows) from different regions in China were enrolled. Genomic DNA was isolated from young leaves and prepared for the SLAF-seq, which generated a total of 1,387.55 M reads and 162,321 high quality SNPs (integrity >0.5 and MAF >0.05). These SNPs were used for the construction of neighbor-joining phylogenetic tree, in which 10 A.fistulosum L. var. viviparum Makino accessions from Yinchuan (Ningxia province) and Datong (Qinghai province) had close genetic relationship. The 3 A.cepa L. clusters (red, white and yellow) had close genetic relationship especially with the 97 A.fistulosum L. var. viviparum Makino accessions. Population structure analysis suggested entire population could be clustered into 3 groups, while principal component analysis (PCA) showed there were 4 genetic groups. We confirmed the SLAF-seq approach was effective in genetic diversity analysis in red onion accessions. The key findings would provide a reference to the Lou onion germplasm in China.