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Future climate change has been predicted to affect the potential distribution of plant species. However, only few studies have addressed how invasive species may respond to future climate change despite the known effects of plant species invasion on nutrient cycles, ecosystem functions, and agricultural yields. In this study, we predicted the potential distributions of two invasive species, Rumex crispus and Typha latifolia, under current and future (2050) climatic conditions. Future climate scenarios considered in our study include A1B, A2, A2A, B1, and B2A. We found that these two species will lose their habitat under the A1B, A2, A2A, and B1 scenarios. Their distributions will be maintained under future climatic conditions related to B2A scenarios, but the total area will be less than 10% of that under the current climatic condition. We also investigated variations of the most influential climatic variables that are likely to cause habitat loss of the two species. Our results demonstrate that rising mean annual temperature, variations of the coldest quarter, and precipitation of the coldest quarter are the main factors contributing to habitat loss of R. crispus. For T. latifolia, the main factors are rising mean annual temperature, variations in temperature of the coldest quarter, mean annual precipitation, and precipitation of the coldest quarter. These results demonstrate that the warmer and wetter climatic conditions of the coldest season (or month) will be mainly responsible for habitat loss of R. crispus and T. latifolia in the future. We also discuss uncertainties related to our study (and similar studies) and suggest that particular attention should be directed toward the manner in which invasive species cope with rapid climate changes because evolutionary change can be rapid for species that invade new areas. [ABSTRACT FROM AUTHOR]

Pulmonary thromboembolism (PTE) is a fatal clinical syndrome that usually occurs in elderly individuals. The present study aimed to identify functional and key genes involved in the early diagnosis of PTE using bioinformatics analysis. The GSE84738 dataset was retrieved from the Gene Expression Omnibus database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were subsequently performed. In addition, Cytoscape software v.3.7.2 was used to construct a protein-protein interaction (PPI) network. Serum samples from patients with PTE and healthy individuals were collected and the expression levels of Toll-like receptor (TLR)4, TLR2, IL-1β, JUN, prostaglandin-endoperoxide synthase 2 (PTGS2), osteopontin (SPP1) and endothelin-1 (ET-1) were analyzed by reverse transcription-quantitative PCR. A total of 160 upregulated and 159 downregulated differentially expressed genes were identified between patients with PTE and healthy individuals. TNF, IL-1β, JUN, TLR4, PTGS2, vascular cell adhesion molecule 1, SPP1, ryanodine receptor 2, TLR2 and ET-1 were considered as hub genes, which are defined as the genes with the highest degree of interaction in the enrichment and PPI network analyses. The top 10 common genes with the highest degree in the PPI network and the top 10 genes in modules 1 and 2 were TLR4, TLR2, IL-1β, JUN, PTGS2, SPP1 and ET-1. Taken together, the present study suggested that TLR4, TLR2, IL-1β and SPP1 were enriched in patients with PTE, thus providing novel potential biomarkers for the diagnosis of PTE. [ABSTRACT FROM AUTHOR]

• The grassland SOS in the ACA showed an advancing trend. • Rising TMX and VPD contributed to the advance of SOS. • Delaying effects of TMN and SM were offset by indirect effects of TMX and VPD. • TMX and TMN had an asymmetric effect on SOS. • The relative contributions of TMN on SOS increased significantly. The dynamics of grassland spring phenology in arid Central Asia (ACA) are critical for the regional carbon cycle, ecological security, and social stability. Nonetheless, the mediating effects of climatic elements on grassland start of season (SOS) and trends in the relative contributions to the SOS in the ACA have not been sufficiently investigated. In this study, we explored the mediating effects of daily maximum temperature (TMX), daily minimum temperature (TMN), vapor pressure deficit (VPD), and soil moisture (SM) on grassland SOS and trends in the relative contributions of TMX, TMN, VPD, SM to SOS in the ACA from 1982 to 2022. We found that the grassland SOS in the ACA showed an advancing trend of 0.28 days/yr. Rising TMX and VPD contributed to the advance of SOS, and the delaying effects of TMN and SM were offset by the indirect effects of TMX and VPD. TMX and TMN had asymmetric effects on SOS, with SOS advanced or delayed for increases in TMX or TMN, respectively. TMX was the dominant factor controlling the SOS, with the largest relative contribution (47.93 % of the ACA). Over the past 41 years, the relative contributions of SM and VPD to SOS showed a non-significant decreasing trend, TMX remained unchanged, and TMN showed a highly significant increasing trend. Under sustained future warming, TMN may undergo more accelerated warming than TMX, and the advance of SOS due to increased TMX may be further offset, potentially leading to the supplantation of TMX by TMN in its impact on SOS. Our results emphasize that characterization of the phenological response should account for the mediating effects of climatic elements and trends in relative contributions. [ABSTRACT FROM AUTHOR]

In the context of global warming, the occurrence and severity of extreme events like atmospheric drought (AD) and warm spell duration index (WSDI) have increased, causing significant impacts on terrestrial ecosystems in Central Asia's arid regions. Previous research has focused on single extreme events such as AD and WSDI, but the effect of compound hot and dry events (CHWE) on grassland phenology in the arid regions of Central Asia remains unclear. This study utilized structural equation modeling (SEM) and the Pettitt breakpoint test to quantify the direct and indirect responses of grassland phenology (start of season - SOS, length of season - LOS, and end of season - EOS) to AD, WSDI, and CHWE. Furthermore, this research investigated the threshold of grassland phenology response to compound hot and dry events. The research findings indicate a significant increasing trend in AD, WSDI, and CHWE in the arid regions of Central Asia from 1982 to 2022 (0.51 day/year, P < 0.01; 0.25 day/year, P < 0.01; 0.26 day/year, P < 0.01). SOS in the arid regions of Central Asia showed a significant advancement trend, while EOS exhibited a significant advance. LOS demonstrated an increasing trend (−0.23 day/year, P < 0.01; −0.12 day/year, P < 0.01; 0.56 day/year). The temperature primarily governs the variation in SOS. While higher temperatures promote an earlier SOS, they also offset the delaying effect of CHWE on SOS. AD, temperature, and CHWE have negative impacts on EOS, whereas WSDI has a positive effect on EOS. AD exhibits the strongest negative effect on EOS, with an increase in AD leading to an earlier EOS. Temperature and WSDI are positively correlated with LOS, indicating that higher temperatures and increased WSDI contribute to a longer LOS. The threshold values for the response of SOS, EOS, and LOS to CHWE are 16.14, 18.49, and 16.61 days, respectively. When CHWE exceeds these critical thresholds, there are significant changes in the response of SOS, EOS, and LOS to CHWE. These findings deepen our understanding of the mechanisms by which extreme climate events influence grassland phenology dynamics in Central Asia. They can contribute to better protection and management of grassland ecosystems and help in addressing the impacts of global warming and climate change in practice. [Display omitted] • Droughts, heat waves, and compound hot and dry events rose sharply in Central Asia. • Grassland SOS and EOS advanced, LOS extended due to temperature and extremes. • Thresholds for hot and dry events' impacts on vegetation phenology were quantified. [ABSTRACT FROM AUTHOR]

ABSTRACT With the rapid urbanization in China, urban land resources gradually become the core of urban development. This study spatially evaluated the urban land resource carrying capacity (LRCC) with a case study of the built‐up area in Wuhan from 2015 to 2020. Following an evaluation index system, five critical LRCC indicators, including population density, GDP per land area, plot ratio, building density, and road network density, were selected by an analytical hierarchical process. The synthesis of indicators, however, is usually challengeable due to homogeneous assumptions of traditional techniques. In this study, we adopted a local technique, geographically weighted principal component analysis, to calculate a comprehensive carrying pressure (CCP) concerning spatially varying contributions of each indicator on their synthesis across different geographic locations. On mapping these spatial outputs of the built‐up area in Wuhan, the highest CCP was found in the central areas, where population size tends to be influential and the dominant variable in 62.69% of subdistricts. Furthermore, increased construction over the 5 years has led to an increased CCP in some of the peripheries of the built‐up area, and 55.22% of subdistricts show rising changes. With the GWPCA technique, this framework works well in evaluating and analyzing urban LRCC from a new local perspective. [ABSTRACT FROM AUTHOR]

Modeling and forecasting tourism demand across destinations has become a priority in tourism research. Most tourism demand studies rely on annual statistics with small sample sizes and lack research on spatial heterogeneity and drivers of tourism demand. This study proposes a new framework for measuring inter-provincial tourism demand's spatiotemporal distribution using search engine indices based on a geographic perspective. A combination of spatial autocorrelation and Geodetector is utilized to recognize the spatiotemporal distribution patterns of tourism demand in 2011 and 2018 in 31 provinces of mainland China and detect its driving mechanisms. The results reveal that the spatial distribution of tourism demand manifests a vital stratification phenomenon with significant spatial aggregation in the southwest and northeast of China. Traffic conditions, social-economic development level, and physical conditions compose a constant and robust interaction network, which dominates the spatial distribution of tourism demand in different development stages through different interactions. [ABSTRACT FROM AUTHOR]

• Spectral, texture, and structural information from UAV-based multispectral image were used to estimate SPAD values in leaves of walnut. • The accuracy of SPAD values estimation model constructed by combining remote sensing indices (spectral indices (SI), texture indices (TI) and structural indices (STI) are combined in pairwise or in full) is better than that of single remote sensing indices. • XGBoost model that combines spectral, texture, and structural indices provided the highest accuracy of SPAD values estimation. An important measure to describe the physiological status of vegetation is the chlorophyll concentration of the vegetation. For managing fields in precision agriculture, monitoring walnut growth, and estimating production, accurate determination of chlorophyll content is crucial. Spectral indices play a crucial role in the non-destructive and efficient monitoring of crop physiological parameters, especially in estimating chlorophyll content. However, spectral indices have low sensitivity to high chlorophyll levels and are susceptible to interference from background signals, which may result in decreased stability of the model. The unmanned aerial vehicle (UAV) captures high-resolution images that contain abundant spatial information, including texture and structural information. These spatial information can reflect crop canopy structure, may help to improve the estimation precision of crop chlorophyll content. However, research on utilizing drone-based spatial information for estimating crop chlorophyll content is relatively limited. The aim of this study is to explore the potential of integrating spectral, textural, and structural information to improve the accuracy of walnut leaf chlorophyll content estimation. This study used a drone equipped with a multispectral camera to capture images of walnut tree canopies. Based on these images, we extracted 17 spectral indices, 8 texture indices, and 5 structural indices. Then, we applied the Boruta algorithm to select the optimal spectral, texture, and structural indices, as well as their combinations. Finally, the SPAD (Soil and plant analyzer development) values estimation model for walnut leaves was established using the Decision Tree Regression (DTR), Random Forest Regression (RFR), and Extreme Gradient Boosting (XGBoost) methods. The research findings indicate that the accuracy of SPAD values estimation model constructed by combining remote sensing indices (spectral indices (SI), texture indices (TI) and structural indices (STI) are combined in pairwise or in full) is better than that of single remote sensing indices. In the combined remote sensing indices models, the accuracy of the model constructed by the pairwise combination of three remote sensing indices is relatively limited. However, when using the combination of spectral indices, texture indices, and structural indices, the estimation accuracy of SPAD values for walnut leaves can be effectively improved, and this combination is considered the best way to estimate SPAD values. Furthermore, among the trio of SPAD values estimation models considered (namely DTR, RFR, and XGBoost), the XGBoost model exhibited superior performance. Notably, when combining SI+TI+STI in the construction of the XGBoost model, it demonstrated the highest level of accuracy in estimating SPAD values (Training: R2 T =0.95, RMSE T =1.08; Validation: R2 v = 0.72, RMSE v =2.13). The findings of this research elucidate that the incorporation of spatial information from UAV multispectral imagery facilitates the monitoring of physiological parameters in walnut trees. By integrating the spatial and spectral information of UAV multispectral imagery, a feasible and accurate estimation method has been provided for monitoring the chlorophyll content in walnut leaves. [ABSTRACT FROM AUTHOR]

Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However, reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6 (CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed. While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ∼33% (with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration (PET) by ∼32% (17.5%–17.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50% (29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation (water deficit) associated with dryland droughts is overestimated by 28% (24%) compared to observations. The observed increasing trends in drought fractional area, occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s, especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs. [ABSTRACT FROM AUTHOR]

Malignancy of the lung is a major source of morbidity and mortality in persons with human immunodeficiency virus infection; as the most prevalent non-acquired immunodeficiency syndrome-defining malignancy, it represents an important and growing problem confronting HIV-infected patients. To evaluate the molecular changes of lung malignancy in HIV infection, we analyzed differential gene expression profiles and screened for early detection biomarkers of HIV-associated lung cancer using Affymetrix arrays and IPA analysis. A total of 59 patients were diagnosed with HIV-associated lung cancer from Jan 2010 to May 2018. The primary outcome was a significant difference in survival outcome between stages III-IV (10.46 ± 1.87 months) and I-II (17.66 ± 2.88 months). We identified 758 differentially expressed genes in HIV-associated lung cancer. The expression levels of SIX1 and TFAP2A are specifically increased in HIV-associated lung cancer and are associated with poorly differentiated tumor tissue. We also found decreased ADH1B, INMT and SYNPO2 mRNA levels in HIV lung cancer. A comprehensive network and pathway analysis of the dysregulated genes revealed that these genes were associated with four network functions and six canonical pathways relevant to the development of HIV-associated lung cancer. The molecular changes in lung malignancy may help screen the growing population of HIV patients who have or will develop this malignancy. [ABSTRACT FROM AUTHOR]

With the development of human society, the balance between the minimum ecological instream flow requirement (MEIFR), which is an essential part of the ecological water demand in arid areas, and anthropogenic water depletion has received increasing attention. However, due to the lack of hydrological station data and river information on arid basins, previous researchers usually considered only the individual ecological water demand of rivers, lakes, or oases. To address this issue, a new method that combines river hydraulic parameters and the wet circumference obtained by an unmanned aerial vehicle (UAV) and remote sensing hydrological station (RSHS) technologies was applied to obtain the MEIFR and, then, systematically and quantitatively explore the balance from the perspective of the entire basin of Aiding Lake from 1990 to 2022, which is the lowest point of Chinese terrestrial territory. The results showed the following: (1) since 1990, the discharge of the seven rivers in the study area increased by 1–6%, and the MEIFR of these rivers increased by 15–100%; both quantities decreased by 3–5% from the upper to the lower reaches of the basin; (2) the surface area and water level of Aiding Lake decreased by 5% and 14%, respectively, but the MEIFR first decreased by 25% from 1990 to 2013 and, then, increased by 66.7% from 2013 to 2022; and (3) from 2011 to 2022, the MEIFR and anthropogenic water depletion exhibited a balance. Against the background of climate change, this research revealed that the MEIFR of the rivers in the Aiding Lake Basin have shown an upward trend over the past 30 years and quantitatively determined the above balance relationship and the period of its occurrence. This study supplied a method that could provide guidance for water resource management by decision-makers at a global level, thus helping achieve the sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

Global warming has exacerbated the threat of drought in Central Asia, amplifying its ecological implications within the region's grassland ecosystems. This has become an increasingly prominent issue that requires attention and action. The temporal link between grassland development and drought is asymmetric. However, a quantitative assessment of the temporal effects of multiscale drought on Central Asian grasslands has yet to be explored. Based on correlation analysis and the coefficient of variation method, this study analysed the cumulative and lag effects of multitimescale drought on grassland NPP (net primary productivity) under different climatic zones, altitudes and water availabilities in Central Asia from 1982 to 2018, and discussed the impact of temporal effects on grassland NPP stability. Our results on the cumulative effects of drought on grasslands indicate the 6.72 months preceding NPP measurement was the duration for which, on average, drought was most strongly correlated with NPP. Additionally, we found a mean lagged effect of 5.36 months, meaning that the monthly drought 5.36 months prior to NPP measurement was, on average, most strongly correlated with NPP. The degree to which grassland NPP was affected by cumulative drought at a given level of water availability was inversely proportional to the number of cumulative drought months. Under different water availabilities, the lagged effect of grassland NPP was stronger in dry areas than in wet areas, and the number of lag months tended to decrease and then increase as the water availability increased. The percentage of areas where grassland NPP was dominated by the cumulative and lagging effects of drought was 30.02% and 69.98%, respectively. The stability of grassland NPP was adversely affected by the drought accumulation effect. The findings of this study contribute to a deeper understanding of the long-term effects of drought on grassland ecosystems. Additionally, it will aid in the development of strategies for mitigating and adapting to drought events, thereby minimizing their negative impacts on agriculture, livestock, and ecosystems. [Display omitted] • The relative roles of drought accumulation and lag on grassland NPP were studied. • The stability of grassland NPP was affected by the drought accumulation effect. • Cumulative and lag effects of drought were related to water balance gradients. • Accumulated (lagged) drought significantly affected 30.02% (69.98%) of the area. [ABSTRACT FROM AUTHOR]

The ecological water diversion project (EWDP) in the Tarim River Basin, China, aims to allocate more surface water to downstream reaches to restore the degraded ecosystems. However, seasonal changes in ecological water diversion; the factors (natural and anthropogenic) controlling the ecological water diversion, whether the seasonal delivery of water temporally corresponded to the vegetation's seasonal water demands; and the benefits of the ecological water diversion through overflowing surface water irrigation are unclear. To address the above issues, this study examines the intra-annual changes and its influencing factors in ecological water diversion (inundation) in the Daliyaboyi Oasis in the lower Keriya River valley within the Tarim Basin, discusses whether the seasonal delivery of water temporally corresponded to the vegetation's seasonal water demands, and assesses the ecological benefits of overflowing surface water irrigation. Inundation was quantified by digitizing monthly changes in the inundated area from 2000 to 2018 in the oasis using 184 Landsat images. The results demonstrate that seasonal changes in the inundated area varied significantly, with maximum peaks occurring in February and August; a period of minimal inundation occurred in May. Differences in the July/August peak (i.e., July or August) in inundation dominated the inter-annual variations in the inundated area over the 19-year study period. The two peaks in the inundation area were temporally consistent with the vegetation's seasonal water demand. Local residents have used ecological water to irrigate vegetation in different parts of the oasis during different seasons, an approach that expanded the inundated area. The February peak in the inundated area is closely linked to elevated downstream groundwater levels and the melting of ice along the river. The August peak is related to a peak in runoff from headwater areas. The minimum May value is correlated to a relatively low value in upstream runoff and an increase in agricultural water demand. Thus, natural factors control the intra-annual and inter-annual variations in the inundated area. Humans changed the spatial distribution of the inundated area and enhanced the water's ecological benefits, but did not alter the correlation between peak periods of inundation and vegetation water demand. The results from this study improve our understanding of the benefits of the EWDP in the Tarim River Basin. [ABSTRACT FROM AUTHOR]

Extreme climate events can cause large risks to ecosystems and human society in a short period. Investigating the changing trends of such events is essential for regional climate risk management. However, there is limited information on the regional assessment of the history and future trends of extreme climate events in Xinjiang, China. This study investigated the historical changes and projected trends of extreme climate events in Xinjiang based on observational data and Coupled Model Intercomparison Project phase 6 (CMIP6) model simulations. The results showed that the bias correction effectively reduced the bias of the CMIP6 model to the extreme climate indices simulation. During the period 1961–2014, the extreme indices representing warmth showed robust growth, while the extreme indices representing cold showed a robust decline. The intensity and frequency indices of extreme precipitation continued to increase, while consecutive dry days (CDDs) shortened and consecutive wet days (CWDs) lengthened. The changing trend of the extreme temperature indices had strong spatial consistency, while the changing trend of the extreme precipitation indices had obvious spatial heterogeneity. Based on the CMIP6 model simulations, the extreme climate indices in the twenty-first century were projected to continue the changing trend of the historical period (1961–2014). Compared with north Xinjiang (NXJ) and south Xinjiang (SXJ), the cold spell duration index (CSDI), cold nights (TN10p), cold days (TX10p), and extreme precipitation events in the Tianshan Mountains (TSM) were projected to experience stronger changes in the twenty-first century. The response of extreme temperature and extreme precipitation indices to global warming was approximately linear. Compared with SSP585, most extreme climate indices under the SSP245 scenario changed slightly in response to global warming. The superposition of the increase (decrease) in extreme warm (cold) events and the increase in extreme precipitation events will exacerbate the threat of extreme climate events to the agricultural and ecological security of the Xinjiang oasis, especially in the TSM. Given the limited water vapor sources and precipitation and the high rate of evapotranspiration, it is projected that the current situation of water shortages in Xinjiang will not be fundamentally changed. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to identify the novel microRNAs (miRNAs) for early diagnosis of bladder cancer. Materials and Methods: Differentially expressed miRNAs between early and advanced bladder cancer were identified by differential expression analysis, using miRNA-seq data from The Cancer Genome Atlas (TCGA). The optimal subset of feature miRNAs for pathologic stage prediction was acquired by Random Forest algorithm and was used to construct a support vector machine (SVM) classifier. The performance of the SVM classifier in predicting the progression of bladder cancer samples was validated using an independent validating dataset. An miRNA-regulated target gene network was finally constructed and functional annotation were performed for the target genes. Results: A total of 52 significantly differentially expressed miRNAs were identified between early and advanced bladder cancer samples and 17 of these miRNAs were identified to be feature miRNAs. The 17 feature miRNAs were used to construct an SVM classifier, which showed a high performance in pathologic stage prediction for both training and validating dataset. Besides, our functional annotation analysis showed that the feature miRNAs were significantly involved in biological processes and pathways related to extracellular matrix process and PI3K/Akt signaling. Conclusions: The optimal subset of miRNAs may act as potential therapeutic targets and diagnostic markers of bladder cancer. [ABSTRACT FROM AUTHOR]

The potential impact of natural factors on the runoff of intermittent rivers and ephemeral streams (IRES) has been largely ignored in the Tarim Basin, China. A representative example is the Keriya River. To quantify the long-term dynamic variations in lower reach surface runoff of IRES, river length, defined as the distance between a selected fix point along the perennial river segment to its dynamic, ephemeral end, was used as an indicator. Using a total of 272 remote sensing images, we digitized and measured the distance (river length) between the center of Yutian County and the river's end point on each image, and then calculated monthly inter-annual and intra-annual variations in length of the lower Keriya River from 2000 to 2019. Hydrometeorological data were combined with descriptors of anthropogenic disturbances to assess the relative influence of natural factors and anthropogenic disturbances on lower reach river runoff. The results showed that intra-annual variations in river length fluctuated seasonally, with the minimum value occurring in June; two main peaks occurred in March and August. The minimum June value in river length was closely linked to an increase in agricultural water demand and a decrease in upper reach runoff. The August peak in river length was related to the peak values in upper reach runoff and agricultural water demand; upper reach runoff made a significant contribution because the former was about 20% more than the latter in summer. The March peak corresponded to elevated lower reach groundwater levels and to the melting of ice along river channels. Inter-annual variations in river length were due to inter-annual variations in upper reach runoff and middle reach agricultural water use which increased slightly during the study period. Inter-annual variations in frequency and amplitude of the fluctuations in river length were mainly controlled by changes in upper reach runoff. The minimum in river length in 2009 was consistent with the low in upper reach runoff of the Keriya River and other rivers in the Tarim Basin. The most significant factors controlling variations in river length are natural in origin. [ABSTRACT FROM AUTHOR]

Background: Recently, more and more studies have highlighted the critical regulatory roles of circular RNAs (circRNAs), a class of non-coding RNAs, in the progression of many human cancers, including prostate cancer (PCa). circRNA microarray analysis was performed to identify circRNAs that are differentially expressed in PCa tissues. Methods: 104 pairs of PCa tissues and matched adjacent normal prostate tissues (at least 2 cm distal to the tumor margin) were obtained. circRNA microarray analysis was performed on four pairs of PCa tissues and matched adjacent normal prostate tissues to investigate the potential involvement of circRNAs in PCa. Flow cytometric analysis was performed to investigate whether the effect of circDPP4 on PCa cell proliferation was associated with the alteration in cell cycle progression. The role of circDPP4 in PCa tumor growth was further explored in vivo. Results: We found that circDPP4 was overexpressed in PCa tissues and cell lines, and its expression was closely associated with Gleason score and clinical stage of PCa patients. In vitro loss- and gain-of-function experiments demonstrated that circDPP4 knockdown inhibited, whereas circDPP4 overexpression promoted the proliferation, migration, invasion and cell cycle progression of PCa cells. Knockdown of circDPP4 also suppressed PCa tumor growth in vivo. We further found that circDPP4 functioned as a competing endogenous RNA (ceRNA) for miR-195 in PCa cells, and miR-195 negatively regulated the expression of oncogenic cyclin D1. Rescue experiments suggested that restoration of miR-195 blocked the oncogenic role of circDPP4 in PCa cells. Conclusions: Taken together, our findings revealed a novel regulatory mechanism between circDPP4 and miR-195/cyclin D1 axis, and offered novel strategies for the treatment of PCa. [ABSTRACT FROM AUTHOR]

• The performances of CatBoost, GRNN and RF were assessed to estimate daily ET 0. • CatBoost model provided the most accurate results among the considered models. • GRNN model showed comparable estimates of daily ET 0 to the RF model. • The generalized analysis confirmed the results obtained in the local analysis. Establishing a computational model for accurate prediction of reference crop evapotranspiration (ET 0) is critical for regional water resources planning and irrigation scheduling design. FAO Penman-Monteith equation is recommended as the standard model to predict ET 0. However, its application is restricted by lack of complete meteorological data in many regions. This study evaluated the performance of CatBoost, an algorithm for gradient boosting on decision trees, for estimating daily ET 0 using limited meteorological data in arid and semi-arid regions of Northern China. The CatBoost model was further compared with their corresponding generalized regression neural network (GRNN) and random forests (RF) models. Eight input combinations of daily meteorological data including daily maximum air temperature (T max), daily minimum air temperature (T min), wind speed at 2 m height (u 2), relative humidity (RH) and net radiation (R n) from 15 weather stations during 1996–2015 were used to train and test the models. Four statistical indicators were used to evaluate the accuracy and performance of the models, including coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and mean bias error (MBE). The results showed that all the three models using T max , T min , u 2 and R n could obtain satisfactory ET 0 estimates in arid and semi-arid regions of Northern China with incomplete sets of data. For the local models, CatBoost (on average RMSE ranging 0.096–0.821 mm d−1) was superior to GRNN (on average RMSE ranging 0.206–0.847 mm d−1) and RF (on average RMSE ranging 0.169–0.866 mm d−1) under the same meteorological parameters as input. The results of the generalized models were similar to the local models, but the former ones performed worse than the latter ones. Overall, CatBoost is observed to be the best alternative for estimating ET 0 , which is helpful for irrigation scheduling in arid and semi-arid regions of Northern China and maybe elsewhere with similar climates. [ABSTRACT FROM AUTHOR]

Ecological security and ecosystem stability in Central Asia depend heavily on the local vegetation. Vegetation dynamics and the response and hysteresis relationships to climate factors and drought on multiple scales over long time series in the region still need to be further explored. Using the net primary productivity (NPP) values as the vegetation change index of interest, in this study, we analyzed vegetation dynamics in Central Asia from 1982 to 2020 and assessed the responses and time lags of vegetation to climate factors and drought. The results showed that NPP gradually decreased from north to south and from east to west. Vegetation was distributed along both sides of the mountains. The temperatures rose from northeast to southwest, while precipitation gradually increased from southwest to northeast. The proportion of dry and wet years was as follows: normal (56.41%) > slightly dry (28.2%) > slightly humid (15.39%). Precipitation and drought conditions were positively correlated with NPP during the growing season, while temperature was negatively correlated with NPP. Increased spring temperature, precipitation, and drought conditions positively affected vegetation, while sustained summer temperature resulted in suppressed vegetation growth. Autumn vegetation was positively affected by temperature and drought, and precipitation was negatively correlated with autumn vegetation. Increasing winter temperatures promoted vegetation growth. The time lag between NPP and temperature gradually increased from northeast to southwest, and the time lag between NPP and precipitation gradually increased from south to north. Spring temperatures had the greatest beneficial impact on forestlands; summer climatic factors and drought had little effect on shrublands; the autumn climate exhibited small differences in its influence of each plant type; and winter temperatures had the greatest positive effect on grasslands. No time lag effect was found between any of the four vegetation types and precipitation. A one-month lag was found between cultivated lands and temperature; a two-month lag was found between forestlands and temperature; and a one-month lag was found between forestlands and drought and between shrublands and drought. The results can provide a scientific foundation for the sustainable development and management of ecosystems. • Analysis of vegetation dynamics from 1982 to 2020 on multiple seasonal scales. • The response and lag of vegetation to climatic factors and drought were analyzed. • The lag between vegetation and temperature increased from northeast to southwest. • The lag between vegetation and precipitation increased from south to north. [ABSTRACT FROM AUTHOR]

It is necessary to quantitatively study the relationship between climate and human factors on net primary productivity (NPP) inorder to understand the driving mechanism of NPP and prevent desertification. This study investigated the spatial and temporal differentiation features of actual net primary productivity (ANPP) in the Ili River Basin, a transboundary river between China and Kazakhstan, as well as the proportional contributions of climate and human causes to ANPP variation. Additionally, we analyzed the pixel-scale relationship between ANPP and significant climatic parameters. ANPP in the Ili River Basin increased from 2001 to 2020 and was lower in the northeast and higher in the southwest; furthermore, it was distributed in a ring around the Tianshan Mountains. In the vegetation improvement zone, human activities were the dominant driving force, whereas in the degraded zone, climate change was the primary major driving force. The correlation coefficients of ANPP with precipitation and temperature were 0.322 and 0.098, respectively. In most areas, there was a positive relationship between vegetation change, temperature and precipitation. During 2001 to 2020, the basin’s climatic change trend was warm and humid, which promoted vegetation growth. One of the driving factors in the vegetation improvement area was moderate grazing by livestock. [ABSTRACT FROM AUTHOR]

Satellite-derived vegetation records (GIMMS3g-NDVI) report that climate warming promotes vegetation greening trends; however, the climate impacts on vegetation growth during the global warming hiatus period (1998–2012) remain unclear. In this study, we focused on the vegetation change trend in Xinjiang in spring and autumn before and during the recent warming hiatus period, and their climate-driving mechanisms, which have not been examined in previous studies. Based on satellite records, our results indicated that the summer normalized difference vegetation index (NDVI) in Xinjiang experienced a greening trend, while a browning trend existed in spring and autumn during this period. The autumn NDVI browning trend in Xinjiang was larger than that in spring; however, the spring NDVI displayed a higher correlation with climatic factors than did the autumn NDVI. During the warming hiatus, spring climatic factors were the main controlling factors of spring NDVI, and spring vapor pressure deficit (VPD) had the highest positive correlation with spring NDVI, followed by spring temperature. The larger increase in air temperature in spring than in autumn resulted in increased VPD differences in spring and autumn. In autumn, summer climatic factors (e.g., VPD, WS, RH, and precipitation) were significantly correlated with the autumn NDVI during the warming hiatus. However, the autumn temperature was weakly correlated with the autumn NDVI. Our results have significant implications for understanding the response of vegetation growth to recent and future climatic conditions. [ABSTRACT FROM AUTHOR]

The requirement of carbon emission reduction promotes the continuous implementation and development of low carbon emission mode in typical high-carbon industry aquaculture, especially in the resourceful treatment of terminal waste. However, the previous studies usually focus on a single process or chain, the difference between the long-chain (LC) and automated integration (AI) in the overall environmental impact needs to be quantified and standardised. This paper intends to make a comparative study on two waste treatment biogas projects of aquaculture, a typical industry with high resource consumption and pollution emission in industry and agriculture, and a typical production mode case of aquaculture. The life cycle assessment method is adopted to analyse the environmental impact intensity, identify key link materials, and put forward targeted improvement and optimization schemes. The study found the LC system's comprehensive environmental impact (CEI) is smaller, which is 59.73% less than the AI system. Biogas slurry returning to the field can effectively avoid inorganic fertilizer input. The pretreatment and storage of feces are the key stages. The key substances are NH 3 and nitrogen oxides. Suggestions were put forward to optimize the manure management process. In practical pig farms, the process of dry-cleaning manure pre-treatment, automatic fermentation gas production and final biogas slurry filtration drip irrigation should be promoted. [Display omitted] • Enterprise low-carbon emission model on agriculture waste management is explored. • Long-chain and automated integration models have been involved and compared. • The long-chain model has much less, 59.73%, environmental impact than the automated integration model. • The pre-treatment and storage of feces are the key stages in the waste management china. [ABSTRACT FROM AUTHOR]

The dynamics of the ecosystem represented by vegetation under the influence of human activities have become an important issue in the study of the regional ecological environment. Xinjiang is one of the most ecologically fragile areas in the world, and vegetation changes have received extensive attention. Xinjiang is one of the most ecologically fragile areas in the world, and vegetation changes have received extensive attention. However, the spatiotemporal patterns and evolutionary trends of anthropogenic impacts on vegetation dynamics in Xinjiang are still unclear. In this study, the anthropogenic impacts on vegetation dynamics were quantitatively assessed by combining the improved normalized difference vegetation index (NDVI) prediction model and the residual analysis method in Xinjiang, China. The human driving factors were analyzed with the support of a stepwise multiple regression model for vegetation changes at the county scale. Based on trend analysis and the Hurst exponent, the spatiotemporal characteristics and evolutionary trends of the impact of human activities on vegetation change were discussed. The results show that (1) the NDVI values in Xinjiang showed a gradually increasing trend at a rate of 0.005/10 years from 1982 to 2018, and the vegetation dynamics mainly showed significant improvements (57.09% of the vegetated areas), especially for crops. (2) The anthropogenic effects of vegetation changes in Xinjiang mainly included positive impact increases (43.22% of the vegetated areas) from 2000 to 2018. Human activities promoted the increase in the NDVI of various vegetation types. Both the positive and negative impacts of human activities increased over the study period, and the growth rate of the positive influence (0.08%/10 years) was higher than that of the negative influence (0.04%/10 years). (3) The cultivated area, GDP of primary industry, and population are the main anthropogenic factors causing the increase in NDVI, which dominate the vegetation greening in 30.34%, 29.22%, and 28.09% of the counties in Xinjiang, respectively. The animal husbandry population, agricultural population, and livestock number are the main anthropogenic factors causing the decrease in NDVI, which dominate the vegetation degradation in 23.60%, 21.35%, and 17.98% of the counties in Xinjiang, respectively. (4) The evolutionary trend of the anthropogenic impact on vegetation dynamics in Xinjiang will be dominated by anti-persistence (53.84% of the vegetated areas), thereby mainly showing that the positive impacts continued to increase (22.56% of the vegetated areas), especially for crops, shrubs, grasslands, and alpine vegetation. Our results are helpful in understanding the characteristics and evolutionary trends of vegetation changes in arid areas caused by human activities and are of significance as a reference for policymakers to appropriately adjust policy guidance in a timely manner to promote the protection and sustainable development of fragile ecosystems. [ABSTRACT FROM AUTHOR]

The vapor pressure deficit (VPD) is the difference between the atmospheric water vapor holding capacity at saturation ( e s ) and actual amount of water vapor ( e a ) in the air at a given temperature. In this study, we investigated the changes in VPD and related variables (air temperature, relative humidity, e s and e a ), and assessed the relationship between VPD and atmospheric conditions in Xinjiang over the period 1961–2017. The annual VPD records showed increasing trends during all seasons. In terms of spatial distribution, the increasing and decreasing trends of annual VPD were 79% (57% significant) and 21% (9% significant) of the observation stations, respectively. A trend reversal from downward to upward was observed in 1993, and the VPD records indicated rapid drying of the atmosphere in Xinjiang for 1994–2017, especially in the summer months. The differences in e s and e a resulted in changes in the VPD, and the e a generally increased less than the e s . We suggest that the increasing VPD in Xinjiang is due to increasing e s from rising temperatures and decreasing e a from decreasing relative humidity since 1994. The decreased relative humidity has a strong influence on the increased VPD and accounts for ~74% of the variance in Xinjiang. In different environments, the VPD trends followed changes in air temperature and e a , with the greatest VPD increase in the desert, followed by the oasis and mountain environments. The increased VPD observed in Xinjiang between 1994 and 2017 is consistent with the global intensification of drought and adverse ecological effects of the 21st century. Thus, VPD change can be an accurate measure of regional drought and vegetation dynamics in Xinjiang. • VPD records show rapid drying of atmosphere in Xinjiang from 1994 to 2017. • VPD has increased since 1994 due to increased e s and decreased e a. • Increased VPD was mainly due to decreased relative humidity, accounting for ~74% of the variance. [ABSTRACT FROM AUTHOR]

As the issue of global climate change becomes increasingly prominent, the grassland ecosystems in Central Asia are facing severe challenges posed by the impacts of climate change. However, the dominant factors, impact pathways, and cumulative and time-lagged effects of climate factors on various grassland indices remain to be explored. This study selected data from 1988 to 2019, including Fractional Vegetation Cover (FVC), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Vegetation Optical Depth (VOD), to characterize grassland coverage, greenness, biomass accumulation, and water content features. Utilizing multiple linear regression, path analysis, and correlation analysis, this study investigated the dominant effects, direct impacts, indirect influences, and cumulative and time-lagged effects of climate factors on various grassland indices from spatial and climatic zone perspectives. The research findings indicate that over time, the grassland FVC and NPP exhibited increasing trends, while the LAI and VOD showed decreasing trends. Grassland indices are primarily influenced by precipitation and soil moisture (SM). The direct impact of SM on grassland indices was higher than precipitation. Vapour pressure deficit (VPD) has a direct negative impact on grassland indices. Grassland indices are subject to positive indirect effects from precipitation via SM and negative indirect effects from VPD via SM. Precipitation and SM mainly exhibited no cumulative and time-lagged effects on the impact of grassland VOD. VPD primarily demonstrated cumulative and time-lagged effects on grassland indices. The research findings offer valuable insights for conserving grassland ecosystems in Central Asia, as well as for shaping socioeconomic strategies and formulating climate policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies., Competing Interests: Declaration of Competing Interest ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests., (Copyright © 2024. Published by Elsevier Inc.)

Purpose: The purpose of this study is to assess the efficacy and safety of cilostazol prescription in patients with femoropopliteal peripheral artery disease (PAD) after endovascular therapy (EVT)., Materials and Methods: We conducted a systematic review and meta-analysis of all studies reporting the outcomes of cilostazol after femoropopliteal EVT of PAD up to September 2022. Clinical outcomes of interest included primary patency, in-stent restenosis (ISR), vessel re-occlusion, freedom from target lesion revascularization (TLR), repeat revascularization, all-cause mortality, amputation, major adverse cardiovascular events (MACEs) and major adverse limb events (MALEs), and bleeding complication., Results: A total of 4 randomized controlled trials (RCTs) and 8 observational studies containing a total of 4898 patients met the inclusion criteria and were included in this systematic review and meta-analysis. We found that the use of cilostazol was associated with higher primary patency after femoropopliteal artery EVT (odds ratio [OR]=1.67, 95% confidence interval [CI]=1.50-1.87, p<0.001, I 2 =33.2%), a lower risk of ISR (OR=0.43, 95% CI=0.29-0.63, p<0.001, I 2 =37.6%), repeat revascularization (OR=0.43, 95% CI=0.24-0.76, p<0.005, I 2 =27.4%), and vessel re-occlusion (OR=0.59, 95% CI=0.38-0.93, p<0.05, I 2 =0%). There was an increase in freedom from TLR rate (OR=2.19, 95% CI=1.58-3.05, p<0.001, I 2 =0%), as well as a reduction in the occurrence of MALEs (OR=0.50, 95% CI=0.29-0.85, p<0.05, I 2 =0%). However, there was no significant difference in amputation, MACEs, all-cause mortality, and major bleeding complications. Subgroup analysis showed that cilostazol treatment in patients with femoropopliteal drug-eluting stents (DES) implantation remained associated with higher primary patency and a lower risk of ISR., Conclusions: After EVT of femoropopliteal artery lesions, additional oral cilostazol enhances primary patency, reduces the occurrences of ISR and vessel re-occlusion, diminishes the risks associated with MALEs, lowers the need for repeat revascularization, and increases freedom from TLR rates. However, it does not impact amputation, MACEs, all-cause mortality, or major bleeding complications. These findings suggest cilostazol as a potentially safe and effective adjunct therapy in patients with femoropopliteal PAD after EVT., Clinical Impact: After undergoing endovascular therapy (EVT) for femoropopliteal artery lesions, the addition of cilostazol to antiplatelet therapy can significantly improve primary patency, reducing the incidence of in-stent restenosis, repeat revascularization, vessel re-occlusion, and major adverse limb events while increasing freedom from target lesion revascularization rate. The simultaneous use of drug-eluting stents in the femoropopliteal artery lesions, combined with cilostazol, potentially results in a synergistic anti-stenotic effect. This therapeutic approach does not appear to be associated with an increased risk of major bleeding events or all-cause mortality. These findings provide additional evidence supporting the treatment of anti-stenosis in patients with femoropopliteal artery lesions after EVT., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

It is crucial to estimate the theoretical carrying capacity of grasslands in Xinjiang to attain a harmonious balance between grassland and livestock, thereby fostering sustainable development in the livestock industry. However, there has been a lack of quantitative assessments that consider long-term, multi-scale grass-livestock balance and its impacts in the region. This study utilized remote sensing and empirical models to assess the theoretical livestock carrying capacity of grasslands. The multi-scale spatiotemporal variations of the theoretical carrying capacity in Xinjiang from 1982 to 2020 were analyzed using the Sen and Mann-Kendall tests, as well as the Hurst index. The study also examined the county-level grass-livestock balance and inter-annual trends. Additionally, the study employed the geographic detector method to explore the influencing factors. The results showed that: (1) The overall theoretical livestock carrying capacity showed an upward trend from 1982 to 2020; The spatial distribution gradually decreased from north to south and from east to west. In seasonal scale from large to small is: growing season > summer > spring > autumn > winter; at the monthly scale, the strongest livestock carrying capacity is in July. The different grassland types from largest to smallest are: meadow > alpine subalpine meadow > plain steppe > desert steppe > alpine subalpine steppe. In the future, the theoretical livestock carrying capacity of grassland will decrease. (2) From 1988 to 2020, the average grass-livestock balance index in Xinjiang was 2.61%, showing an overall increase. At the county level, the number of overloaded counties showed an overall increasing trend, rising from 46 in 1988 to 58 in 2020. (3) Both single and interaction factors of geographic detectors showed that annual precipitation, altitude and soil organic matter were the main drivers of spatiotemporal dynamics of grassland load in Xinjiang. The results of this study can provide scientific guidance and decision-making basis for achieving coordinated and sustainable development of grassland resources and animal husbandry in the region., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ma, Zheng, Pen, Xiao, Liu, Liu, Han, Li and Zhang.)

The long-term dynamic comprehensive evaluation of the water resource carrying capacity (WRCC) and the analysis of its potential driving mechanism in arid areas are contemporary research issues and technical means of mitigating and coordinating the conflict between severe resource shortages and human needs. The purpose of this study was to explore the distribution of the WRCC and the spatiotemporal heterogeneity of drivers in arid areas based on an improved two-dimensional spatiotemporal dynamic evaluation model. The results show that (1) the spatial distribution of the WRCC in Xinjiang, China, is high in the north, low in the south, high in the west, and low in the east. (2) From 2005 to 2020, the centers of gravity of the WRCC in northern and southern Xinjiang moved to the southeast and west, respectively, and the spatial distribution exhibited slight diffusion. (3) The factors influencing the WRCC exhibit more obvious spatial and temporal heterogeneity. The domestic waste disposal rate and ecological water use rate were the main factors influencing the WRCC in the early stage, while the GDP per capita gradually played a dominant role in the later stage. (4) In the next 30 years, the WRCC in Xinjiang will increase. The results provide a theoretical reference for the sustainable development of water resources in arid areas., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: Chromosome 3 loss is an independent risk factor for uveal melanoma (UM), but its exact molecular mechanisms remain unclear. This study was designed to investigate the relationship between chromosome 3 loss and molecular alterations at multiple levels to construct a prognostic model., Methods: Forty-four UM cases with chromosome 3 loss (chr3 del group) and 36 UM cases without copy number variation on chromosome 3 (chr3 wt group) were collected from the Cancer Genome Atlas (TCGA). The TCGA dataset was subjected to a univariate Cox regression analysis to identify different expressed genes, and a subsequent random forest algorithm analysis revealed significant changes in different expressed genes, which were used to develop key biomarkers for UM. Following that, the immune cell infiltration analysis and drug sensitivity analyses were carried out. The UM cell line was then utilized to investigate the potential functions of the key biomarker via cell apoptosis, proliferation, cycle assays, WB, and RT-qPCR., Results: By analyzing the 80 cases data in TCGA, the authors unveiled molecular changes relevant to loss of chromosome 3 in UM as well as their poor survival. In addition, machine learning analysis identified three hub genes (GRIN2A, ACAN, and MMP9) as potential therapeutic targets. The differentially enriched pathways between the two groups were mainly about immune-system activity, and hub genes expression was also highly correlated with immune infiltration levels., Conclusion: Chromosome 3 loss has considerable clinical significance for UM, and GRIN2A may be useful in diagnosing, treating, and prognosticating the condition., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

China possesses abundant grassland resources, making it imperative to comprehend the influence of climate change on Chinese grassland ecosystems. Nonetheless, the impact pathways and lag effects of climate factors on various grassland types in this region at multiple temporal scales are still to be investigated in long-term sequences. This study investigated the dynamics of grassland FVC (fractional vegetation cover), temperature, precipitation, and drought from 1982 to 2021 using trend analysis, multiple linear regression, path analysis, and correlation analysis and explored the dominant, direct, indirect, and time-lag effects of climate factors on different grassland types at multiple time scales. Precipitation-grassland correlation pathways dominated the annual-scale grassland FVC. The correlation path of temperature to grassland FVC and the direct path of temperature dominated spring grassland FVC. The correlation path of drought to grassland FVC and the direct path of drought dominated summer grassland FVC. The correlation path of temperature to grassland FVC and the direct path of temperature dominated autumn and winter grassland FVC. The effects of temperature and precipitation on alpine and subalpine meadows, desert grasslands, and alpine and subalpine plains grasslands had a 1-month lag. The response to drought exhibited a 1-month lag in desert grasslands, a 2-month lag in alpine and subalpine meadows, plains grasslands, meadows, and alpine and subalpine plains grasslands, and a 3-month lag in sloped grasslands. This study seeks to provide a scientific reference to reveal the impact of climate change on grasslands and to protect grassland ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The leaf chlorophyll content (LCC) of vegetation is closely related to photosynthetic efficiency and biological activity. Jujube ( Ziziphus jujuba Mill.) is a traditional economic forest tree species. Non-destructive monitoring of LCC of jujube is of great significance for guiding agroforestry production and promoting ecological environment protection in arid and semi-arid lands. Hyperspectral data is an important data source for LCC detection. However, hyperspectral data consists of a multitude of bands and contains extensive information. As a result, certain bands may exhibit high correlation, leading to redundant spectral information. This redundancy can distort LCC prediction results and reduce accuracy. Therefore, it is crucial to select appropriate preprocessing methods and employ effective data mining techniques when analyzing hyperspectral data. This study aims to evaluate the performance of hyperspectral data for estimating LCC of jujube trees by integrating different derivative processing techniques with different dimensionality reduction algorithms. Hyperspectral reflectance data were obtained through simulations using an invertible forest reflectance model (INFORM) and measurements from jujube tree canopies. The least absolute shrinkage and selection operator (LASSO) and elastic net (EN) were employed to identify the important bands in the original spectra (OS), first derivative spectra (FD), and second derivative spectra (SD). Support vector regression (SVR) was used to establish the estimation model. The results show that compared with full-spectrum modeling, LASSO and EN algorithms are effective methods for preventing overfitting in LCC machine learning estimation models for different spectral derivatives. The LASSO/EN-based estimation models constructed using FD and SD exhibited superior R 2 compared to the OS. The important band of SD can best reveal the relevant information of jujube LCC, and SD-EN-SVR is the most ideal model in both the simulated dataset (R 2  = 0.99, RMSE=0.61) and measured dataset (R 2  = 0.89, RMSE=0.91). Our results provided a reference for rapid and non-destructive estimation of the LCC of agroforestry vegetation using canopy hyperspectral data., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Tuerxun, Zheng, Wang, Wang and Liu.)

Purpose: Atherosclerosis (AS) is a primary cause of cardiovascular diseases. This study investigated the mechanism of methyltransferase-like 3 (METTL3) in AS plaques via modulating the phenotypic transformation of vascular smooth muscle cells (VSMCs)., Methods: AS mouse models and MOVAS cell models were established through high-fat diet and the treatment of ox-LDL, respectively. METTL3 expression in AS models was detected via RT-qPCR and Western blot. The AS plaques, lipid deposition, and collagen fibers were examined via histological staining. The levels of Ly-6c, α-SMA, and OPN were examined via Western blot. The blood lipid indexes in mouse aortic tissues were determined using kits. The proliferation and migration of MOVAS cells were detected via CCK-8 and Transwell assays. The m 6 A modification level of mRNA was quantified. The binding relationship between pri-miR-375 and DGCR8, and the enrichment of m 6 A on pri-miR-375 were detected via RIP. The binding relationship between miR-375-3p and 3-phosphoinositide-dependent protein kinase-1 (PDK1) was verified via dual-luciferase assay. Joint experiments were designed to investigate the role of miR-375-3P/PDK1 in the phenotypic transformation of VSMCs., Results: METTL3 was highly expressed in AS. Silencing METTL3 alleviated AS progression and stabilized AS plaques in mice, and limited the phenotypic transformation of VSMCs induced by ox-LDL. Silencing METTL3 inhibited m 6 A level and decreased the binding of DGCR8 to pri-miR-375 and further limited miR-375-3p expression. miR-375-3p targeted PDK1 transcription. miR-375-3p upregulation or PDK1 downregulation facilitated the phenotypic transformation of VSMCs., Conclusion: METTL3-mediated m 6 A modification promoted VSMC phenotype transformation and made AS plaques more vulnerable via the miR-375-3p/PDK1 axis., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Han, Guan, Zheng, Liu, Ju, Liu, Li, Mao and Li.)

Purpose: Pancreatic cancer is the worst prognosis among all human cancers, and novel effective treatments are urgently needed. Signal transducer and activator of transcription 3 (STAT3) has been demonstrated as a promising target for pancreatic cancer. Meanwhile, selectively targeted STAT3 with small molecule remains been challenging., Experimental Design: To specifically identify STAT3 inhibitors, more than 1.3 million compounds were screened by structure-based virtual screening and confirmed with the direct binding assay. The amino acid residues that WB436B bound to were verified by induced-fit molecular docking simulation, RosettaLigand computations, and site-directed mutagenesis. On-target effects of WB436B were examined by microscale thermophoresis, surface plasmon resonance, in vitro kinase assay, RNA sequencing, and selective cell growth inhibition assessment. In vivo studies were performed in four animal models to evaluate effects of WB436B on tumor growth and metastasis. Kaplan-Meier analyses were used to assess survival., Results: WB436B selectively bound to STAT3 over other STAT families protein, and in vitro antitumor activities were improved by 10 to 1,000 fold than the representative STAT3 inhibitors. WB436B selectively inhibits STAT3-Tyr705 phosphorylation, STAT3 target gene expression, and the viability of STAT3-dependent pancreatic cancer cells. WB436B significantly suppresses tumor growth and metastasis in vivo and prolongs survival of tumor-bearing mice. Mechanistic studies showed that WB436B have unique binding sites located in STAT3 Src homology 2 domain., Conclusions: Our work presents the first-in-class selective STAT3 inhibitor WB436B as a potential therapeutic candidate for the treatment of pancreatic cancer., (©2022 American Association for Cancer Research.)

Under global warming, the gradual pattern of spring phenology along elevation gradients (EG) has significantly changed. However, current knowledge on the phenomenon of a more uniform spring phenology is mainly focused on the effect of temperature and neglected precipitation. This study aimed to determine whether a more uniform spring phenology occurs along EG in the Qinba Mountains (QB) and explore the effect of precipitation on this pattern. We used Savitzky-Golay (S-G) filtering to extract the start of season (SOS) of the forest from the MODIS Enhanced Vegetation Index (EVI) during 2001-2018 and determined the main drivers of the SOS patterns along EG by partial correlation analyses. The SOS showed a more uniform trend along EG in the QB with a rate of 0.26 ± 0.01 days 100 m -1 per decade during 2001-2018, but there were differences around 2011. A delayed SOS at low elevations was possibly due to the reduced spring precipitation (SP) and spring temperature (ST) between 2001 and 2011. Additionally, an advanced SOS at high elevations may have been caused by the increased SP and reduced winter temperature (WT). These divergent trends contributed to a significant uniform trend of SOS with a rate of 0.85 ± 0.02 days 100 m -1 per decade. Since 2011, significantly higher SP (especially at low elevations) and rising ST advanced the SOS, and the SOS at lower altitudes was more advanced than at higher altitudes, resulting in greater SOS differences along EG (0.54 ± 0.02 days 100 m -1 per decade). The SP determined the direction of the uniform trend in SOS by controlling the SOS patterns at low elevations. A more uniform SOS may have important effects on local ecosystem stability. Our findings could provide a theoretical basis for establishing ecological restoration measures in areas experiencing similar trends., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Guan, Han, Tian, Lu, Yu and Zheng.)

Background: Angiotensin-converting enzyme 2 (ACE2) is implicated as a host cell receptor that causes infection in the pathogenesis of coronavirus disease 2019 (COVID-19), and its genetic polymorphisms in the ACE2 gene may promote cardiovascular disease and systemic inflammatory injury in COVID-19 patients. Hence, the genetic background may potentially explain the broad interindividual variation in disease susceptibility and/or severity. Methods: Genetic susceptibility to COVID-19 was analyzed by examining single-nucleotide polymorphisms (SNPs) of ACE2 in 246 patients with COVID-19 and 210 normal controls using the TaqMan genotyping assay. Results: We demonstrated that the ACE2 SNPs rs4646142, rs6632677, and rs2074192 were associated with COVID-19 (for all, p  <  0.05), and the differences in the ACE2 SNPs rs4646142 and rs6632677 were correlated with COVID-19-related systemic inflammatory injury and cardiovascular risk. Specifically, rs4646142 was associated with high-sensitivity C-reactive protein (hs-CRP), prealbumin (PAB), apolipoprotein A (APOA), high-density lipoprotein (HDL), and acid glycoprotein (AGP) levels. Rs6632677 was also associated with elevated CRP, acid glycoprotein (AGP), and haptoglobin (HPT). Conclusions: Our results suggest that the ACE2 SNPs rs4646142 and rs6632677 may be common genetic loci and optimal early identification genetic markers for COVID-19 with cardiovascular risk.

Pedicularis longiflora Rudolph and its variant ( P. longiflora var. tubiformis (Klotzsch) Tsoong) are alpine plants and traditional Chinese medicines with important medicinal value, and future climate changes may have an adverse impact on their geographic distribution. The maximum entropy (MAXENT) model has the outstanding ability to predict the potential distribution region of species under climate change. Therefore, given the importance of the parameter settings of feature classes (FCs) and the regularization multiplier (RM) of the MAXENT model and the importance of add indicators to evaluate model performance, we used ENMeval to improve the MAXENT niche model and conducted an in-depth study on the potential distributions of these two alpine medicinal plants. We adjusted the parameters of FC and RM in the MAXENT model, evaluated the adjusted MAXENT model using six indicators, determined the most important ecogeographical factors (EGFs) that affect the potential distributions of these plants, and compared their current potential distributions between the adjusted model and the default model. The adjusted model performed better; thus, we used the improved MAXENT model to predict their future potential distributions. The model predicted that P. longiflora Rudolph and its variant ( P. longiflora var. tubiformis (Klotzsch) Tsoong) would move northward and showed a decrease in extent under future climate scenarios. This result is important to predict their potential distribution regions under changing climate scenarios to develop effective long-term resource conservation and management plans for these species., Competing Interests: The authors declare that they have no competing interests., (© 2022 Bao et al.)

Background: Pancreatic ductal adenocarcinoma (PDAC) is dominated by an immunosuppressive microenvironment, which makes immune checkpoint blockade (ICB) often non-responsive. Understanding the mechanisms by which PDAC forms an immunosuppressive microenvironment is important for the development of new effective immunotherapy strategies. Methods: This study comprehensively evaluated the cell-cell communications between malignant cells and immune cells by integrative analyses of single-cell RNA sequencing data and bulk RNA sequencing data of PDAC. A Malignant-Immune cell crosstalk (MIT) score was constructed to predict survival and therapy response in PDAC patients. Immunological characteristics, enriched pathways, and mutations were evaluated in high- and low MIT groups. Results: We found that PDAC had high level of immune cell infiltrations, mainly were tumor-promoting immune cells. Frequent communication between malignant cells and tumor-promoting immune cells were observed. 15 ligand-receptor pairs between malignant cells and tumor-promoting immune cells were identified. We selected genes highly expressed on malignant cells to construct a Malignant-Immune Crosstalk (MIT) score. MIT score was positively correlated with tumor-promoting immune infiltrations. PDAC patients with high MIT score usually had a worse response to immune checkpoint blockade (ICB) immunotherapy. Conclusion: The ligand-receptor pairs identified in this study may provide potential targets for the development of new immunotherapy strategy. MIT score was established to measure tumor-promoting immunocyte infiltration. It can serve as a prognostic indicator for long-term survival of PDAC, and a predictor to ICB immunotherapy response., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Luo, Ren, Chen, Bao, Zheng and Zuo.)

Desert locusts are notorious for their widespread distribution and strong destructive power. Their influence extends from the vast arid and semiarid regions of western Africa to northwestern India. Large-scale locust outbreaks can have devastating consequences for food security, and their social impact may be long-lasting. Climate change has increased the uncertainty of desert locust outbreaks, and predicting suitable habitats for this species under climate change scenarios will help humans deal with the potential threat of locust outbreaks. By comprehensively considering climate, soil, and terrain variables, the maximum entropy (MaxEnt) model was used to predict the potential habitats of solitary desert locusts in the 2050s and 2070s under the four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. The modeling results show that the average area under the curve (AUC) and true skill statistic (TSS) reached 0.908 ± 0.002 and 0.701, respectively, indicating that the MaxEnt model performed extremely well and provided outstanding prediction results. The prediction results indicate that climate change will have an impact on the distribution of the potential habitat of solitary desert locusts. With the increase in radiative forcing overtime, the suitable areas for desert locusts will continue to contract, especially in the 2070s under the SSP585 scenario, and the moderately and highly suitable areas will decrease by 0.88 × 10 6 km 2 and 1.55 × 10 6 km 2 , respectively. Although the potentially suitable area for desert locusts is contracting, the future threat posed by the desert locust to agricultural production and food security cannot be underestimated, given the combination of maintained breeding areas, frequent extreme weather events, pressure from population growth, and volatile sociopolitical environments. In conclusion, methods such as monitoring and early warning, financial support, regional cooperation, and scientific prevention and control of desert locust plagues should be further implemented., Competing Interests: The authors declare that they have no competing interests., (© 2021 Guan et al.)

A huge amount of evidence indicates that sirtuin 7 (SIRT7), a key mediator of many cellular activities, plays a crucial role in the pathogenesis of various diseases. However, little is known about the role of SIRT7 in atherosclerosis. This study investigated the potential role of SIRT7 in regulating the proliferation and migration of human vascular smooth muscle cells (HAVSMCs) and its possible molecular mechanism. In this study, human vascular smooth muscle cells (HAVSMCs) were induced by oxidized low-density lipoprotein (ox-LDL) to establish atherosclerosis (AS) cell model. Immunofluorescence staining and Western blot were used to detect the level of α -SMA expression, which was a marker protein in AS. In addition, RT-qPCR and Western blot assay were applied for exploring the mRNA and protein expression levels of SIRT7, Wnt, β -catenin, and cyclin D1 after knockdown or overexpression of SIRT7. And, furthermore, Cell Counting Kit-8 assay, flow cytometry, and wound-healing assay were used to assess HAVSMCs proliferation, cell cycle, and migration. Dickkopf-1 (DKK-1), a secretory glycoprotein that can block Wnt/ β -catenin pathway, was used in SIRT7 overexpression HAVSMCs; subsequently cells proliferation and migration were assessed by Cell Counting Kit-8 assay, flow cytometry analysis, and wound-healing assay. We found that knockdown of SIRT7 significantly promoted cell proliferation and migration, decreased the percentages of cells in the G1 and G2 phases, and increased those in the S phase and downregulated the protein expression levels of Wnt, β -catenin, and cyclin D1, while overexpression of SIRT7 had reverse results. After treatment with Wnt/beta-catenin pathway inhibitor DKK-1 in SIRT7 overexpression HAVSMCs, cell proliferation and migration were increased, respectively. In conclusion, SIRT7 inhibited HAVSMCs proliferation and migration via enhancing Wnt/ β -catenin activation, which provided a novel therapeutic strategy for antiatherosclerosis.

Murine double minute 2 (MDM2) is a crucial negative regulator of p53 function through several mechanisms. There are many studies performed to assess the association between MDM2 rs2279744 polymorphism and hepatocellular carcinoma risk, but the impact of MDM2 rs2279744 polymorphism on hepatocellular carcinoma in East Asians is unclear owing to the inconsistent findings from previous studies. We conducted a comprehensive meta-analysis of epidemiological studies to shed some light on these contradicting results. We used pooled odds ratio (OR) with its 95 % confidence intervals (95 % CI) to assess the association. Overall, seven studies with a total of 4,993 subjects were finally included. The meta-analysis suggested that MDM2 rs2279744 polymorphism was significantly associated with increased risk of hepatocellular carcinoma in East Asians (G versus T: OR = 1.27, 95 % CI 1.06-1.52, P = 0.01; GG versus TT: OR = 1.59, 95 % CI 1.11-2.27, P = 0.01; GG/GT versus TT: OR = 1.41, 95 % CI 1.07-1.87, P = 0.02; GG versus TT/GT: OR = 1.32, 95 % CI 1.08-1.62, P = 0.008). Sensitivity analysis by excluding low-quality study still suggested that the association above was still significant. Thus, the findings from the meta-analysis support that MDM2 rs2279744 polymorphism is significantly associated with increased risk of hepatocellular carcinoma in East Asians.

Objective: To clone and express the immunodominant domain gene of the chlamydial protease-like activity factor (CPAF) from Chlamydophila pneumoniae. The value of the recombinant protein was evaluated for diagnosing early infection., Methods: According to bioinformatics analyses and references, we chose the immunodominant region epitope of chlamydial protease-like activity factor (CPAF) from Chlamydophila pneumoniae, then amplified the genes of the epitope by PCR, and then ligated the genes into a pGEX6p-2 vector. We purified the expressed recombinant protein with glutathione S-transferase (GST) agarose gel FF, then identified it by SDS-PAGE. By immuning New Zealand rabbits evaluated the immunogenicity of the recombinant protein, and analyzed its antigenicity with Western blot. The specific IgM antibodies in 300 clinical sera samples and C. pneumoniae reference sera, the antigen of C. pneumoniae in 120 sputum and throat swabs were detected with the developed indirect ELISA. At last, we investigated the cross-reactivity against Chlamydia trachomatis with the developed ELISA method to detect anti-C. trachomatis positive antisera and secretions in genitourinary tract., Results: We attained successfully a 51.3kDa recombinant protein. Western blot assay proved the recombinant protein could only specifically react with human anti-C. pneumoniae antisera. The titer of the specific IgM antibodies in the immuned New Zealand rabbits was above 1:8000. The developed ELISA detected anti-C. pneumoniae IgM positive and negative reference sera, the sensitivity and specificity were both 100% (40/40). The concordance rate between the indirect ELISA and the MIF to 300 clinical sera samples was 98.3%. The concordance rate of antigen detection between the new ELISA and the PCR reagent to 120 sputum and throat swabs was 88.3%. When detecting anti-C.trachomatis positive antisera and secretions in genitourinary tract with the developed ELISA, we didn't found any cross reaction against C. trachomatis., Conclusion: The prepared recombinant protein of the CPAF immunodominant region epitope gene from C. pneumoniae shows excellent antigenicity and can highly benefit on developing new indirect ELISA as methods to detect IgM antibodies and antigen of C. pneumoniae for diagnosing early infection.