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Background and Aims: Immune checkpoint inhibitor therapy causes numerous immune-related adverse events, including autoimmune pancreatic injury (AIPI), which results in rapid organ atrophy. We profiled the clinico-radiological features, short-term natural history, and response to steroids of AIPI. Methods: We retrospectively reviewed medical records of 229/11,165 (2.1%) adult patients with AIPI. One hundred and ten out of 229 (48%) had abdominal computerized tomography (CT) scan at lipase elevation; data of 110 without pancreatic metastases were analyzed. We analyzed serial CT-based pancreas volumetry data in 48 patients with AIPI (32 with normal CT and 16 with pancreatitis on CT at lipase elevation). We examined impact of steroids on pain and disease course. Results: In AIPI (n = 229), median lipase elevation was 4x upper limit of normal (range: 3–40x). The injury was more often asymptomatic than painful (143/229 (62%) vs 86/229 (38%), P < .000). Majority (83/110 (75%) had normal CT, often in painless vs painful disease: 51/57 (90%) vs 32/53 (60%), P < .001) 25% had interstitial pancreatitis. On serial pancreas volumetry, marked volume (cc) loss occurred 1 year after vs 3 months before lipase elevation in both normal CT (median 81.6 vs 61.3, P = .00) and pancreatitis on CT groups (91.8 vs 60.5, P = .00), ≥20% volume loss occurred in 47% vs 73%, respectively (P = .08). Steroids, when used did not mitigate pain, biochemical relapse, pancreas volume loss or 1-year diabetes incidence (7.2%). Conclusion: Autoimmune pancreatic injury (AIPI) is uniquely characterized by painless lipase elevation, normal pancreas on CT and rapid pancreatic volume loss on follow-up. Steroids do not appear to have a role in management.

In order to solve the issue of idle rural homesteads and enhance the welfare of peasant households, the Chinese government has implemented various rural homestead withdrawal patterns. In the context of land spatial planning regulation, based on the field survey data from 210 peasant households in Xuzhou City and Ganzhou City, this study constructs a bilateral matching model between rural homestead withdrawal patterns and types of welfare needs of peasant households. This study uses a Discrete Particle Swarm Optimization algorithm improved on the 0–1 knapsack strategy to solve the matching model, aiming to find the optimal homestead withdrawal patterns that match the types of peasant households. The results show that: (1) The matching of rural homestead withdrawal patterns and types of peasant households conforms to the principle of comparative advantage. (2) In the case of “one-to-one matching” between peasant households and homestead withdrawal patterns, matching the “economic-material-oriented” peasant households with the withdrawal pattern of “monetary compensation”, matching the “social-service-oriented” peasant households with withdrawal pattern of “indicator replacement”, and matching the “welfare-assistance-oriented” peasant households with the withdrawal pattern of “asset replacement”. (3) The bilateral overall preference of the combined rural homestead withdrawal patterns is higher than that of the single rural homestead withdrawal pattern, and satisfaction has increased by at least 8 %. The authors argue that the government should design and implement diversified withdrawal patterns based on a full understanding of the welfare needs of peasant households.

Identifying the dominant factors influencing ecosystem health and their optimal thresholds is essential for the management and restoration of ecosystems. Most of the works, however, have less detected the importance level of individual factors, especially their changes over time and scale, and rarely determined their threshold effects on ecosystem health (EH), which seriously hinders the formulation of targeted policies for sustainable ecosystem management. To address these research gaps, we present an innovative visualization approach to reveal importance changes in natural and anthropogenic variables and their nonlinear coupling process with EH in the China’s Yellow River Basin (YRB) in the last two decades. Results show that (i) Although the EH in the YRB has improved slightly in the past 20 years, it is still not optimistic and shows distinct spatial heterogeneity. (ii) The impact of human activities on the ecosystem health of the YRB has increased and increasingly plays a decisive role, while that of the natural aspect has decreased recently. Specifically, environmental factors (slope, NDVI, and annual temperature) are the dominant factors affecting the upstream EH. Midstream EH is significantly affected by the synergistic effect of natural and anthropogenic factors, but the importance of the proportion of built-up land is intensified (ranked from 8th to 4th). Anthropogenic factors exert the greatest influence on downstream EH variation, especially for population density whose importance order rising from 7th to 2nd. (iii) By illustrating the nonlinear response curves of EH at multi-scale, the tipping point caused ecosystem deterioration in the YRB is explored and the optimal thresholds of leading factors oriented towards the most effective ecosystem conservation goal are obtained. These results help precisely identify the current health status of YRB's ecosystem, as well as providing a valuable reference for moderate restoration standards and sustainable ecosystem management.

Introduction: Acute myocardial infarction (AMI) accounts for the majority of deaths caused by coronary artery disease (CAD). Early warning of AMI, especially for patients with stable coronary artery disease (sCAD), is urgently needed. Our previous study showed that alterations in the gut microbiota were correlated with CAD severity. Objectives: Herein, we tried to discover accurate and convenient biomarkers for AMI by combination of gut microbiota and fecal/blood/urinary metabolomics. Methods: We recruited 190 volunteers including 93 sCAD patients, 49 AMI patients, and 48 subjects with normal coronary artery (NCA), and measured their blood biochemical parameters, 16S rRNA-based gut microbiota and NMR-based fecal/blood/urinary metabolites. We further selected 20 subjects from each group and analyzed their gut microbiota by whole-metagenome shotgun sequencing. Results: Multi-omic analyses revealed that AMI patients exhibited specific changes in gut microbiota and serum/urinary/fecal metabolites as compared to subjects with sCAD or NCA. Fourteen bacterial genera and 30 metabolites (11 in feces, 10 in blood, 9 in urine) were closely related to AMI phenotypes and could accurately distinguish AMI patients from sCAD patients. Some species belonging to Alistipes, Streptococcus, Ruminococcus, Lactobacillus and Faecalibacterium were effective to distinguish AMI from sCAD and their predictive ability was confirmed in an independent cohort of CAD patients. We further selected nine indicators including 4 bacterial genera, 3 fecal and 2 urinary metabolites as a noninvasive biomarker set which can distinguish AMI from sCAD with an AUC of 0.932. Conclusion: Combination of gut microbiota and fecal/urinary metabolites provided a set of potential useful and noninvasive predictive biomarker for AMI from sCAD.

Public participation in river basin ecological compensation is one of the effective means to adjust the multi stakeholder relationship and promote low-carbon development. This paper takes the upper Yellow River basin section as the research area, adds ecological compensation policy variables to the Theory of Planned Behavior (TPB). An integrated theoretical framework is established from the two levels of personal psychological cognition and policy environment, which can comprehensively consider multiple factors that affect individual behavior. This paper uses the Structural Equation Modeling (SEM) to empirically analyze the impact of psychological factors and river basin ecological compensation policy on the public's willingness and behavior to participate in river basin ecological compensation. The results showed that the three psychological cognitive factors of behavior attitude, subjective norm and perceived behavior control had a significant impact on the public's willingness to participate in ecological compensation. The ecological compensation policy also has a significant impact on the willingness and behavior of the public to participate in ecological compensation. The impact coefficient of ecological compensation policy on the participation willingness is 0.085, and the impact coefficient on the participation behavior is 0.551. The existing ecological compensation policies in carbon neutral contexts have a stronger effect on the public participation behavior, but a weaker impact on the public's willingness to participate. The existing policies in carbon neutral contexts play a small role in mobilizing the public's enthusiasm from the psychological cognitive level, but the willingness to participate has a significant direct impact on the participation behavior. The research conclusions of this paper can help to broaden the theoretical framework of public participation and provide new ideas and methods for improving the ecological compensation mechanism of the river basin.

Summary: Owing to the impact of the western development of China, there have been signs of air pollution over the Qinghai-Tibet Plateau in recent years. However, monitoring data on atmospheric volatile organic compounds (VOCs) are lacking in plateau areas. Here, VOCs concentrations in urban and background areas in North China and the Qinghai-Tibet Plateau were observed from 2012 to 2014 and 2020 to 2022, respectively. Compared to 2012–2014, the concentration of VOCs increased to 2.5 times in urban areas on the Qinghai-Tibet Plateau, which was equivalent to that in North China. Oil, gas, and solvent evaporation caused by a low atmospheric pressure is the primary factor for the increase in VOCs in plateau areas, and weak VOCs degradation is the secondary factor. Hence, we put forward the VOCs control strategies in plateau areas and point out the defects in the current research.

Identifying spatiotemporal heterogeneity and impact mechanism of ecosystem service value (ESV) is critical for enhancing ecosystem management and regional sustainability. However, the existing findings have failed to investigate the synergetic effect of multiple drivers on ESV, nor have considered the threshold effects under different conditions, which is important to understand the complex and frequently interacting ecosystem. In this study, we applied the improved ESV calculation method, Pearson correlation analysis and conditional inference tree model to depict the dynamic changes of ESV, to explore separate and synergetic effects of various factors, and further to identify key thresholds under combined effects in urban agglomerations along the upper and middle Yellow River area (UMYRA). The results showed that: (1) The total ESV of the study area increased by 5936.63 million CNY over the study period. With the exception of the urban agglomeration along the Yellow River in Ningxia (YRNX), four types of sub-services in Hulunbeier-Baotou-Erdos-Yulin urban agglomeration (HBEY) and Taiyuan urban agglomeration (TY) showed a rising trend. Spatially, the greater growth of ESV mainly concentrated in the northern desert belt, whereas the major grain production areas and urban areas presented different degrees of degradation. (2) Climate factors and land use intensity are the main factors affecting the total ESV, followed by economic density and terrain condition, while landscape metrics exert a relatively small impact on ESV. But the influences of these factors on single ESV show distinct internal differences. (3) Synergetic effects of multi-factors showed that: ①When the evapotranspiration and precipitation are at a certain threshold (1277 mm＜PET＜1317 mm and PRE＞417.55 mm), rising temperature can effectively promote the growth of ESV. The same effect is also observed on steep slopes under matched hydrothermal conditions; ②When economic development is at a high level, intensifying human activities within a certain range (0.11＜HAI＜0.29 and 184.32＜LUI＜210.6) could greatly promote the ESV, but the opposite effect was also true when the thresholds were breached; ③Fragmented landscapes with low diversity (SHDI＜0.86) can promote ESV improvement, but high diversity fragmented landscapes (PD＞0.14 or SHDI＞0.85) would lead to ESV decline. Our research sheds light on the key thresholds under synergetic effect of multiple factors on ESV from a novel perspective, which provide a specific and practical guidance for achieving sustainable management.