Enhancing sustainability of vegetation ecosystems through ecological engineering: A case study in the Qinghai-Tibet Plateau.

Ecological engineering is an important measure to promote ecosystem adaptation and restoration to deal with environmental change and human disturbance. To assess the effectiveness of ecological construction and analyze the influencing factors of ecosystem changes in the Qinghai-Tibet Plateau (QTP), this study detected the spatial changes and dynamic hotspots of vegetation ecosystems in the ecological construction regions of the QTP (QTPE) and regions without ecological construction (QTPWE) using hot spot analysis and comprehensive dynamic degree model. Then the random forest (RF) model and geographical weighted regression model were used to study the degree and spatial heterogeneity of impacts of climate and human activities on normalized difference vegetation index (NDVI). Results showed that the vegetation restoration of the QTPE was obvious during 2001-2018 as the area of the increasing NDVI accounted for 74.15%. In addition, the effects of climate and human activities on NDVI of vegetation ecosystem showed significant spatial heterogeneity. The RF model showed that population density was the most significant factor affecting ecosystem vegetation in the QTPE, and its relative importance was between 26.1-32.6%, followed by downward shortwave radiation (7.9-16.8%). However, climate factors still had the greatest impact in the QTPWE, with the relative importance of precipitation and temperature being 45% and 15%, respectively. These findings provide a scientific basis for the restoration and management of vegetation on the QTP, and are of great significance for the deployment of future ecological engineering projects.

Evaluating the performance of five scoring systems for prescreening obstructive sleep apnea-hypopnea syndrome.

PURPOSE: A comparison of all scoring systems used for screening for obstructive sleep apnea-hypopnea syndrome (OSAHS) is lacking. The aim of this investigation was to evaluate the performance of five scoring systems for screening for OSAHS, as well as to validate the use of the NoSAS and SACS in the Chinese population. METHODS: Data were retrospectively collected from hospital-based, manned, overnight sleep monitoring studies for 105 consecutive outpatients using a portable monitor (PM) device. RESULTS: The 105 participants had an average age of 46 years and were mostly men (75%). STOP-Bang, SACS, and NoSAS scoring exhibited moderate predictive values at different AHI cutoffs (AUC 0.761-0.853, 0.722-0.854, and 0.724-0.771 respectively), followed by the STOP and Berlin questionnaire (AUC 0.680-0.781vs 0.624-0.724). Both STOP-Bang and SACS showed excellent sensitivity (89.5-100% vs 93.4-94.6%) and negative predictive value (68-100% vs 77.3-90.9%), while STOP-Bang, STOP, and SACS showed low negative likelihood ratios (- LR) (0-0.2). CONCLUSIONS: Our study indicated that the STOP-Bang questionnaire and the SACS both show better predictive value than other scoring systems among the five screening tools for OSAHS. Both scoring systems are simple and easy to implement for screening for OSAHS in the community and in hospitals.

Emerging insights into cuproptosis and copper metabolism: implications for age-related diseases and potential therapeutic strategies.

The expanding geriatric population, whose predisposition toward disabling morbidities and age-related diseases (ARD) is well-documented, has become a paramount social issue, exerting an onerous burden on both the healthcare industry and wider society. ARD manifest as the progressive deterioration of bodily tissues and organs, eventually resulting in the failure of these vital components. At present, no efficacious measures exist to hinder the onset of ARD. Copper, an essential trace element, is involved in a wide range of physiological processes across different cell types. In recent research, a novel variant of copper-dependent cell death, termed cuproptosis, has been identified. This mode of cellular demise stands apart from previously recognized types of cell death. Cuproptosis occurs when copper binds with acyl-CoA synthetase in the tricarboxylic acid (TCA) cycle, resulting in protein aggregation and protein toxicity stress, ultimately leading to cell death. In this paper, we provide a concise overview of the current understanding concerning the metabolism of copper, copper-related diseases, the hallmarks of copper toxicity, and the mechanisms that regulate copper toxicity. Additionally, we discuss the implications of cuproptosis mutations in the development of ARD, as well as the potential for targeting cuproptosis as a treatment for ARD.

Genetic association of inflammatory marker GlycA with lung function and respiratory diseases.

Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = -0.14), FVC (rg = -0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (including chr3p21.31 and chr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/ß-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.

The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis.

Background: Body mass index (BMI) and fasting plasma glucose (FPG) are known risk factors for type 2 diabetes mellitus (T2DM), but data on the prospective association of the combination of BMI and FPG with T2DM are limited. This study sought to characterize the association of the combination of BMI and FPG (ByG) with T2DM. Methods: The current study used the NAGALA database. We categorized participants by tertiles of ByG. The association of ByG with T2DM was expressed with hazard ratios (HRs) with 95% confidence intervals (CIs) after adjustment for potential risk factors. Results: During a median follow-up of 6.19 years in the normoglycemia cohort and 5.58 years in the prediabetes cohort, the incidence of T2DM was 0.75% and 7.79%, respectively. Following multivariable adjustments, there were stepwise increases in T2DM with increasing tertiles of ByG. After a similar multivariable adjustment, the risk of T2DM was 2.57 (95% CI 2.26 - 2.92), 1.97 (95% CI 1.53 - 2.54) and 1.50 (95% CI 1.30 - 1.74) for a per-SD change in ByG in all populations, the normoglycemia cohort and the prediabetes cohort, respectively. Conclusion: ByG was associated with an increased risk of T2DM in Japan. The result reinforced the importance of the combination of BMI and FPG in assessing T2DM risk.

Waist circumference glucose, a novel and effective predictor of type 2 diabetes: a prospective cohort study.

Introduction: Waist circumference (WC) and fasting plasma glucose (FPG) have been demonstrated as risk factors for type 2 diabetes mellitus (T2DM). Evidence is limited regarding the association of the combination of WC and FPG (WyG) with the risk of T2DM. The primary aim of the study was to investigate the relationship between WyG and T2DM. Research design and methods: The current study was a population-based cohort study using data from the NAGALA database. Participants were divided into tertiles based on WyG. Cox proportional hazard regression model was applied to identify the association of WyG with T2DM. Results: During a median follow-up of 6.19 years in the normoglycemia group and 5.58 years in the prediabetes group, respectively, 88 and 285 individuals in the two groups received a diagnosis of T2DM. After full adjustment, risk of T2DM increased in step-wise fashion with increasing tertiles of WyG. For a per-SD increase in WyG, the hazard ratios for T2DM were 3.05 (95% CI 2.64 - 3.51) in all populations, 1.94 (95% CI 1.46 - 2.58) in the normoglycemia group and 1.63 (95% CI 1.40 - 1.90) in the prediabetes group. The interaction between WyG and fatty liver on T2DM was statistically significant in the prediabetes group (P for interaction = 0.034). Conclusions: Elevated WyG was independently associated with incident T2DM in Japan. Baseline WyG help identify individuals at high risk of T2DM and implement effective preventive measures.

Assessment of the urban waterlogging resilience and identification of its driving factors: A case study of Wuhan City, China.

With rapid urbanization and extreme rainstorm events associated with climate change, urban waterlogging has become one of the most frequent and severe disasters globally. In this study, a multi-dimensional and multi-process index system based on the Pressure-State-Response (PSR) framework was developed to measure the level of urban waterlogging resilience (UWR). The spatial distribution of UWR on a block scale was explored based on the entropy weight method with the natural breakpoint method (EWM-NBM) in the central district of Wuhan City, China. In addition, the effects of the runoff control facilities and early warning measures on UWR were also quantified. Further, the Geodetector was used to investigate the main driving factors of UWR and their interactions. Results showed that the constructed index system for UWR based on the PSR framework performed reasonably, and the EWM-NBM was validated to be effective in the integrated assessment. In terms of the validation results, 82.72 % of the recorded waterlogging points belonged to high and very-high risk levels. The spatial heterogeneity of UWR was significant in the study area where the higher-level UWR mainly appears in the areas near the undeveloped suburban and water bodies (lakes and rivers), and the lower-level UWR was concentrated in central urban areas with more impervious surfaces. There was a clear increasing trend in UWR after the implementation of runoff control facilities and early warning measures, but its spatial distribution remained almost invariant. Among all the indexes, the impervious surface percentage had the strongest (69.58 %) explanatory ability for the UWR, and mean annual precipitation (15.51 %), GDP (14.03 %), and population density (11.98 %) also demanded attention. Most driving factors of UWR showed nonlinear interactions. This research could provide a benchmark for urban planning to enhance UWR to mitigate the waterlogging within the main urban area.

Analysis of microplastics in soils on the high-altitude area of the Tibetan Plateau: Multiple environmental factors.

Microplastics (MPs), a class of emerging contaminants, are ubiquitous in the environment, but limited information is known about them in remote terrestrial environment at high-altitude areas with inconvenient traffic and sparsely populated. In this study, 54 soil samples were collected from various land use patterns (greenhouse, ordinary farmland, grassland, and bare land) in western area of the Tibetan Plateau to determine the influence of land use type, altitude, meteorological parameters, and distance from the road edge on MP distribution. The MP abundance ranged from 0 (not detected) to 190 items/kg, with an average number of 64.8 items/kg. The concentration of MPs was slightly negatively correlated with altitude because of less human activities in high-altitude areas (especially agricultural activities). The random forest (RF) models showed that altitude was the most important driving factor that affected the MP distribution. Small-sized MPs were more abundant at higher altitudes than at low ones, and the special natural environment of the high-altitude areas (tall vegetation scarcely, UV, and strong wind speed) may be conducive to the degradation of MPs in surface soils. The special source of MPs in non-agricultural soils was associated with traffic behavior: parking and rest behavior beside roads at high altitude areas, which filled an important source of MPs in the plateau area. This study emphasized the need to investigate the effects of traffic activities on MPs in remote areas at high altitudes.

Relationship between lipid accumulation product and new-onset diabetes in the Japanese population: a retrospective cohort study.

Background: Diabetes has become a global public health problem. Obesity has been established as a risk factor for diabetes. However, it remains unclear which of the obesity indicators (BMI, WC, WhtR, ABSI, BRI, LAP, VAI) is more appropriate for monitoring diabetes. Therefore, the objective of this investigation is to compare the strength of the association of these indicators and diabetes and reveal the relationship between LAP and diabetes. Methods: 15,252 people took part in this research. LAP was quartered and COX proportional risk model was applied to explore the relationship between LAP and new-onset diabetes. Smooth curve fitting was employed to investigate the non-linear link between LAP and diabetes mellitus. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the aforementioned indicators for diabetes. Results: After adjusting for confounding factors, multiple linear regression analysis showed that each unit increase in LAP was associated with a 76.8% increase in the risk of developing diabetes (HR=1.768, 95% CI: 1.139 to 2.746, P=0.011). In addition, LAP predicted new-onset diabetes better than other indicators, and the AUC was the largest [HR: 0.713, 95% CI: 0.6806-0.7454, P<0.001, in women; HR: 0.7922, 95% CI: 0.7396-0.8447; P<0.001, in men]. When LAP was used as a lone predictor, its AUC area was largest both men and women. However, after adding classical predictors (FPG, HbA1c, SBP, exercise, age) to the model, the LAP is better than the ABSI, but not better than the other indicators when compared in pairs. Conclusions: High levels of LAP correlate very strongly with diabetes and are an important risk factor for diabetes, especially in women, those with fatty liver and current smokers. LAP was superior to other indicators when screening for diabetes susceptibility using a single indicator of obesity, both in men and in women. However, when obesity indicators were added to the model together with classical predictors, LAP did not show a significant advantage over other indicators, except ABSI.

A U-shaped association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of incident type 2 diabetes mellitus in Japanese men with normal glycemic levels: a population-based longitudinal cohort study.

Background: Several studies have verified that a high baseline TG/HDL-C ratio is a risk factor for incident type 2 diabetes mellitus (T2DM). However, for low baseline TG/HDL-C levels, the findings were inconsistent with ours. In addition, the association between baseline TG/HDL-C ratio and the risk of incident T2DM in Japanese men with normal glycemic levels is unclear. As a result, our study further investigated the relationship between baseline TG/HDL-C and the risk of incident T2DM in Japanese men with normal glycemic levels. Methods: This was a secondary longitudinal cohort study. We selected 7,684 male participants between 2004 and 2015 from the NAGALA database. A standardized Cox regression model and two piecewise Cox regression models were used to explore the relationship between the baseline high-density lipoprotein cholesterol ratio (TG/HDL-C) and incident T2DM. Results: During a median follow-up of 2,282 days, 162 men developed incident T2DM. In the adjusted model, the baseline TG/HDL-C ratio was strongly associated with the risk of incident T2DM, and no dose-dependent positive association was observed between the baseline TG/HDL-C ratio and incidence of T2DM throughout the baseline TG/HDL-C quartiles. Two-piecewise linear regression analysis showed a U-shaped association between baseline TG/HDL-C ratio and incidence of incident T2DM. A baseline TG/HDL-C ratio below 1.188 was negatively associated with incident T2DM (H.R. = 0.105, 95% CI = 0.025, 0.451; P = 0.002). In contrast, a baseline TG/HDL-C ratio >1.188 was positively associated with incident T2DM (H.R. = 1.248, 95% CI = 1.113, 1.399; P<0.001). The best TG/HDL-C threshold for predicting incident T2DM was 1.8115 (area under the curve, 0.6837). Conclusion: A U-shaped relationship between baseline TG/HDL-C ratio and incident T2DM in Japanese men with normal glycemic levels was found.

Optimized multilateral crop trade patterns can effectively mitigate phosphorus imbalance among the involved countries.

Phosphorus imbalance for cropland can greatly influence environmental quality and productivity of agricultural systems. Resolving cropland phosphorus imbalance may be possible with more efficient multilateral crop trade within the involved trading countries; however, the driving mechanisms are unclear. This study calculates phosphorus budgets in China and five central Asian countries and proposes two optimal multilateral crop trade models to mitigate the phosphorus imbalance. Results show that the current trading pattern between China and Central Asia is causing a phosphorus imbalance intensification. Phosphorus surpluses in China and Uzbekistan are 41.7 and 8.9 kg/ha, while Kazakhstan, Kyrgyzstan, Tajikistan, and Turkmenistan exhibit phosphorus deficits with the negative value of -0.7, -1.2, -0.8, and -0.8 kg/ha, respectively. However, under the optimal multilateral crop trade patterns, phosphorus budget of China and Central Asia will become balanced. Phosphorus imbalance intensification for China is reduced to -2525 and -2472 kt under the single- and bilevel-objective-based crop trades. In Kyrgyzstan, it will drop 61.5 % and 50.0 % and change to 321 and 417 kt under the two optimal crop trades. Moreover, changes of phosphorus imbalance mitigations for other central Asian countries range from 11.9 % to 28.2 %. This provides a scientific basis when establishing policies for strengthening optimal multilateral crop trading across the world to promote global phosphorus management.

Bias correction framework for satellite precipitation products using a rain/no rain discriminative model.

Despite the benefits of global coverage with high spatiotemporal resolutions, satellite precipitation products (SPPs) still suffer from inadequate accuracy in natural hazard forecasts, hydrology, and water resources management. Rain/no-rain (R/NR) detection error significantly affects the accuracy of daily SPPs, which has attracted increasing attention in recent years. This paper proposed a precipitation bias correction framework (PBCF) to improve the accuracy of daily SPPs, focusing on improving the ability of SPPs to detect the occurrence of the precipitation based on a R/NR discriminative model. Multiple land and climate variables derived from ERA5-Land reanalysis dataset were used to construct the R/NR discriminative model using the artificial neural network (ANN) method. A case study on the bias correction of daily precipitation of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) over Hanjiang River Basin (HRB) was conducted for the period 2004-2018. Daily precipitation of 64 meteorological stations in HRB were spatially and randomly divided into two groups: 44 stations were used for training, validating and testing the constructed R/NR discriminative model, and the other 20 stations were used to evaluate the performance of the R/NR discriminative model in different topographic areas. The results indicate that the proposed PBCF could reduce the bias of IMERG, with the correlation coefficient (R) increased by 19.4%, the root mean square error (RMSE) and the mean absolute error (MAE) decreased by 19.0% and 29.8% on the daily scale, respectively. The constructed R/NR discriminative model could improve the ability of IMERG for detecting the precipitation occurrence, with a classification accuracy of about 86.5% and the equitable threat score (ETS) increased from 0.15 to 0.58. Further analyses showed that the proposed PBCF was more efficient than the cumulative distribution function mapping method in correcting IMERG. This study provides a novel insight for the correction of daily SPPs.

Triglyceride Glucose-Body Mass Index and Risk of Incident Type 2 Diabetes Mellitus in Japanese People With Normal Glycemic Level: A Population-Based Longitudinal Cohort Study.

Background: It has been proved that triglyceride glucose-body mass index (TyG-BMI) is a readily available and clinically significant indicator of insulin resistance (IR). Nevertheless, the association between TyG-BMI and incident Type 2 diabetes mellitus (T2DM) remains uncertain. This study aimed to study the relationship between TyG-BMI and T2DM and explore the predictive characteristics of TyG-BMI. Methods: Our study was conducted as a longitudinal cohort study. 8,430 men and 7,034 women were enrolled and analyzed. They were both non-diabetic subjects with normal glycemic levels. Follow-up lasted for 13 years, from 1994 to 2016. To make the number of TyG-BMI in each group similar, the subjects were divided into four groups with 3866 subjects in each group. Results: During the 13-year follow-up period, 373 subjects were diagnosed with incident T2DM. Our multivariate Cox regression analysis revealed that TyG-BMI was an independent predictor of incident T2DM. In addition, our research identified four specific groups, young people (18-44 years old), women, the non-hypertensive population and non-drinkers were at significantly higher risk of developing TyG-BMI-related diabetes (P-interaction< 0.05). The best threshold TyG-BMI for predicting incident T2DM was 197.2987 (area under the curve 0.7738). Conclusions: Our longitudinal cohort study demonstrated the positive correlation between baseline TyG-BMI and risk of incident T2DM in Japanese with normal glycemic levels, and this risk was significantly higher in the young people, women, the non-hypertensive population and non-drinkers.

Identification of cuproptosis-associated IncRNAs signature and establishment of a novel nomogram for prognosis of stomach adenocarcinoma.

Purpose: Stomach adenocarcinoma (STAD) is one of the common cancers globally. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in STAD is unknown. Methods: STAD patient data from TCGA were used to identify prognostic lncRNAs by Cox regression and LASSO. A nomogram was constructed to predict patient survival. The biological profiles were evaluated through GO and KEGG. Results: We identified 298 cuproptosis-related lncRNAs and 13 survival-related lncRNAs. Patients could be categorized into either high risk group or low risk group with 9-lncRNA risk model with significantly different survival time (p < 0.001). ROC curve and nomogram confirmed the 9-lncRNA risk mode had good prediction capability. Patients in the lower risk score had high gene mutation burden. We also found that patients in the two groups might respond differently to immune checkpoint inhibitors and some anti-tumor compounds. Conclusion: The nomogram with 9-lncRNA may help guide treatment of STAD. Future clinical studies are necessary to verify the nomogram.

Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.

Introduction: Semen quality has decreased gradually in recent years, and lifestyle changes are among the primary causes for this issue. Thus far, the specific lifestyle factors affecting semen quality remain to be elucidated. Materials and methods: In this study, data on the following factors were collected from 5,109 men examined at our reproductive medicine center: 10 lifestyle factors that potentially affect semen quality (smoking status, alcohol consumption, staying up late, sleeplessness, consumption of pungent food, intensity of sports activity, sedentary lifestyle, working in hot conditions, sauna use in the last 3 months, and exposure to radioactivity); general factors including age, abstinence period, and season of semen examination; and comprehensive semen parameters [semen volume, sperm concentration, progressive and total sperm motility, sperm morphology, and DNA fragmentation index (DFI)]. Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. Furthermore, the accuracy of the model was verified via multiple logistic regression following k-fold cross-validation analyses. Results: The results indicated that for semen volume, sperm concentration, progressive and total sperm motility, and DFI, the area under the curve (AUC) values ranged from 0.648 to 0.697, while the AUC for sperm morphology was only 0.506. Among the 13 factors, smoking status was the major factor affecting semen volume, sperm concentration, and progressive and total sperm motility. Age was the most important factor affecting DFI. Logistic combined with cross-validation analysis revealed similar results. Furthermore, it showed that heavy smoking (>20 cigarettes/day) had an overall negative effect on semen volume and sperm concentration and progressive and total sperm motility (OR = 4.69, 6.97, 11.16, and 10.35, respectively), while age of >35 years was associated with increased DFI (OR = 5.47). Conclusion: The preliminary lifestyle-based model developed for semen quality prediction by using the XGBoost algorithm showed potential for clinical application and further optimization with larger training datasets.

Water environmental pressure assessment in agricultural systems in Central Asia based on an Integrated Excess Nitrogen Load Model.

Agricultural runoff is the main source of water pollution in Central Asia. Excessive nitrogen (N) inputs from overuse of chemical fertilizers are threatening regional water resources. However, the scarcity of quantitative data and simplified empirical models limit the reliability of grey water footprint (GWF), particularly in undeveloped regions. In this study, we developed an Integrated Excess Nitrogen Load Model (IENLM) to calculate excess N load and evaluate its potential water environmental pressure in Central Asia. The model optimized the biological N fixation and atmospheric N deposition modules by involving more environmental variables and human activities. Results showed that N fertilizer application contributed over 60% to total N input and was mainly responsible for 42.9% increase of total GWF from 101.5 to 145.0 billion m3 during 1992 - 2018. Water pollution level (WPL) increased from 0.55 in 1992 to 2.41 in 2018 and the pollution assimilation capacity of water systems has been fully consumed just by N load from agriculture since 2005. GWF intensity and grey water pollution - efficiency types in all Central Asian countries have improved in recent years except for Turkmenistan. N fertilizer application and agricultural economy development were the main driving factors induced N pollution. Results were validated by riverine nitrate concentrations and the estimates from prior studies. In future, combining the N fertilizer reduction with other farm management practices were projected to effectively improve the WPL. The modeling framework is favorable for N pollution research in data-scarce regions and provides a scientific basis for decision-making for agriculture and water resource managements.

Residual Risk of Coronary Atherosclerotic Heart Disease and Severity of Coronary Atherosclerosis Assessed by ApoB and LDL-C in Participants With Statin Treatment: A Retrospective Cohort Study.

Background: Low-density lipoprotein cholesterol (LDL-C) is the primary target of lipid-lowering therapy on the management of hypercholesterolemia in the United States and European guidelines, while apolipoprotein B (apoB) is the secondary target. The objective was to determine if elevated levels of apoB is superior to LDL-C in assessing residual risk of coronary atherosclerotic heart disease and severity of coronary atherosclerosis in participants with statin treatment. Methods: This study included 131 participants with statin treatment. The generalized linear model and relative risk regression (generalized linear Poisson model with robust error variance) were used to analyze the association of the levels of apoB and LDL-C with the severity of coronary atherosclerosis and residual risk of coronary atherosclerotic heart disease. Results: Categorizing apoB and LDL-C based on tertiles, higher levels of apoB were significantly associated with the severity of coronary atherosclerosis (Ptrend = 0.012), whereas no such associations were found for elevated levels of LDL-C (Ptrend = 0.585). After multivariate adjustment, higher levels of apoB were significantly associated with residual risk of coronary atherosclerotic heart disease. When compared with low-level apoB (≤0.66 g/L), the multivariate adjusted RR and 95% CI of intermediate-level apoB (0.67-0.89 g/L) and high-level apoB (≥0.90 g/L) were 1.16 (1.01, 1.33) and 1.31 (1.08, 1.60), respectively (Ptrend = 0.011). There was a 45% increased residual risk of coronary atherosclerotic heart disease per unit increment in natural log-transformed apoB (Ptrend <0.05). However, higher levels of LDL-C were not significantly associated with residual risk of coronary atherosclerotic heart disease. When compared with low-level LDL-C (≤1.56 mmol/L), the multivariate adjusted RR and 95% CI of intermediate-level LDL-C (1.57-2.30 mmol/L) and high-level LDL-C (≥2.31 mmol/L) were 0.99 (0.84, 1.15) and 1.10 (0.86, 1.42), respectively (Ptrend = 0.437). Similar results were observed in the stratified analyses and sensitivity analyses. No significant interactions were detected for both apoB and LDL-C (all Pinteraction>0.05). Conclusions: Elevated apoB are superior in assessing the residual risk of coronary atherosclerotic heart disease and severity of coronary atherosclerosis in participants with statin treatment.

Impact of thermal condition on vegetation feedback under greening trend of China.

In China, an unambiguous greening trend was observed over the last three decades. The feedback induced by vegetation growth can affect regional climate. Here, we investigated how vegetation feeds back to land surface temperature (LST) in temperature zones and land-use types in China using 18-years (2001-2018) of Moderate Resolution Imaging Spectroradiometer (MODIS) LST and Normalized Difference Vegetation Index (NDVI) data. We first showed that vegetation feedback was significantly negative (p < 0.1, t-test) in most parts of China. Specifically, we discovered a downtrend of vegetation feedback from the coldest temperature zone to the hottest temperature zone. Moreover, vegetation feedback and thermal condition showed an inverse relationship among temperature zones. The inverse relationship clarified that vegetation growth can cool most parts of China during climate change. In the end, we showed the pattern of vegetation feedback among land-use types. Due to the expansion of grassland, vegetation feedback may temporarily positive. Suitable vegetation coverage in urban land, banning deforestation, and cultivating land reasonably can decrease the local temperature by inducing negative vegetation feedback.

Microplastic footprints in the Qinghai-Tibet Plateau and their implications to the Yangtze River Basin.

Microplastics (MPs) are pervasive in the environment and have posed growing threat to ecosystems and human health. This study investigated MP abundances in surface water (fresh and salt lakes, urban and rural rivers, etc.) from 28 stations in the Qinghai-Tibet Plateau. MPs were detected in 25 out of 28 water samples with relatively low abundance (average 584.82 particles m-3). Fibers were the most frequently observed shape, particle sizes mostly ranged from 100 to 500 µm, and the greatest number of MPs was polypropylene. Source analysis identified the major sources of domestic wastewater and tourism in some areas. The concentration and proportion of small MPs (20-100 µm) in salty water were apparently greater than that in fresh water, indicating Salt intrusion accelerated MPs fragmentation. As the study area is the origin of the Yangtze River, we further compared the MP distribution throughout the watershed. Nearly two orders of magnitude in MP concentrations were increased associated with urban agglomeration in the middle and downstream areas, but the highest level was marked around the Yichang City (location of the Three Gorges Reservoir) due to interception associated with sedimentation and precipitation. This study provides data and theoretical bases for analyzing MPs migration and degradation processes in high altitudes.

Spatial characteristics of microplastics in the high-altitude area on the Tibetan Plateau.

Microplastics (MPs) have been widely detected in the environments, yet the sources of MPs in freshwater of remote areas at high altitude were not well understood. This study investigated the abundance and distribution of MPs in water bodies and sediments at the Qinghai-Tibet Plateau (QTP). MPs were detected in all samples (47 water and 33 sediment samples) with the mean abundance of 624.70 ± 411.39 items/m3 in water and 41.52 ± 22.31 items/kg in sediment. In descending order, the highest MP oncentrations were found in turbid rivers＞agricultural channel water＞lakes＞ordinary rivers. The results showed that MP abundance was associated with the water quality (especially COD) on the QTP, and it was negatively correlated with altitude due to less human activities (especially agricultural activities) at high altitude areas. In addition, more abundant MPs with small sized was found in the higher altitudes than low ones. Determining the effects of different environments on the distribution and degradation of MPs in the high altitude area of the QTP, this study emphasized the attention to be given to this emerging pollutant in the high altitude remote areas.