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To evaluate the risk of acquiring syphilis from a donated kidney, we evaluated kidney transplantation pairs from West China Hospital, Sichuan, China, during 2007–2022. Donor-derived syphilis was rare. Risk may be higher if donors have active syphilis and may be reduced if recipients receive ceftriaxone.

During continuous spraying operations, the liquid in the pesticide tank gradually decreases, and the flight speed changes as the route is altered. To maintain stable flight, the rotor speed of a multi-rotor unmanned aerial spraying system (UASS) constantly adjusts. To explore the variation law of rotor speed in a multi-rotor UASS under objective operation attributes, based on indoor and outdoor experimental data, this paper constructs a mathematical model of the relationship between rotor speed and thrust. The model fitting parameter (R2) is equal to 0.9996. Through the neural network, the rotor speed prediction model is constructed with the real-time flight speed and the payload of the pesticide tank as the input. The overall correlation coefficient (R2) of the model training set is 0.728, and the correlation coefficients (R2) of the verification set and the test set are 0.719 and 0.726, respectively. Finally, the rotor speed is matched with the load of the whole UASS through thrust conversion. It is known that the single-axis load capacity under full-load state only reaches about 50% of its maximum load capacity, and the load increase is more than 75.83% compared with the no-load state. This study provides a theoretical and methodological reference for accurately predicting the performance characterization results of a power system during actual operation and investigating the dynamic feedback mechanism of a UASS during continuous operation.

In the context of global climate change and the increase in drought frequency, monitoring and accurately assessing the impact of hydrological process limitations on vegetation growth is of paramount importance. Our study undertakes a comprehensive evaluation of the efficacy of satellite remote sensing vegetation indices—Normalized Difference Vegetation Index (MODIS NDVI product), kernel NDVI (kNDVI), and Solar-Induced chlorophyll Fluorescence (GOSIF product) in this regard. Initially, we applied the LightGBM-Shapley additive explanation framework to assess the influencing factors on the three vegetation indices. We found that Vapor Pressure Deficit (VPD) is the primary factor affecting vegetation in southern China (18°–30°N). Subsequently, using Gross Primary Productivity (GPP) estimates from flux tower sites as a performance benchmark, we evaluated the ability of these vegetation indices to accurately reflect vegetation GPP changes during drought conditions. Our findings indicate that SIF serves as the most effective surrogate for GPP, capturing the variability of GPP during drought periods with minimal time lag. Additionally, our study reveals that the performance of kNDVI significantly varies depending on the estimation of different kernel parameters. The application of a time-heuristic estimation method could potentially enhance kNDVI’s capacity to capture GPP dynamics more effectively during drought periods. Overall, this study demonstrates that satellite-based SIF data are more adept at monitoring vegetation responses to water stress and accurately tracking GPP anomalies caused by droughts. These findings not only provide critical insights into the selection and optimization of remote sensing vegetation product but also offer a valuable framework for future research aimed at improving our monitoring and understanding of vegetation growth status under climatic changes.

The tidal wetlands in Jiangsu Province (JS) play a crucial role as a major blue carbon sink in the eastern coastal area of China. These wetlands also contribute significantly function to biodiversity and the provision of ecosystem services. However, due to the escalating impact of anthropogenic activities and climatic changes, the ecological scope, structure, and function of tidal wetlands have changed drastically. This study aims to depict the spatiotemporal dynamics of these wetlands and explore the driving forces behind these changes. Based on the Google Earth Engine (GEE) platform, we conducted a comprehensive analysis of all the available Landsat imagery (5096 images, 30-m spatial resolution) using the Continuous Change Detection and Classification (CCDC) algorithm. The outputs consist of annual land cover maps of JS coastal zone, from 1990 to 2020. Results indicate that the generated coastal maps generally exhibit an exceptionally high average accuracy (92.62%) and there were 2666.54 km2 of tidal wetlands (Spartina alterniflora: 240.86 km2, Suaeda salsa: 37.31 km2, Phragmites australis: 150.63 km2, intertidal flat: 2158.18 km2, supratidal barren flat: 79.53 km2) in 2020, amounting to a 23.43% decrease of the initial year 1990. The tidal wetlands landscape had a staged decline during 1990–2020, and the hydrological vegetation habitat was the area with the greatest variability. Over the past three decades, the losses of tidal wetlands amounted to 1,466.22 km2, partially offset by gains of 650.05 km2. The two most substantial sources of losses were intertidal flat and Suaeda salsa with the most significant ratio of loss to gain (4.80, 10.31, respectively). Generally, we categorized tidal wetlands degradation into three transformation processes: human activities, species invasion, and natural succession. Human activities, particularly the conversion of intertidal flat into aquafarm, dominated the entire degradation process. Meanwhile, in the main driving analysis, we discovered that 60% of these losses and gains were directly tied to human activities. The indirect driving process includes natural coastal movements, climate change, unobservable human activities, and their aggregate effects, which gradually assist tidal wetlands ecosystems to re-establish and recover. The annual coastal wetland maps and detailed information on the evolutionary patterns and the corresponding drivers are valuable for identifying blue carbon distribution and enhancing the ecological services of the coastal zone.

The patterns of interaction between terrestrial vegetation and the atmosphere are complex, and some are poorly understood. Linear or general linear methods have been widely used to explore the dynamics of vegetation and climate changes. However, linear thinking may hinder our understanding of complex nonlinear systems, and it is difficult to extract the underlying causality of linear correlations directly from observational data. In this study, we aimed to quantify the interactions between vegetation and climate, using nonlinear dynamical methods based on state-space reconstruction and datasets from Chinese meteorological stations and remote sensing data during 1982–2015 in Northeast China (NEC). Specifically, we identified the causal links between meteorological factors (temperature and precipitation) and the vegetation index (NDVI) by reconstructing the state space from historical records. During the study period, vegetation exhibited a strong bidirectional causal relationship with both temperature and precipitation across Northeast China. The NDVI can be accurately reconstructed from the state information of meteorological factors (temperature and precipitation). The results of the multivariate EDM scenarios reveal varying sensitivities of different vegetation types to meteorological factors. Overall, slight temperature changes have a stronger impact on vegetation compared to precipitation. Mixed forest and broad-leaved forest demonstrate lower sensitivity to precipitation changes compared to other vegetation types. This study on the causal relationship between vegetation and meteorological factors in Northeast China contributes to a deeper understanding of climate change and vegetation feedback in middle and high latitudes. Our work demonstrates that the EDM-based convergent cross-mapping nonlinear causal analysis method is valuable for comprehending the interactions within complex systems in earth science.

The LAI (leaf area index) is an important parameter describing the canopy structure of citrus trees and characterizing plant photosynthesis, as well as providing an important basis for selecting parameters for orchard plant protection operations. By fusing LiDAR data with multispectral data, it can make up for the lack of rich spatial features of multispectral data, thus obtaining higher LAI inversion accuracy. This study proposed a multiscale LAI inversion method for citrus orchard based on the fusion of point cloud data and multispectral data. By comparing various machine learning algorithms, the mapping relationship between the characteristic parameters in multispectral data and point cloud data and citrus LAI was established, and we established the inversion model based on this, by removing redundant features through redundancy analysis. The experiment results showed that the BP neural network performs the best at both the community scale and the individual scale. After removing redundant features, the R2, RMSE, and MAE of the BP neural network at the community scale and individual scale were 0.896, 0.112, 0.086, and 0.794, 0.408, 0.328, respectively. By adding the three-dimensional gap fraction feature to the two-dimensional vegetation index features, the R2 at community scale and individual scale increased by 4.43% and 7.29%, respectively. The conclusion of this study suggests that the fusion of point cloud and multispectral data exhibits superior accuracy in multiscale citrus LAI inversion compared to relying solely on a single data source. This study proposes a fast and efficient multiscale LAI inversion method for citrus, which provides a new idea for the orchard precise management and the precision of plant protection operation.

BackgroundCurrent guidelines do not recommend routine antiviral prophylaxis to prevent hepatitis B virus (HBV) reactivation in non-liver solid organ transplant (SOT) recipients with resolved HBV infection, even in anti-hepatitis B surface antigen (anti-HBs)-negative recipients and those receiving intense immunosuppression. This systematic review and meta-analysis aimed to determine the incidence, risk factors, and clinical outcomes of HBV reactivation in non-liver SOT recipients.Methods and findingsThree databases (PubMed, Embase, and Cochrane Library) were systematically searched up to December 31, 2022. Clinical studies reporting HBV reactivation in non-liver SOT recipients were included. Case reports, case series, and cohort studies with a sample size of less than 10 patients were excluded. Random-effects analysis was used for all meta-analyses. We included 2,913 non-liver SOT recipients with resolved HBV infection from 16 retrospective cohort studies in the analysis. The overall HBV reactivation rate was 2.5% (76/2,913; 95% confidence interval [95% CI 1.6%, 3.6%]; I2 = 55.0%). Higher rates of reactivation were observed in recipients with negative anti-HBs (34/421; 7.8%; 95% CI [5.2%, 10.9%]; I2 = 36.0%) by pooling 6 studies, experiencing acute rejection (13/266; 5.8%; 95% CI [2.3%, 14.5%]; I2 = 63.2%) by pooling 3 studies, receiving ABO blood type-incompatible transplantation (8/111; 7.0%; 95% CI [2.9%, 12.7%]; I2 = 0%) by pooling 3 studies, receiving rituximab (10/133; 7.3%; 95% CI [3.4%, 12.6%]; I2 = 0%) by pooling 3 studies, and receiving anti-thymocyte immunoglobulin (ATG, 25/504; 4.9%; 95% CI [2.5%, 8.1%]; I2 = 49.0%) by pooling 4 studies. Among recipients with post-transplant HBV reactivation, 11.0% (7/52; 95% CI [4.0%, 20.8%]; I2 = 0.3%) developed HBV-related hepatic failure, and 11.0% (7/52; 95% CI [4.0%, 20.8%]; I2 = 0.3%) had HBV-related death. Negative anti-HBs (crude odds ratio [OR] 5.05; 95% CI [2.83, 9.00]; p < 0.001; I2 = 0%), ABO blood type-incompatible transplantation (crude OR 2.62; 95% CI [1.05, 6.04]; p = 0.040; I2 = 0%), history of acute rejection (crude OR 2.37; 95% CI [1.13, 4.97]; p = 0.022; I2 = 0%), ATG use (crude OR 3.19; 95% CI [1.48, 6.87]; p = 0.003; I2 = 0%), and rituximab use (crude OR 3.16; 95% CI [1.24, 8.06]; p = 0.016; I2 = 0%) increased the risk of reactivation. Adjusted analyses reported similar results. Limitations include moderate heterogeneity in the meta-analyses and that most studies were conducted in kidney transplant recipients.ConclusionsNon-liver SOT recipients with resolved HBV infection have a high risk of HBV-related hepatic failure and HBV-related death if HBV reactivation occurs. Potential risk factors for HBV reactivation include rituximab use, anti-thymocyte immunoglobulin use, anti-HBs negative status, acute rejection history, and ABO blood type-incompatible transplantation. Further research on monitoring and routine antiviral prophylaxis of non-liver SOT recipients at higher risk of HBV reactivation is required.

Achieving equitable and harmonized socio-economic development is a vital gauge of national progress, particularly in geographically extensive nations such as China. This study, employing nighttime lights as a socio-economic development indicator and remote sensing vegetation indices, investigates spatial variations in wealth distribution across China’s eastern and western regions, delineated by the Hu Huanyong Line. It uncovers the balance between economic growth and green space preservation and discrepancies in development and green space allocation. A thorough county-level analysis using this nighttime light (NTL) and vegetation index exposes the dynamic shifts in socio-economic focal points. The Gini coefficient, assessing inequality and spatial autocorrelation within the index ratio, enriches our regional development understanding. The findings depict a heterogeneous yet rapid economic expansion, primarily within a 30 km coastal buffer zone. Despite a decrease in Gini coefficients in both eastern and western regions, the potential for inland development escalates as coastal illumination approaches saturation. This study unveils enduring, yet lessening, economic disparities between eastern and western China, underscoring the necessity for green preservation in eastern development plans. Moreover, inland regions emerge as potential areas for accelerated development. This study offers crucial insights for formulating balanced, sustainable regional development strategies in China.

Global climate change and human activities have increased the frequency and severity of droughts. This has become a critical factor affecting vegetation growth and diversity, resulting in detrimental effects on agricultural production, ecosystem stability, and socioeconomic development. Therefore, assessing the response of vegetation dynamics to drought can offer valuable insights into the physiological mechanisms of terrestrial ecosystems. Here, we applied long-term datasets (2001–2020) of solar-induced chlorophyll fluorescence (SIF) and normalized difference vegetation index (NDVI) to unveil vegetation dynamics and their relationship to meteorological drought (SPEI) across different vegetation types in the Yangtze River Basin (YRB). Linear correlation analysis was conducted to determine the maximum association of SPEI with SIF and NDVI; we then compared their responses to meteorological drought. The improved partial wavelet coherence (PWC) method was utilized to quantitatively assess the influences of large-scale climate patterns and solar activity on the relationship between vegetation and meteorological drought. The results show that: (1) Droughts were frequent in the YRB from 2001 to 2020, and the summer’s dry and wet conditions exerted a notable influence on the annual climate. (2) SPEI exhibits a more significant correlation with SIF than with NDVI. (3) NDVI has a longer response time (3–6 months) to meteorological drought than SIF (1–4 months). Both SIF and NDVI respond faster in cropland and grassland but slower in evergreen broadleaf and mixed forests. (4) There exists a significant positive correlation between vegetation and meteorological drought during the 4–16 months period. The teleconnection factors of Pacific Decadal Oscillation (PDO), El Niño Southern Oscillation (ENSO), and sunspots are crucial drivers that affect the interaction between meteorological drought and vegetation, with sunspots having the most significant impact. Generally, our study indicates that drought is an essential environmental stressor that disrupts vegetation growth over the YRB. Additionally, SIF demonstrates great potential in monitoring vegetation response to drought. These findings will be meaningful for drought prevention and ecosystem conservation planning in the YRB.

Background: Bladder urothelial carcinoma (BLCA) is the most common type of bladder cancer. In this study, the correlation between the metabolic status and the outcome of patients with BLCA was evaluated using data from the Cancer Genome Atlas and Gene Expression Omnibus datasets.Methods: The clinical and transcriptomic data of patients with BLCA were downloaded from the Cancer Genome Atlas and cBioPortal datasets, and energy metabolism-related gene sets were obtained from the Molecular Signature Database. A consensus clustering algorithm was then conducted to classify the patients into two clusters. Tumor prognosis, clinicopathological features, mutations, functional analysis, ferroptosis status analysis, immune infiltration, immune checkpoint-related gene expression level, chemotherapy resistance, and tumor stem cells were analyzed between clusters. An energy metabolism-related signature was further developed and verified using data from cBioPortal datasets.Results: Two clusters (C1 and C2) were identified using a consensus clustering algorithm based on an energy metabolism-related signature. The patients with subtype C1 had more metabolism-related pathways, different ferroptosis status, higher cancer stem cell scores, higher chemotherapy resistance, and better prognosis. Subtype C2 was characterized by an increased number of advanced BLCA cases and immune-related pathways. Higher immune and stromal scores were also observed for the C2 subtype. A signature containing 16 energy metabolism-related genes was then identified, which can accurately predict the prognosis of patients with BLCA.Conclusion: We found that the energy metabolism-associated subtypes of BLCA are closely related to the immune microenvironment, immune checkpoint-related gene expression, ferroptosis status, CSCs, chemotherapy resistance, prognosis, and progression of BLCA patients. The established energy metabolism-related gene signature was able to predict survival in patients with BLCA.

IntroductionABO blood group antigens within grafts are continuously exposed to anti-A/B antibodies in the serum of recipients after ABO-incompatible (ABOi) kidney transplantation and are instrumental in antibody-mediated rejection. Some individuals secrete soluble blood group antigens into body fluids. In this study, we investigated the effect of donor and recipient secretor status on the outcomes of ABOi kidney transplantation.MethodsData of a total of 32 patients with ABOi living donor kidney transplantation were retrospectively collected between 2014 and 2020 in West China Hospital. The genotype and phenotype of both donors and recipients were examined and evaluated with post-transplantation anti-A/B titer changes, graft function, and rejection.ResultsOf the 32 recipients and 32 donors, 23 (71.9%) recipients and 27 (84.4%) donors had secretor genotypes, whereas 9 (28.1%) recipients and 5 (15.6%) donors did not. Anti-A/B titers after ABOi kidney transplantation were not significantly influenced by the secretor status of either donors or recipients. The post-transplantation serum creatinine (Scr) levels and estimated glomerular filtration rate (eGFR) was better in weak- or non-secretor recipients at day 30 (Scr P = 0.047, eGFR P = 0.008), day 90 (Scr P = 0.010, eGFR P = 0.005), and month 9 (eGFR P = 0.008), and recipients from secretor donors had a lower incidence of graft rejection in the first year after ABOi transplantation (P = 0.004).ConclusionsA weak secretor status phenotype was found in both genotypes, i.e., individuals who secreted soluble antigens as well as those who did not. The recipient ABH-secretor status may have an influence on early posttransplant renal function, and the donor ABH-secretor status might affect the incidence of graft rejection.

With the continuous and rapid rise of urbanization in China, land use transition research has been carried out extensively. Multiple cropping is the content of land use recessive morphology research, and it is also a common agricultural system in China. Accordingly, further research on multiple cropping index (MCI) can enrich the land use transition research and help to evaluate China’s food security. In order to examine the spatiotemporal changes and factors influencing the MCI of cultivated land in China, we collected MODIS remote sensing image data and land use classification data and conducted a remote sensing inversion on China’s MCI from 2000, 2005, 2010, and 2015. The spatial distributions and evolution processes of the MCI were explored through spatial mapping, statistical analysis, and processing with the Geographic Information System; moreover, the influencing factors of MCI were explored quantitatively with principal component regression. The results were as follows: (1) at the provincial scale, the average MCI across Guangdong, Guangxi, Hainan, Henan, Anhui, and Jiangsu was high; meanwhile, the average MCI across Heilongjiang, Inner Mongolia, Ningxia, and Qinghai was low. Between 2000 and 2015, the number of provinces with low MCI increased gradually, and the average MCI decreased greatly in the southern provinces. (2) At the county scale, the Taihang Mountains, Qinling Mountains, and Hengduan Mountains formed the boundary of China’s single cropping and multiple cropping indices. Dynamic changes in China’s MCI were obvious, and the number of counties with MCI change values lower than 0 increased gradually. Last, (3) natural conditions, nonagricultural process, cultivated land quality, and agricultural intensification demonstrated different degrees of impact on the MCI; in particular, the influence of nonagricultural industries, pesticides, and agricultural plastic film on the MCI proved especially important. Future research should strengthen the existing work on related transformations in farmers’ livelihoods, especially in terms of the return of rural labor force, the body of agricultural production, agricultural ecological issues, and the balance between increased crop production and reduced environmental pollution. In addition, agricultural policy design should pay more attention to cultivated land quality, the farmer who cultivates the land, and the multiple cropping potential of cultivated land.

Objective: To investigate the desirable healing time of micro-screws by histomorphologic and histomorphometric evaluations of osseointegration after immediate and early loading. Materials and Methods: Fifty-four micro-screws were bilaterally placed in the maxillary premolar regions of nine beagles. Then the micro-screws with various healing time of 0 day (0D group), 2 weeks (2W group), and 4 weeks (4W group) were loaded with an orthodontic force (100 g) for 8 weeks. The direction of the orthodontic force was vertical to the long axis of the micro-screws. Hard tissue sections containing micro-screws were prepared for histomorphologic and histomorphometric evaluations. Results: The survival rate of the micro-screws in this study was 100%. Bone remodeling, close contact bone-implant interface, and endochondral ossification were observed in all osseous specimens. Activated osteoblasts aggregated to the bone-implant interface of the 4W group, and lamellar bone was found in the pen-implant regions. Micro-screws of the 2W group were partially surrounded by collagen fibers; and neonatal lines of bone, woven bone, and osteoclasts were found in the pen-implant regions. Micro-screws of the 0D group were surrounded by more collagen fibers compared with the other two groups. Bone implant contact ratios of the three groups were 43.74% (0D group), 66.26% (2W group), and 73.28% (4W group), respectively and statistical differences were significant (ANOVA, P < .01). Conclusion: All micro-screws in the three groups can provide stable orthodontic anchorage. However, to obtain improved stationary anchorage, a 4-week healing time is recommended before orthodontic loading. [ABSTRACT FROM AUTHOR]

Surface tension measurements were carried out for the solutions of polyoxyethylene (20) sorbitan monolaurate (Tween 20) in 1-butyl-3-methylimidazolium tetrafluoroborate (bmimBF 4) and hexafluorophosphate (bmimPF 6) at various temperatures. Two transition points were found in the surface tension−concentration curves at each temperature. The freeze-fracture transmission electron microscopy revealed that two kinds of particles with different sizes are formed at the concentrations of each transition point. Thus, the surfactant concentrations of the two transition points are regarded as critical aggregation concentrations, CAC 1and CAC 2. From the CAC values and their temperature dependence, we estimated the thermodynamic parameters of the aggregate formation, Δ Gagg0, Δ Hagg0, and Δ Sagg0. The thermodynamic parameters related to CAC 1are almost independent of temperature. On the other hand, as for the aggregate formation at CAC 2, a positiveΔ Sagg0contributes to a negative Δ Gagg0at low temperature, while a negative Δ Hagg0contributes to a negative Δ Gagg0at high temperature. The behavior of the thermodynamic parameters as a function of temperature, combined with the variation of 1H NMR chemical shifts of the bmim +protons as a function of the surfactant concentration, demonstrated that the aggregates formed at CAC 1are nanodroplets of Tween 20 segregated from the solution phase, while those formed at CAC 2are similar to the usual surfactant micelles formed in aqueous solution. [ABSTRACT FROM AUTHOR]