Assessment of efficacy and safety of MET tyrosine kinase inhibitors in non-small-cell lung cancer patients with MET alterations.

Background: While targeted therapy has become the standard treatment for certain non-small-cell lung cancer (NSCLC) patients with gene mutation positivity, there remains a lack of enough reports of the efficacy of mesenchymal-epithelial transition (MET) alterations in the real world. Objectives: We aimed to explore the efficacy and toxicity of targeted therapy in NSCLC patients with different types of MET alterations and hope to provide more clinical medication guidance. Design: Designed different subgroups to compare the efficacy and safety of targeted therapy in NSCLC patients with MET alterations. Methods: We conducted analyses on the efficacy and safety of mesenchymal-epithelial transition factor-tyrosine kinase inhibitor (MET-TKI) therapy in NSCLC patients with MET alterations. Tumor response was evaluated based on the Response Evaluation Criteria in Solid Tumors version 1.1 criteria, and both progression-free survival (PFS) and overall survival were determined using the Kaplan-Meier method. Results: Our study encompassed 116 NSCLC patients with MET alterations, including MET ex14 skipping mutation (n = 50), MET primary amplification (amp) (n = 25), and secondary amp (n = 41). Among treated patients, 34 achieved a partial response, while 52 exhibited stable disease. The overall response rate for the entire cohort was 29.31%, with a disease control rate of 74.14%. A significant difference was observed in the median PFS among patients with MET ex14 skipping mutation, MET primary amplification (amp), and secondary amp (10.4 versus 6.6 versus 4.5 months, p = 0.002). In all, 69 patients experienced drug-related adverse effects, with the most common being peripheral edema (35.34%), nausea and vomiting (21.55%), and fatigue (10.34%). In total, 29 patients (25%) encountered drug-related adverse reactions of grade 3 or higher. Conclusion: MET-TKI therapy works better for MET ex14 skipping mutation than other types of MET gene alteration. In the two MET amplified groups, the secondary amp was less effective. This study may provide more research support for the treatment of these patients.

Temporal trends in prevalence and disability of chronic kidney disease caused by specific etiologies: an analysis of the Global Burden of Disease Study 2019.

BACKGROUND: The prevalence of disability in CKD is high. In this context the aim of the present study was to assess the  temporal trends of prevalence and disability progression for chronic kidney disease (CKD) caused by specific etiologies. METHODS: Using data from the Global Burden of Diseases Study (GBD) 2019, we examined the age-standardized rates of CKD prevalence and disability-adjusted life-years for different etiologies, including Type 1/2 diabetes mellitus (T1DM/T2DM), glomerulonephritis, and hypertension. We also calculated the average annual percentage changes to assess trends. Additionally, we utilized the joinpoint regression model to identify significant shifts over time. RESULTS: From 1990 to 2019, the global prevalence of CKD due to various etiologies exhibited an overall increasing trend, albeit with fluctuations. Notably, CKD due to T1DM, glomerulonephritis, and hypertension consistently demonstrated a significant upward trend across all continents, while the prevalence of CKD due to T2DM varied across continents. In terms of disability-adjusted life-years, CKD due to T2DM and hypertension exhibited a significant rising trend over the past 30 years. However, changes in age standardized disability-adjusted life-years for CKD due to different etiologies were not consistent across continents, with an upward trend observed in The Americas and a contrasting trend in Asia. Furthermore, both age-standardized prevalence rate and age standardized disability-adjusted life-year trends for CKD varied significantly across 204 countries and territories. Additionally, a negative association was observed between the Socio-demographic Index and the disability progression of CKD. CONCLUSION: The prevalence and disability burden of CKD caused by specific etiologies show substantial heterogeneity worldwide, highlighting significant disparities in the distribution of CKD. It is crucial to implement geographic and personalized strategies in different regions to alleviate the burden of CKD effectively.

The impact of the digital economy on industrial structure upgrading in resource-based cities: Evidence from China.

The digital economy provides a new path to promote industrial structure upgrading. Using panel data from 2011 to 2020 for 85 resource-based cities in China, this paper empirically investigates the impact of the digital economy on industrial structure upgrading and the primary mechanism. The results show that the digital economy is conducive to promoting industrial structure upgrading in resource-based cities, and innovation is the primary mechanism of action. According to the different stages of resource development, we classify resource-based cities into growth, maturity, decline, and regeneration cities, and we further analyze the heterogeneous influence. In terms of influence degree, the digital economy has a more prominent role in promoting industrial structure upgrading in resource-exhausted cities. In addition, we also found that the closer to the provincial capital city, the more pronounced the promotion of the digital economy to the industrial structure upgrading.

Evaluation and prediction of carbon emission from logistics at city scale for low-carbon development strategy.

Low-carbon is a part of China's efforts to pursue the national strategy of "carbon peaking and carbon neutrality." Meanwhile, the path of low-carbon transformation of logistics has become a topic of global concern. This study constructs a technical framework of logistics carbon emissions (LCE), which is composed of carbon emission evaluation, carbon emission prediction and low-carbon strategy. All 13 prefecture-level cities in Jiangsu, China, are the application objects in empirical research. Then, the influence analysis of the LCE efficiency based on the panel Tobit model and the evolution of LCE under different scenarios are explored. The results show that: (ⅰ) during the study period (2013-2020), the LCE in Jiangsu showed an overall upward trend, with Xuzhou, Suzhou and Nanjing being the cities with the highest carbon emissions; (ⅱ) the static efficiency of LCE in Jiangsu is at a medium level, with fluctuations in Suzhou, Changzhou, Zhenjiang, Nantong, and Suqian caused by the technical change index; (ⅲ) economic level, industrial structure, fixed asset utilization rate, and ecological environment in Jiangsu are significantly positively correlated with LCE efficiency, while education popularization and energy intensity are negative; (ⅳ) LCE in Jiangsu has been drastically reduced in the low-carbon scenario compared to the baseline scenario. On the above basis, this study proposes suggestions for the low-carbon development strategies of logistics in Jiangsu.

Comparison of the effectiveness, safety, and costs of anti-Parkinson drugs: A multiple-center retrospective study.

AIMS: This study aimed to systematically compare the effectiveness, safety, and costs of different anti-Parkinson drugs (APDs). METHODS: This is a multi-center study that retrospectively analyzed the data of 8420 outpatients with PD from 2014 to 2019 across 30 tertiary hospitals in China. The effectiveness was evaluated by changes in total dosages of APDs, normalized by levodopa equivalent dose (LED) and presented as ΔLEDs; levodopa equivalent dose cost (LEDc) represented the daily cost of APDs; and newly added diagnostics were represented as APDs-related adverse events. RESULTS: A total of 384 patients with eligible medical records for three consecutive years were enrolled. Patients treated with carbidopa/levodopa or levodopa/benserazide had significantly lower mean ΔLEDs than other groups (p < 0.01), followed by pramipexole and selegiline. The piribedil group had the highest ΔLEDs, with mean differences of 112.56-355.04 mg compared to other groups (p < 0.01). Meanwhile, LEDc in the levodopa/benserazide, carbidopa/levodopa, and piribedil groups were significantly lower than those in pramipexole or selegiline groups ($0.088-0.135/day for levodopa/benserazide; $0.070-0.126/day for carbidopa/levodopa; $0.112-0.138/day for piribedil; $0.290-0.332/day for pramipexole; $0.229-0.544/day for selegiline; p < 0.01). Patients with piribedil had more adverse events, with an incidence rate of 35.7%, followed by levodopa/benserazide (25.6%), selegiline (23.5%), carbidopa/levodopa (23.3%), and pramipexole (16.4%). Pramipexole showed a lower incidence rate of adverse events than piribedil, including neuropsychiatric symptoms (p = 0.006), headache/dizziness (p = 0.016), and gastrointestinal symptoms (p = 0.031). CONCLUSIONS: Carbidopa/levodopa or levodopa/benserazide might exhibit better clinical improvement with less medical cost, while piribedil presented less clinical improvement but a higher risk of headache/dizziness, gastrointestinal, and neuropsychiatric symptoms.

Rapid and Non-Destructive Estimation of Moisture Content in Caragana Korshinskii Pellet Feed Using Hyperspectral Imaging.

Moisture content is an important parameter for estimating the quality of pellet feed, which is vital in nutrition, storage, and taste. The ranges of moisture content serve as an index for factors such as safe storage and nutrition stability. A rapid and non-destructive model for the measurement of moisture content in pellet feed was developed. To achieve this, 144 samples of Caragana korshinskii pellet feed from various regions in Inner Mongolia Autonomous Region underwent separate moisture content control, measurement using standard methods, and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 935.5-2539 nm. The Monte Carlo cross validation (MCCV) was used to eliminate abnormal sample data from the spectral data for better model accuracy, and a global model of moisture content was built by using partial least squares regression (PLSR) with seven preprocessing techniques and two spectral feature extraction techniques. The results showed that the regression model developed by PLSR based on second derivative (SD) and competitive adaptive reweighted sampling (CARS) resulted in better performance for moisture content. The model showed predictive abilities for moisture content with a coefficient of determination of 0.9075 and a root mean square error (RMSE) of 0.4828 for the training set; and a coefficient of determination of 0.907 and a root mean square error (RMSE) of 0.5267 for the test set; and a relative prediction error of 3.3 and the standard error of 0.307.

Analysis of the spatial-temporal evolution of Green and low carbon utilization efficiency of agricultural land in China and its influencing factors under the goal of carbon neutralization.

Agricultural land is the most basic input factor for agricultural production and an essential component of terrestrial ecosystems, which plays a vital role in achieving carbon neutrality. Giving full play to the carbon-neutral contribution of agricultural land is a crucial part of China's economic transformation and green development. It incorporates carbon and pollution emissions from agricultural land use into the unexpected outputs of the Green and Low-carbon Utilization Efficiency of Agricultural Land (GLUEAL) evaluation system. The study utilized several advanced analytical tools, including the super-efficient Slacks-Based Measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method, Geodetector, and Geographically and Temporally Weighted Regression (GTWR) model. The objective was to examine the spatial-temporal evolution of GLUEAL and identify the factors that influenced it in all 31 provinces of China from 2005 to 2020. The results show that: (1) The overall spatial-temporal evolution of GLUEAL showed an increasing trend, but the disparity between provinces and regions became wider. (2) Most provinces have not yet made significant spatial and temporal jumps. They have high spatial cohesion with specific "path-dependent" characteristics. (3) The Geodetector results reveal that the Number of Rural Labor Force with Higher Education (NRLFHE) and Technology Support for Agriculture (TSA) have insufficient explanatory power on average for GLUEAL. Agricultural Economic Development Level (AEDL), Urbanization Level (UL), Multiple Crop Index (MCI), Planting Structure (PS), Degree of Crop Damage (DCD), Financial support for agriculture (FSA), and Agricultural mechanization level (AML) had stronger explanatory power on average for GLUEAL and were important factors influencing GLUEAL levels. (4) The average influence of AEDL, UL, FSA, and AML on GLUEAL changed from negative to positive. The average influence of MCI and DCD on GLUEAL was negative, and the average influence of PS on GLUEAL changed from positive to negative. This study provides a comprehensive description of the spatial and temporal evolution of GLUEAL in China. It reveals the key factors influencing GLUEAL and analyzes their spatial variations and impact patterns. These findings offer robust evidence for government policymakers to formulate policy measures for sustainable agricultural development and optimized resource allocation, promoting the transformation of agricultural land towards green and low-carbon practices and advancing the achievement of sustainable development goals.

Environmental regulation, industrial agglomeration, and marine green development efficiency: an empirical analysis from China's coastal provinces.

Environmental regulation (ER) and industrial agglomeration (IA) are important factors that affect green development efficiency (GDE). However, there is a lack of studies on their relation in the context of the marine economy. This paper integrates ER, IA, and marine GDE (MGDE) into a unified analytical framework and uses balanced panel data from China's 11 coastal provinces during 2008-2019 to quantify the linear, nonlinear, and spatial spillover effects between the three using the spatial Durbin model (SDM) and threshold effect model. The results show that ER has a negative impact on local and surrounding MGDE through the direct and spatial spillover effects. IA has a positive impact on local and surrounding MGDE through direct and spatial spillover effects. The synergistic impact of ER and IA can significantly boost local and surrounding MGDE. When ER surpasses a certain threshold, it amplifies the positive impact of IA on MGDE. These findings offer theoretical and practical references for the Chinese government to formulate marine environmental governance and industrial development policies.

SNAr Regioselectivity Predictions: Machine Learning Triggering DFT Reaction Modeling through Statistical Threshold.

Fast and accurate prospective predictions of regioselectivity can significantly reduce the time and resources spent on unproductive transformations in the pharmaceutical industry. Density functional theory (DFT) reaction modeling through transition state theory (TST) and machine learning (ML) methods has been widely used to predict reaction outcomes such as selectivity. However, TST reaction modeling and ML methods are either time-consuming or data-dependent. Herein, we introduce a prototype seamlessly bridging ML and TST modeling by triggering resource-intensive but much less domain-sensitive DFT calculations only on less confident ML predictions. The proposed workflow was trained and tested on both the Pfizer internal dataset and the USPTO public dataset to predict regioselectivity for SNAr reactions. Our method is accurate and fast, which achieves 96.3 and 94.7% accuracy in predicting the correct major product on Pfizer and USPTO datasets, respectively, in a fraction of conventional TST computing time.

The combining and cooperative effects of carbon price and technological innovation on carbon emission reduction: Evidence from China's industrial enterprises.

To achieve the carbon peaking and neutrality targets in China, carbon price and technological innovation will play increasingly important roles in recent future. It is widely-known that carbon price and technological innovation can contribute significantly to emission reduction, respectively; but it is still unclear whether the cooperation effects of carbon price and technological innovation would be positive or negative. In this paper, we assume that there are 3 types of emission reduction measures in China's industrial enterprises, which are improvement of energy efficiency, adjustment of energy structure, and substitution of pollution inputs and non-pollution inputs; then we introduce carbon price and technological innovation respectively and simultaneously, and establish 12 scenarios based on the Data Envelopment Analysis models combined with material balance principal (DEA-MBP), and estimate the additional emission reductions and additional production costs of China's industrial enterprises when carbon price and technological innovation exist respectively or simultaneously. The counterfactually estimating results show that there would be significant regional and sectorial heterogeneities in carbon emission reduction characteristics for China's industrial enterprises. If low-carbon technologies in some sectors have the ability to reduce carbon emissions at the expense of high additional production cost, carbon pricing policies would encourage enterprises to adopt new mitigation technologies and increase additional emission reduction by more than 20%, especially technologies focusing on the adjustment of energy structure and the substitution of pollution inputs by non-pollution inputs. However, in some sectors which have already been covered by carbon pricing policies, the additional carbon pricing policy may not have a significant effect on emission reduction, and the emission reduction would decrease by 10%.

The economic impact of climate change: a bibliometric analysis of research hotspots and trends.

Climate change has been a widely concerned issue for decades. As the key policy target, the economic impact caused by climate change has received general attention from scholars and governments around the world. For the number of literatures is huge and the relationships among the literatures are not clear, we aim to clarify the research hotpots and the research trends of current literatures and provide inspiration for the development directions of future research in this paper. Using the bibliometric method, this paper characterizes the literatures on the economic impact of climate change based on the Web of Science (WoS) Core Collection. The results reveal that the USA occupies the leading position of the studies, which publishes most documents, and contains the most productive institutes and well-known scholars. From 2009, the number of documents published by a Chinese scholar started to increase rapidly, which makes China the second most productive country in recent years. The journals both belong to the WoS Categories of economics and environmental sciences and tend to publish more literatures than others. Adaptation, vulnerability, uncertainty, economic growth, climate policy, ecosystem service, energy consumption, renewable energy, food security, and land use are the representative keywords that have both high frequency and high centrality. Potential benefits, fat-tailed risk, social cost, international migration, and sustainable intensification are the top five main research hotspots. Based on the citation network of the top 50 documents with the highest local citation score, four research trends are sorted out: (i) the methodological innovation to monetized estimate the economic impact of climate change, (ii) the effect of current and future adaptive measures on agriculture, (iii) the interactional relationship between induced technological change and carbon tax, and (iv) the effect on labor market caused by climate change.

Evaluating green productivity of the regional transport sector in South Asia considering environmental and safety constraints: the evolution from static and dynamic perspectives.

The assessment of green productivity not only establishes the production ability but also involves economic, environmental, and social aspects which are the ultimate goals in achieving the sustainability. In this context, unlike the majority of previous literature, we have simultaneously considered the environmental and safety aspects to measure the static and dynamic evolution of green productivity to achieve a safe, eco-friendly, and sustainable development of the regional transport sector in South Asia. First, we proposed the super-efficiency ray-slack-based measure model with undesirable output to assess the static efficiency, which can effectively characterize weak and strong disposability relationship between desirable and undesirable outputs. Second, the biennial Malmquist-Luenberger index has been adopted to examine the dynamic efficiency, which can overcome recalculation issue once an additional time period is included in the data. Therefore, the proposed methodology provides more comprehensive, robust, and reliable insight in comparison to the conventional models. The results indicate (i) both static and dynamic efficiencies decreased during 2000-2019, implying that the transport sector in South Asia follows an unsustainable green development path at the regional level; (ii) dynamic efficiency was primarily held back by green technological innovation whereas green technical efficiency had a modest positive contribution. The policy implications suggest effective ways to improve green productivity of the transport sector in South Asia by promoting coordinated development among the transport structure, environmental and safety aspects, strengthening advance and innovative production technologies, endorsing green transportation practices, and implementing safety regulations and emission standards for the sustainable transport sector.

Piezoelectric Materials and Sensors for Structural Health Monitoring: Fundamental Aspects, Current Status, and Future Perspectives.

Structural health monitoring technology can assess the status and integrity of structures in real time by advanced sensors, evaluate the remaining life of structure, and make the maintenance decisions on the structures. Piezoelectric materials, which can yield electrical output in response to mechanical strain/stress, are at the heart of structural health monitoring. Here, we present an overview of the recent progress in piezoelectric materials and sensors for structural health monitoring. The article commences with a brief introduction of the fundamental physical science of piezoelectric effect. Emphases are placed on the piezoelectric materials engineered by various strategies and the applications of piezoelectric sensors for structural health monitoring. Finally, challenges along with opportunities for future research and development of high-performance piezoelectric materials and sensors for structural health monitoring are highlighted.

Fiscal decentralization, industrial structure upgrading, and carbon emissions: evidence from China.

The debate over the role of fiscal decentralization and industrial structure upgrading in China's environmental governance has received increasing attention. Based on China's provincial panel data from 2003 to 2019, this paper investigates the impact of fiscal decentralization and industrial structure upgrading on carbon emissions to provide empirical evidence for the above theoretical argument. The results show that fiscal decentralization and industrial structure upgrading are negatively correlated with carbon emissions, while the interaction term for fiscal decentralization with industrial structure upgrading presents a facilitating effect on carbon emissions. Besides, fiscal decentralization, industrial structure upgrading, and the interaction term have significant regional heterogeneity on carbon emissions. When fiscal decentralization and industrial structure upgrading are taken as threshold variables, the effects of industrial structure upgrading and fiscal decentralization are significantly nonlinear. Moreover, environmental regulation, transportation infrastructure, and carbon emissions are positively correlated. There exists an inverted U-shaped relationship between carbon emissions and economic growth, which proves environmental Kuznets curve theorem. However, FDI and urbanization have no significant effect on carbon emissions. According to the above conclusions, it is necessary to strengthen the positive interaction between fiscal decentralization and industrial structure upgrading in mitigating carbon emissions, promoting the green and low-carbon transformation of China's economy, thus realizing the goals of "carbon peak" and "carbon neutrality."

Assessment of the role and mechanism of Bifidobacterium animalis subsp. lactis isolated from neonates' feces in protecting neonatal rats from Salmonella infection.

OBJECTIVES: It is now well known that Bifidobacterium animalis subsp. lactis (B. lactis), an important early-life colonizer of the gut, provides immune-related benefits to infants. The aim of the work is to explore the intraspecific resistance to Salmonella infection of B. lactis isolated from neonatal feces, and to learn more insights into how B. lactis mediates beneficial roles in early-life infection resistance. METHODS: Five strains of B. lactis (NFBAL11/NFBAL23/NFBAL44/NFBAL63/NFBAL92) were screened from fecal samples of neonates born within fifteen days and pretreated neonatal rats prior to infection with Salmonella typhimurium (S. typhimurium) SL1344. The survival rate, fecal occult blood, diarrhea and hepatosplenomegaly were detected to assess the ability of B. lactis to prevent S. typhimurium infection. Furthermore, the structure of mucus layer, gene expression, cytokine levels, antioxidant levels and intestinal microflora composition were detected to explore the mechanism. RESULTS: All strains showed activity against S. typhimurium, with B. lactis NFBAL23 being the most active, followed by NFBAL63 and NFBAL92. And these advantages weren't attained by enhancing physical growth and development. Mechanistically, the neonatal rats treated with B. lactis (NFBAL23/NFBAL63/NFBAL92) had improved intestinal barrier function involving physical, chemical, immune and biological barriers in the face of challenges posed by S. typhimurium. CONCLUSIONS: These findings revealed the intraspecific difference, beneficial roles and mechanisms of action of B. lactis against Salmonella infection early in life, which highlighted the necessity of supplementing appropriate B. lactis, and provided several potential B. lactis candidates for Salmonella infection treatment.

The impact of low-carbon city pilot policy on green total-factor productivity in China's cities.

Whether the low-carbon city construction can coordinate urban economy and environment has attracted increasing attention in recent years. In this study, the impact of low-carbon city pilot (LCCP) policy on urban green total-factor productivity is systematically examined theoretically and empirically. Specifically, the biennial Malmquist-Luenberger (BML) index is adopted to measure urban green productivity. Then, propensity score matching-difference-in-differences (PSM-DID) and spatial DID model are used to quantitatively identify the local and spatial spillover effect of the LCCP policy on urban green productivity during 2004-2018 in China. The results show that (1) The LCCP policy can significantly promote urban green productivity, as confirmed through a series of robustness tests. (2) For transmission mechanism, the LCCP policy can enhance urban green productivity through energy consumption reduction and technological innovation but not through industrial structure optimization. (3) With regard to heterogeneity, cities with better transportation infrastructure, stricter environmental regulation and higher urbanization level, as well as non-resource-based cities have more significantly positive effects of the LCCP policy on urban green productivity. (4) The LCCP policy mainly relies on technological progress rather than technical efficiency improvement to drive urban green productivity. (5) The LCCP policy's effect on urban green productivity has significant positive spatial spillover feature, which can significantly promote green productivity in both pilot cities and their neighboring cities. Our findings can provide valuable insights for low-carbon city construction to promote urban sustainable development in China.

The role of advanced glycation end products in fracture risk assessment in postmenopausal type 2 diabetic patients.

Objective: The objective of this study was to analyze the quantitative association between advanced glycation end products (AGEs) and adjusted FRAX by rheumatoid arthritis (FRAX-RA) in postmenopausal type 2 diabetic (T2D) patients. The optimal cutoff value of AGEs was also explored, which was aimed at demonstrating the potential value of AGEs on evaluating osteoporotic fracture risk in postmenopausal T2D patients. Methods: We conducted a cross-sectional study including 366 postmenopausal participants (180 T2D patients [DM group] and 186 non-T2D individuals [NDM group]). All the subjects in each group were divided into three subgroups according to BMD. Physical examination, dual-energy x-ray absorptiometry (DXA), and serum indicators (including serum AGEs, glycemic parameters, bone turnover markers and inflammation factors) were examined. The relationship between FRAX-RA, serum laboratory variables, and AGEs were explored. The optimal cutoff value of AGEs to predict the risk of osteoporotic fracture was also investigated. Results: Adjusting the FRAX values with rheumatoid arthritis (RA) of T2D patients reached a significantly increased MOF-RA and an increasing trend of HF-RA. AGEs level was higher in the DM group compared to the NDMs, and was positively correlated with MOF-RA (r=0.682, P<0.001) and HF-RA (r=0.677, P<0.001). The receiver operating characteristic curve analysis revealed that the area under the curve was 0.804 (P<0.001), and the optimal AGEs cut-off value was 4.156mmol/L. Subgroup analysis for T2D patients revealed an increase in TGF-ß, IL-6 and SCTX in the osteoporosis group, while a decreased PINP in the osteoporosis group compared to the other two subgroups. AGEs were positively associated with FBG, HbA1c, HOMA-IR, S-CTX, IL-6 and TGF-ß in T2D patients, and negatively associated with PINP. Conclusions: RA-adjusted FRAX is a relevant clinical tool in evaluating fracture risk of postmenopausal T2D patients. Our study analyzed the relationship between AGEs and FRAX-RA, and explored the threshold value of AGEs for predicting fracture risk in postmenopausal T2D patients. AGEs were also associated with serum bone turnover markers and inflammation factors, indicating that the increasing level of AGEs in postmenopausal T2D patients accelerated the expression of inflammatory factors, which led to bone metabolism disorders and a higher risk of osteoporotic fractures.

Green Finance Evaluation Based on Neural Network Model.

The weights of green finance indicators are established in accordance with the AHP in order to suggest an evaluation system that is more thorough and reasonable and to construct an evaluation index system. The findings indicate that the growth of urban green finance is more closely correlated with the development of environmental protection businesses, capital allocation efficiency, and governmental and social capital support. Regulation of consumption also has a significant impact. In order to encourage the growth of urban green finance, this paper analyzes the scoring outcomes and changes for each city and offers solutions and recommendations.

An apparatus for qualitative assessment of the shading ratio of oblique illumination and real-time high-contrast imaging.

Oblique illumination imaging can significantly improve the contrast of transparent thin samples. However, in traditional oblique illumination methods, either the condenser is offset or a block is added to the condenser, which makes it complicated and challenged to build a stable oblique illumination imaging. Herein, we present a method to measure the optimal shading ratio of oblique illumination in an inverted microscope, and develop an apparatus for stable high-speed high-contrast imaging with uniform brightness. At optimal shading ratio, the oblique illumination imaging has better imaging quality than differential interference contrast, which characteristic is independent on sample. In oblique illumination with low magnification objective, the images have uneven brightness. According to target brightness, we have developed a brightness unevenness correction algorithm to form uniform background brightness for oblique illumination. Integrating the algorithm with imaging acquisition, corrected oblique illumination microscopy is appropriate to observe living cells with high contrast.

Cost-effectiveness of lung cancer screening combined with nurse-led smoking cessation intervention: A population-based microsimulation study.

BACKGROUND: The appropriate screening inclusion criteria of low-dose computed tomography screening for lung cancer in Chinese population remains unclear and the effect of combining screening with nurse-led smoking cessation intervention is poorly understood as well. OBJECTIVE: We compared the benefits and costs of lung cancer screening with and without nurse-led smoking cessation intervention in different inclusion criteria to help select optimal screening strategies. METHODS: Different screening strategies were set based on diverse starting ages, smoking pack-year and whether nurse-led smoking cessation intervention was applied. We use nationally representative data published by the China Health and Retirement Longitudinal Survey, based on a microsimulation model, to predict incremental cost-effectiveness ratio and net health benefits under different strategies. RESULTS: The incremental cost-effectiveness ratios for all lung cancer screening strategies were less than three times GDP per capita, and screening combined with smoking cessation intervention had lower incremental cost-effectiveness ratios. The largest net health benefits and probability of cost-effectiveness were both obtained in the strategy which conducted screening and nurse-led smoking cessation intervention for people over 45 years with at least 20 pack-year smoking history. In strategies screening alone, it was obtained in screening for people over 50 years and with at 20 pack-year smoking history. CONCLUSIONS: Nurse-led smoking cessation intervention is recommended provided in conjunction with lung cancer screening. The optimal strategy is conducted screening with cessation intervention for current smokers or smoking quitters in the past 15 years who are over 45 years with at least 20 pack-year smoking history. For strategies screening alone, the target population should be over 50 years old with at least 20 pack year smoking history, when willingness to pay less than three times GPD per capita.