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P/TGMS (Photo/thermo-sensitive genic male sterile) lines are crucial resources for two-line hybrid rice breeding. Previous studies revealed that slow development is a general mechanism for sterility-fertility conversion of P/TGMS in Arabidopsis. However, the difference in P/TGMS genes between rice and Arabidopsis suggests the presence of a distinct P/TGMS mechanism in rice. In this study, we isolated a novel P/TGMS line, ostms19, which shows sterility under high-temperature conditions and fertility under low-temperature conditions. OsTMS19 encodes a novel pentatricopeptide repeat (PPR) protein essential for pollen formation, in which a point mutation GTA(Val) to GCA(Ala) leads to ostms19 P/TGMS phenotype. It is highly expressed in the tapetum and localized to mitochondria. Under high temperature or long-day photoperiod conditions, excessive ROS accumulation in ostms19 anthers during pollen mitosis disrupts gene expression and intine formation, causing male sterility. Conversely, under low temperature or short-day photoperiod conditions, ROS can be effectively scavenged in anthers, resulting in fertility restoration. This indicates that ROS homeostasis is critical for fertility conversion. This relationship between ROS homeostasis and fertility conversion has also been observed in other tested rice P/TGMS lines. Therefore, we propose that ROS homeostasis is a general mechanism for the sterility-fertility conversion of rice P/TGMS lines.

Energy-energy correlators (EECs) are promising observables to study the dynamics of jet evolution in the quark-gluon plasma (QGP) through its imprint on angular scales in the energy flux of final-state particles. We carry out the first complete calculation of EECs using realistic simulations of high-energy heavy-ion collisions and dissect the different dynamics underlying the final distribution through analyses of jet propagation in a uniform medium. The EECs of γ-jets in heavy-ion collisions are found to be enhanced by the medium response from elastic scatterings instead of induced gluon radiation at large angles. In the meantime, EECs are suppressed at small angles due to energy loss and transverse momentum broadening of jet shower partons. These modifications are further shown to be sensitive to the angular scale of the in-medium interaction, as characterized by the Debye screening mass. Experimental verification and measurement of such modifications will shed light on this scale and the short-distance structure of the QGP in heavy-ion collisions.

Abstract Background Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments but also expedites drug development process. However, achieving the desired level of computational accuracy for DTA identification methods remains a significant challenge. Results We proposed a novel multi-view-based graph deep model known as MvGraphDTA for DTA prediction. MvGraphDTA employed a graph convolutional network (GCN) to extract the structural features from original graphs of drugs and targets, respectively. It went a step further by constructing line graphs with edges as vertices based on original graphs of drugs and targets. GCN was also used to extract the relationship features within their line graphs. To enhance the complementarity between the extracted features from original graphs and line graphs, MvGraphDTA fused the extracted multi-view features of drugs and targets, respectively. Finally, these fused features were concatenated and passed through a fully connected (FC) network to predict DTA. Conclusions During the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.

Pseudopoda Jäger, 2000 is currently the largest genus in the family Sparassidae Bertkau, 1872, comprising 255 species. Of these, 154 species have been recorded in China, representing 60.4% of the global species.In October 2023, a spider survey was conducted in Shennongjia National Nature Reserve, Hubei Province, China. After examination and morphological comparison, one new species of the genus Pseudopoda was identified and is described here.In this paper, a new species of Pseudopoda collected in Hubei Province, China, is proposed and named Pseudopoda guanmenshan sp. nov. A detailed description, diagnosis, photographs and distribution map of the new species are provided.

Abstract Urban open spaces (UOS) are crucial for urban life, offering benefits across individual and societal levels. However, the understanding of the systematic dynamic of UOS scaling with city size and its potential non-linear performance remains a limited clarity area. This study bridges this gap by integrating urban scaling laws with remote sensing data from 1990 to 2020, creating a framework to analyze UOS trends in China. Our findings reveal that UOS growth is sub-linear scaling with city size, exhibiting economies of scale with scaling exponents between 0.55 and 0.65 and suggesting potential shortages. The distribution structure of UOS across cities is becoming increasingly balanced, as indicated by the rising Zipf’s slope from 0.66 to 0.88. Southeastern coastal cities outperform, highlighting spatial variations and path dependency in UOS development. Additionally, using metrics of Scale-adjusted metropolitan indicator (SAMI) and the ratio of open space consumption to population growth rates (OCRPGR), we observe a trend towards more coordinated development between UOS and population, with a declining proportion of uncoordinated cities. Our long-term, large sample coverage study of UOS in China may offer positive significance for urban ecological planning and management in similar rapidly urbanizing countries, contributing to critical insights for quantifying and monitoring urban sustainable development.

Introduction Osteoporotic fractures are a leading cause of disability and contribute significantly to medical care costs worldwide. Variations in bone mineral density and the risk of osteoporosis are notably influenced by altitude. This study aims to longitudinally examine individuals with osteoporosis and low bone mass at three different altitudes (low, high and very high) to understand the effects of high-altitude environments on bone density.Methods and analysis This multicentre, prospective cohort study will involve 893 participants divided into three groups based on altitude: low (500–1500 m), high (2500–4500 m) and very high (4500–5500 m). Participants will undergo comprehensive diagnostic assessments, including demographic data collection, structured questionnaires, medical examinations and clinical laboratory tests. Follow-up visits will occur annually for a minimum of 5 years. The primary outcome will be changes in bone mineral density values. Secondary outcomes will include the incidence of osteoporosis and osteoporotic fractures. Cox proportional hazard models will be used to calculate the risk associated with osteoporotic events and related fractures.Ethics and dissemination The study has been approved by the Institutional Review Board of the Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (No: 2024-70). The acquired insights will be disseminated via academic forums, scholarly articles and stakeholder engagement sessions.Trial registrationnumber ChiCTR2300078872.

The diffusion wake accompanying the jet-induced Mach cone provides a unique probe of the properties of quark-gluon plasma in high-energy heavy-ion collisions. It can be characterized by a depletion of soft hadrons in the opposite direction of the propagating jet. We explore the 3D structure of the diffusion wake induced by γ-triggered jets in Pb+Pb collisions at the LHC energy within the coupled linear Boltzmann transport and hydro model. We identify a valley structure caused by the diffusion wake on top of a ridge from the initial multiple parton interaction (MPI) in jet-hadron correlation as a function of rapidity and azimuthal angle. This leads to a double-peak structure in the rapidity distribution of soft hadrons in the opposite direction of the jets as an unambiguous signal of the diffusion wake. Using a two-Gaussian fit, we extract the diffusion wake and MPI contributions to the double peak. The diffusion wake valley is found to deepen with the jet energy loss as characterized by the γ-jet asymmetry. Its sensitivity to the equation of state and shear viscosity is also studied.

To analyze the speciation distribution of arsenic in agaric, shiitake mushroom, matsutake and agrocybe, the ion chromatography-inductive coupled plasma mass spectrometer (IC-ICP-MS) was used to determine arsenobetaine, dimethyl arsenic, arsenous acid, arsenic choline, monomethyl arsenic and arsenic acid, and the methodological investigation and content determination were carried out. The results showed that the method could completely separate all six arsenic forms within 5 minutes, and the peak patterns were good. The linear relationship of the method was good (mass concentration of 0.5~20 μg/L, r>0.999). The detection limit and quantification limit of six arsenic species were not more than 0.005 and 0.017 mg/kg respectively. The recovery rate of six arsenic forms in agaric, agrocybe and shiitake mushroom could reach 80%~120% with standard addition. For matsutake, the standard addition recovery rate could also reach 80%~120% when adding right standard amounts (0.05 mg/kg dimethyl arsenic, arsenic choline and arsenic acid; 0.2 mg/kg arsenite and monomethyl arsenic; 5 mg/kg arsenic betaine). Combined with the dehydration rate of dry products, the inorganic arsenic content of the tested samples met the requirements of GB 2762-2022. The content of total arsenic in matsutake was the highest, but the proportion of inorganic arsenic（arsenic choline+arsenic acid） in total arsenic was the lowest 3.6%~6.8%, and the highest proportion was arsenobetaine (75.8%~87.3%). The main form of arsenic in agaric, agrocybe, and shiitake mushroom were inorganic arsenic. The proportion of inorganic arsenic to total arsenic could reach 58.4%~66.1%、60.0%~66.7%、81.2%~91.7%, respectively. There was a risk of food safety when the total arsenic content was high.

Abstract Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive types of squamous cell carcinoma and represents a significant proportion of esophageal cancer. Metabolic reprogramming plays a key role in the occurrence and development of ESCC. Unsupervised clustering analysis was employed to stratify ESCC samples into three clusters: MPC1-lipid type, MPC2-amino acid type, and MPC3-energy type, based on the enrichment scores of metabolic pathways extracted from the Reactome database. The MPC3 cluster exhibited characteristics of energy metabolism, with heightened glycolysis, cofactors, and nucleotide metabolism, showing a trend toward increased aggressiveness and poorer survival rates. On the other hand, MPC1 and MPC2 primarily involved lipid and amino acid metabolism, respectively. In addition, liquid chromatography‒mass spectrometry-based metabolite profiles and potential therapeutic agents were explored and compared among ESCC cell lines with different MPCs. MPC3 amplified energy metabolism markers, especially carnitines. In contrast, MPC1 and MPC2 predominantly had elevated levels of lipids (primarily triacylglycerol) and amino acids, respectively. Furthermore, MPC3 demonstrated a suboptimal clinical response to PD-L1 immunotherapy but showed increased sensitivity to the doramapimod chemotherapy regimen, as evident from drug sensitivity evaluations. These insights pave the way for a more personalized therapeutic approach, potentially enhancing treatment precision for ESCC patients.

Abstract Many machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institute’s L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.

As an exogenous pollutant, the microplastics accumulated in soil could alter microbial activity. The use of plastic mulch in greenhouse vegetable planting not only enhances vegetable yield and quality, but also leads to the formation and accumulation of microplastics in the soil over time. It is essential to determine the characteristics of microplastics and microorganisms in soils with varying years of planting is crucial for ensuring vegetable quality and quantity. Therefore, this study investigated the abundance and particle size of microplastics, the concentration of phthalates (PAEs), and the dynamics of soil microbial activity in greenhouse soils with different planting years (5, 10, 15, 20, 25, and 30 years). Results showed that microplastics increased in abundance, particle size, and PAEs concentration as planting years progressed. Specifically, the abundance of microplastics rose from 70.0 ± 8.7 to 224.0 ± 10.4 items/kg, with the proportion of microplastics sized 0–2 mm increasing from 14.02 to 69.11 %, and the total PAEs concentration in the soil escalating from 0.31 to 1.89 mg/kg. Additionally, Bacteroidetes and Actinobacteria levels increased, correlating with organic matter degradation. Metabolic pathway linked to degradation were enriched according to KEGG analysis. Correlation analysis revealed that microplastics notably decreased soil pH, creating an acidic environment that boosted urease activity and the relative abundance of Nitrospirae. This study sheds light on the accumulation characteristics of microplastics and their impact on soil microbial activity following prolonged planting.

This study examined the impact of brief mindfulness meditation (BMM) training on attention function and dispositional mindfulness in young males. 126 male participants aged 18–26 from the security industry were recruited, with 66 participants (M = 22.84, SD = 2.41) undergoing 4-week mindfulness meditation training and 60 participants (M = 23.07, SD = 2.29) in the active control group. The intervention was integrated into the participants' schedules. Measures included Five Facets Mindfulness Questionnaires (FFMQ), concentration and assignment attention tasks, Attention Network Test (ANT), and saliva cortisol concentration. Findings indicate that brief mindfulness meditation training led to significant improvements in participants' FFMQ scores), with marginally significant enhancements in the executive control network. However, it had no discernible effect on alertness and orientation networks. Additionally, brief mindfulness meditation training enhanced attention allocation to light stimulation and prolonged individual attention. Surprisingly, there was no observed decrease in saliva cortisol concentration among meditation training participants. However, this study did not find a decrease in saliva cortisol concentration in the brief mindfulness meditation group. In conclusion, this study highlights the potential of a 4-week brief mindfulness meditation training program to enhance dispositional mindfulness and specific aspects of attention function in young men, offering practical insights into the benefits of mindfulness meditation practices for this demographic.

In order to qualitatively and quantitatively identify syrup adulteration in honey, a method for rapid identification of adulterated honey by Raman spectroscopy and chemometrics was proposed. Raman spectroscopy was used to acquire spectral data of honey samples, and principal component analysis (PCA) was used to extract features from the spectral data. Principal components with a cumulative contribution rate of more than 85% were selected for modeling and prediction. By using linear discriminant analysis (LDA) and partial least squares-discriminant analysis (PLS-DA), models to identify honey adulterated with 20% syrup were established. A support vector machine (SVM) model to identify honey adulterated with 5% syrup, and all LDA, PLS-DA and SVM models could distinguish adulterated honey samples with 1% syrup content from pure honey with an accuracy of more than 0.9. Raman spectroscopy combined with chemometrics is a fast and non-destructive method for the identification of adulterated honey with high accuracy, which is significant to maintaining the order of the honey market.

This study aimed to observe the antiobesity and lipid-lowering effects of wheat bran polyphenols (WBP) in diet-induced obese rats, and to explore its possible mechanism. Eighty 6-week-old SD rats, half from each gender, were adaptively fed for one week. Ten rats were randomly selected from them and fed on a basal diet to serve as a blank control group. The remaining 70 rats were fed on a high-fat diet until the body mass gain exceeded 20%. Totally 50 obese rats were selected from the 70 rats and randomly divided into five groups of 10 rats each: model (distilled water 5.0 mL/kg mb), positive control (trimethylglycine (TMG), 0.10 g/kg mb), low-dose WBP (WBP-L, 1.50 g/kg mb), medium-dose WBP (WBP-M, 3.00 g/kg mb), and high-dose WBP (WBP-H, 6.00 g/kg mb). Each drug was administered daily at a dose of 5.0 mL/kg mb by gavage. The rats in the blank control group were gavaged with distilled water (5.0 mL/kg mb) for nine weeks. During the intervention period, body mass and food intake of the rats were measured once a week and food effect was calculated. After completion of the intervention period, the rats were fasted for 12 hours with access to water and then anesthetized with ether to collect blood samples from the abdominal aorta and liver and surrounding adipose tissue to calculate liver coefficients and obesity indexes. Sera were separated from the blood samples for measurement of biochemical indicators. Liver tissues were homogenized for analyses of antiinflammatory and antioxidant parameters. Moreover, the degree of hepatic steatosis was pathohistologically observed. The results showed that WBP at all doses could reduce the food effect, inhibit the body mass gain in obese rats, reduce the liver mass and liver coefficient, and significantly lower the levels of triglycerides (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and creatinine (CREA) in the sera of obese rats. In addition, all doses of WBP decreased the levels of interleukin-6 (IL-6), IL-1β. tumor necrosis factor-α (TNF-α), adiponectin (ADPN) and leptin (LEP) in the liver homogenate of obese rats to varying degrees, but significantly increased glutathione peroxidase (GSH-Px), lipoprotein lipase (LPL), and hepaticlipase (HL) levels (P < 0.05 or P < 0.01); the effect of WBP was more pronounced than that of TMG. In conclusion, WBP can exert antiobesity, lipid-lowering and hepatoprotective functions by inhibiting the degree of obesity in simple obesity rats, reducing serum lipid levels, alleviating chronic inflammation caused by obesity, and inhibiting liver injury. Therefore, WBP has the potential to be developed as a functional food and health product with antiobesity and lipid-lowering effects. This study provides a theoretical reference for scientific and reasonable development of wheat bran.

An innovative form of steel–concrete composite beam, the steel–coarse aggregate reactive powder concrete (CA-RPC) composite beam with uplift-restricted and slip-permitted (URSP) connectors, is introduced in this paper. The aim is to enhance the cracking resistance under negative bending moments, which is a difficult problem for traditional composite beams, and to make the cost lower than using ordinary reactive powder concrete (RPC). An experimental investigation of the behavior of six specimens of simply supported steel–CA-RPC composite beams with URSP connectors under negative bending moments is presented in this paper. The test results validated that the cracking load of steel–CA-RPC composite beams could be approximately three times that of the ordinary steel–concrete composite beams while the bearing capacity and stiffness are almost the same. A numerical model, using the concrete damaged plasticity (CDP) model to simulate the behavior of the CA-RPC material, was proposed and successfully calculated the overall load–displacement relationship of the composite beams with sufficient accuracy compared with the experimental results, and the distribution of cracks and the failure mode of the beams could also be captured by this model. Furthermore, a parametric analysis was carried out to find out how the application of prestress, CA-RPC, and URSP connectors could affect the cracking resistance of the composite beams, and the results indicated that using CA-RPC and prestress made the main contributions and that the usage of URSP could boost the effect of the other two factors. The plastic resistance moment of the beams was also compared with the calculation results using the methods introduced in Eurocode 4, and it was proved that the calculation results were lower than the experimental results by approximately 10%, which meant that the method was reliable for this kind of composite beam.

With the development of ecological civilization construction, urban planning and development in China have entered a phase in which optimizing and constructing ecological spaces is required. As a national livable city, Xuchang has experienced rapid economic development in recent years, leading to significant urban expansion that has impacted the layout of ecological space networks in the central urban area and its surroundings. Therefore, identifying and optimizing the spatial layout of ecological corridors in Xuchang City are crucial for ecological development and park city construction. This study utilizes multisource geospatial data to identify and extract ecological corridors in the central urban area of Xuchang City. Ecological resistance and gravity models are employed to identify and verify that the primary ecological corridor pattern in Xuchang City is situated in Weidu District, which is a central urban area. Finally, 11 main ecological corridors in the central urban area are delineated. In response to the identification of ecological corridors, this study integrates spatial analysis methods and text analysis methods to evaluate the characteristics of urban ecological corridors. The results indicate that Xudu Park extends outward, serving as the hub of the ecological network, and that West Lake Park and Luming Lake Park form the core of the urban park system. Finally, based on the spatial relationships, ecological benefits, and citizen experience of each ecological corridor and the green parks it traverses, strategies for optimizing the layout of urban ecological corridors are proposed.

The issue of water pollution is one of the hot topics of global concern, which requires us to efficiently treat pollutants in water, especially printing and dyeing sewage. There are varieties of dyestuffs and intermediates, which are complex and difficult to degrade, and they even contain heavy metals. In this study, a bacterial strain named Q3-6 with potential for sewage treatment was isolated and its physiological, biochemical, and genomic characteristics, and potential application value, were further investigated. The genome sequence confirmed that it belongs to Bacillus thuringiensis. Strain Q3-6 has a significant decolorization effect on the dyes. The decolorization rate for Brilliant blue G-250 (0.1 g/L) and Congo Red (0.1 g/L) can reach 93.9% and 91.9%, respectively. In addition, strain Q3-6 is resistant to many kinds of antibiotics and heavy metals. Further, it has strong heat resistance, and heating at 80 °C can promote the biomass of the strain. Genomic analysis revealed the presence of genes related to heat shock proteins (GroES, GrpE, DnaJ, GroEL, DnaK, ClpB, and ClpA) in strain Q3-6. These results suggest the strain’s exceptional resilience and adaptability to intricate environments with heavy metals, antibiotics, or high-temperature environments, suggesting its pivotal role in the bioremediation of complex contaminated effluents.