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The WRKY transcription factor family is involved in responding to biotic and abiotic stresses. Its members contain a typical WRKY domain and can regulate plant physiological responses by binding to W-boxes in the promoter regions of downstream target genes. We identified the sweet sorghum SbWRKY50 (Sb09g005700) gene, which encodes a typical class II of the WRKY family protein that localizes to the nucleus and has transcriptional activation activity. The expression of SbWRKY50 in sweet sorghum was reduced by salt stress, and its ectopic expression reduced the salt tolerance of Arabidopsis thaliana plants. Compared with the wild type, the germination rate, root length, biomass and potassium ion content of SbWRKY50 over-expression plants decreased significantly under salt-stress conditions, while the hydrogen peroxide, superoxide anion and sodium ion contents increased. Real-time PCR results showed that the expression levels of AtSOS1, AtHKT1 and genes related to osmotic and oxidative stresses in over-expression strains decreased under salt-stress conditions. Luciferase complementation imaging and yeast one-hybrid assays confirmed that SbWRKY50 could directly bind to the upstream promoter of the SOS1 gene in A. thaliana. However, in sweet sorghum, SbWRKY50 could directly bind to the upstream promoters of SOS1 and HKT1. These results suggest that the new WRKY transcription factor SbWRKY50 participates in plant salt response by controlling ion homeostasis. However, the regulatory mechanisms are different in sweet sorghum and Arabidopsis, which may explain their different salt tolerance levels. The data provide information that can be applied to genetically modifying salt tolerance in different crop varieties.Key message(1) Sweet sorghum SbWRKY50 is negatively involved in salt response.(2) Over-expression of SbWRKY50 in A. thaliana affects plant growth, ROS and the ion contents.(3) SbWRKY50 could directly bind to the upstream promoter of the SOS1 gene in A. thaliana and the promoter of SOS1 and HKT1 in sweet sorghum.

Alzheimer's disease (AD) is a sporadic or familial neurodegenerative disease of insidious onset with progressive cognitive decline. Although numerous studies have been conducted or are underway on AD, there are still no effective drugs to reverse the pathological features and clinical manifestations of AD. Rapamycin is a macrolide antibiotic produced by Streptomyces hygroscopicus. As a classical mechanistic target of rapamycin (mTOR) inhibitor, rapamycin has been shown to be beneficial in a variety of AD mouse and cells models, both before the onset of disease symptoms and the early stage of disease. Although many basic studies have demonstrated the therapeutic effects of rapamycin in AD, many questions and controversies remain. This may be due to the variability of experimental models, different modes of administration, dose, timing, frequency, and the availability of drug-targeting vehicles. Rapamycin may delay the development of AD by reducing [beta]-amyloid (A[beta]) deposition, inhibiting tau protein hyperphosphorylation, maintaining brain function in APOE [epsilon]4 gene carriers, clearing chronic inflammation, and improving cognitive dysfunction. It is thus expected to be one of the candidates for the treatment of Alzheimer's disease. Keywords: [beta]-amyloid, chronic inflammation, therapeutic effect, macrolide antibiotic

Background Cases of Wallerian degeneration of bilateral cerebral peduncles after acute carbon monoxide poisoning have not yet been reported. To date, most of the delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) lesions captured in magnetic resonance imaging (MRI) has been located in the subcortical white matter and basal ganglia. Here we report two cases of DEACMP with abnormalities in the bilateral cerebral peduncles. The etiology of abnormalities, which were strictly confined to the bilateral cerebral peduncles, was Wallerian degeneration secondary to upstream nerve axonal damage, making this the first report on such bilateral cerebral peduncle abnormalities after DEACMP. Case presentation In this report, we present two cases of DEACMP with abnormal signals in the bilateral cerebral peduncles captured during brain MRIs. Case 1 was of a 68-year-old man who presented with paroxysmal disturbance of the consciousness, left limb weakness for 16 days, and lagging responses for 2 days. Case 2 was of a 55-year-old man who was unconscious for 6 h. In addition to the above mentioned characteristics on the brain MRIs, the electroencephalography of case 1 indicated that his forehead scans had a mixture of wide sharp, sharp, and three-phase waves. Brain diffusion tensor imaging of case 2 further proved that the bilateral cerebral anomalies represented Wallerian degeneration secondary to upstream axonal damage. After the definitive diagnosis, the patients returned to the local hospital for hyperbaric oxygen therapy. Conclusions Wallerian degeneration of the bilateral cerebral peduncles after acute carbon monoxide poisoning has never been reported before. The abnormal signals in the bilateral cerebral peduncles captured during brain MRIs indicated Wallerian degeneration secondary to upstream axonal damage; thus, these two cases may further our understanding of DEACMP imaging.

bHLH family proteins play an important role in plant stress response. However, the molecular mechanism regulating the salt response of bHLH is largely unknown. This study aimed to investigate the function and regulating mechanism of the sweet sorghum SbbHLH85 during salt stress. The results showed that SbbHLH85 was different from its homologs in other species. Also, it was a new atypical bHLH transcription factor and a key gene for root development in sweet sorghum. The overexpression of SbbHLH85 resulted in significantly increased number and length of root hairs via ABA and auxin signaling pathways, increasing the absorption of Na+. Thus, SbbHLH85 plays a negative regulatory role in the salt tolerance of sorghum. We identified a potential interaction partner of SbbHLH85, which was phosphate transporter chaperone PHF1 and modulated the distribution of phosphate, through screening a yeast two-hybrid library. Both yeast two-hybrid and BiFC experiments confirmed the interaction between SbbHLH85 and PHF1. The overexpression of SbbHLH85 led to a decrease in the expression of PHF1 as well as the content of Pi. Based on these results, we suggested that the increase in the Na+ content and the decrease in the Pi content resulted in the salt sensitivity of transgenic sorghum.

One of the most critical steps in cereal threshing is the ease with which seeds are detached from sticky glumes. Naked grains with low glume coverage have dramatically increased threshing efficiency and seed quality. Here, we demonstrate that GC1 ( Glume Coverage 1 ), encoding an atypical G protein γ subunit, negatively regulates sorghum glume coverage. Naturally truncated variations of GC1 C-terminus accumulate at higher protein levels and affect the stability of a patatin-related phospholipase SbpPLAII-1. A strong positive selection signature around the GC1 genic region is found in the naked sorghum cultivars. Our findings reveal a crucial event during sorghum domestication through a subtle regulation of glume development by GC1 C-terminus variation, and establish a strategy for future breeding of naked grains. Low glume coverage is the preferred for easy threshing in grain production, but the genetic basis remains unclear. Here, the authors report the gene GC1 , which encodes an atypical G protein γ subunit, negatively regulates sorghum glume coverage and the naturally truncated alleles can be useful in the naked grain breeding.

This study introduces a deep learning-based automatic evaluation method for analyzing the microstructure of steel with scanning electron microscopy (SEM), aiming to address the limitations of manual marking and subjective assessments by researchers. By leveraging advanced computer vision algorithms, specifically a suitable model for long-term dendritic solidifications named Tang Rui Detect (TRD), the method achieves efficient and accurate detection and quantification of microstructure features. This approach not only enhances the training process but also simplifies loss function design, ultimately leading to a proper evaluation of surface modifications in steel materials. The results demonstrate the method’s potential in automating and improving the reliability of microstructural analysis in materials science.

Background The global epidemic of diabetes mellitus continues to grow and affects developed and developing countries alike. Intensive glycemic control is thought to modify the risks for vascular complications, hence the risks for diabetes-related death. We investigated the trend of diabetic vascular complication-related deaths between 2000 and 2016 in the global diabetes landscape. Methods We collected 17 years of death certificates data from 108 countries in the World Health Organization mortality database between 2000 and 2016, with coding for diabetic complications. Crude and age-standardized proportions and rates were calculated. Trend analysis was done with annual average percentage change (AAPC) of rates computed by joinpoint regression. Results From 2000 through 2016, 7,108,145 deaths of diabetes were reported in the 108 countries. Among them, 26.8% (1,904,787 cases) were attributed to vascular complications in damaged organs, including the kidneys (1,355,085 cases, 71.1%), peripheral circulatory (515,293 cases, 27.1%), nerves (28,697 cases, 1.5%) and eyes (5751 cases, 0.3%). Overall, the age-standardized proportion of vascular complication-related mortality was 267.8 [95% confidence interval (95% CI), 267.5–268.1] cases per 1000 deaths and the rate was 53.6 (95% CI 53.5–53.7) cases per 100,000 person-years. Throughout the 17-year period, the overall age-standardized proportions of deaths attributable to vascular complications had increased 37.9%, while the overall age-standardized mortality rates related to vascular complications had increased 30.8% (AAPC = 1.9% [1.4–2.4%, p < 0.05]). These increases were predominantly driven by a 159.8% increase in the rate (AAPC = 2.7% [1.2–4.3%, p < 0.05]) from renal complications. Trends in the rates and AAPC of deaths varied by type of diabetes and of complications, as well as by countries, regions and domestic income. Conclusion Diabetic vascular complication-related deaths had increased substantially during 2000–2016, mainly driven by the increased mortality of renal complications.

With the goal of automatic sea ice mapping during the summer sea ice melt cycle, this study involved designing a fully automatic sea ice segmentation method based on a deep learning semantic segmentation network applicable to summer SAR images, which achieved high accuracy and the fully automatic extraction of sea ice segmentation during the summer ice melt cycle by optimizing the process, improving the pixel-level semantic segmentation network, and introducing high-resolution sea ice concentration features. Firstly, a convolution-based, high-resolution sea ice concentration calculation method is proposed and was applied to the deep learning task. Secondly, the proposed DF-UHRNet network was improved upon by designing high- and low-level fusion modules, introducing an attention mechanism, and reducing the number of convolution layers and other operations, and it can effectively fuse high- and low-scale semantic features and global contextual information based on reducing the overall number of network parameters, enabling it to achieve pixel-level classification. The results show that this method meets the needs associated with the automatic mapping and high-precision classification of thin ice, one-year ice, open water, and multi-year ice and effectively reduces the model size.

Timely and accurate traffic speed predictions are an important part of the Intelligent Transportation System (ITS), which provides data support for traffic control and guidance. The speed evolution process is closely related to the topological structure of the road networks and has complex temporal and spatial dependence, in addition to being affected by various external factors. In this study, we propose a new Speed Prediction of Traffic Model Network (SPTMN). The model is largely based on a Temporal Convolution Network (TCN) and a Graph Convolution Network (GCN). The improved TCN is used to complete the extraction of time dimension and local spatial dimension features, and the topological relationship between road nodes is extracted by GCN, to accomplish global spatial dimension feature extraction. Finally, both spatial and temporal features are combined with road parameters to achieve accurate short-term traffic speed predictions. The experimental results show that the SPTMN model obtains the best performance under various road conditions, and compared with eight baseline methods, the prediction error is reduced by at least 8%. Moreover, the SPTMN model has high effectiveness and stability.

Introduction We have previously reported that Toll-like receptor 3 ( TLR3 ) acts as a suppressor gene for breast cancer initiation and progression. In this study, we evaluated the role of TLR3 in breast cancer using our original Fudan University Shanghai Cancer Center (FUSCC) datasets and breast cancer tissue microarrays. Methods Using FUSCC multiomics datasets on triple- negative breast cancer (TNBC), we compared the mRNA expression of TLR3 in TNBC tissue and the adjacent normal tissue. A Kaplan–Meier plotter was performed to investigate the expression of TLR3 on prognosis in the FUSCC TNBC cohort. We performed immunohistochemical staining to analyze TLR3 protein expression in the TNBC tissue microarrays. Furthermore, bioinformatics analysis was performed using the Cancer Genome Atlas (TCGA) data to verify the results of our FUSCC study. The relationship between TLR3 and clinicopathological features was analyzed with logistic regression and the Wilcoxon signed-rank test. The association between clinical characteristics and overall survival in TCGA patients was assessed using the Kaplan–Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify signaling pathways that are differentially activated in breast cancer. Results The mRNA expression of TLR3 was lower in TNBC tissue than in the adjacent normal tissue in the FUSCC datasets. The TLR3 had high expression in immunomodulatory (IM) and mesenchymal-like (MES) subtypes and low expression in luminal androgen receptor (LAR) and basal-like immune-suppressed (BLIS) subtypes. High expression of TLR3 in TNBC predicted better prognosis in the FUSCC TNBC cohort. Immunohistochemical staining of the tissue microarrays showed that TLR3 had lower expression in breast cancer tissues than in the adject normal tissues. Furthermore, the TLR3 expression was positively associated with B cell, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and myeloid dendritic cells. Bioinformatic analysis using high-throughput RNA-sequencing data from the TCGA demonstrated that the reduced expression of TLR3 in breast cancer was associated with advanced clinicopathological characteristics, survival time, and poor prognosis. Conclusions TLR3 has low expression in TNBC tissue. High expression of TLR3 in triple-negative breast cancer predicts better prognosis. TLR3 expression may be a potential prognostic molecular marker of poor survival in breast cancer.