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Abstract The COVID-19 pandemic affected countries across the globe, demanding drastic public health policies to mitigate the spread of infection, which led to economic crises as a collateral damage. In this work, we investigate the impact of human mobility, described via international commercial flights, on COVID-19 infection dynamics on a global scale. We developed a graph neural network (GNN)-based framework called Dynamic Weighted GraphSAGE (DWSAGE), which operates over spatiotemporal graphs and is well-suited for dynamically changing flight information updated daily. This architecture is designed to be structurally sensitive, capable of learning the relationships between edge features and node features. To gain insights into the influence of air traffic on infection spread, we conducted local sensitivity analysis on our model through perturbation experiments. Our analyses identified Western Europe, the Middle East, and North America as leading regions in fueling the pandemic due to the high volume of air traffic originating or transiting through these areas. We used these observations to propose air traffic reduction strategies that can significantly impact controlling the pandemic with minimal disruption to human mobility. Our work provides a robust deep learning-based tool to study global pandemics and is of key relevance to policymakers for making informed decisions regarding air traffic restrictions during future outbreaks.

Abstract Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.

Abstract Cognitive impairment is a core symptom of schizophrenia (SZ), with GABAergic dysfunction in the brain potentially serving as a critical pathological mechanism underlying this condition. Intracortical inhibition (ICI), which includes short-interval intracortical inhibition (SICI) and long-interval intracortical inhibition (LICI), can be used to assess the inhibitory function of cortical GABAergic neurons. The aim of this study was to investigate the relationship between ICI and cognitive function, as well as psychopathological symptoms, in SZ patients. We recruited 130 SZ patients and 105 healthy controls (HCs). All subjects underwent paired-pulse transcranial magnetic stimulation (ppTMS) measurements, which included resting motor threshold (RMT), SICI and LICI. The cognitive function of all subjects was assessed using the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB). The psychopathological symptoms of the SZ group were assessed using the Positive and Negative Syndrome Scale (PANSS). We examined group differences in MCCB scores, RMT, SICI, and LICI. Within the SZ group, we assessed the relationship between ICI and cognitive function, as well as psychopathological symptoms. Two-way ANOVA, Mann–Whitney U test, Receiver operating characteristic (ROC) curves, and partial Spearman correlation analysis were performed. The SZ group showed a worse cognitive score in all 6 cognitive dimensions of the MCCB compared to the HC group (all p

Abstract We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models of key mechanisms underlying ICI therapy that may not be directly measurable in the clinic and easily measurable quantities or patient characteristics that are not always readily incorporated into predictive mechanistic models. A deep learning time-to-event predictive model trained on a hybrid mechanistic + clinical data set from 93 patients achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when trained on only mechanistic model-derived values or only clinical data. Feature importance analysis revealed that both clinical and model-derived parameters play prominent roles in increasing prediction accuracy, further supporting the advantage of our hybrid approach.

Abstract Background Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. Therapeutic targeting of miR-155 through its antagonist, anti-miR-155, has proven challenging due to its dual molecular effects. Methods We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. Results Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimens to prevent antagonistic effects. Conclusions This work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

Abstract Background The Diplolepideae are the larger group within the Arthrodontae mosses, characterized by peristomes formed from residual cell walls. It is now understood that these peristomes exhibit diverse hygroscopic movements, playing a crucial role in spore release. However, the exact mechanism behind this movement remains unclear, lacking direct evidence. This study investigated the microscopic and submicroscopic structures of the peristomes in three Diplolepideae species: Hypopterygium fauriei (Besch.), Pylaisia levieri (Müll. Hal.) Arikawa and Regmatodon declinatus (Hook.) Brid. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to reveal the differences in their hygroscopic movement mechanisms. Results The three species exhibited distinct responses upon wetting: H. fauriei’s exostome closed inwards, P. levieri’ opened outwards, and R. declinatus’ elongated significantly. These differences are attributed to the varying microfibril deposition in the exostome layers. Uniform deposition in the inner layer and minimal deposition in the outer layer enabled exostome opening upon wetting and closing when dry. Our findings suggest that the diastole and contraction of fine microfibrils in the exostome plates and ridges are the key drivers of hygroscopic movement. Conclusions This study provides further evidence at both the structural and submicroscopic levels, contributing to the unraveling of the hygroscopic movement mechanism in Diplolepideae peristomes. This enhanced understanding sheds light on the relationship between peristome structure and function.

Background: Spinal cord injury (SCI) is a severe impairment of the central nervous system, leading to motor, sensory, and autonomic dysfunction. The present study investigates the efficacy of the polyethylene glycol (PEG)-mediated spinal cord fusion (SCF) techniques, demonstrating efficacious in various animal models with complete spinal cord transection at the T10 level. This research focuses on a comparative analysis of three SCF treatment models in beagles: spinal cord transection (SCT), vascular pedicle hemisected spinal cord transplantation (vSCT), and vascularized allograft spinal cord transplantation (vASCT) surgical model. Methods: Seven female beagles were included in the SCT surgical model, while four female dogs were enrolled in the vSCT surgical model. Additionally, twelve female dogs underwent vASCT in a paired donor-recipient setup. Three surgical model were evaluated and compared through electrophysiology, imaging and behavioral recovery. Results: The results showed a progressive recovery in the SCT, vSCT and vASCT surgical models, with no statistically significant differences observed in cBBB scores at both 2-month and 6-month post-operation (both P>0.05). Neuroimaging analysis across the SCT, vSCT and vASCT surgical models revealed spinal cord graft survival and fiber regrowth across transection sites at 6 months postoperatively. Also, positive MEP waveforms were recorded in all three surgical models at 6-month post-surgery. Conclusion: The study underscores the clinical relevance of PEG-mediated SCF techniques in promoting nerve fusion, repair, and motor functional recovery in SCI. SCT, vSCT, and vASCT, tailored to specific clinical characteristics, demonstrated similar effective therapeutic outcomes.

Gross primary productivity (GPP) is a key parameter in research on the global carbon cycle and changes. Understanding the spatiotemporal dynamics and influencing factors of GPP on the Loess Plateau (LP) helps identify the health status of ecosystems, thereby enabling the implementation of effective conservation and restoration measures. In this study, we used a modified vegetation photosynthesis model (VPM) to simulate a long-term series of GPP in the LP from 2001 to 2022, and the impacts of different land-use patterns and meteorological factors on GPP were investigated using a transition matrix, linear regression, and partial correlation analyses. The findings suggested that the modified simulation yielded a more reliable performance (coefficient of determination (R2) = 0.89, root mean square error (RMSE) = 143.47 gC·m−2·yr−1) and was suitable for further research endeavors. (1) The GPP on the LP significantly increased by 232.65 TgC from 2001 to 2022. The southeastern region contributed more than the northwestern region, and the GPP exhibited higher multi-year averages and growth rates below 1000 m elevation. (2) Forests in the southeastern region of the LP, characterized by a heightened growth rate, will influence future spatial variations in GPP increases across the LP. Despite the decline in grassland and cultivated land areas, substantial land coverage has significantly contributed to the overall GPP growth. Urbanization encroaching on cultivated land has emerged as a key contributor to the decline in GPP in low-altitude regions. (3) Air temperature was the main physical driving force for GPP change in the LP. Additionally, the GPP in forested regions exhibited a negative correlation with rainfall, whereas the GPP in areas undergoing the return of cropland to forest–grassland and cropland reclamation correlated negatively with solar radiation. (4) The attribution analysis indicated that the surge in vegetation GPP on the LP was collectively driven by human activities and meteorological changes, with human activities dominating these changes by 61.41 %. This study deepens the understanding of terrestrial ecology in semi-humid regions and provides scientific insights for implementing ecological governance strategies in the LP.

Background The aim of this study was to develop and validate a prediction model for predicting the risk of preoperative asymptomatic lower extremity venous thrombosis (LEVT) in patients with knee osteoarthritis (KOA). Methods Patients with KOA diagnosed at our hospital between March 2022 and July 2023 were included in this study. Five factors were identified as independent risk factors for the development of preoperative asymptomatic LEVT in patients with KOA by univariate and multivariate logistic regression analysis and a prediction model was constructed by analyzing the results. The performance of the model was evaluated using receiver operating characteristic (ROC) curves. The accuracy of the model and its predictive ability were evaluated using calibration curves. The clinical application value of the prediction model was evaluated using decision curve analysis (DCA). Results A total of 354 patients diagnosed with KOA were included in the study. Multivariate logistic regression analysis revealed HDL 0.55 mg/L ( P = 0.049 ) were the independent risk factors for the occurrence of preoperative asymptomatic LEVT in patients with KOA. The combined-variable ROC curve suggested greater predictability and accuracy (AUC = 0.843, specificity = 90.3%, sensitivity = 71.4%). The calibration curve showed good model agreement and DCA suggested good clinical value of the model. Conclusion Low HDL, high LDL, Na + , Ca 2+ , and D-dimer levels can be used as independent risk factors for the preoperative prediction of asymptomatic LEVT in patients with KOA, and the present study also provides a simple prediction model for clinicians and patients.

Nitrate leaching is the main pathway of reactive nitrogen loss in Chinese agricultural systems, leading to groundwater contamination. However, the effect of fertilization on reactive nitrogen losses through nitrate leaching under various natural conditions and key influencing factors in Chinese agricultural systems remains unclear. Therefore, we conducted a comprehensive meta-analysis of 394 observations from 50 published articles to investigate how management practices, climatic conditions, and soil properties influence nitrate leaching from upland and paddy fields in China. Our results showed that nitrogen fertilizer application (NFP) significantly increased nitrate leaching in paddy and upland fields, with paddy fields exhibiting lower nitrate leaching than upland fields. In paddy fields, soil pH and NFP timing were the main drivers of nitrate leaching, while in upland fields, NFP rate and pH were the main driving factors. The NFP rate showed a significant positive correlation with nitrate leaching in both upland and paddy fields. Combining chemical fertilizer and organic manure applications was the effective method for mitigating nitrate leaching in paddy and upland fields. The structural equation modeling (SEM) revealed significant effects of soil properties on the nitrate leaching in paddy and upland fields during the crop growing season (P15 ℃ helped mitigate the risk of nitrate leaching. Our findings provide valuable guidance for optimizing NFP in agricultural production to improve nitrogen use efficiency and reduce groundwater pollution.

Soil moisture content (SMC), as a pivotal component in the energy and matter exchange processes within the soil-plant-atmosphere continuum, plays a crucial role in surface water dynamics, energy fluxes, and carbon cycling within ecosystems. The development of remote sensing technology has offered new perspectives for monitoring soil moisture at regional scales. Unmanned aerial vehicles (UAV) equip with multispectral have distinct advantages for vegetation monitoring, including rapidity and cost-effectiveness, which has superior applicability and practicality. Therefore, in a 5a ''Daya'' late-maturing citrus orchard, the vegetation index (VI) and texture feature (TF) information of citrus canopy based on UAV multi-spectral images were extracted, and soil and plant analyzer development (SPAD) of citrus was collected. These different data sources were integrated into the framework of the random forest algorithm (RF) and genetic algorithm-optimized random forest (GA-RF) to evaluate the accuracy of surface SMC (SSMC) estimation in citrus orchard. The Biswas model was utilized to simulate the root zone SMC (RSMC). The spatiotemporal variations of SMC in citrus orchard were analyzed, and the potential of low-cost sensor-equipped drones in rapidly acquiring spatial and temporal distribution information of SMC at a large regional scale was explored. The results indicated that the GA-RF models outperformed the RF models in estimating citrus orchard SMC (with R2 ranging from 0.502 to 0.949 and RMSE ranging from 0.552 % to 3.166 % for GA-RF, compared to R2 ranging from 0.430 to 0.936 and RMSE ranging from 0.587 % to 3.449 % for the RF). The GA-RF models using VI+SPAD as inputs exhibited the best performance for SMC at depths of 5 cm, 10 cm, 20 cm and 40 cm (SMC5, SMC10, SMC20 and SMC40) across citrus growth stages (R2 ranging from 0.793 to 0.949 at 5 cm, R2 ranging from 0.702 to 0.938 at 10 cm, R2 ranging from 0.714 to 0.927 at 20 cm). In bud bust to flowering, young fruit and fruit maturation stages (stage Ⅰ, ⅠⅠ and ⅠⅤ), all models demonstrated good accuracy in estimating SMC at depth of 10 cm (R2 ranging from 0.567 to 0.908 in stage Ⅰ, with R2 ranging from 0.681 to 0.916 in stage ⅠⅠ and R2 ranging from 0.579 to 0.938 in stage ⅠⅤ). In fruit expansion stage (stage III), the models performed best in predicting SMC5 (R2 ranging from 0.698 to 0.861). The Biswas model was constructed to simulate SMC40 by utilizing the inverted SMC10 and SMC20, thereby generating spatiotemporal distribution maps of SMC at different depths in citrus orchard. The SSMC was susceptible to environmental factors, exhibiting significant spatiotemporal heterogeneity. In summary, this study illustrated that the integration of multiple data sources into GA-RF enhanced the estimation performance of SMC at different growth stages of late-maturing citrus orchard in the Southwest China. Additionally, it enabled the rapid and efficient monitoring of spatiotemporal variations in SMC, providing an effective method and practical foundation for precision irrigation and improved water use efficiency.

Abstract The development of intrinsically stretchable polymer semiconductor holds substantial promise in the field of wearable electronics. However, charge transport mobility is typically compromised in existing stretchable semiconductors to achieve the desired stretchability. Herein, a novel “regional conjugation” strategy is proposed to design an intrinsically stretchable polymer semiconductor oligo‐diketopyrrolopyrrole‐thieno[3,2‐b]thiophene (DPPTT)–urethane, in which oligo‐DPPTT conjugated units and alkyl urethane nonconjugated units are introduced. The regional conjugation of oligo‐DPPTT in the polymer backbone endows DPPTT–urethane with good molecular packing, leading to a high mobility of up to 1.7 cm2 V−1 s−1. Additionally, incorporating alkyl urethane nonconjugated units in the backbone can reduce film crystallinity and chain aggregation, which contribute to the stretchability of the polymer thin film. Consequently, fully stretchable transistors retain carrier mobility even at 100% biaxial tensile strain. Furthermore, the fully stretchable organic field‐effect transistor arrays show remarkable charge transport reversibility and durability after 1000 stretch–release cycles at 25% strain. Additionally, the device exhibits extraordinary electrical stability in air atmosphere. Overall, these results indicate that the “regional conjugation” strategy provides an effective and promising methodology to design intrinsically stretchable and high‐performance polymer semiconductor that can advance the development of soft and wearable electronics.

Hydrological changes in groundwater coupled with earthquakes had been documented in previous studies by global researchers. Although few reports investigate multiple geochemical parameters that respond to earthquakes, trace elements received less attention, whereas they were suggested to be more sensitive to small earthquakes than the commonly used geochemical parameters. Beijing is located in the Zhangjiakou-Bohai (Zhang-Bo) seismic belt of North China, and although the occurrence of small earthquakes is frequent, the great historic earthquake in the Sanhe-Pinggu area M8 in 1679 in the adjoining southeast of Beijing gained widespread public attention. To find effective precursors that are significant for operational earthquake forecasting of the Beijing area, we carried out a one year test research project through weekly collection of groundwater samples during June 2021 to June 2022 from the seismic monitoring well of Wuliying in northwest Beijing. The 41 trace elements chemical compositions were analyzed for each sample. During the project ongoing period, the biggest earthquake with a magnitude of ML3.3 occurred in the Chaoyang District of Beijing on 3 February 2022. The content changes in these trace elements were systematically monitored before and after the earthquake. Through retrospective research, it was found that a few sensitive trace elements were anomalous to be coupled to the earthquake, including Li, Sc, Rb, Mo, Cs, Ba, W, U, Sr, Mn, Ni, and Zn. In addition to trace elements, we examined stable isotopes of hydrogen and oxygen and the existing hydrological data on groundwater level, temperature, major ions, and gases to assess the validity of geochemistry as a monitoring and predictive tool. We only found that F- (fluorine) ions and He (helium) gas had apparent shifts related to the earthquakes, while no shifts in the groundwater level were observed. Such characteristics of multiple geochemical parameters indicate that trace elements are likely to be more sensitive to crustal strain than the groundwater level and major ions. We assumed a most likely mechanism of the combination of mixing and water–rock interactions to explain the phenomenon. The probable scenario was that minor stresses caused by the earthquakes might create micro-cracks in bedrocks, thereby leading to a small volume of chemically distinct water mixing with the original water of the aquifer, and finally, the earthquake-induced rock fractures enhance the water–rock interactions, resulting in the post-seismic recovery of trace elements and δ18O value migration to the GWML. More testing works to find other sensitive sites to investigate multiple geochemical characteristics aiming at long-term to short-term earthquake prediction in the Beijing area and Zhang-Bo seismic belt are in progress.

With the rapid expansion of artificial light in the global nocturnal environment, the ecological impacts of artificial light at night (ALAN) on plant communities have garnered increasing research interest. However, the role of phyllosphere microorganisms as mediators in the regulation between ALAN and plants remains unclear. In this study, we conducted a field experiment in natural grassland plots, employing two treatments: one with no artificial light at night (control) and another with artificial light at night (ALAN). We then investigated the response of phyllosphere microorganisms in three grassland plant species (Leymus chinensis, Vicia sepium, and Aster altaicus) to ALAN exposure. The results revealed that the constructive species L. chinensis demonstrated a markedly higher diversity of phyllosphere bacteria and fungi compared to V. sepium and A. altaicus and thus had the most abundant microbial community. However, ALAN exposure reduced the diversity of phyllosphere bacteria and fungi in all three plant species to varying degrees. ALAN induced certain changes to the phyllosphere bacterial community composition, particularly manifesting in a reduction in the abundance of beneficial bacteria, including Sphingomonas, Hymenobacter, Methylobacterium-Methylorubrum, and Bacillus. Compared with phyllosphere bacterial communities, the alterations in phyllosphere fungal communities were more sensitive, characterized by a significant decrease in the abundance of certain fungi, including Zymoseptoria, Mycosphaerella, Cladosporium, and Epicoccum. The functional predictions of phyllosphere bacteria and fungi further corroborate these conclusions. In summary, ALAN exposure may suppress the functional capacity of phyllosphere microorganisms in grassland plants while decreasing the probability of fungal pathogen occurrence.

The effects of deoxidation methods on the inclusion characteristics and corrosion behaviour of high-strength low-alloy steels were examined in marine environments using various microcharacterisation techniques and first-principles calculations. After Ca treatment, MnS–MgO–Al2O3 inclusions were modified to CaS–MgO–Al2O3 and microcrevices were existed at the interface between inclusions and Fe. After Zr–Ti-RE deoxidation, spherical CaS + TiN + ZrO2+MgAl2O4+(Ca, La) Al3O7 inclusions appeared. (Ca, La)Al3O7 in steel displayed similar mechanical properties to Fe, reducing the degree of lattice distortion and the formation of microcrevices around the inclusions. Micro-galvanic corrosion between Fe and MnS accelerated the localised corrosion rate and promoted the formation of large pits on the surface. However, the chemical activity of CaS resulted in dissolution of the inclusion, which relatively inhibited the localised corrosion propagation. The enrichment of Cr in the rust layer after Zr–Ti-RE deoxidation improved the compactness, contributed to a reduction in the localised corrosion rate and long-term corrosion rate. Finally, the underlying mechanism influencing corrosion behaviour was established.

Tungsten-rhenium alloys with high-temperature strength and creep resistance are widely used in the cutting-edge scientific and technological sectors. However, W-5Re alloy with Re content of 5 wt% shows brittleness at room temperature, limiting its aviation temperature measurement. This work provides W-5Re-xB4C (x = 0∼2.0 wt%) tungsten-rhenium alloys with high compressive performance by introducing B4C ceramic phase and regulating the B4C content. The alloys are composed of W(Re) solid solution, W2B phase and a few W2C. When increasing B4C addition, the grain size of the W(Re) matrix decreases from about 200 μm to 17 μm in W-5Re-2B4C and the content of intermetallic compounds increase to be about 12% in W-5Re-0.5B4C and 58% in W-5Re-2B4C. The W-5Re-0.5 wt% B4C alloy exhibits a high yield strength of 1.19 GPa and compressive plasticity with a plastic strain of 42.50%, while the W-5Re-0.75B4C alloy has a high yield strength of 1.52 GPa and good compressive plasticity of 22.52%, obviously higher than the reported W-5Re alloys. Fine-grain strengthening from the refinement of W(Re) and second-phase strengthening from intermetallic compounds simultaneously enhance the alloys, while good deformability of W(Re) metallic phase contributes to the room-temperature plasticity. This study provides necessary data accumulation and theoretical support for the application of tungsten-rhenium alloys.

Abstract This study investigated the effects of bamboo age, bamboo parts, and pyrolysis temperatures on the physiochemical properties of bamboo char throughout a series of pyrolysis processes spanning from 150 °C to 1000 °C. The results indicated that as the pyrolysis temperature increased from 150 °C to 500 °C, the yield of bamboo char experienced a rapid decline, settling at a maximum of 69%, with no significant impact from bamboo age and parts. Subsequently, as the pyrolysis temperature continued to rise from 500 °C to 1000 °C, the yield stabilized at 25.74–32.64%. Besides, fixed carbon (FC), volatile matter (VM), and ash content were temperature-dependent, while the H/C, O/C, (N + O)/C, and aromatic index kept constant after reaching 500 °C. Notably, 800 °C was confirmed to be a crucial turning point for physiochemical properties, at which the graphitic structural changes occurred, pore collapsed, and potassium salts released. Bamboo age was proved to enhance the stability. Pearson correlation coefficient (PCC) analysis revealed that the pyrolysis temperature was positively correlated (p

Based on the five main activation mechanisms, this study explored the potential activating elements in Al-based sacrificial anodes (SAs) combining electrochemical experiments and theoretical calculation. Mn, Y, Zr, Nb, and Ta, aligning with several activation mechanisms, are expected to be the potential activating elements besides the acknowledged activating elements (In, Sn, Ga, Zn, Bi). In addition, the negative shift of potential effect of In to Al matrix is denied both experimentally and theoretically. This study will contribute to establish a comprehensive understanding for the development of Al SAs.

ABSTRACTSince the initiation of the Grain for Green Project (GFGP) in 1999, dramatic change in vegetation status on the Loess Plateau. Spatially, geographical detector was employed to detect dominant variables influencing the spatial arrangement of normalized difference vegetation index (NDVI). Temporally, lagged or accumulated monthly precipitation, temperature and standardized precipitation evapotranspiration indices (SPEIs) sensitive to the monthly NDVI were first detected for every individual pixel, and the correlation between the NDVI and meteorological elements with time-lag effects was established a random forest model of unchanged land cover, followed by attributing impacts of climatic alterations and human interventions through residual examination across changed land cover. The findings indicate that (1) precipitation, slope, and soil dominantly influence the spatial arrangement of the NDVI. (2) Precipitation in current the month and cumulative temperatures of the previous 1–2 months steadily affect vegetation growth significantly, the optimal accumulation time interval for SPEI around 2000 are 8 months and 4 months, respectively. (3) Increases in the average NDVI within woodland and meadow vegetation on the Loess Plateau were primarily driven by climate change before 2000, accounting for 76.2%, whereas after 2000 it was dominantly driven by human activities, accounting for 64.16%.

ABSTRACTAccurate monitoring of the leaf area index (LAI) and aboveground biomass (AGB) using remote sensing at a fine scale is crucial for understanding the spatial heterogeneity of vegetation structure in mountainous ecosystems. Understanding discrepancies in various retrieval strategies considering topographic effects or not is necessary to improve LAI and AGB estimations over mountainous areas. In this study, the performances of the look-up table method (LUT) using radiative transfer model (RTM), machine learning algorithms (MLAs), and hybrid RTM integrating RTM and MLAs based on Landsat surface reflectance (SR) before and after topographic correction were compared and analyzed. The results show that topographic correction improves the accuracies of retrieval methods involving RTM more significantly than the MLAs, meanwhile, it reduces the performance variability of different MLAs. Based on the topographically corrected Landsat SR, the random forest (RF) combined with RTM improves the retrieval accuracy of RTM-based LUT by 7.7% for LAI and 13.8% for AGB, and reduces the simulation error of MLA by 15.1% for LAI and 20.1% for AGB. Compared with available remote sensing products, the hybrid RTM based on Landsat SR with topographic correction has better feasibility to capture LAI and AGB variation at 30 m scale over mountainous areas.

The ‘Okitsu No. 58’ citrus variety is highly prone to fruit cracking, which jeopardizes yield and results in economic losses. In this study, we investigated the impacts of spraying 5 distinct concentrations (0.1, 0.2, 0.3, 0.4, and 0.5 g/L) of chelated calcium (Ca) or silicon (Si) fertilizers at the young fruit stage (60-90 days after flowering, DAF) on fruit cracking and quality in the citrus variety ‘Okitsu No. 58’. The results showed either Ca or Si fertilizer treatments reduced fruit cracking. We found that all Ca and partial Si treatments (0.4 and 0.5 g/L) significantly promoted the accumulation of Ca content in the peel. Notably, Ca or Si treatments significantly reduced polygalacturonase (PG) activity and inhibited the production of water-soluble pectin (WSP) in the peel. Additionally, Ca or Si treatments elevated the superoxide dismutase (SOD) activity and decreased the malondialdehyde (MDA) content of the peels. Changes in these parameters likely contributed to strengthening the durability of peel cell wall constituents, thus enhancing the fruit’s resistance to fruit cracking. Overall, except for the C3 (0.3 g/L of Ca), Ca or Si fertilizers contributed to fruit conventional quality, mainly in terms of higher soluble sugars (SS) and SS/TA (titratable acid). Therefore, our findings will provide a reference for the prevention and control of citrus fruit cracking and the development of new fertilizers.

BackgroundThe study aimed to evaluate the positivity rates and genotype distribution of the multiplex PCR capillary electrophoresis (MPCE) and PCR-Reverse Dot Blot (PCR-RDB) assays for human papillomavirus (HPV) detection in cervical cancer tissue specimens, and to explore their detection principles and applications in large-scale population screening.MethodsThe MPCE and PCR-RDB assays were performed separately on 425 diagnosed cervical cancer tissue specimens. Subsequently, the results of both assays were compared based on the HPV infection positivity rates and genotype distribution.ResultsThe overall positive rates of HPV genotypes for the MPCE and PCR-RDB assays were 97.9% and 92.9%, respectively. A p-value < 0.001 indicated a statistically significance difference in consistency between the two assays. The kappa value was 0.390, indicating that the consistency between both assays was fair. HPV16 was the most common single-genotype infection type, with infection rates detected via MPCE and PCR-RDB assays being 75.7% and 68.3%, respectively. In the age group >50 years, the HPV multiple-type infection rate detected via MPCE assay was significantly higher than that detected by the PCR-RDB assay, with a statistically significant difference (p = 0.002).ConclusionTo reduce the false-negative rate and improve screening efficiency, the MPCE assay, which targets the oncogenic gene E6/E7 segments, can be extended to the general female population for the early detection, diagnosis, and treatment of cervical cancer.

The phenomenon of nitrogen deposition resulting in species loss in terrestrial ecosystems has been demonstrated in several experiments. Nitrogen (N) and phosphorus (P), as major nutrients required for plant growth, exhibit ecological stoichiometric coupling in many ecosystems. The increased availability of nitrogen can exacerbate the ecological effects of phosphorus. To reveal the ecological effects of phosphorus under nitrogen-limiting and non-limiting conditions, we conducted a controlled N–P interaction experiment over 5 years in the Hulunbuir meadow steppe, where two nitrogen addition levels were implemented: 0 g N·m-2·a-1 (nitrogen-limiting condition) and 10 g N·m-2·a-1 (nitrogen-non-limiting condition), together with six levels of phosphorus addition (0, 2, 4, 6, 8, and 10 g P·m-2·a-1). The results showed that nitrogen addition (under nitrogen-non-limiting conditions) significantly decreased species diversity in the steppe community, which was exacerbated under phosphorus addition. Under nitrogen-limiting conditions, phosphorus addition had no marked impact on species diversity compared to the control; however, there were substantial differences between different levels of phosphorus addition, exhibiting a unimodal change. Under both experimental nitrogen conditions, the addition of 6 g P·m-2·a-1 was the threshold for affecting the community species diversity. Nitrogen addition reduced the relative biomass of legumes, bunch grasses, and forbs, but substantially increased the relative biomass of rhizomatous grasses. In contrast, phosphorus addition only markedly affected the relative biomass of forbs and rhizomatous grasses, with the former showing a unimodal pattern of first increasing and then decreasing with increasing phosphorus addition level, and the latter exhibiting the opposite pattern. The different responses of rhizomatous grasses and other functional groups to nitrogen and phosphorus addition were observed to have a regulatory effect on the changes in grassland community structure. Phosphorus addition may increase the risk of nitrogen deposition-induced species loss. Both nitrogen and phosphorus addition lead to soil acidification and an increase in the dominance of the already-dominant species, and the consequent species loss in the forb functional group represents the main mechanism for the reduction in community species diversity.

Volatile compounds are important determinants affecting fruit flavor. Previous study has identified a bud mutant of ‘Ehime 38’ (Citrus reticulata) with different volatile profile. However, the volatile changes between WT and MT during fruit development and underlying mechanism remain elusive. In this study, a total of 35 volatile compounds were identified in the pulps of WT and MT at five developmental stages. Both varieties accumulated similar and the highest levels of volatiles at stage S1, and showed a downward trend as the fruit develops. However, the total volatile contents in the pulps of MT were 1.4–2.5 folds higher than those in WT at stages S2-S5, which was mainly due to the increase in the content of d-limonene. Transcriptomic and RT-qPCR analysis revealed that most genes in MEP pathway were positively correlated with the volatile contents, of which DXS1 might mainly contribute to the elevated volatiles accumulation in MT by increasing the flux into the MEP pathway. Moreover, temporal expression analysis indicated that these MEP pathway genes functioned at different developmental stages. This study provided comprehensive volatile metabolomics and transcriptomics characterizations of a citrus mutant during fruit development, which is valuable for fruit flavor improvement in citrus.

Functional characteristics of microbiomes are good predictors of nitrogen (N) biogeochemistry, but soil microbial N-functional profiles under different land use practices and their dominant drivers at continental scale remain unclear. For this study, we selected soils having a broad range of edaphic factors across different land use practices and soil types in China and used metagenomic sequencing to investigate N-functional profiles of microbiomes. The N-pathway frequencies were highest in paddy soils, and the composition of N-cycling genes in paddy soils significantly diverged from upland and forest soils. Differential abundance analysis showed that genes associated with nitrogen dissimilatory pathways exhibited enrichment in paddy soils, whereas those linked to assimilatory pathways were enriched in forest soils. Aggregated boosted tree analysis revealed that the frequencies of N-pathways and relative abundances of N-cycling genes were mainly explained by soil moisture and pH. Partial Mantel and redundancy analysis consistently showed that N-functional composition correlated strongest with moisture and pH. Overall, our results demonstrated that soil moisture and pH were vital drivers of microbial N-functional profiles, providing novel evidence for soil moisture and pH’s role in driving whole nitrogen cycling. Considering the large fluctuations in moisture over time, soil pH, with minor seasonality, could be used as indicators to reflect microbial N-functional profiles at the continental scale.

Internet of Electric Things (IoET) based on edge computing mode has advantages in functionality, communication efficiency and construction cost. However, the incompleteness of relevant security protocols restricts their application in smart grids. Therefore, we propose a lightweight three-layer device identity mutual authentication and key agreement protocol suitable for IoET with two-hops architecture. The simulation results of formal security analysis and automated security analysis toolset AVISPA on security attacks show that this protocol can meet the security requirements of identity authentication, device ID anti tracking, and session keys. Compared with recent lightweight third-party authentication protocols, our proposed scheme has advantages in resource consumption of servers and IoET Connector (IoetC) when multiple sensors require simultaneous authentication.

The coastal environment functional zoning in Zhejiang Province plays an important role in the protection of the coastal environment and the adjustment of the coastal resources exploitation and utilization, and has become an important basis for the coastal environment supervision. However, under the optimization of territorial spatial planning and high-quality development of marine economy, it has showed a significant lag. This paper analyzed its main problems through the experience of the coastal environment functional zoning in Zhejiang Province in compiling, adjusting, monitoring and evaluating. On this basis, policy recommendations for the management were put forward, including the important principle of ecological priority and bottom-line constraint, the orderly connection to the Zhejiang Province′s territorial spatial planning, the scientific control measures of different zones, the integration of various marine planning and protection objectives, and the sound management boundaries based on land-sea coordination.

Abstract The study investigates the optimization of life cycle carbon emissions in smart sustainable energy systems through power transformation and transmission project power load predictions. Firstly, a multi-task learning-based short-term user load forecasting technique is developed, where the power load curves of multiple residential customers are grouped and classified using the K-means clustering method. Additionally, the Bidirectional Long Short-Term Memory (BiLSTM) technique is introduced to anticipate the power load intelligently. Secondly, a life cycle carbon emission assessment model for the power transmission and transformation project (PTTP) is constructed based on the life cycle assessment (LCA) method, which divides the project's life cycle into four stages: production, installation and construction, operation and maintenance, and demolition. Finally, an experimental evaluation of this model is conducted. The results demonstrate that compared with the baseline model Long Short-Term Memory (LSTM), this model achieves a significantly lower average Mean Absolute Error (MAE) at 3.62% while achieving significantly higher accuracy in power load forecasting at 94.34%. A comprehensive examination of carbon emissions across all four phases reveals that overall carbon emissions are highest during the operation and maintenance stage followed by the equipment production stage and installation/construction stage, with the lowest overall carbon emissions observed. Hence, this study endeavors to forecast power load demand with precision and identify the principal determinants of carbon emissions in power engineering. By discerning and managing these key factors, an optimal, energy-efficient intelligent power load scheme can be derived.

High-quality porous ceramics are extremely attractive in terms of energy conservation and consumption reduction, and thus are one of the research hotspots pursued in recent years. For this purpose, porous MgO-based ceramics with outstanding thermal shock resistance and thermal insulation performance were designed and prepared by using the direct firing method and introducing alumina with different paticle sizes as additives. The results reveal that the in-situ formed MgAl2O4 phase by alumina additives simultaneously improves the apparent porosity, thermal insulation, and thermal shock resistance of the prepared MgO-based ceramics. Specifically, the increase in the apparent porosity can be attributed to the volume expansion effect of MgAl2O4 phase, so the industrial alumina with larger particle size is more effective (20 wt% addition: the apparent porosity from 43.5 % to 55.4 %, the thermal conductivity from 0.977 to 0.389 W m−1 K−1 at 800 °C); moreover, the enhancement in thermal shock resistance can be ascribed to the residual stress effect caused by the MgAl2O4 particles, so the micron alumina with smaller particle size is more efficient (10 wt% addition: the residual strength ratio from 93.48 % to 65.13 %–113.92 % and 94.47 % after one and five air-quenching). Therefore, this work demonstrates a novel synthetic strategy for porous ceramics with great potential in the field of high-temperature thermal insulation.

Combining first-principles calculations and classical nucleation theory, the results of elemental doping on the structure, electrons and stability of niobium carbides are investigated. Ti, Cr and Mn doping altered the physical characteristics of the carbides, resulting in lower mismatch strains and interfacial energies between the carbide and the substrate. Elemental doping reduced the critical nucleation size of carbides and contributed to the promotion of carbide nucleation. However, excessive doping with Cr and Mn increases the formation energy of carbides and unfavorable to carbide stabilization. Therefore, Cr and Mn are involved in the early elemental aggregation of carbides, while Ti and Nb are the main carbide-forming elements. The nano-precipitated phases of various compositions produced in niobium microalloyed steel were experimentally validated utilizing transmission electron microscopy (TEM) and three-dimensional atom probe tomography (3D-APT). The carbides primarily composed of Nb, Ti and C elements, with the presence of Cr and Mn in the core region leading to the formation of a core-shell structure, which is consistent with theoretical calculations.

Abstract Introduction The mitochondrial alanyl‐tRNA synthetase 2 (AARS2) as one of aminoacyl‐tRNA synthases (ARSs) performs amino acid transportation and involves protein synthesis. However, its role in cancer remains largely unexplored. Methods In this study, more than 10,000 samples were enrolled to explore genomic alterations, biological function, prognosis, and clinical treatment based on AARS2 across pan‐cancer. The molecular characterization of AARS2 was confirmed in hepatocellular carcinoma (HCC) using proteomics analysis, quantitative real‐time PCR, western blotting, immunohistochemical staining, and cell experiments. Results For genomic landscape, the AARS2 was dramatically upregulated in multiple cancers, which might be mainly caused by copy number alteration rather than mutation and methylation. The abnormal expression of AARS2 was prominently associated with activity of cancer pathways and performed oncogenic roles in most cancers. Systematic experiments in vitro substantiated the elevated expression of AARS2, and the deficiency of it inhibited cell proliferation and cell migration in HCC. Meanwhile, our findings suggested that AARS2 could serve as a novel promising and stable biomarker for assessing prognosis and immunotherapy. Moreover, a variety of therapeutic drugs and targeted pathways were proposed for cancer treatment, which might enhance clinical efficacy. Conclusion The AARS2 could serve as a new oncogenic gene that promotes cell proliferation and migration in HCC. The comprehensive investigations increased the understanding of AARS2 across human cancers and generated beginning insights of AARS2 in genomic landscape, molecular biological function, prognosis, and clinical treatment.

Abstract Background Glycosylation, catalyzed by UDP-glycosyltransferase (UGT), was important for enhancing solubility, bioactivity, and diversity of flavonoids. Peanut (Arachis hypogaea L.) is an important oilseed and cash crop worldwide. In addition to provide high quality of edible oils and proteins, peanut seeds contain a rich source of flavonoid glycosides that benefit human health. However, information of UGT gene family was quite limited in peanut. Results In present study, a total of 267 AhUGTs clustered into 15 phylogenetic groups were identified in peanut genome. Group I has greatly expanded to contain the largest number of AhUGT genes. Segmental duplication was the major driving force for AhUGT gene family expansion. Transcriptomic analysis of gene expression profiles in various tissues and under different abiotic stress treatments indicated AhUGTs were involved in peanut growth and abiotic stress response. AhUGT75A (UGT73CG33), located in mitochondria, was characterized as a flavonoid 7-O-UGT by in vitro enzyme assays. The transcript level of AhUGT75A was strongly induced by abiotic stress. Overexpression of AhUGT75A resulted in accumulating less amount of malondialdehyde (MDA) and superoxide, and enhancing tolerance against drought and/or salt stress in transgenic Arabidopsis. These results indicated AhUGT75A played important roles in conferring abiotic stress tolerance through reactive oxygen species scavenging. Conclusions Our research only not provides valuable information for functional characterization of UGTs in peanut, but also gives new insights into potential applications in breeding new cultivars with both desirable stress tolerance and health benefits.

The improved heat dissipation observed in 3D micro-ribbed tubes is primarily influenced by the intricate interplay of multiple structural parameters. Nevertheless, research into the coupling mechanisms of these multi-structural parameters remains constrained by the absence of effective methodology in numerical solutions. In the present work, a new 3D micro-rib structure based on discrete adjoint method is established. Firstly, the research examines the interplay of different parameters (such as arrangement, relative roughness height, angle of attack, and circumferential rows) on the thermo-hydraulic performance. It is noted that the heat transfer efficiency is notably impacted by the relative roughness height. And the arrangement methodology dictates the optimal positioning for heat transfer efficiency. An increase in the number of circumferential rows enhances fluid mixing, while the angle of attack plays a crucial role in the formation of longitudinal vortices. Secondly, the coupling optimization technique is employed to obtain the optimal structure featuring non-uniform relative roughness height by the developed numerical solution. Overall, in comparison to the smooth tube, the optimized ribbed tube exhibits a remarkable 64.9% enhancement in performance evaluation criteria. Finally, a notable enhancement of 10.65–22.78% is observed when comparing with the prevailing micro-rib structures.

In this work, we applied commercially available 2-pyridinecarboxylic acid to modify cellulose by simple manipulations, and then anchored low-toxicity metal nickel onto the modified cellulose to prepare the heterogeneous catalyst (CL-AcPy-Ni). The obtained catalyst was characterized by FT-IR, TG-DSC, BET, XRD, SEM-EDS, ICP-OES, XPS, and GPC. The catalytic performance of CL-AcPy-Ni in the Suzuki cross-coupling reaction was investigated using 4-methyl iodobenzene and phenylboronic acid as the model substrates reacting in THF under 120 °C for 24 h. The catalytic ability of CL-AcPy-Ni for various halobenzenes and phenylboronic acid derivatives was also further investigated under optimal conditions and demonstrated good catalytic activity, and a series of diaryls were successfully synthesized. Finally, this green nickel-based catalyst could be reused for five successive cycles by simple centrifugation.

Albizia odoratissima is a deciduous tree species belonging to the family Leguminosae. It is widely distributed in the southern subtropical and tropical areas of China and has important ecological and economic value. The growth and metabolic processes of A. odoratissima are affected by drought stress, but the molecular mechanisms remain unknown. Therefore, this study investigated the physicochemical properties, gene expression, and metabolites of A. odoratissima seedlings under drought stress. The results show that, in leaves of A. odoratissima seedlings, drought stress reduced the moisture content, chlorophyll content, photosynthetic efficiency, superoxide dismutase (SOD) activity, and gibberellin (GA) and indoleacetic acid (IAA) contents while increasing the catalase (CAT) and peroxidase (POD) activities and malondialdehyde (MDA), proline, soluble sugar, and soluble protein contents. Within the CK5 (Day 5 of control group) vs. T5 (Day 5 of drought treatment), CK10 vs. T10, CK15 vs. T15, and CK20 vs. T20 groups (CK: control group; T: drought treatment), a total of 676 differentially expressed genes (DEGs) were upregulated and 518 DEGs were downregulated, and a total of 228 and 143 differential accumulation metabolites (DAMs) were identified in the CK10 vs. T10 and CK20 vs. T20 groups. These were mainly involved in the amino acid and alkaloid metabolism pathways in the leaves of the A. odoratissima seedlings. In the amino acid and alkaloid biosynthesis pathways, the relative expression levels of the AoproA (Aod04G002740, ORTHODONTIC APPLIANCE), AoOAT (Aod07G015970, ORNITHINE-OXO-ACID TRANSAMINASE), and AoAOC3 (Aod12G005010/08G003360/05G023920/08G003000/08G003010, AMINE OXIDASE COPPER CONTAINING 3) genes increased, which concurrently promoted the accumulation of arginine, proline, piperine, cadaverine, and lysine. Furthermore, some key transcription factors in the response to drought were identified in the leaves using the weighted gene co-expression network analyses (WGCNA) method. These findings reveal that A. odoratissima seedlings respond to drought stress by improving the capacities of the antioxidant system and secondary metabolism.

This paper proposes a novel method for diagnosing faults in oil-immersed transformers, leveraging feature extraction and an ensemble learning algorithm to enhance diagnostic accuracy. Initially, Dissolved Gas Analysis (DGA) data from transformers undergo a cleaning process to ensure data quality and reliability. Subsequently, an interactive ratio method is employed to augment features and project DGA data into a high-dimensional space. To refine the feature set, a combined Filter and Wrapper algorithm is utilized, effectively eliminating irrelevant and redundant features. The final step involves optimizing the Light Gradient Boosting Machine (LightGBM) model using IAOS algorithm for transformer fault classification; this model is an ensemble learning model. Experimental results demonstrate that the proposed feature extraction method enhances LightGBM model’s accuracy to 86.84%, representing a 6.58% improvement over the baseline model. Furthermore, optimization with IAOS algorithm increases the diagnostic accuracy of LightGBM model to 93.42%, an additional gain of 6.58%.

Ecosystems that experience elevated CO2 (eCO2) are crucial interfaces where intricate interactions between plants and microbes occur. This study addressed the impact of eCO2 and a N supply on faba bean (Vicia faba L.) growth and the soil microbial community in auto-controlled growth chambers. In doing so, two ambient CO2 concentrations (aCO2, daytime/nighttime = 410/460 ppm; eCO2, 550/610 ppm) and two N supplement levels (without a N supply—N0—and 100 mg N as urea per kg of soil—N100) were applied. The results indicated that eCO2 mitigated the inhibitory effects of a N deficiency on legume photosynthesis and affected the CO2 assimilation efficiency, in addition to causing reduced nodulation. While the N addition counteracted the reductions in the N concentrations across the faba beans’ aboveground and belowground plant tissues under eCO2, the CO2 concentrations did not significantly alter the soil NH4+-N or NO3−-N responses to a N supply. Notably, under both aCO2 and eCO2, a N supply significantly increased the relative abundance of Nitrososphaeraceae and Nitrosomonadaceae, while eCO2 specifically reduced the Rhizobiaceae abundance with no significant changes under aCO2. A redundancy analysis (RDA) highlighted that the soil pH (p < 0.01) had the most important influence on the soil microbial community. Co-occurrence networks indicated that the eCO2 conditions mitigated the impact of a N supply on the reduced structural complexity of the soil microbial communities. These findings suggest that a combination of eCO2 and a N supply to crops can provide potential benefits for managing future climate change impacts on crop production.

Water deficit drip irrigation (WDDI) in citrus orchards was found has a positive effect on fruit quality, particularly enhancing the soluble sugar content during the late period of fruit growth. However, the underlying molecular mechanism remains unclear. In this study, four deficit irrigation levels of D-60%, D-45%, D-30%, and D-15% were set at fruit expansion stage (stage III) and maturation stage (stage IV), respectively, and a fully irrigated treatment was set as the control (CK). Combined analysis of metabolomics and transcriptomics was used to reveal the molecular mechanism of sugar accumulation changes under different water deficit (WD) treatments. The results showed that sugar metabolism was growth stage dependent: stage III is a key period of sucrose metabolism and synthesis, while for stage IV, the accumulation of glucose and fructose increased significantly. Importantly, III-D15% and IV-D30% treatments were identified as optimal strategies for enhancing sugar content of citrus fruits. WDDI during the late growth stages up-regulated the expression of sugar metabolism-related differential expression genes (DEGs), consequently increasing the content of sugar-related differential expression metabolites (DEMs), and ultimately enhancing sugar accumulation in citrus fruits. For III-D15% treatment, DEMs related to sugar metabolism were mainly enriched in ‘carbon metabolism’, with significant increases in Sucrose, ɑ-D-Glucose-6 P and ß-D-Fructose-6 P content observed. SPS showed significant up-regulation, wihle BGLU, GN, TPS11, TPPF and TPPJ were down-regulated. For IV-D30% treatment, most DEMs were significantly enriched in ‘Glycolysis/Gluconeogenesis’. Key DEMs (Sucrose, D-Glucose-6 P, ß-D-Fructose-6 P) and DEGs (SUS, SPS, BGLU, HXK) involved in the metabolism and synthesis of sucrose, fructose and glucose were significantly increased. This study sheds light on the molecular mechanisms of sugar accumulation in citrus fruit under appropriate WDDI, providing valuable guidance for high-quality fruit production.

Context: Deficit drip irrigation is an advanced agricultural technology widely promoted and applied around the world to maintain/increase yield and quality while simultaneously minimizing water consumption. However, there is still a lack of comprehensive research on the effects of deficit drip irrigation at different stages on apple yield, water productivity, and quality. Objective: The aim was to investigate the effects of deficit drip irrigation treatments (DDITs) on apple yield, quality, and water productivity (WP), and optimize the deficit drip irrigation strategy for apples in the Loess Plateau of China. Methods: a two-year field experiment was conducted with 17 irrigation treatments, including a control treatment (CK, full irrigation (FI)) and four DDITs (D15%, D30%, D45%, D60%) during the bud burst to leafing stage (I), flowering to fruit set stage (II), fruit expansion stage (III), and fruit maturation stage (IV). The optimal irrigation management was determined using the fuzzy Borda combined model, which was based on four different single evaluation models of the TOPSIS method, principal component analysis (PCA), grey correlation analysis (GCA), and membership function analysis (MFA). Results: The DDITs at stage IV decreased midday leaf water potential (Ψs) by 2.57–20.00% compared with CK, and the difference of Ψs between IV-D30%, IV-D45%, IV-D60%, and CK were significant in two years (P

Summary: Background: Parkinson's disease (PD) has become a public health concern with global ageing. However, comprehensive assessments of the temporal and geographical trend of PD disease burden in China remain insufficient. This study aimed to examine the burden of PD by age, gender, and geographical region in China during 1990–2021. Methods: Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, we analysed the incidence, prevalence, mortality, and DALY burden of PD in 33 Chinese provinces/regions. We compared the national figure with the global average and the corresponding estimates from the G20 countries. The estimated annual percentage change (EAPC) was used to quantify the temporal trends of PD burden during 1990–2021. We further assessed the PD burden by age and gender during 1990–2021. We used a decomposition analysis to investigate the changes in the number of new cases, patients, and deaths of PD during 1990–2021. Findings: In 2021, China recorded the highest age-standardised incidence and prevalence of PD among the G20 countries, at 24.3 per 100,000 and 245.7 per 100,000, respectively, figures that were much higher than the global average. During 1990–2021, the age-standardised incidence of PD in China increased by 89.7%, and the age-standardised prevalence by 167.8%, both marking the largest increases among the G20 countries. In contrast, the age-standardised mortality for PD has significantly decreased since 1990, whereas the age-standardised DALY rate for PD has remained relatively unchanged since 1990. The PD burden gradually increased with age, especially in the elderly population aged ≥65 years. During 1990–2021, the burden in males consistently surpassed that in females, with the gender difference widening over time. The increase in new cases and patients of PD was primarily driven by changes in age-specific rates, while the rise in PD-related deaths was largely attributable to population ageing. The disease burden of PD varied considerably across the Chinese provinces. In 2021, age-standardised incidence and prevalence of PD were generally higher in China's southeastern coastal regions than in the western regions, and age-standardised DALY rates were higher in the northern regions than in other regions. Interpretation: The disease burden of PD in China has consistently risen over the past three decades, particularly among elderly men. The increasing causative factors and population aging highlight the need for enhancing public health intervention and resource allocation, especially in etiological research, early diagnosis, preventive strategies, and region-specific management for PD. Funding: Ministry of Science and Technology of the People's Republic of China (2022YFC2304900, 2022YFC2505100); National Key R&D Program of China (2022YFC2505100, 2022YFC2505103, 2018YFC1315300); Outstanding Young Scholars Support Program (grant number: 3111500001); Epidemiology modeling and risk assessment (grant number: 20200344), and Xi'an Jiaotong University Young Scholar Support Grant (grant number: YX6J004).

Peanuts (Arachis hypogaea) are an essential oilseed crop known for their unique developmental process, characterized by aerial flowering followed by subterranean fruit development. This crop is polyploid, consisting of A and B subgenomes, which complicates its genetic analysis. The advent and progression of omics technologies—encompassing genomics, transcriptomics, proteomics, epigenomics, and metabolomics—have significantly advanced our understanding of peanut biology, particularly in the context of seed development and the regulation of seed-associated traits. Following the completion of the peanut reference genome, research has utilized omics data to elucidate the quantitative trait loci (QTL) associated with seed weight, oil content, protein content, fatty acid composition, sucrose content, and seed coat color as well as the regulatory mechanisms governing seed development. This review aims to summarize the advancements in peanut seed development regulation and trait analysis based on reference genome-guided omics studies. It provides an overview of the significant progress made in understanding the molecular basis of peanut seed development, offering insights into the complex genetic and epigenetic mechanisms that influence key agronomic traits. These studies highlight the significance of omics data in profoundly elucidating the regulatory mechanisms of peanut seed development. Furthermore, they lay a foundational basis for future research on trait-related functional genes, highlighting the pivotal role of comprehensive genomic analysis in advancing our understanding of plant biology.

Soil moisture is a significant variable in agricultural study and precision irrigation decision-making. It determines the soil water availability for plants, directly influencing plant growth, yield and quality. Owing to the variations in regional microclimate, landform difference, soil type and vegetation coverage, the soil moisture has strong spatial-temporal heterogeneity on a large regional scale. Micro-wave remote sensing can be used to invert soil moisture based on the dielectric constant under different weather conditions, while optical remote sensing utilizes spectral characteristics to estimate the physiological and ecological information of vegetation. In this study, two new hybrid models (ACO-RF and SSA-RF) were structured by optimizing the standalone random forest (RF) based on the ant colony optimization algorithm (ACO) and sparrow search algorithm (SSA), and six input combinations based on the multi-temporal Sentinel-1 and Landsat-8 remote sensing data from different sensors (optical, thermal and radar sensors) were used. The standalone RF, ACO-RF, and SSA-RF models with different combinations of inputs were employed to predict the soil moisture at different depths (5 cm, 10 cm, 20 cm, 40 cm) in a large-scale drip-irrigated citrus orchard. The results showed that the ACO-RF and SSA-RF outperformed the standalone RF model in terms of prediction accuracy at a depth of 0–40 cm, with R2 of 0.800–0.921 and 0.504–0.798, RRMSE of 7.214–16.284% and 11.124–22.214%, respectively. In the hybrid model, the ACO-RF model had better prediction accuracy than the SSA-RF model, with R2 of 0.805–0.921 and 0.800–0.911, RRMSE of 7.214–13.244% and 8.274–16.284%, respectively. At depths of 5 cm, 10 cm and 20 cm, the inversion accuracy of the model with microwave inputs was higher than that with multispectral inputs, with R2 of 0.556–0.888 and 0.541–0.886, RRMSE of 9.015–19.544% and 9.124–22.214%, respectively. However, at a depth of 40 cm, the inversion accuracy of the model with multispectral inputs was higher than that with microwave inputs, with R2 of 0.532–0.841 and 0.508–0.831, RRMSE of 9.124–21.021% and 9.142–21.214%, respectively. The model with multispectral, thermal, and microwave inputs exhibited the highest accuracy in predicting soil moisture, with R2 of 0.635–0.921, RRMSE of 7.214−18.564%, respectively. Therefore, the ACO-RF with multisource remote sensing data is recommended to predict the soil moisture in the drip-irrigated citrus orchard. This approach can provide data support for making intelligent irrigation decisions on a large-scale grid land lots.

In dealing with the occurrence of earthquakes, urban communities and people within the system should primarily consider the geological background, secondary hazards caused by earthquakes, countermeasures to mitigate earthquake disasters, community connectivity, and the impact of various indicators and criteria on the earthquake-proof capacity of the community. It is important to comprehensively assess these factors to ensure that a community is well-prepared to withstand an earthquake. This study takes Shenzhen (China) as an example to conduct a preliminarily evaluation of a method of earthquake-proof capacity during an earthquake, with the results reflecting the comprehensive capacity of communities. The evaluation framework focuses more on effectively improving the disaster response capacity and resilience of urban communities.

Accurate reference crop evapotranspiration (ET0) estimation is essential for agricultural water management, crop productivity, and irrigation systems. As the standard ET0 estimation method, the Penman-Monteith equation has been widely recommended worldwide. However, its application is still restricted to comprehensive meteorological data deficiency, making the exploration of alternative simpler models for acceptable ET0 estimation highly meaningful. Concerning the aforementioned requirement, this study developed the novel deep learning model (MA-CNN-BiLSTM), which incorporates Multi-Head Attention mechanism (MA), Convolutional Neural Network (CNN), and Bidirectional Long Short-Term Memory network (BiLSTM) as intricate relationship processor, feature extractor, and regression component, to estimate ET0 based on radiation-based (Rn-based), humidity-based (RH-based), and temperature-based (T-based) input combinations at 600 stations during 1961–2020 throughout China under internal and external cross-validation strategies. Besides, through a comparative evaluation among MA-CNN-BiLSTM, CNN-BiLSTM, BiLSTM, LSTM, Multivariate Adaptive Regression Splines (MARS), and empirical models, the result indicated that MA-CNN-BiLSTM achieved superior precision, with values of Determination Coefficient (R2), Nash–Sutcliffe efficiency coefficient (NSE), Relative Root Mean Square Error (RRMSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) ranging 0.877–0.972, 0.844–0.962, 0.129–0.292, 0.294–0.644 mm d−1, 0.244–0.566 mm d−1 for internal strategy and 0.797–0.927, 0.786–0.920, 0.162–0.335, 0.409–0.969 mm d−1, 0.294–0.699 mm d−1 for external strategy. Specifically, Rn-based MA-CNN-BiLSTM excelled in the temperate continental zone (TCZ) and mountain plateau zone (MPZ), while RH-based MA-CNN-BiLSTM yielded best precision in others. Furthermore, the internal strategy was superior to external strategy by 2.74–106.04% for R2, 1.11–120.49% for NSE, 1.41–40.27% for RRMSE, 1.68–45.53% for RMSE, and 1.21–38.87% for MAE, respectively. In summary, the main contribution of the present study is the proposal of a novel LSTM-type ET0 model (MA-CNN-BiLSTM) to cope with various data-missing scenarios throughout China, which can provide effective support for decision-making in regional agriculture water management.

Superoxide dismutase (SOD) protects plants from abiotic stress-induced reactive oxygen species (ROS) damage. Here, the effects of cadmium (Cd) exposure on ROS accumulation and SOD isozymes, as well as the identification of significant SOD isozyme genes, were investigated under different Cd stress treatments to Zhe-Maidong (Ophiopogon japonicus). The exposure to Cd stress resulted in a notable elevation in the SOD activity in roots. Cu/ZnSODa and Cu/ZnSODb were the most critical SOD isozymes in response to Cd stress, as indicated by the detection results for SOD isozymes. A total of 22 OjSOD genes were identified and classified into three subgroups, including 10 OjCu/ZnSODs, 6 OjMnSODs, and 6 OjFeSODs, based on the analysis of conserved motif and phylogenetic tree. Cu/ZnSOD-15, Cu/ZnSOD-18, Cu/ZnSOD-20, and Cu/ZnSOD-22 were the main genes that control the increase in SOD activity under Cd stress, as revealed via quantitative PCR and transcriptome analysis. Additionally, under various heavy metal stress (Cu2+, Fe2+, Zn2+, Mn2+), Cu/ZnSOD-15, Cu/ZnSOD-18, and Cu/ZnSOD-22 gene expression were significantly upregulated, indicating that these three genes play a critical part in resisting heavy metal stress. The molecular docking experiments performed on the interaction between oxygen ion (O2•−) and OjSOD protein have revealed that the critical amino acid residues involved in the binding of Cu/ZnSOD-22 to the substrate were Pro135, Ile136, Ile140, and Arg144. Our findings provide a solid foundation for additional functional investigations on the OjSOD genes, as well as suggestions for improving genetic breeding and agricultural management strategies to increase Cd resistance in O. japonicus.

Sugar is a primary determinant of citrus fruit flavour, but undergoes varied accumulation processes across different citrus varieties owing to high genetic variability. Sucrose phosphate synthase (SPS), a key enzyme in glucose metabolism, plays a crucial role in this context. Despite its significance, there is limited research on sugar component quality and the expression and regulatory prediction of SPS genes during citrus fruit development. Therefore, we analysed the sugar quality formation process in ‘Kiyomi’ and ‘Succosa’, two citrus varieties, and performed a comprehensive genome-wide analysis of citrus CsSPSs. We observed that the accumulation of sugar components significantly differs between the two varieties, with the identification of four CsSPSs in citrus. CsSPS sequences were highly conserved, featuring typical SPS protein domains. Expression analysis revealed a positive correlation between CsSPS expression and sugar accumulation in citrus fruits. However, CsSPS expression displays specificity to different citrus tissues and varieties. Transcriptome co-expression network analysis suggests the involvement of multiple transcription factors in shaping citrus fruit sugar quality through the regulation of CsSPSs. Notably, the expression levels of four CsWRKYs (CsWRKY2, CsWRKY20, CsWRKY28, CsWRKY32), were significantly positively correlated with CsSPSs and CsWRKY20 might can activate sugar accumulation in citrus fruit through CsSPS2. Collectively, we further emphasize the potential importance of CsWRKYs in citrus sugar metabolism, our findings serve as a reference for understanding sugar component formation and predicting CsSPS expression and regulation during citrus fruit development.

IntroductionPeanut (Arachis hypogaea L.), also called groundnut is an important oil and cash crop grown widely in the world. The annual global production of groundnuts has increased to approximately 50 million tons, which provides a rich source of vegetable oils and proteins for humans. Low temperature (non-freezing) is one of the major factors restricting peanut growth, yield, and geographic distribution. Since the complexity of cold-resistance trait, the molecular mechanism of cold tolerance and related gene networks were largely unknown in peanut.MethodsIn this study, comparative transcriptomic analysis of two peanut cultivars (SLH vs. ZH12) with differential cold tolerance under low temperature (10°C) was performed using Oxford Nanopore Technology (ONT) platform.Results and discussionAs a result, we identified 8,949 novel gene loci and 95,291 new/novel isoforms compared with the reference database. More differentially expressed genes (DEGs) were discovered in cold-sensitive cultivar (ZH12) than cold-tolerant cultivar (SLH), while more alternative splicing events were found in SLH compared to ZH12. Gene Ontology (GO) analyses of the common DEGs showed that the “response to stress”, “chloroplast part”, and “transcription factor activity” were the most enriched GO terms, indicating that photosynthesis process and transcription factors play crucial roles in cold stress response in peanut. We also detected a total of 708 differential alternative splicing genes (DASGs) under cold stress compared to normal condition. Intron retention (IR) and exon skipping (ES) were the most prevalent alternative splicing (AS) events. In total, 4,993 transcription factors and 292 splicing factors were detected, many of them had differential expression levels and/or underwent AS events in response to cold stress. Overexpression of two candidate genes (encoding trehalose-6-phosphatephosphatases, AhTPPs) in yeast improves cold tolerance. This study not only provides valuable resources for the study of cold resistance in peanut but also lay a foundation for genetic modification of cold regulators to enhance stress tolerance in crops

BackgroundThe inability of patients with recurrent implantation failure (RIF) to achieve pregnancy and a live birth after multiple high-quality embryo transfer treatments has been recognized as a major obstacle to successful application of artificial reproductive technologies. The objective of this study was to establish and validate a nomogram for prediction of subsequent first-cycle live births to guide clinical practice in patients diagnosed with RIF.MethodsA total of 538 patients who underwent in vitro fertilization/intracytoplasmic sperm injection treatment and were first diagnosed with RIF at the Reproductive Center of the First Affiliated Hospital of Xinjiang Medical University between January 2017 and December 2020 were enrolled. The patients were randomly divided into a training cohort (n=408) and a validation set (n=175) in a ratio of 7:3. A nomogram model was constructed using the training set based on the results of univariate and multivariate logistic regression analyses and validated in the validation set.ResultsAge, body mass index, duration of RIF, endometrial thickness, type of embryo transferred, and number of previous biochemical pregnancies were included in the nomogram for prediction of subsequent first-cycle live births in patients diagnosed with RIF. Analysis of the area under the receiver-operating characteristic curve, calibration plots, and decision curve analysis showed that our predictive model for live births had excellent performance.ConclusionWe have developed and validated a novel predictive model that estimates a woman’s chances of having a live birth after a diagnosis of RIF and provides clinicians with a personalized clinical decision-making tool.

‘Fengtang‘ plums soften quickly and lose flavor after harvest. This study comprehensively evaluated the effect of exogenous melatonin on the fruit quality of ‘Fengtang’ plums. According to our findings, exogenous melatonin prevented plum fruit from losing water, delayed the decline in firmness, and preserved a high TSS/TA level. Additionally, exogenous melatonin also enhanced the activity of antioxidant enzymes and increased the non-enzymatic antioxidants, thereby further increasing the antioxidant capacity of plum fruit. Notably, exogenous melatonin delayed the degradation of covalent soluble pectin (CSP), cellulose, and hemicellulose, as well as the rise in water-soluble pectin (WSP) concentration and the activity of cell wall degrading enzymes. Further investigation using atomic force microscopy (AFM) revealed that the chain-like structure of ionic-soluble pectin (ISP) and the self-assembly network structures of CSP were depolymerized, and melatonin treatment retarded the depolymerization of pectin structures. Our results showed that exogenous melatonin preserved the postharvest quality of plum fruits by controlling fruit softness and antioxidant capacity during storage.