One-to-Nine Single Spectroscopic Intelligent Probe for Risk Assessment of Multiple Metals in Drinking Water.

26% of the world's population lacks access to clean drinking water; clean water and sanitation are major global challenges highlighted by the UN Sustainable Development Goals, indicating water security in public water systems is at stake today. Water monitoring using precise instruments by skilled operators is one of the most promising solutions. Despite decades of research, the professionalism-convenience trade-off when monitoring ubiquitous metal ions remains the major challenge for public water safety. Thus, to overcome these disadvantages, an easy-to-use and highly sensitive visual method is desirable. Herein, an innovative strategy for one-to-nine metal detection is proposed, in which a novel thiourea spectroscopic probe with high 9-metal affinity is synthesized, acting as "one", and is detected based on the 9 metal-thiourea complexes within portable spectrometers in the public water field; this is accomplished by nonspecialized personnel as is also required. During the processing of multimetal analysis, issues arise due to signal overlap and reproducibility problems, leading to constrained sensitivity. In this innovative endeavor, machine learning (ML) algorithms were employed to extract key features from the composite spectral signature, addressing multipeak overlap, and completing the detection within 30-300 s, thus achieving a detection limit of 0.01 mg/L and meeting established conventional water quality standards. This method provides a convenient approach for public drinking water safety testing.

The global burden of cataracts and its attributable risk factors in 204 countries and territories: a systematic analysis of the global burden of disease study.

Introduction: The global distribution and trends in the attributable burden of cataract risk have rarely been systematically explored. To guide the development of targeted and accurate cataract screening and treatment strategies, we analyzed the burden of cataract disease attributable to known risk factors. Method: This study utilized detailed cataract data from the Global Burden of Disease e 2019, and we analyzed disability-adjusted life years (DALYs) e each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. Results: The results revealed that from 1990-2019, the global age-standardized DALYs of e attributable to particulate matter pollution, smoking, high fasting glucose plasma and high BMI showed steady downward trends (1990-2009: EAPC = -0.21 [-0.57 -0.14]); 2000-2009: EAPC = -0.95 [-1.01 -0.89]; 2010-2019: EAPC = -1.41 [-1.8 -1.02]). The age-standardized DALYs and mortality caused by each risk factor were highest in the low-middle sociodemographic index (SDI) region (EAPC = -1.77[(-2.19--1.34)]). The overall disease burden of cataracts is lower in males than in females. When analyzing the EAPCs of cataract disease burden for each risk factor individually, we found that the age-standardized disability-adjusted life years caused by particulate matter pollution and smoking decreased (PMP1990-2009: EAPC = -0.53 [-0.9--0.16]; 2000-2009: EAPC = -1.39 [-1.45--1.32]; 2010-2019: EAPC = -2.27 [-2.75--1.79]; smoking 2000 to 2009: EAPC = -1.51 [-1.6--1.43], 2009 to 2019: EAPC = -1.34 [-1.68--1])), while high fasting plasma glucose and high body mass index increased annually (HFPG1990 to 1999: EAPC = 1.27 [0.89-1.65], 2000 to 2009: EAPC = 1.02 [0.82-1.22], 2010-2019: EAPC = 0.44 [0.19-0.68]; HBMI 1990 to 1999: EAPC = 1.65 [1.37-1.94], 2000 to 2009: EAPC = 1.56 [1.43-1.68], 2010-2019: EAPC = 1.47 [1.18-1.77]). Disscussion: The burden of cataracts caused by ambient particulate matter and smoking is increasing in low, low-middle SDI areas, and specific and effective measures are urgently needed. The results of this study suggest that reducing particulate matter pollution, quitting smoking, controlling blood glucose, and lowering BMI could play important roles in reducing the occurrence of cataracts, especially in older people.

An Improved RAIM Availability Assessment Method Based on the Characteristic Slope.

The availability assessment is an important step for onboard application in Receiver Autonomous Integrity Monitoring (RAIM)s. It is commonly implemented using the protection level (PL)-based method. This paper analyzes the deficiencies of three kinds of PL-based methods: RAIM availability might be optimistically or conservatively assessed using the classic-PL-base method; might be conservatively assessed using the enhanced-PL-based method, and neither be optimistically nor conservatively assessed using the ideal-PL-based method with the cost of large calculation amount on-board. An improved slope-based RAIM availability assessment method is proposed, in which the characteristic slope is designed as the assessment basis, and its threshold that can exactly match the integrity risk requirement is derived. The slope-based method has the same RAIM availability assessment result as the ideal-PL-based method. Moreover, because the slope threshold can be calculated offline and searched online, the on-board calculation burden can be reduced using the slope-based method. Simulation is presented to verify the theoretical analysis of the RAIM availability assessment performances for the three PL-based and the slope-based methods.

Global, regional and national burden of Glaucoma: an update analysis from the Global Burden of Disease Study 2019.

PURPOSE: As the epidemiological and burden trends of glaucoma are changing, it is extremely necessary to re-investigate geographical differences and trends. Here we use data from the 2019 Global burden of Disease, which aims to report the prevalence and disability-adjusted life years of glaucoma injury to assess the latest epidemiological models and trends from 1990 to 2019. METHOD: Annual case numbers, age-standardized rates of prevalence, DALYs, and their estimated annual percentage changes (EAPCs) for glaucoma between 1990 and 2019 were derived from the GBD 2019 study. The relationship between glaucoma disease burden and social demographic index (SDI) was also investigated in this study. RESULTS: In 2019, there were 7.47 million prevalent cases and 0.75 million DALYs cases, which increased by 92.53% and 69.23% compared with 1990 respectively. The global age-standardized rate of prevalence (ASPR) and age-standardized rate of DALYs (ASDR) decreased during 1990-2019 (EAPC = - 0.55 and - 1, respectively). In 2019, the highest ASPR and ASDR of Glaucoma were all observed in Mali, whereas the lowest occurred in Taiwan (Province of China). In terms of gender, males were more likely to suffer from glaucoma than females, especially the elderly. CONCLUSIONS: The global prevalence and DALYs of glaucoma had an absolute increase during the past 30 years. The disease burden caused by glaucoma is closely related to socioeconomic level, age, gender, and other factors, and these findings provide a basis for policymakers from the perspective of social management.

Investigating the temporal and spatial evolution of bank performance and its impact pathways in the context of financial technology development.

Financial technology transforms humans and businesses as globalization and the digital economy accelerate. This affects bank performance. Thus, studying whether financial technology affects bank performance is crucial to enhancing living standards and business development. This article examines the development and interaction between financial technology and bank performance from 2012 to 2021 using standard deviation ellipses, kernel density estimation, Moran's index, and spatial econometric models. The research found that (1) financial technology development improves regional bank performance. In contrast, control variables like economic development, urbanization, tax burden, capital adequacy ratio, net interest margin, and loan-to-deposit ratio also affect bank performance. (2) From 2012 to 2021, Chinese bank performance initially grew, then declined, while financial technology declined slowly and improved rapidly. Financial technology and bank performance development were highest in the eastern coastal regions and lowest in the northwest and northeast. (3) China's financial technology and bank performance had high-high or low-low spatial agglomeration. (4) Financial technology and control variables have a spatial spillover effect on bank performance, so their development in one region can affect neighboring regions. This article provides recommendations for governments and banks based on these findings.

Refining the rheological characteristics of high drug loading ointment via SDS and machine learning.

This paper presents an optimized preparation process for external ointment using the Definitive Screening Design (DSD) method. The ointment is a Traditional Chinese Medicine (TCM) formula developed by Professor WYH, a renowned TCM practitioner in Jiangsu Province, China, known for its proven clinical efficacy. In this study, a stepwise regression model was employed to analyze the relationship between key process factors (such as mixing speed and time) and rheological parameters. Machine learning techniques, including Monte Carlo simulation, decision tree analysis, and Gaussian process, were used for parameter optimization. Through rigorous experimentation and verification, we have successfully identified the optimal preparation process for WYH ointment. The optimized parameters included drug ratio of 24.5%, mixing time of 8 min, mixing speed of 1175 rpm, petroleum dosage of 79 g, liquid paraffin dosage of 6.7 g. The final ointment formulation was prepared using method B. This research not only contributes to the optimization of the WYH ointment preparation process but also provides valuable insights and practical guidance for designing the preparation processes of other TCM ointments. This advanced DSD method enhances the screening approach for identifying the best preparation process, thereby improving the scientific rigor and quality of TCM ointment preparation processes.

A regionally tailored epidemiological forecast and monitoring program to guide a healthcare system in the COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, analytics and predictive models built on regional data provided timely, accurate monitoring of epidemiological behavior, informing critical planning and decision-making for health system leaders. At Atrium Health, a large, integrated healthcare system in the southeastern United States, a team of statisticians and physicians created a comprehensive forecast and monitoring program that leveraged an array of statistical methods. METHODS: The program utilized the following methodological approaches: (i) exploratory graphics, including time plots of epidemiological metrics with smoothers; (ii) infection prevalence forecasting using a Bayesian epidemiological model with time-varying infection rate; (iii) doubling and halving times computed using changepoints in local linear trend; (iv) death monitoring using combination forecasting with an ensemble of models; (v) effective reproduction number estimation with a Bayesian approach; (vi) COVID-19 patients hospital census monitored via time series models; and (vii) quantified forecast performance. RESULTS: A consolidated forecast and monitoring report was produced weekly and proved to be an effective, vital source of information and guidance as the healthcare system navigated the inherent uncertainty of the pandemic. Forecasts provided accurate and precise information that informed critical decisions on resource planning, bed capacity and staffing management, and infection prevention strategies. CONCLUSIONS: In this paper, we have presented the framework used in our epidemiological forecast and monitoring program at Atrium Health, as well as provided recommendations for implementation by other healthcare systems and institutions to facilitate use in future pandemics.

Sparsified federated learning with differential privacy for intrusion detection in VANETs based on Fisher Information Matrix.

With the continuous development of vehicular ad hoc networks (VANET) security, using federated learning (FL) to deploy intrusion detection models in VANET has attracted considerable attention. Compared to conventional centralized learning, FL retains local training private data, thus protecting privacy. However, sensitive information about the training data can still be inferred from the shared model parameters in FL. Differential privacy (DP) is sophisticated technique to mitigate such attacks. A key challenge of implementing DP in FL is that non-selectively adding DP noise can adversely affect model accuracy, while having many perturbed parameters also increases privacy budget consumption and communication costs for detection models. To address this challenge, we propose FFIDS, a FL algorithm integrating model parameter pruning with differential privacy. It employs a parameter pruning technique based on the Fisher Information Matrix to reduce the privacy budget consumption per iteration while ensuring no accuracy loss. Specifically, FFIDS evaluates parameter importance and prunes unimportant parameters to generate compact sub-models, while recording the positions of parameters in each sub-model. This not only reduces model size to lower communication costs, but also maintains accuracy stability. DP noise is then added to the sub-models. By not perturbing unimportant parameters, more budget can be reserved to retain important parameters for more iterations. Finally, the server can promptly recover the sub-models using the parameter position information and complete aggregation. Extensive experiments on two public datasets and two F2MD simulation datasets have validated the utility and superior performance of the FFIDS algorithm.

Comprehensive Assessment of Polysaccharides Extracted from Squash by Subcritical Water under Different Conditions.

The effects of subcritical water microenvironment on the physiochemical properties, antioxidant activity and in vitro digestion of polysaccharides (SWESPs) from squash were investigated. After single-factor experiments, twenty samples were successfully prepared at different extraction temperatures (110, 130, 150, 170 and 190 °C) and extraction times (4, 8, 12 and 16 min). Under a low temperature environment, the whole process was mainly based on the extraction of SWESP. At this time, the color of SWESP was white or light gray and the molecular mass was high. When the temperature was 150 °C, since the extraction and degradation of SWESP reached equilibrium, the maximum extraction rate (18.67%) was reached at 150 °C (12 min). Compared with traditional methods, the yield of squash SWESP extracted by subcritical water was 3-4 times higher and less time consuming. Under high temperature conditions, SWESPs were degraded and their antioxidant capacity and viscosity were reduced. Meanwhile, Maillard and caramelization reactions turned the SWESPs yellow-brown and produced harmful substances. In addition, different SWESPs had different effects on in vitro digestion. In brief, SWESPs prepared under different conditions have different structures and physicochemical properties, allowing the obtainment of the required polysaccharide. Our results show that squash polysaccharides prepared in different subcritical water states had good development potential and application in the food industry.

Chemical Speciation, Leaching Behavior, and Environmental Risk Assessment of Trace Elements in the Bottom Ash from Biomass Power Plant.

Biomass combustion for power generation stands as a pivotal method in energy utilization, offering a promising approach for renewable energy utilization. However, the substantial volume of slag produced by biomass burning plants poses environmental challenges, impeding sustainable energy practices. This article systematically studies the characteristics of ash generated from typical biomass direct combustion power plant ash and analyzes the chemical composition, trace element content characteristics, leaching characteristics, and chemical forms of biomass bottom ash. Furthermore, it assesses the environmental ecology and bioavailability of trace elements in bottom ash using the ecological risk assessment method and RAC method. The results demonstrate that the biomass bottom ash contains plant nutrients, such as K, Ca, Mg, and P, while the content of harmful trace elements is lower than the relevant Chinese standards. In dissolution experiments, the leaching rate of nearly all elements remains exceptionally low, primarily due to the distribution of trace elements within the lattice structure of stable minerals. Trace elements predominantly exist in the residual phase, Cu and Zn primarily found in organic compounds and sulfide bound states, while other elements mostly exist in the form of iron manganese oxide bound states. Ecological risk assessment indicates a significant risk level for Cd, contrasting with the slight risk associated with other elements. RAC results indicated no ecological risk of all of the trace elements. Consequently, the utilization of bottom ash in agricultural and forestry soils is deemed to be viable. These findings serve as a crucial foundation for biomass bottom ash resource utilization and underpin the sustainable utilization of biomass energy.

A Cost-Effective and Labor-Saving Method for Detecting Human Leukocyte Antigen B27 Status via Sequence-Encoded Fluorescence Amplification Assay.

Identification of human leukocyte antigen B27 (HLA-B27) by flow cytometry (FCM) has been widely applied in clinical practice for auxiliary diagnosis of ankylosing spondylitis (AS). However, FCM requires freshly prepared samples and relies on expensive equipment, reagents, and an experienced operator. To provide a cheaper and more convenient method for HLA-B27 detection, we proposed a new method termed sequence-encoded fluorescence amplification assay (SEFA), which specially recognized sequences of HLA-B27 gene (HLA-B∗27) covering current common subtypes in a single closed tube. SEFA could detect as low as 10 pg (equal to 3 copies) genomic DNA per reaction and distinguish HLA-B∗27 from other HLA-B alleles with highly similar sequences. A total of 288 clinical samples were tested by SEFA, including 181 patients with AS and 107 healthy controls. Compared with the detection results from FCM, two controversial samples of patients with AS were obtained and further confirmed to be consistent with SEFA by Sanger sequencing, indicating that this method was more accurate than FCM. Moreover, SEFA could detect HLA-B27 status by using supernatant from crude extract of 10-µL blood without commercial reagents. Overall, SEFA has the potential to be an alternative for HLA-B27 identification with the advantage of convenience and low cost, especially suitable for early diagnosis of AS in areas with limited medical resources.

Can digital transformation change a firm's green innovation strategy? Evidence from China's heavily polluting industries.

Enterprises are facing the superimposed challenges of digitalization and greening. The shift from reactive green technology innovation (RGT) to proactive green technology innovation (PGT) has special significance for sustainable economic development. Which strategies will companies choose? Can digital transformation (DT) motivate companies to transform their green innovation strategies? Enterprises' green innovation strategy choices must be explained with regard to digitalization. The purpose of this paper is to reveal how digitalization affects the choice of green innovation strategies and to provide a realistic basis for the sustainable development of heavily polluting enterprises. We formulated a "DT-capability-strategy" theoretical framework incorporating external constraints and internal attitudes to empirically test the microdata of 505 heavily polluting enterprises. The results show that: (1) DT can shift the heavily polluting enterprises' green innovation strategies from RGT to PGT. Endogenous tests and robustness tests support this conclusion. (2) A mechanism test shows that environmental regulations cannot significantly regulate a green innovation strategy. Only a company's capabilities and attitudes can influence PGT but their effects on RGT are not statistically significant. (3) The influence of DT on green innovation strategies shows multi-dimensional heterogeneity in the digital infrastructure, scale, and innovation level of the enterprise. The conclusions provide implications for enterprises to integrate their digital and green behaviors.

Comparison of 3D and 2D laparoscopy: Initial experience of perioperative outcomes and clinical assessment.

INTRODUCTION: This study was designed to compare three-dimensional (3D) laparoscopy and conventional two-dimensional (2D) laparoscopy in surgical performance and clinical assessment during laparoscopic radical hysterectomy with pelvic lymphadenectomy (LRHND) for treating early-stage cervical cancer. MATERIAL AND METHODS: In this study, we included 67 consecutive patients underwent LRHND for treating early-stage cervical cancer by the experienced laparoscopic surgeons between August 2018 and December 2020. amongst these patients, 32 patients underwent 3D laparoscopy (2D group) and 35 patients underwent 2D laparoscopy (2D group). Demographic data, clinical and surgical parameters were obtained from each patient. An end-of-operation questionnaire was administered regarding subjective perception of 3D laparoscopy system. RESULTS: Patient characteristics, including age, BMI, FIGO stage, and histology, were comparable between the two groups. Compared with 2D imaging system, 3D system significantly shortened the operation time, especially bilateral lymph node dissection time. Blood loss was lower in 3D group compared with 2D group. There were no significant differences regarding pelvic nodes retrieved, incidence of complications, hospital stay, the recovery time of bowel, abdominal drainage fluid, hospitalization costs and visual symptoms. In addition, 3D system significantly improved depth perception and precision, and reduced surgical strain and eye strain for surgeon. No statistical difference was observed in visual symptoms and adverse events between the two groups. The surgeon was more willing to accept 3D laparoscopy. CONCLUSION: The 3D laparoscopy is safe, feasible and comfortable, with obvious advantage in depth perception, precision and surgical strain. It triggered no increase in the complications and adverse events.

Protocol of the development of a core outcome set for stroke in multidimensional value assessment of traditional Chinese medicine.

INTRODUCTION: Stroke is the most common cause of death in China. In Chinese clinical practise, traditional Chinese medicine (TCM) and integrative medicine have been widely used as adjuvant therapies for the treatment of stroke. However, their clinical effectiveness, particularly their clinical value, has been inconsistent in the literature mainly because various outcome measures have been used and reported in clinical research. Hence, obtaining a comprehensive list of outcomes for TCM value assessment is crucial for a multidimensional value assessment. Therefore, the main objective of this protocol was to develop an outcome set used in health technology assessment (HTA) decision-making for TCM treatment of stroke. METHODS AND ANALYSIS: The outcome set will be developed in four phases: (1) we will perform a systematic literature review to identify candidate outcomes that have been previously measured in published studies; (2) we will develop a comprehensive list of outcome measures by conducting a multistakeholder semistructured interview; (3) we will conduct two-round Delphi surveys to prioritise outcomes for each HTA domain; and (4) we will finalise the outcome sets by holding a ratification meeting with multiple stakeholder groups. The developed outcome set should be measured and reported as the minimum set of outcomes for HTA assessment for the TCM treatment of acute ischaemic stroke (AIS). ETHICS AND DISSEMINATION: This protocol was reviewed and approved by the Institutional Review Board of the Minhang Hospital of Fudan University. Our findings will be shared at academic conferences and in peer-reviewed publications.

Integrated treatment guided by RNA-seq-based endometrial receptivity assessment for infertility complicated by MEN1.

Background: Preimplantation genetic testing (PGT) serves as a tool to avoid genetic disorders in patients with known genetic conditions. However, once a selected embryo is transferred, implantation success is attained independent of embryo quality. Using PGT alone is unable to tackle implantation failure caused by endometrial receptivity (ER) abnormalities in these patients. Methods: We validated our newly developed RNA-seq-based ER test (rsERT) in a retrospective cohort study including 511 PGT cycles and reported experience in treating an infertile female patient complicated by multiple endocrine neoplasia type 1 (MEN1). Results: Significant improvement in the clinical pregnancy rate was found in the performed personalized embryo transfer (pET) group (CR, 69.7%; P = 0.035). In the rare MEN1 case, pET was done according to the prediction of the optimal time of window of implantation after unaffected blastocysts were obtained by PGT-M, which ultimately led to a healthy live birth. However, none of the mRNA variants identified in the patient showed a strong association with the MEN1 gene. Conclusions: Applying the new rsERT along with PGT improved ART outcomes and brought awareness of the importance of the ER examination in MEN1 infertile female patients. MEN1-induced endocrine disorder rather than MEN1 mutation contributes to the ER abnormality. Trial Registration: Reproductive Medicine Ethics Committee of Xiangya Hospital Registry No.: 2022010.

The economy-employment-environmental health transfer and embedded inequities of China's capital metropolitan area: a mixed-methods study.

BACKGROUND: Metropolitan areas have complex trade linkages internally and externally. This complexity stimulates the unequal spatial transfer of environmental health consequences, economy, and employment embodied in internal trade or trade with the outside regions, resulting in unequal exchange. Existing research has rarely discussed this issue at a refined scale, hindering targeted inequity alleviation policies. METHODS: We conducted a mixed-methods study, focusing on the most polluted metropolitan area in the world, the Beijing-Tianjin-Hebei region of China, and developed an integrated modelling framework to downscale the analysis of the trade-driven unequal transfer of PM2·5- related premature deaths, value added, and job opportunities to the city scale within Beijing-Tianjin-Hebei. The study couples a nested Multi-Regional Input-Output model table containing data from 13 Beijing-Tianjin-Hebei cities and 28 outer provinces in 2017 with a bottom-up emission inventory, value added and employment statistical data, the Weather Research and Forecasting-Comprehensive Air Quality Model with Extensions, the Global Exposure Mortality Model, and human capital methods. We also constructed two indices measuring unequal exchanges between PM2·5-related deaths and economic and employment gains embodied in trades between cities in Beijing-Tianjin-Hebei and trades with outside regions. FINDINGS: The Beijing-Tianjin-Hebei region as a single entity shifted 14 985 (95% CI 12 800-16 948) net deaths to regions outside the Beijing-Tianjin-Hebei through trade, most of which occurred in the central region of China. The industrial-based peripheral Beijing-Tianjin-Hebei cities suffered the most serious inequities when trading with other Beijing-Tianjin-Hebei cities and outside regions. While gaining equivalent local jobs, these industrial-based peripheral cities had 250% higher PM2·5-related deaths (10·2 PM2·5-related deaths for obtaining 1000 local jobs) than core cities (2·9 PM2·5-related deaths for obtaining 1000 local jobs) and 57·7% higher PM2·5-related deaths than agricultural-based peripheral cities (6·5 PM2·5-related deaths for obtaining 1000 local jobs). While gaining equivalent value added, industrial-based peripheral cities had 50·6% higher PM2·5-related deaths (¥13·9 of reduced human capital due to PM2·5-related premature deaths to obtain ¥1000 local value added) than core cities (¥9·2 of reduced human capital due to PM2·5-related premature deaths to obtain ¥1000 local value added) and 67·4% higher PM2·5-related deaths than agricultural-based peripheral cities (¥8·3 of reduced human capital due to PM2·5-related premature deaths to obtain ¥1000 local value added). INTERPRETATION: Treating metropolitan areas as a single entity obscured internal heterogeneity, potentially misleading policy makers into imposing strict regulations on the whole metropolitan area to alleviate the inequities it posed on outside regions. However, several peripheral Beijing-Tianjin-Hebei cities were disadvantaged in their trade with core Beijing-Tianjin-Hebei cities and outside regions. Therefore, policies should be tailored for particular cities within metropolitan areas. Future targeted policies should include, but not be limited to, making ecological compensations and incorporating the environment and health costs into the price of pollution-intensive goods and services. FUNDING: National Key Research and Devlopment Program of China, National Natural Science Foundation of China, and Jiangsu Natural Science Foundation.

Assessment of Forest Ecosystem Variations in the Lancang-Mekong Region by Remote Sensing from 2010 to 2020.

Five countries in the Lancang-Mekong region, including Myanmar, Laos, Thailand, Cambodia, and Vietnam, are facing the threat of deforestation, despite having a high level of forest coverage. Quantitatively assessing the forest ecosystem status and its variations based on remote sensing products for vegetation parameters is a crucial prerequisite for the ongoing phase of our future project. In this study, we analyzed forest health in the year 2020 using four vegetation indicators: forest coverage index (FCI), leaf area index (LAI), fraction of green vegetation cover (FVC), and gross primary productivity (GPP). Additionally, we introduced an ecosystem quality index (EQI) to assess the quality of forest health. To understand the long-term trends in the vegetation indicators and EQI, we also performed a linear regression analysis from 2010 to 2020. The results revealed that Laos ranked as the top-performing country for forest ecosystem status in the Lancang-Mekong region in 2020. However, the long-term trend analysis results showed that Cambodia experienced the most significant decline across all indicators, while Vietnam and Thailand demonstrated varying degrees of improvement. This study provides a quality assessment of forest health and its variations in the Lancang-Mekong region, which is crucial for implementing effective conservation strategies.

In vitro and in vivo assessment of a bilayered degradable rapamycin-eluting stent for ureteral stricture caused by holmium: YAG laser lithotripsy.

Ureteral stricture caused by holmium: YAG laser lithotripsy is one of the most challenging issues for urologists. Currently, evidence for rapamycin application in reducing ureterostenosis is not sufficient. This study aimed to assess the inhibition of ureteral stricture of rapamycin-eluting stents in vitro and in vivo. A bilayered drug-eluting ureteral stent consisted of drug blending with poly (lactic-co-glycolic acid) (PU/drug stent), which was over-layered by polycaprolactone (PCL) by ultrasonic atomizing spraying. Stent morphology was observed by scanning electron microscope. A kidney-ureter-bladder model was established to simulate the stents-releasing condition, and high-performance liquid chromatography was used to measure the drug release rate. The inhibitory proliferation was detected by CCK-8. The bladder of rats was injured through electro tome, and stents were implanted for 7, 14, and 28 days. The effects of drug-eluting stents was investigated by hematoxylin-eosin staining, immunofluorescence staining, real-time quantitative polymerase chain reaction and western blot. The bilayered stents could block the burst loss of the drug and maintained a sustained delivery period because of the 5.3 µm thickness of the PCL layer. The relative growth rates of cells plotted inhibitory effect on the proliferation of human urethral scar fibroblast cells. For in vivo results of 28 days, the bilayered stent maintained structural integrity and induced less deposition of crystals, thinner and less lamina propria connective tissues were formed, and α-SMA and TGF-ß1 were downregulated. Bilayered rapamycin-eluting stent is significantly effective in alleviating fibrosis in in vitro and in vivo models. STATEMENT OF SIGNIFICANCE: The occurrence of ureteral stricture resulting from holmium: YAG laser lithotripsy presents a significant challenge for urologists. Traditional double J stents have not been proven to offer a shorter indwelling time or improved inhibition of tissue blocking. While drug-eluting stents containing rapamycin, paclitaxel, and other substances have been extensively used in treating artery stenosis, there is insufficient evidence supporting their application in reducing ureterostenosis. Consequently, a biodegradable polymer ureteric scaffold incorporating rapamycin was fabricated in this study, employing ultrasonic atomization spraying technology to optimize the bilayers composed of 75/25 poly (lactic-co-glycolic acid) (PLGA) and polycaprolactone (PCL). The efficacy of the scaffold was subsequently confirmed through in vitro and in vivo experiments.

Remote Sensing Monitoring and Assessment of Global Vegetation Status and Changes during 2016-2020.

Vegetation plays a fundamental role within terrestrial ecosystems, serving as a cornerstone of their functionality. Presently, these crucial ecosystems face a myriad of threats, including deforestation, overgrazing, wildfires, and the impact of climate change. The implementation of remote sensing for monitoring the status and dynamics of vegetation ecosystems has emerged as an indispensable tool for advancing ecological research and effective resource management. This study takes a comprehensive approach by integrating ecosystem monitoring indicators and aligning them with the objectives of SDG15. We conducted a thorough analysis by leveraging global 500 m resolution products for vegetation Leaf Area Index (LAI) and land cover classification spanning the period from 2016 to 2020. This encompassed the calculation of annual average LAI, identification of anomalies, and evaluation of change rates, thereby enabling a comprehensive assessment of the global status and transformations occurring within major vegetation ecosystems. In 2020, a discernible rise in the annual Average LAI of major vegetation ecosystems on a global scale became evident when compared to data from 2016. Notably, the ecosystems demonstrating a slight increase in area constituted the largest proportion (34.23%), while those exhibiting a significant decrease were the least prevalent (6.09%). Within various regions, such as Eastern Europe, Central Africa, and South Asia, substantial increases in both forest ecosystem area and annual Average LAI were observed. Furthermore, Eastern Europe and Central America recorded significant expansions in both grassland ecosystem area and annual average LAI. Similarly, regions experiencing notable growth in both cropland ecosystem areas and annual average LAI encompassed Southern Africa, Northern Europe, and Eastern Africa.