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Due to the complex coupling between phenology and climatic factors, the influence mechanism of climate, especially preseason temperature and preseason precipitation, on vegetation phenology is still unclear. In the present study, we explored the long-term trends of phenological parameters of different vegetation types in China north of 30°N from 1982 to 2014 and their comprehensive responses to preseason temperature and precipitation. Simultaneously, annual double-season phenological stages were considered. Results show that the satellite-based phenological data were corresponding with the ground-based phenological data. Our analyses confirmed that the preseason temperature has a strong controlling effect on vegetation phenology. The start date of the growing season (SOS) had a significant advanced trend for 13.5% of the study area, and the end date of the growing season (EOS) showed a significant delayed trend for 23.1% of the study area. The impact of preseason precipitation on EOS was overall stronger than that on SOS, and different vegetation types had different responses. Compared with other vegetation types, SOS and EOS of crops were greatly affected by human activities while the preseason precipitation had less impact. This study will help us to make a scientific decision to tackle global climate change and regulate ecological engineering.

Cities worldwide are expanding greenspaces, including parks, urban forests, and grasslands. However, population exposure to tree and nontree vegetation is less well understood. Here, we use multiple satellite-derived datasets on vegetation, climate, and socioeconomic factors to examine the variations of urban tree and nontree vegetation cover, drivers of changes, and the impacts on global urban population exposure between 2000 to 2020. We find that approximately 90% of cities experienced an ascending trend in tree cover, and 49% of cities showed growth in nontree vegetation ( p < 0.05). The increase in urban tree cover is most evident in high-latitude areas, such as Eastern Russia and Northern Europe. Human exposure to urban tree vegetation considerably declined in the Global South, widening the disparity between the North and South. Our study underscores persistent inequalities in human exposure to green space in cities and calls for evidence-based strategies that reduce increasing disparities.

Climate change has exacerbated the frequency and severity of droughts worldwide. Evaluating the response of gross primary productivity (GPP) to drought is thus beneficial to improving our understanding of the impact of drought on the carbon cycle balance. Although many studies have investigated the relationship between vegetation productivity and dry/wet conditions, the capability of different drought indices of assessing the influence of water deficit is not well understood. Moreover, few studies consider the effects of drought on vegetation with a focus on periods of drought. Here, we investigated the spatial-temporal patterns of GPP, the standardized precipitation evapotranspiration index (SPEI), and the vapor pressure deficit (VPD) in China from 2001 to 2020 and examined the relationship between GPP and water deficit/drought for different vegetation types. The results revealed that SPEI and GPP were positively correlated over approximately 70.7% of the total area, and VPD was negatively correlated with GPP over about 66.2% of the domain. Furthermore, vegetation productivity was more negatively affected by water deficit in summer and autumn. During periods of drought, the greatest negative impact was on deciduous forests and croplands, and woody savannas were the least impacted. This research provides a scientific reference for developing mitigation and adaptation measures to lessen the impact of drought disasters under a changing climate.

Background This study sought to examine the associations between cardiometabolic indices and the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) as well as its progression to liver fibrosis. Methods This study comprised 25,366 subjects aged 18 years and older, free of MASLD at baseline, from the Dalian Health Management Cohort (DHMC). Cardiometabolic indices include cardiometabolic index (CMI), atherogenic index of plasma (AIP), triglyceride glucose (TyG), triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC) and triglyceride glucose-waist height ratio (TyG-WHtR). All participants were categorized into quartile groups based on cardiometabolic indices. Cox proportional hazards regression models and restricted cubic splines were employed to examine the relationship between cardiometabolic indices and the incidence of MASLD as well as its progression to liver fibrosis, and analyses were performed between different subgroups. Mediation analysis was employed to explore how obesity and inflammation serve as mediators in the connection between cardiometabolic indices and MASLD. To evaluate the predictive ability of cardiometabolic indices for the onset of MASLD, the time-dependent receiver operating characteristic (ROC) curve was utilized. Results A total of 5378 (21.2%) individuals developed MASLD during the follow-up period of 82,445 person-years. Multivariates Cox regression analyses showed that participants in the highest quartile of cardiometabolic indices had greater risk of MASLD than those in the lowest quartile (CMI: HR = 6.11, 95% CI 5.45–6.86; AIP: HR = 4.58, 95% CI 4.11–5.10; TyG: HR = 3.55, 95% CI 3.21–3.92; TyG-BMI: HR = 13.55, 95% CI 11.80–15.57; TyG-WC: HR = 12.52, 95% CI 10.93–14.34; TyG-WHtR: HR = 11.37, 95% CI 9.96–12.98). TyG-BMI (HR = 1.36, 95% CI 1.18–1.57), but not other cardiometabolic indices, was associated with liver fibrosis. Mediation analysis indicated that BMI mediated 40.4%, 33.2%, 36.5%, − 10.4%, 37.4%, 48.5% of the associations between CMI, AIP, TyG, TyG-BMI, TyG-WC, TyG-WHtR and MASLD. Time-dependent ROC curves demonstrated that TyG-BMI had a superior predictive ability for MASLD onset compared to other indicators. Conclusions The risk of developing MASLD increases as the level of cardiometabolic indices increases. Obesity may serve as a mediating factor in the aforementioned association. TyG-BMI showed the strongest association with the onset of MASLD and its progression to liver fibrosis, proved to be outperformed other cardiometabolic indicators, and could be the best clinical non-invasive biomarker for early screening of MASLD and liver fibrosis.

Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI r2: 0.47~0.86, SIF r2: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIFyield) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology.

To investigate the relationship between SUA-related ratios [the SUA-to-creatinine ratio (UCR) and the SUA-to-high-density lipoprotein cholesterol ratio (UHR)] and the risk of new-onset metabolic dysfunction-associated steatotic liver disease (MASLD) prospectively. In this study, data from 37,575 patients from the Dalian Health Management Cohort (DHMC) were analysed. A restricted cubic spline was used to analyse the nonlinear relationship between the SUA-related ratios and MASLD. Generalized additive mixed models were used to evaluate the interaction of SUA with SCr and HDL-C levels. Cox proportional risk modelling was used to explore the relationships between SUA-related ratios and MASLD scores. Results were validated through subgroup and sensitivity analyses. Receiver operating characteristic curves and decision curve analysis evaluated predictive utility. During follow-up (mean 3.20 years), 891 (2.37%) developed lean MASLD and 7,043 (18.74%) nonlean MASLD. Higher UCR and UHR were associated with greater cumulative risk (log-rank test P  = 0.001). Each 1.0-SD increase in UCR and UHR conferred 23% ( HR : 1.23, 95% CI : 1.21–1.26) and 28% ( HR : 1.28, 95% CI : 1.24–1.33) greater MASLD risk, respectively. Nonlinear relationships were observed ( P nonlinearity <0.001). The results of the ROC curves indicate C statistics of 0.773 and 0.769, respectively, with the incorporation of UCR and UHR into the base model. Elevated UCR and UHR independently predict MASLD incidence, demonstrating utility for risk stratification in both lean and nonlean populations.

Satellite-estimated solar-induced chlorophyll fluorescence (SIF) is proven to be an effective indicator for dynamic drought monitoring, while the capability of SIF to assess the variability of dryland vegetation under water and heat stress remains challenging. This study presents an analysis of the responses of dryland vegetation to the worst extreme drought over the past two decades in Australia, using multi-source spaceborne SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) and TROPOspheric Monitoring Instrument (TROPOMI). Vegetation functioning was substantially constrained by this extreme event, especially in the interior of Australia, in which there was hardly seasonal growth detected by neither satellite-based observations nor tower-based flux measurements. At a 16-day interval, both SIF and enhanced vegetation index (EVI) can timely capture the reduction at the onset of drought over dryland ecosystems. The results demonstrate that satellite-observed SIF has the potential for characterizing and monitoring the spatiotemporal dynamics of drought over water-limited ecosystems, despite coarse spatial resolution coupled with high-retrieval noise as compared with EVI. Furthermore, our study highlights that SIF retrieved from TROPOMI featuring substantially enhanced spatiotemporal resolution has the promising capability for accurately tracking the drought-induced variation of heterogeneous dryland vegetation.

This study aimed to determine whether remnant cholesterol (RC) and its variability can predict the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) independently of low-density lipoprotein cholesterol (LDL-C) levels. A longitudinal cohort study involving 43,065 participants who underwent at least two physical examinations was conducted. This study used Cox proportional hazards models to assess the relationships among RC quartile levels (Q1–Q4), visit-to-visit variability, and the risk of MASLD. This variability was quantified using several metrics: standard deviation (SD), logSD, average real variability (ARV), logARV, mean absolute deviation (MAD), and logMAD. Concurrently, this study utilized a combined analysis of RC and LDL-C groups to assess the independent risk of MASLD associated with RC. During a mean visit-to-visit of 3.19 years (SD 2.06 years), 8374 patients (19.45%) developed MASLD. Compared with Q1, Q4 was associated with a significantly greater risk of MASLD (hazard ratio [ HR ] 1.309, 95% confidence interval [ CI ] 1.220–1.403, P  < 0.001). The fully adjusted Cox model revealed that the HRs of SD, logSD, ARV, logARV, MAD and logMAD were 1.400 (95% CI 1.305–1.502), 1.278 (95% CI 1.188–1.374), 1.152 (95% CI 1.079–1.229), 1.183 (95% CI 1.140–1.227), 1.578 (95% CI 1.433–1.737) and 1.263 (95% CI 1.175–1.358), respectively. In both LDL-C subgroups (≥ 3.4 mmol/L and < 3.4 mmol/L), high baseline RC was associated with elevated MASLD risk ( HR 1.208, 95% CI 1.148–1.270, P  < 0.001; HR 1.246, 95% CI 1.129–1.374, P  < 0.001). RC levels were independently associated with MASLD in healthy individuals, irrespective of LDL-C level. The variability of RC during visit-to-visit periods provides a predictive marker for identifying individuals at heightened risk of MASLD.

Human obesity is the fifth leading cause of global mortality. Fat mass loss and maintenance are central challenges for obesity management. In contrast, birds exhibit modest weight gain and limited fat accumulation due to rapid fat utilization as flight fuel. The physiology of this adaptation remained a mystery for a century. Here we show that cross-species single-nucleus RNA-sequencing analysis revealed high GCGR expression levels in avian adipocytes, while minimal in the adipose tissue of other vertebrates. Avian GCGR employs a unique rapid fat utilization mechanism for retaining a light body. Avian GCGR or other constitutively active GCGR variants (human GCGR H339R ) expressed in white adipose tissue of male mice with obesity effectively promoted fat mobilization and sustained body weight loss, with decreased food intake partially contributing to the observed weight reduction. We suggest that avian GCGR plays this crucial role for fat utilization and may offer therapeutic potential for human obesity. Birds uniquely exhibit high expression of constitutively active GCGR in white adipose tissue (WAT) enhancing lipid metabolism, WAT browning, and weight loss in mice. A naturally occurring human GCGRH339R mutation mimics this avian-like metabolism, suggesting therapeutic potential for obesity

Cities are increasingly recognizing the benefits of incorporating urban greening strategies into their planning and design to improve sustainability and livability. However, the specific contribution of tree versus nontree vegetation has not been adequately studied in the context of urban greening and rapid urbanization. In this study, we investigated the spatiotemporal variations of urban tree and nontree coverage in China during 2000–2020 by using satellite observations. Results show the nationwide mean urban tree coverage increased by 0.073 ± 0.511% per year (mean ± 1 standard deviation), while nontree vegetation coverage decreased by 0.584 ± 1.022% per year. We found that the majority of mega- and large cities had a contrasting vegetation pattern, with significantly ascending trends in both tree and nontree coverages in urban core areas but descending trends in peri-urban areas. These trends were positively associated with multiple greenness indices, suggesting the importance of the vegetation structure for growth and productivity in urban areas. This study highlights the predominance of enhancing vegetation growth in urban areas primarily driven by significantly increasing tree cover in China, and can further serve as a reference for global vegetation study.