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【Objective】Functional modifications of plant histones, including acetylation modification and methylation modification, play important roles in plant growth and development and in response to adversity. The biological functions and molecular mechanisms of the histone modification (HM) gene family in tomato are still unclear. The present study aims to further clarify the biological functions of the HM genes in tomato, and to lay a foundation for the study of their molecular mechanisms and genetic improvement of tomato.【Method】We identified tomato HM members based on the tomato genome database, systematically analyzed the phylogeny, gene structure, and chromosomal localization of its HM gene family members with bioinformatics methods, and analyzed the spatio-temporal expression patterns of the tomato HM gene family through an online transcriptome database.【Result】A total of 148 tomato HM genes were identified in this study, including 32 encoded histone acetyltransferase (HAT), 11 encoded histone deacetylase (HDAC), 50 encoded histone methyltransferase (HMT), and 55 encoded histone demethylase (HDM). The 148 genes were unevenly distributed on different chromosomes, with the highest number of genes on chromosome 3 (21 genes) and the lowest number of genes on chromosome 12 (4 genes). Gene structure characterization showed that the exons varied greatly among tomato HM genes, with the most exons amounting to 34 and the least to only 1. Protein structure domain analysis showed that Solyc07g064130, Solyc11g005670 and Solyc10g006480 contained only the Ubl structure domains, Solyc07g062100, Solyc10g077110 and Solyc03g083310 contained only the Zn-finger structure domain, another 10 proteins contain the Bromo structure domain, 48 proteins contained only the SET structure domain, and other proteins contained other structure domains such as PLN02529 and PRMT5. In addition, the homologous proteins of tomato HM were distantly related to those of both Arabidopsis and Oryza sativa, and the protein sequences of the tomato HM were more closely related to those of the Arabidopsis thaliana than to those of Oryza sativa. Based on the clustering analysis, the tomato HM members were divided into four families, HAT, HDAC, HMT, and HDM. Tissue expression analysis showed that the HAT family was highly expressed in flowers at 30 d after germination (F30), fruits at 10 d post-anthesis (10DPA), flowers (fr), roots (rr), and immature fruits (Plgfr); the HDAC family was highly expressed in flowers (F30) and immature fruits (Plgfr); the HMT family was highly expressed in flowers (F30), when 50% of the whole plant flowers open (F45), flower buds (br), 3 cm fruits (3fr), and immature 5 cm fruits (PB+5fr); the HDM family was highly expressed in flowers (F30), when 50% of the whole plant flowers open (F45), flower buds (br), flowers (fr), roots (rr), 3 cm fruits (3fr), and immature 5 cm fruits (PB+5fr).【Conclusion】The gene structures of different tomato HM vary greatly and contain multiple functional structural domains. The homologous members of tomato HM are distant from those of Arabidopsis thaliana and Oryza sativa, and tomato HM are expressed in different growth and developmental stages of plants and in different organ tissues, suggesting that this class of genes may be involved in a variety of growth and developmental processes in tomato.

Abstract The IVa subfamily of glycine-rich proteins (GRPs) comprises a group of glycine-rich RNA binding proteins referred to as GR-RBPa here. Previous studies have demonstrated functions of GR-RBPa proteins in regulating stress response in plants. However, the mechanisms responsible for the differential regulatory functions of GR-RBPa proteins in different plant species have not been fully elucidated. In this study, we identified and comprehensively studied a total of 34 GR-RBPa proteins from five plant species. Our analysis revealed that GR-RBPa proteins were further classified into two branches, with proteins in branch I being relatively more conserved than those in branch II. When subjected to identical stresses, these genes exhibited intensive and differential expression regulation in different plant species, corresponding to the enrichment of cis-acting regulatory elements involving in environmental and internal signaling in these genes. Unexpectedly, all GR-RBPa genes in branch I underwent intensive alternative splicing (AS) regulation, while almost all genes in branch II were only constitutively spliced, despite having more introns. This study highlights the complex and divergent regulations of a group of conserved RNA binding proteins in different plants when exposed to identical stress conditions. These species-specific regulations may have implications for stress responses and adaptations in different plant species.

The increasingly large scale of location-based social networks (LBSN) promotes the rapid development of point-of-interest (POI) recommendation business. POI geospatial distance directly adopted by traditional methods is difficult to simulate the highly random behavior path of users. And the point-of-interest recommendation process brings sensitivity to the location distance measurement. Meanwhile, the sparse POI check-in data of users in social networks are also easy to have a huge impact on the recommendation accuracy. To solve the above issues, geographically insensitive spatio-temporal POI recommendation model based on heterogeneous graph embedding (GIPR) is proposed. Firstly, the user behavior sequence is introduced to construct the spatial and temporal topological diagram of the behavior POI. The weighted spatial path is used to represent the relative location distance. It can not only conform to the characteristics of user behavior, but also reduce the sensitivity of the recommendation process to the distance between POI, thus enhancing the ability to explain the recommendation results. As for heterogeneous and highly sparse interaction data, the proposed recommendation method can learn the complete LBSN heterogeneous graph from local and global perspectives, and integrate richer user and POI features. Finally, the long-term and short-term preferences of users are extracted through the attention layer to achieve more personalized POI recommendation. Experiments on two large-scale real datasets Foursquare and Gowalla show that GIPR has higher recommendation accuracy and stronger interpretability.

Low light stress seriously affects the growth and yield of crops and the phytohormone brassinosteroid (BRs) plays a vital role in regulating plant adaptation to low light conditions. However, the molecular mechanism underlying this process remains largely unknown. In this study, we showed that exogenous BR effectively alleviated damages to photosynthesis and antioxidant systems, improved the plant biomass under low light stress mimicking treatments in tomato (Lycopersicon esculentum Mill.). Comparative transcriptome profiling analysis revealed that genes related with photosynthesis and Calvin cycle pathways were enriched among the differentially expressed genes (DEG) co-regulated by low light stress and BR. The combination of transcriptome and metabolome analysis showed that BR could mitigate the down-regulation of photosynthesis and Calvin cycle caused by low light stress, and partially restore the up-regulation of Glycolysis / Gluconeogenesis and tricarboxylic acid (TCA) cycle through transcriptional and metabolic reprogramming to alleviate the effects of low light stress. Moreover, we further identified the crucial transcription factors, SIEPR1 and SIERF059, and their potential target genes involved in the regulation of low light stress alleviation mediated by BR signaling. Our results shed new light on the molecular mechanisms underlying the alleviation of low light stress by BR.

Histone modification plays a crucial role in chromatin remodeling and regulating gene expression, and participates in various biological processes, including plant development and responses to stress. Several gene families related to histone modification have been reported in various plant species. However, the identification of members and their functions in the rice (Oryza sativa L.) histone modification gene family (OsHM) at the whole-genome level remains unclear. In this study, a total of 130 OsHMs were identified through a genome-wide analysis. The OsHM gene family can be classified into 11 subfamilies based on a phylogenetic analysis. An analysis of the genes structures and conserved motifs indicates that members of each subfamily share specific conserved protein structures, suggesting their potential conserved functions. Molecular evolutionary analysis reveals that a significant number of OsHMs proteins originated from gene duplication events, particularly segmental duplications. Additionally, transcriptome analysis demonstrates that OsHMs are widely expressed in various tissues of rice and are responsive to multiple abiotic stresses. Fourteen OsHMs exhibit high expression in rice anthers and peaked at different pollen developmental stages. RT-qPCR results further elucidate the expression patterns of these 14 OsHMs during different developmental stages of anthers, highlighting their high expression during the meiosis and tetrad stages, as well as in the late stage of pollen development. Remarkably, OsSDG713 and OsSDG727 were further identified to be nucleus-localized. This study provides a fundamental framework for further exploring the gene functions of HMs in plants, particularly for researching their functions and potential applications in rice anthers’ development and male sterility.

Abstract Purpose To compare the performance of Neutrophil-to-Lymphocyte Ratio (NLR) with that of Platelet-to-Lymphocyte Ratio (PLR) in diagnosing neonatal sepsis (NS). Methods PubMed and Embase were searched for relevant studies from the inception of the databases to May, 2022. The pooled sensitivity (SEN), specificity (SPE), and area under the receiver operator characteristic curve (AUC) were measured. Results Thirteen studies involving 2610 participants were included. The SEN, SPE, and AUC of NLR were 0.76 (95%CI: 0.61–0.87), 0.82 (95%CI: 0.68–0.91), and 0.86 (95%CI: 0.83–0.89), respectively, and those of PLR were 0.82 (95%CI: 0.63–0.92), 0.80 (95%CI: 0.24–0.98), and 0.87 (95%CI: 0.83–0.89), respectively. Significant heterogeneity was observed among the studies. Subgroup analysis and meta-regression showed that types of sepsis (p = 0.01 for SEN), gold standard (p = 0.03 for SPE), and pre-set threshold (p

Sphingosine-1-phosphate (S1P) is a versatile sphingolipid that is generated through the phosphorylation of sphingosine by sphingosine kinase (SPHK). S1P exerts its functional effects by binding to the G protein-coupled S1P receptor (S1PR). This lipid mediator plays a pivotal role in various cellular activities. The S1P/S1PR signaling pathway is implicated in the pathogenesis of immune-mediated diseases, significantly contributing to the functioning of the immune system. It plays a crucial role in diverse physiological and pathophysiological processes, including cell survival, proliferation, migration, immune cell recruitment, synthesis of inflammatory mediators, and the formation of lymphatic and blood vessels. However, the full extent of the involvement of this signaling pathway in the development of autoimmune diseases remains to be fully elucidated. Therefore, this study aims to comprehensively review recent research on the S1P/S1PR axis in diseases related to autoimmunity.

Proline/P5C cycle between mitochondria and cytosol, play important roles in energy supply and ROS (Reactive oxygen species) generation in mammalian cell. Recently, in plant, proline-dependent ROS via proline/P5C cycle was proposed to be involved in hypersensitive reaction during plant response to avirulent pathogens. However, much remains to be elucidated about the regulation of proline/P5C cycle upon pathogen infection. Here, we reported the isolation and characterization of an Arabidopsis mutant proline resistance 2 (pre2), with a single dominant mutation in a single gene. Our results showed that the proline resistance phenotype of pre2 is not due to decreased intracellular proline content, when treated with exogenous proline. Upon proline treatment, pre2 showed reduced induction of PDH transcript level and enhanced induction of that of P5CDH, accompanied by lower level of mitochondrial ROS, suggesting an attenuated proline/P5C cycle activity. Proline-induced SA (Salicylic acid) signaling was also less activated in pre2, as evidenced by reduced free SA content and PR1 transcript level, compared to the WT. On the other hand, SA activation on the proline/P5C activity is to a lesser extent in pre2 than in WT. Significantly, pre2 demonstrated increased susceptibility to infection by avirulent pathogen Pst. DC3000 (avrRps4), accompanied also by lesser induced proline/P5C cycle activity by the pathogen. Our results indicated that there is a correlation between proline/P5C cycle and plant response to avirulent pathogen.

Abstract Salt stress poses physiological drought, ionic toxicity and oxidative stress to plants, which causes premature senescence and death of the leaves if the stress sustained. Salt tolerance varied between different rice varieties, but how different rice varieties respond at the early stage of salt stress has been seldom studied comprehensively. By employing third generation sequencing technology, we compared gene expressional changes in leaves of three rice varieties that varied in their level of tolerance after salt stress treatment for 6 h. Commonly up-regulated genes in all rice varieties were related to water shortage response and carbon and amino acids metabolism at the early stage of salt stress, while reactive oxygen species cleavage genes were induced more in salt-tolerant rice. Unexpectedly, genes involved in chloroplast development and photosynthesis were more significantly down-regulated in the two salt tolerant rice varieties ‘C34’ and ‘Nona Bokra’. At the same time, genes coding ribosomal protein were suppressed to a more severe extent in the salt-sensitive rice variety ‘IR29’. Interestingly, not only variety-specific gene transcriptional regulation, but also variety-specific mRNA alternative splicing, on both coding and long-noncoding genes, were found at the early stage of salt stress. In summary, differential regulation in gene expression at both transcriptional and post-transcriptional levels, determine and fine-tune the observed response in level of damage in leaves of specific rice genotypes at early stage of salt stress.

Abstract Background Paralogs that arise from gene duplications during genome evolution enable genetic redundancy and phenotypic robustness. Variation in the coding or regulatory sequence of paralogous transcriptional regulators diversifies their functions and relationships, which provides developmental robustness against genetic or environmental perturbation. The fate transition of plant shoot stem cells for flowering and reproductive success requires a robust transcriptional control. However, how paralogs function and interact to achieve such robustness is unknown. Results Here, we explore the genetic relationship and protein behavior of ALOG family transcriptional factors with diverse transcriptional abundance in shoot meristems. A mutant spectrum covers single and higher-order mutant combinations of five ALOG paralogs and creates a continuum of flowering transition defects, showing gradually enhanced precocious flowering, along with inflorescence simplification from wild-type-like to progressively fewer flowers until solitary flower with sterile floral organs. Therefore, these paralogs play unequal roles and act together to achieve a robust genetic canalization. All five proteins contain prion-like intrinsically disordered regions (IDRs) and undergo phase separation. Accumulated mutations following gene duplications lead to IDR variations among ALOG paralogs, resulting in divergent phase separation and transcriptional regulation capabilities. Remarkably, they retain the ancestral abilities to assemble into a heterotypic condensate that prevents precocious activation of the floral identity gene ANANTHA. Conclusions Our study reveals a novel genetic canalization mechanism enabled by heterotypic transcriptional condensates formed by paralogous protein interactions and phase separation, uncovering the molecular link between gene duplication caused IDR variation and robust transcriptional control of stem cell fate transition.

In wire electrical discharge machining (WEDM), cutting efficiency is a significant process index whose improvement has always been the research focus. Among the many factors affecting cutting efficiency, discharge energy is the most important factor. Different energy distribution form pulses were obtained by changing the peak currents at single-pulse different discharge stages. Through single-pulse discharge experiments, pulse energy distribution how to impact discharge channel motion characteristics was studied. When the energy distribution is changed through gradually increasing the peak current, an outward-pointing pressure difference will be formed inside the channel, which provides a driving force for the channel to move faster, accelerating the material erosion rate and increasing the discharge crater surface size. The cutting results reveal consistent variations in the cutting efficiency and surface size of individual discharge crater with the pulse energy distribution form. Through changing single-pulse energy distribution, the cutting efficiency can be improved by about 21%. [ABSTRACT FROM AUTHOR]

Runoff prediction plays an important role in the construction of intelligent hydraulic engineering. Most of the existing deep learning runoff prediction models use recurrent neural networks for single-step prediction of a single time series, which mainly model the temporal features and ignore the river convergence process within a watershed. In order to improve the accuracy of runoff prediction, a dynamic spatiotemporal graph neural network model (DSTGNN) is proposed considering the interaction of hydrological stations. The sequences are first input to the spatiotemporal block to extract spatiotemporal features. The temporal features are captured by the long short-term memory network (LSTM) with the self-attention mechanism. Then, the upstream and downstream distance matrices are constructed based on the river network topology in the basin, the dynamic matrix is constructed based on the runoff sequence, and the spatial dependence is captured by combining the above two matrices through the diffusion process. After that, the residual sequences are input to the next layer by the decoupling block, and, finally, the prediction results are output after multi-layer stacking. Experiments are conducted on the historical runoff dataset in the Upper Delaware River Basin, and the MAE, MSE, MAPE, and NSE were the best compared with the baseline model for forecasting periods of 3 h, 6 h, and 9 h. The experimental results show that DSTGNN can better capture the spatiotemporal characteristics and has higher prediction accuracy.

Laryngeal cancer (LC) is an aggressive malignancy resistant to drug treatments. It has been postulated that cancer stem cells (CSCs) persist in a unique population of cancer cells involved in tumor progression and drug-resistance. In the present study, the effects of PLOD2 expression on ordinary and Cisplatin (DDP)-resistance (R) cells were investigated in TU686 and TU138 cells and Xenograft model. Cell viability, invasion and cell apoptosis, CD44 and CD133 expressions, MRP1 and P-gp expressions were measured by CCK-8 assay, Transwell, flow cytometry, immunofluorescence and Western blotting respectively. The results of our study demonstrated that suppressing the expression of PLOD2 could meditate LC stem cell-like features by decrease cell viability and invasion, increase apoptotic rate, decrease CD44 and CD133 expressions via Integrin β1. Meanwhile, the inhibition of PLOD2 expression could decrease P-gp and MRP1expression thus markedly regulate DDP-R LC cells stemness and drug-resistance via Integrin β1. Our findings provided a new rationale for subsequent academic and clinical research on LC drug-resistance.

During the COVID-19 pandemic, the number of suspected cases, confirmed cases and those who passed away from the virus has been reported in major media and the internet, and has caused a high degree of tension. In addition, people’s outdoor activities have been limited, making it more difficult to find outlets for releasing stress. Under this situation, some people began to experience emotions of anxiety and depression. This article reports a case of depression with fever caused by the stress tension of the pandemic. The patient was highly suspected to have contracted COVID-19. The reported patient, who had a history of depression and had been to Wuhan to attend an exam, showed obvious pre-exam anxiety under the epidemic situation, which gradually increased the patient's pressure and then caused some adverse symptoms, such as insomnia, anxiety, sweating and a reoccurrent fever. Local community authorities paid close attention to him and later sent him to a general hospital in Jingmen for quarantine and treatment, as he was suspected of having COVID-19. After being hospitalised for half a month, he was ruled out from having ‘COVID-19’ and was cured of depression and discharged from the hospital. From this case, we can realise that, under the situation of the epidemic, people are easily prone to insomnia, anxiety and even depression. As clinicians in general hospitals, especially when encountering large emergencies, we must carefully inquire about the patient’s medical history while strengthening our understanding of psychiatric knowledge to improve the recognition rate for depression.

Land use change alters the accumulation of heavy metals (HMs) in soils and might have significant influence on the assembly and functions of soil microbial community. Although numerous studies have discussed the impacts of either total amounts or availability of metals on soil microbes in land change, there is still limited understanding on which one is more critical. In the present study, soils from three land use types (forest, mining field, and operating factory) located in Shaoguan city (Guangdong Province, China) were collected to investigate the impacts of soil HMs on soil enzyme activities and bacterial community structures. Mining activities remarkably increased the concentrations of HMs in soils, and land use patterns changed soil properties and nutrition level. Soil pH, total and available HMs (Cu, Pb, Zn, and Cd) and organic matters (SOM) were identified as the key influential factors shaping soil ecological functions (soil enzyme activities) and community assembly (bacterial community composition), explained by HMs accumulation and soil acidification caused by human activities. In addition, total amount and availability of some metals (Zn, Pb, Cu, and Cd) showed similar and significant effects on soil bacterial communities. Our findings provide new clues for reassessing the environmental risks of HMs in soils with different land use.

The belt conveyor is essential in coal mine underground transportation. The belt properties directly affect the safety of the conveyor. It is essential to monitor that the belt works well. Traditional non-contact detection methods are usually time-consuming, and they only identify a single instance of damage. In this paper, a new belt-tear detection method is developed, characterized by two time-scale update rules for a multi-class deep convolution generative adversarial network. To use this method, only a small amount of image data needs to be labeled, and batch normalization in the generator must be removed to avoid artifacts in the generated images. The output of the discriminator uses a multi-classification softmax function to identify the scratches, cracks, and tears in the belt. In addition, we have improved the two time-scale update rule, by which the generator and discriminator use different learning rates, updated it according to α: β, and defined α: β as 2:1. It can strike a balance between the generator and discriminator, speed up discriminator training, and improve real-time damage detection. Experimental results show that the detection accuracy of tears reaches 100%, and the detection accuracy of non-serious damage is up to 97.1%. [ABSTRACT FROM AUTHOR]

In underground mining, the belt is a critical component, as its state directly affects the safe and stable operation of the conveyor. Most of the existing non-contact detection methods based on machine vision can only detect a single type of damage and they require pre-processing operations. This tends to cause a large amount of calculation and low detection precision. To solve these problems, in the work described in this paper a belt tear detection method based on a multi-class conditional deep convolutional generative adversarial network (CDCGAN) was designed. In the traditional DCGAN, the image generated by the generator has a certain degree of randomness. Here, a small number of labeled belt images are taken as conditions and added them to the generator and discriminator, so the generator can generate images with the characteristics of belt damage under the aforementioned conditions. Moreover, because the discriminator cannot identifymultiple types of damage, the multi-class softmax function is used as the output function of the discriminator to output a vector of class probabilities, and it can accurately classify cracks, scratches, and tears. To avoid the features learned incompletely, skiplayer connection is adopted in the generator and discriminator. This not only can minimize the loss of features, but also improves the convergence speed. Compared with other algorithms, experimental results show that the loss value of the generator and discriminator is the least. Moreover, its convergence speed is faster, and the mean average precision of the proposed algorithm is up to 96.2%, which is at least 6% higher than that of other algorithms. [ABSTRACT FROM AUTHOR]