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Abstract Coronary slow flow (CSF) is characterized by slow progression of coronary angiography without epicardial stenosis. The aim of this study was to explore the potential biomarkers and regulatory mechanism for CSF. Peripheral blood mononuclear cells from 3 cases of CSF and 3 healthy controls were collected for high-throughput sequencing of mRNA and miRNA, respectively. The differentially expressed mRNAs (DE-mRNAs) and miRNAs (DE-miRNAs) was identified. A total of 117 DE-mRNAs and 32 DE-miRNAs were obtained and they were mainly enriched in immune and inflammatory responses. Twenty-six DE-mRNAs were the predicted target genes for miRNAs by RAID, and then the regulatory network of 15 miRNAs were constructed. In addition, through the PPI network, we identified the three genes (FPR1, FPR2 and CXCR4) with larger degrees as hub genes. Among them, FPR1 was regulated by hsa-miR-342-3p, hsa-let-7c-5p and hsa-miR-197-3p and participated in the immune response. Finally, we validated the differential expression of hub genes and key miRNAs between 20 CSF and 20 control. Moreover, we found that miR-342-3p has a targeted regulatory relationship with FPR1, and their expression is negatively correlated. Then we established a hypoxia/reoxygenation (H/R) HUVEC model and detected FPR1, cell proliferation and apoptosis. Transfection with miR-342-3p mimics can significantly promote the proliferation of HUVEC under H/R conditions. FPR1 were associated with CSF as a biomarker and may be regulated by miR-342-3p potential biomarkers.

Forests have experienced unprecedented decline and mortality beyond their historical range in past decades, which is attributed to disturbances like drought, fire, insects and disease. Traditional disturbance detection methods that typically employ a time series perspective to identify discrete disturbance events within continuous tree growth signals and were mainly designed for gap-scale often fail to identify disturbances across populations. To more accurately identify growth suppression and release clusters based on the perspective of forest population dynamics, here we applied a novel method of detecting forest disturbances using a Gaussian mixture model with an expectation maximisation algorithm (DGE), to fit annual distributions of growth indicators, i.e., tree-ring index. We further compared our novel approach of DGE with five traditional methods based on two sets of real tree-ring data and simulated tree-ring data. The results show an improvement of accuracy (35.5 %–48.1 %), sensitivity (36.6 %–58.1 %), precision (21.2 %–51.5 %) and specificity (11.1 %–20.6 %) for the average of two real radial growth datasets and an improvement of accuracy (7.6 %–13.9 %), sensitivity (70 %), precision (100 %) and specificity (9.1 %–9.7 %) for the simulation radial growth dataset, indicating that our DGE approach performs much better than the traditional methods. This study contributes to an improved strategy and understanding for sustainable forest management in the context of climate warming, demonstrating that our DGE approach can be better applied to global forest disturbance detection under global change.

Reactive astrocytes play critical roles in the occurrence of various neurological diseases such as multiple sclerosis. Activation of astrocytes is often accompanied by a glycolysis-dominant metabolic switch. However, the role and molecular mechanism of metabolic reprogramming in activation of astrocytes have not been clarified. Here, we found that PKM2, a rate-limiting enzyme of glycolysis, displayed nuclear translocation in astrocytes of EAE (experimental autoimmune encephalomyelitis) mice, an animal model of multiple sclerosis. Prevention of PKM2 nuclear import by DASA-58 significantly reduced the activation of mice primary astrocytes, which was observed by decreased proliferation, glycolysis and secretion of inflammatory cytokines. Most importantly, we identified the ubiquitination-mediated regulation of PKM2 nuclear import by ubiquitin ligase TRIM21. TRIM21 interacted with PKM2, promoted its nuclear translocation and stimulated its nuclear activity to phosphorylate STAT3, NF-κB and interact with c-myc. Further single-cell RNA sequencing and immunofluorescence staining demonstrated that TRIM21 expression was upregulated in astrocytes of EAE. TRIM21 overexpressing in mice primary astrocytes enhanced PKM2-dependent glycolysis and proliferation, which could be reversed by DASA-58. Moreover, intracerebroventricular injection of a lentiviral vector to knockdown TRIM21 in astrocytes or intraperitoneal injection of TEPP-46, which inhibit the nuclear translocation of PKM2, effectively decreased disease severity, CNS inflammation and demyelination in EAE. Collectively, our study provides novel insights into the pathological function of nuclear glycolytic enzyme PKM2 and ubiquitination-mediated regulatory mechanism that are involved in astrocyte activation. Targeting this axis may be a potential therapeutic strategy for the treatment of astrocyte-involved neurological disease.

Plasma membrane intrinsic proteins (PIPs) are conserved plant aquaporins that transport small molecules across the plasma membrane to trigger instant stress responses and maintain cellular homeostasis under biotic and abiotic stress. To elucidate their roles in plant immunity to pathogen attack, we characterized the expression patterns, subcellular localizations, and H2O2-transport ability of 11 OsPIPs in rice (Oryza sativa), and identified OsPIP2;6 as necessary for rice disease resistance. OsPIP2;6 resides on the plasma membrane and facilitates cytoplasmic import of the immune signaling molecule H2O2. Knockout of OsPIP2;6 increases rice susceptibility to Magnaporthe oryzae, indicating a positive function in plant immunity. OsPIP2;6 interacts with OsPIP2;2, which has been reported to increase rice resistance to pathogens via H2O2 transport. Our findings suggest that OsPIP2;6 cooperates with OsPIP2;2 as a defense signal transporter complex during plant–pathogen interaction.

Objective To investigate the effect of YTH domain family protein 1(YTHDF1) on apoptosis and oxidative damage in H9c2 cells under hypoxic reoxygenation(H/R) conditions. Methods The H/R model was constructed with H9c2 cells.Cells were transfected with YTHDF1 small interfering RNA(siRNA) and overexpression plasmid,and cell viability was measured by MTT colorimetric assay.Apoptosis,superoxide dismutase(SOD) activity,malondialdehyde(MDA) content in cells and lactate dehydrogenase(LDH) activity in cell culture medium supernatant were measured by Hirst staining and flow cytometry.The protein levels of YTHDF1,cleaved caspase-3,Bax and FasL in the cells were determined by Western blot,and the apoptosis and oxidative damage of H9c2 cells in the control,H/R,YTHDF1 gene interference and overexpression groups were compared. Results LDH activity and MDA content were significantly increased,SOD activity and cell viability were significantly decreased after H/R injury(P

Sound event localization and detection have been applied in various fields. Due to the polyphony and noise interference, it becomes challenging to accurately predict the sound event and their occurrence locations. Aiming at this problem, we propose a Multiple Attention Fusion ResNet, which uses ResNet34 as the base network. Given the situation that the sound duration is not fixed, and there are multiple polyphonic and noise, we introduce the Gated Channel Transform to enhance the residual basic block. This enables the model to capture contextual information, evaluate channel weights, and reduce the interference caused by polyphony and noise. Furthermore, Split Attention is introduced to the model for capturing cross-channel information, which enhances the ability to distinguish the polyphony. Finally, Coordinate Attention is introduced to the model so that the model can focus on both the channel information and spatial location information of sound events. Experiments were conducted on two different datasets, TAU-NIGENS Spatial Sound Events 2020, and TAU-NIGENS Spatial Sound Events 2021. The results demonstrate that the proposed model significantly outperforms state-of-the-art methods under multiple polyphonic and noise-directional interference environments and it achieves competitive performance under a single polyphonic environment.

ObjectiveTo examine the prognostic values of systemic immune-inflammation indices of hemodialysis (HD) vascular access failure and develop a prediction model for vascular access failure based on the most pertinent systemic immune-inflammation index.Study designA prospective cohort study.Setting & participantsPatients undergoing autogenous HD vascular access surgeries or arteriovenous graft as a permanent hemodialysis access in a tertiary center in southwest China from January 2020 to June 2022.PredictorsSystemic immune-inflammation indices, including NLR, dNLR, AAPR, SIRI, SII, PNI, PLR, and LIPI, and clinical variables.OutcomesThe outcome was defined as survival of the hemodialysis access, with both occluded and stenotic access being considered as instances of access failure.Analytical approachCox proportional hazard regression model.Results2690 patients were included in the study population, of whom 658 experienced access failure during the follow-up period. The median duration of survival for HD vascular access was 18 months. The increased systemic immune-inflammation indices, including dNLR, NLR, SII, PNI, SIRI, PLR, and LIPI, are predictive of HD access failure, with SII demonstrating the strongest prognostic value. A simple SII-based prediction model for HD access failure was developed, achieving C-indexes of 0.6314 (95% CI: 0.6249 – 0.6589) and 0.6441 (95% CI: 0.6212 – 0.6670) for predicting 6- and 12-month access survival, respectively.ConclusionsSystemic immune-inflammation indices are significantly and negatively associated with HD vascular access survival. A simple SII-based prediction model was developed and anticipates further improvement through larger study cohort and validation from diverse centers.

Accurate estimation of soil moisture content (SMC) in the field is a critical aspect of precise irrigation management. The development of unmanned aerial vehicle (UAV) platforms has provided an economically efficient means for field-scale SMC measurements. However, previous studies have mostly focused on single-sensor estimates of SMC. Additionally, the lack of differentiation between various crops and their growth stages has resulted in an unclear understanding of how crop types and growth stages affect the accuracy of SMC estimation at different soil depths. Therefore, the purpose of this paper was to use UAV multimodal remote sensing and a machine learning algorithm to estimate the SMC in agricultural fields and investigate estimation’s effectiveness under different scenarios. The results indicated the following: (1) The multispectral remote sensing method provided higher accuracy in SMC estimation compared to thermal infrared remote sensing. Moreover, the integration of multimodal data improved the accuracy of SMC estimation, enhancing the coefficient of determination (R2) by approximately 14% over that achieved through the use of multispectral data alone and 39% over that of thermal infrared data alone. (2) Across the entire growth period, the optimal soil depths of SMC estimation for soybean were 10 cm and 20 cm (average R2 were 0.81 and 0.82, respectively), while for corn, they were 10 cm, 20 cm, and 40 cm (average R2 were 0.59, 0.60, and 0.55, respectively). (3) The SMC estimation model performed better for both crops during the first three growth stages, with accuracy declining in the maturity stage. These results demonstrate that this approach can provide relatively accurate root zone SMC estimates for different crops throughout their main growth periods. Thus, it can be employed for SMC monitoring and precision irrigation system design.

Abstract Background Excessive production of androgen drives oxidative stress (OS) and inflammasome activation in ovarian granulosa cells (GCs). Therefore, the induced follicular developmental disorder is the major cause of infertility in women with polycystic ovary syndrome (PCOS). Exercise-induced upregulation of irisin is capable of regulating metabolism by reducing OS and inflammation. Exercise has been shown to alleviate a range of PCOS symptoms, including maintaining a normal menstrual cycle, in several clinical trials. Methods Female Sprague–Dawley (SD) rats and primary ovarian cells were treated with two different androgens, dehydroepiandrosterone (DHEA) and dihydrotestosterone (DHT), to simulate a hyperandrogenic environment, followed by eight weeks of exercise training and irisin intervention. The levels of reactive oxygen species (ROS), tissue inflammation and fibrosis were examined using hematoxylin and eosin (H&E) staining, western blot, quantitative real-time PCR (qRT-PCR), dichlorofluorescein diacetate (DCF-DA) probe detection, immunofluorescence staining, immunohistochemistry, and Sirius red staining. Results Exercise for eight weeks improved polycystic ovarian morphology and decreased the levels of inflammation, OS, and fibrosis in PCOS rats. Hyperandrogen increased ROS production in ovarian cells by inducing endoplasmic reticulum stress (ERS) and activating the inositol-requiring enzyme 1α (IRE1α)-thioredoxin-interacting protein (TXNIP)/ROS-NOD-like receptor family pyrin domain containing 3 (NLRP3) signaling pathway, further enhancing the levels of inflammation. Irisin suppressed the expression of IRE1α and its downstream targets, thus improving the ovarian dysfunction of PCOS rats induced by hyperandrogen. Conclusion Exercise can alleviate various phenotypes of PCOS rats induced by DHEA, and its therapeutic effect may be mediated by secreting beneficial myokines. IRE1α may be an important target of irisin for reducing OS and inflammation, thereby improving ovarian fibrosis.

The evaluation of water resource vulnerability to nonpoint source pollution in the presence of uncertainty remains a crucial concern. To enhance the accuracy of the assessment and pinpoint the key factors that affect watershed water quality, the integration of an artificial neural network (ANN) into the evaluation process is imperative. The research involved the collection of streams baseflow samples from thirty-eight sites between 1994 and 1999 in the Tomorrow-Waupaca River Watershed in central Wisconsin, USA, with a focus on examining the relationship between nitrate concentrations and a range of environmental and land use variables extracted from the watershed GIS database. This study utilized ANN methodology, combined with a bootstrap technique that employed a random resampling approach from a single input dataset, to simulate monthly stream baseflow nitrate concentrations. The effectiveness and predictive ability of the ANN model were assessed by comparing it to conventional multivariate regression methods. Through the use of ANN, more precise outcomes can be achieved while taking into account the uncertainty associated with the analysis. The findings demonstrated that the ANN outperformed both the multivariate linear regression and nonlinear quadratic response surface models in explaining the variance of stream nitrate and in external prediction consistency. This study also highlighted several key variables, such as the areal percentage of agricultural land and grassland, stream order, and the average slope of the groundwater flow path, that significantly impacted the stream baseflow nitrate concentrations in this watershed that was dominated by dairy farming and groundwater. Of these variables, the percentage of agricultural land emerged as the most significant factor.

Existing macroeconomic forecasting methods primarily focus on the characteristics of economic data, but they overlook the energy-related features concealed behind these economic characteristics, which may lead to inaccurate GDP predictions. Therefore, this paper meticulously analyzes the relationship between energy big data and economic data indicators, explores the coupling feature mining of energy big data and economic data, and constructs features coupling economic and energy data. Targeting the nonlinear variation coupling features in China’s quarterly GDP data and using the long short-term memory (LSTM) neural network model based on deep learning, we employ wavelet analysis technology (WA) to decompose selected macroeconomic variables and construct a prediction model combining LSTM and WA, which is further compared with multiple benchmark models. The research findings show that, in terms of quarterly GDP data prediction, the combined deep learning model and wavelet analysis significantly outperform other methods. When processing structurally complex, nonlinear, and multi-variable data, the LSTM and WA combined prediction model demonstrate better generalization capabilities, with its prediction accuracy generally surpassing other benchmark models.

Eriobotrya is an evergreen fruit tree native to South-West China and adjacent countries. There are more than 26 loquat species known in this genus, while E. japonica is the only species yet domesticated to produce fresh fruits from late spring to early summer. Fruits of cultivated loquat are usually orange colored, in contrast to the red color of fruits of wild E. henryi (EH). However, the mechanisms of fruit pigment formation during loquat evolution are yet to be elucidated. To understand these, targeted carotenoid and anthocyanin metabolomics as well as transcriptomics analyses were carried out in this study. The results showed that β-carotene, violaxanthin palmitate and rubixanthin laurate, totally accounted for over 60% of the colored carotenoids, were the major carotenoids in peel of the orange colored ‘Jiefangzhong’ (JFZ) fruits. Total carotenoids content in JFZ is about 10 times to that of EH, and the expression levels of PSY, ZDS and ZEP in JFZ were 10.69 to 23.26 folds to that in EH at ripen stage. Cyanidin-3-O-galactoside and pelargonidin-3-O-galactoside were the predominant anthocyanins enriched in EH peel. On the contrary, both of them were almost undetectable in JFZ, and the transcript levels of F3H, F3’H, ANS, CHS and CHI in EH were 4.39 to 73.12 folds higher than that in JFZ during fruit pigmentation. In summary, abundant carotenoid deposition in JFZ peel is well correlated with the strong expression of PSY, ZDS and ZEP, while the accumulation of anthocyanin metabolites in EH peel is tightly associated with the notably upregulated expressions of F3H, F3’H, ANS, CHS and CHI. This study was the first to demonstrate the metabolic background of how fruit pigmentations evolved from wild to cultivated loquat species, and provided gene targets for further breeding of more colorful loquat fruits via manipulation of carotenoids and anthocyanin biosynthesis.

Abstract In this paper, we present an inexact multiblock alternating direction method for the point-contact friction model of the force-optimization problem (FOP). The friction-cone constraints of the FOP are reformulated as the Cartesian product of circular cones. We focus on the convex quadratic circular-cone programming model of the FOP, which is an exact cone-programming model. Coupled with the separable convex quadratic objective function, we recast the circular-cone-programming model as a multiblock separable cone model. A parallel inexact multiblock alternating direction method is used to solve the FOP. We prove the global convergence of the proposed method. Simulation results of the three-fingered FOP are reported, which verified the efficiency of the proposed method.

Abstract Aim This study aimed to explore the effect of training on organizational commitment, the mediating effect of employability and the moderating role of person–organization fit. Design A correctional cross‐sectional research design was adopted for this study. Methods A questionnaire‐based survey of 859 nurses in a public hospital in Western China was conducted to identify their perceptions of training, employability, organizational commitment and person–organization fit. Hierarchical linear regression and conditional process analysis on moderated mediation were performed. Results Training had a positive effect on organizational commitment (p

Epidemiological studies have established an association between chronic exposure to PM2.5 and male infertility. However, the underlying mechanisms were not fully revealed. In this study, we established mice models exposed to PM2.5 for 16 weeks, and a significant decrease in sperm quality accompanied by an increase in testosterone levels were observed after PM2.5 exposure. Moreover, treatment with ferrostatin-1 (Fer-1), a specific ferroptosis inhibitor, effectively mitigated PM2.5-induced testicular dysfunction in mice. And lipid peroxidation and ferritin accumulation were found to be significantly increased in Leydig cells of testes with a PM2.5-dose dependent manner. Further investigations revealed that TM-3 cells, a mouse Leydig cell line, were prone to ferroptosis after PM2.5 exposure, and the cell viability was partly rescued after the intervention of Fer-1. Furthermore, our results supported that the ferroptosis of TM-3 cells was attributed to the upregulation of ferredoxin 1 (FDX1), which was the protein transferring electrons to cytochrome P450 family 11 subfamily A member 1 to aid lysing cholesterol to pregnenolone at initial of steroidogenesis. Mechanically, PM2.5-induced FDX1 upregulation resulted in cellular ROS elevation and ferrous iron overload, which together initiated an autoxidation process of polyunsaturated fatty acids in the cell membrane of Leydig cells until the accumulated lipid peroxides triggered ferroptotic cell death. Simultaneously, upregulation of FDX1 promoted steroidogenesis and let to an increased level of testosterone. In summary, our work suggested that FDX1, a mediator involving steroidogenesis, was a key regulator in PM2.5-induced Leydig cells ferroptosis.

Introduction: Traditional Chinese medicine (TCM) injections, as a relatively safe and low-cost treatment, have been widely used in the prevention and treatment of anthracyclines-induced cardiotoxicity in China. However, the quality of the relevant systematic reviews and meta-analyses published in recent years is uneven, so that the effectiveness and safety of TCM injections in preventing and treating anthracyclines-induced cardiotoxicity remain to be discussed. A systematic overview is therefore needed to provide a more advanced evidentiary reference for clinical practice. Methods: Eight Chinese and English databases were searched by computer to screen the meta-analyses/systematic reviews on the efficacy of traditional Chinese medicine injections for the prevention and treatment of anthracyclines-induced cardiotoxicity from the database establishment to October 2022. The methodological quality and evidence quality of outcome indicators included in the study were evaluated by AMSTAR 2 tool, PRISMA statement and GRADE classification. Results: A total of 7 articles were included in the study. The quality evaluation of AMSTAR 2 showed that 7 studies were extremely low-level; PRISMA stated that the evaluation results showed that the reports of 7 studies were of intermediate quality; The GRADE rating indicated that most of the evidence was of low quality. Conclusion: The methodological quality and evidence quality of meta-analysis/system evaluation concerning the prevention and treatment of anthracyclines-induced cardiotoxicity by Chinese medicine are currently low, and the effectiveness of Chinese medicine in the treatment of anthracyclines-induced cardiotoxicity needs more high-quality evidence-based evidence.

Reliable detection and attribution of vegetation dynamics in the National Barrier Zone (NBZ) of China is fundamental to determining the effectiveness of ecological restoration projects and developing adaptive conservation strategies. Nevertheless, limited knowledge of the climate temporal effects on vegetation growth creates uncertainties in understanding vegetation-climate interactions. We evaluated the spatial and temporal patterns of climate temporal effects on vegetation in the NBZ by the Normalized Difference Vegetation Index (NDVI) and climate datasets during 1982–2015. The residual trend analysis was then utilized to attribute vegetation dynamics before and after the implementation of the “Grain for Green Program” (GGP) launched in 1999. The results indicated that the NBZ experienced significant and persistent greening during 1982–2015, with most areas recording a greater increase in NDVI after the GGP than before it was implemented. Climate temporal effects affected over 75 % of the vegetated areas in the NBZ, and the overall explanations of NDVI variations explained by climate variables increased by 5.7 % when time-lag and cumulative effects were considered. Precipitation was the dominant climatic controller of vegetation dynamics in the northern sand belt, whereas temperature was the principal controller in other zones. Additional cropland before the implementation of the GGP in the NBZ was 28,807 km2, which was ten times more than what was added after the GGP was implemented. Climate change and human activities explained 47.4 % and 52.6 % of vegetation variations in the NBZ, respectively, with all zones except the ecological barrier of Qinghai-Tibet Plateau (TPEB) being dominated by anthropogenic factors. Anthropogenic contributions to vegetation dynamics increased significantly after the implementation of the GGP. The study offers theoretical guidance for developing ecological conservation strategies in China.

Microcystin-leucine-arginine (MC-LR) is a cyclic heptapeptide compound produced by cyanobacteria with strong cytotoxicity. Previous studies have confirmed that MC-LR could exert toxic effects on the genitourinary system, but there are few reports about its toxicity to the bladder. In this study, we investigated the effects of MC-LR on mouse bladder and human bladder epithelial cells (SV-HUC-1 cells). We observed that the bladder weight and the number of bladder epithelial cells were markedly increased in mice following chronic low-dose exposure to MC-LR. Further investigation showed that MC-LR activates AKT/NF-kB signaling pathway to induce the production of proinflammatory cytokines TNF-α and IL-6. In addition, the expression of matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9) in bladder tissue was increased and the relative migration and invasion capacities of SV-HUC-1 cells were enhanced upon exposure to MC-LR. In conclusion, these results suggest that chronic exposure to MC-LR induced epithelial hyperplasia and inflammation, upregulated the expression of matrix metalloproteinases (MMPs) and promoted the migration and invasion of bladder epithelial cells, which provides a basis for further exploring the potential mechanism by which environmental factors increasing the risk of bladder cancer.

Yellow River Basin (YRB), a climate-sensitive and ecologically compromised area in China, is increasingly affected by extreme climate events (especially droughts) resulting from climate change and frequent human activity. Vegetation responds asymmetrically to drought with cumulative and time-lag effects, whereas response across various climatic zones and diverse vegetation types in the YRB remains unclear. To address this deficiency, we examined the spatiotemporal patterns of accumulated and lagged drought effects on vegetation dynamics for the period 1982 to 2015. The examination was based on the long-term Normalized Difference Vegetation Index (NDVI) and multiscale dataset of the Standardized Precipitation Evapotranspiration Index (SPEI). Cumulative (time-lag) effects were determined via the maximum correlation between the NDVI and the one- to 12-month timescale SPEI (one-month timescale SPEI), as well as the corresponding months of optimal response to drought. The main findings were as follows: (1) Accumulated and lagged drought significantly affected approximately 50% and 60% of the vegetated area in the YRB, respectively, with the strongest effects and the corresponding optimal months varying across climatic zones and vegetation types. (2) In general, vegetation in the arid zone tended to be more sensitive and resistant to drought, as evidenced by the occurrence of lagged and accumulated drought effects mostly in the short-term (one–three months) and medium-term (six–eight months), respectively. This finding may be related to the vegetation’s strategy for coping with water deficits. (3) The biome-level effects of drought on grassland and cultivated vegetation were stronger than those on forests, which may be associated with differences in the functional characteristics of root systems. (4) Annual water availability significantly affected the spatiotemporal patterns by which the NDVI responded to droughts of multiple timescales, with the correlation coefficients and corresponding months of response decreasing with increasing average annual SPEI. These results indicate that vegetated areas with low water availability were more susceptible to cumulative (time-lag) droughts. (5) Independent of the climate zone or vegetation type, drought cumulatively affected vegetation more than time-lag effects. The study improves the knowledge of climate–vegetation relationships in the YRB and provides theoretical support for addressing drought risk in a changing climate.

Evapotranspiration (ET) is an essential part of energy flow between the surface of the earth and the atmosphere, simultaneously involving the water, carbon, and energy cycles. It is mainly determined by climate, land use, and land cover changes. Additionally, there is still a need for quantitative characterization of the impacts of climate factors and human activities on ET and regional water resource efficiency in arid and semiarid regions. Based on Landsat-8 remote sensing imagery and land use data, the crop planting structures in the Liangzhou District of the middle reaches of the Shiyang River Basin were identified using a multiband and multi-temporal approach in this study. Subsequently, the ET of major cash crops was inverted using the three-temperature model. This research quantitatively describes the responses of wheat and corn to the climate and human activities over a two-year period. Furthermore, the impact of crop planting structures and climatic factors on ET was elucidated. The results indicate that a combination of multi-temporal green and shortwave infrared 1 bands is the optimal spectral combination to extract the planting structures. Compared to 2019, the wheat area decreased by 23.27% in 2020, while the corn area increased by 5.96%. Both crops exhibited significant spatial heterogeneity in ET during the growing season. The typical daily range of ET for wheat was 0.4–7.2 mm/day, and for corn, it was 1.5–4.0 mm/day. Among the climatic factors, temperature showed the highest correlation with ET (R = 0.80, p ≤ 0.05). Our research findings provide valuable insights for the fine identification of crop planting structures and a better understanding of the response of ET to climatic factors and planting structures.

Plastics in the environment can break down into nanoplastics (NPs), which pose a potential threat to public health. Studies have shown that the nervous system constitutes a significant target for nanoplastics. However, the potential mechanism behind nanoplastics’ neurotoxicity remains unknown. This study aimed to investigate the role of lncRNA in the depressive-like responses induced by exposure to 25 nm polystyrene nanoplastics (PS NPs). Forty mice were divided into four groups administered doses of 0, 10, 25, and 50 mg/kg via gavage for 6 months. After conducting behavioral tests, RNA sequencing was used to detect changes in mRNAs, miRNAs, and lncRNAs in the prefrontal cortex of the mice in the 0 and 50 mg/kg PS NPs groups. The results revealed that mice exposed to chronic PS NPs developed depressive-like responses in a dose-dependent manner. It was demonstrated that 987 mRNAs, 29 miRNAs, and 116 lncRNAs were significantly different between the two groups. Then, a competing endogenous RNA (ceRNA) network containing 6 lncRNAs, 18 miRNAs, and 750 mRNAs was constructed. Enrichment results suggested that PS NPs may contribute to the onset of depression-like responses through the activation of axon guidance, neurotrophin-signaling pathways, and dopaminergic synapses. This study provided evidence of the molecular relationship between PS NPs and depression-like responses.

Soft clay is of the characteristics of strong compressibility and low bearing capacity. Cement is used as curing agent to strengthen soft clay in engineering. Mica is a kind of mineral widely distributed in soft clay, and its content and particle size will affect the strength of the cement-reinforced soft clay. The influence law among the mica content and mica mesh number on strength of the cement-reinforced soft clay is studied based on direct shear tests and unconfined compressive strength tests. Based on the experimental data, the mathematical relationship between the content and mesh number of mica and soil-cement strength is established. The number of mica meshes in the experiment is 10, 20, 40 and 80 mesh, and the mica content is set as 0%, 8%, 16% and 32%. The results show that as the content of mica increases or the number of mica meshes decreases, the unconfined compressive strength and shear strength of the cement-reinforced soft clay show a decreasing trend, and the effect of mica on the unconfined compressive strength is more significant. When the number of mica mesh in the cement soft clay is 10 mesh and the content is 32%, the strength of the cement soft clay decreases the most. In this case, the unconfined compressive strength of 0.33 MPa is 25.5% of that of the cement soft clay without mica, the cohesion is 76.5 kPa, which is 12.24 kPa less than that of the cement soft clay without mica, and the internal friction angle decreases from 23.71° to 21.77°. It is speculated that the lamellar morphology of mica and adverse effect on cement hydration are the main reasons for the decrease of the cement soil strength.