Revisiting large-scale interception patterns constrained by a synthesis of global experimental data

Rainfall interception loss remains one of the most uncertain fluxes in the global water balance, hindering water management in forested regions and precluding an accurate formulation in climate models. Here, a synthesis of interception loss data from past field experiments conducted worldwide is performed, resulting in a meta-analysis comprising 166 forest sites and 17 agricultural plots. This meta-analysis is used to constrain a global process-based model driven by satellite-observed vegetation dynamics, potential evaporation and precipitation. The model considers sub-grid heterogeneity and vegetation dynamics and formulates rainfall interception for tall and short vegetation separately. A global, 40-year (1980–2019), 0.1∘ spatial resolution, daily temporal resolution dataset is created, analysed and validated against in situ data. The validation shows a good consistency between the modelled interception and field observations over tall vegetation, both in terms of correlations and bias. While an underestimation is found in short vegetation, the degree to which it responds to in situ representativeness errors and difficulties inherent to the measurement of interception in short vegetated ecosystems is unclear. Global estimates are compared to existing datasets, showing overall comparable patterns. According to our findings, global interception averages to 73.81 mm yr−1 or 10.96 × 103 km3 yr−1, accounting for 10.53 % of continental rainfall and approximately 14.06 % of terrestrial evaporation. The seasonal variability of interception follows the annual cycle of canopy cover, precipitation, and atmospheric demand for water. Tropical rainforests show low intra-annual vegetation variability, and seasonal patterns are dictated by rainfall. Interception shows a strong variance among vegetation types and biomes, supported by both the modelling and the meta-analysis of field data. The global synthesis of field observations and the new global interception dataset will serve as a benchmark for future investigations and facilitate large-scale hydrological and climate research.</p

The Prevalence and Risk Factors of Diabetic Retinopathy: Screening and Prophylaxis Project in 6 Provinces of China.

Purpose: To investigate the prevalence and associated factors of diabetic retinopathy (DR) and advanced DR in Chinese adults with diabetes mellitus (DM). Patients and Methods: A cross-sectional study was performed on 4831 diabetic patients from 24 hospitals from April 2018 to July 2020. Non-mydriatic fundus of patients were interpreted by an artificial intelligence (AI) system. Fundus photos that were unsuitable for AI interpretation were interpreted by two ophthalmologists trained by one expert ophthalmologist at Beijing Tongren Hospital. Medical history, height, weight, body mass index (BMI), glycosylated hemoglobin (HbA1c), blood pressure, and laboratory examinations were recorded. Results: A total of 4831 DM patients were included in this study. The prevalence of DR and advanced DR in the diabetic population was 31.8% and 6.6%, respectively. In multiple logistic regression analysis, male (odds ratio [OR], 1.39), duration of diabetes (OR, 1.05), HbA1c (OR, 1.11), farmer (OR, 1.39), insulin treatment (OR, 1.61), region (northern, OR, 1.78; rural, OR, 6.96), and presence of other diabetic complications (OR: 2.03) were associated with increased odds of DR. The factors associated with increased odds of advanced DR included poor glycemic control (HbA1c > 7.0%) (OR, 2.58), insulin treatment (OR, 1.73), longer duration of diabetes (OR, 3.66), rural region (OR, 4.84), and presence of other diabetic complications (OR, 2.36), but overweight (BMI > 25 kg/m2) (OR, 0.61) was associated with reduced odds of advanced DR. Conclusion: This study shows that the prevalence of DR is very high in Chinese adults with DM, highlighting the necessity of early diabetic retinal screening

Efficacy of calcium dobesilate in treating Chinese patients with mild-to-moderate non-proliferative diabetic retinopathy (CALM-DR): protocol for a single-blind, multicentre, 24-armed cluster-randomised, controlled trial.

INTRODUCTION Calcium dobesilate (CaD) has been used in the treatment of diabetic retinopathy (DR) due to its potential in protecting against retinal vascular damage. However, there is limited evidence exploring its efficacy in combating DR progression. This study is aimed at evaluating whether CaD could prevent DR progression into an advanced stage among Chinese patients with mild-to-moderate non-proliferative DR (NPDR). METHODS AND ANALYSIS This study is a single-blind, multicentre, cluster-randomised, controlled superiority trial. A total of 1272 patients with mild-to-moderate NPDR will be enrolled and randomly assigned at a 1:1 ratio into the control group (conventional treatment group) and the intervention group (conventional treatment plus CaD (500 mg three times per day) for 12 months). Patients will be followed at 1, 3, 6 and 12 months after randomisation and receiving treatments, with the severity of DR assessed by the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. The primary endpoint is the progression of DR during follow-up, which is defined as an increase of two or more steps in the ETDRS scale. The secondary endpoints include the concomitant changes in visual acuity, presence, number, location and type of retinal lesions, and retinal blood vessel diameter as well as the arteriovenous ratio at different visits. ETHICS AND DISSEMINATION Each local ethics committee (first Vote: Ethical Review Committees of Zhongda Hospital of Southeast University (2019ZDSYLL132-P01)) has approved the study. The results will be published in high impact peer-reviewed scientific journals aimed at the general reader. TRIAL REGISTRATION NUMBERS NCT04283162

ABC-transporter upregulation mediates resistance to the CDK7 inhibitors THZ1 and ICEC0942.

The CDK7 inhibitors (CDK7i) ICEC0942 and THZ1, are promising new cancer therapeutics. Resistance to targeted drugs frequently compromises cancer treatment. We sought to identify mechanisms by which cancer cells may become resistant to CDK7i. Resistant lines were established through continuous drug selection. ABC-transporter copy number, expression and activity were examined using real-time PCR, immunoblotting and flow cytometry. Drug responses were measured using growth assays. ABCB1 was upregulated in ICEC0942-resistant cells and there was cross-resistance to THZ1. THZ1-resistant cells upregulated ABCG2 but remained sensitive to ICEC0942. Drug resistance in both cell lines was reversible upon inhibition of ABC-transporters. CDK7i response was altered in adriamycin- and mitoxantrone-resistant cell lines demonstrating ABC-transporter upregulation. ABCB1 expression correlated with ICEC0942 and THZ1 response, and ABCG2 expression with THZ2 response, in a panel of cancer cell lines. We have identified ABCB1 upregulation as a common mechanism of resistance to ICEC0942 and THZ1, and confirmed that ABCG2 upregulation is a mechanism of resistance to THZ1. The identification of potential mechanisms of CDK7i resistance and differences in susceptibility of ICEC0942 and THZ1 to ABC-transporters, may help guide their future clinical use

Preliminary utility of the retrospective IMERG precipitation product for large-scale drought monitoring over Mainland China

This study evaluated the suitability of the latest retrospective Integrated Multi-satellitE Retrievals for Global Precipitation Measurement V06 (IMERG) Final Run product with a relatively long period (beginning from June 2000) for drought monitoring over mainland China. First, the accuracy of IMERG was evaluated by using observed precipitation data from 807 meteorological stations at multiple temporal (daily, monthly, and yearly) and spatial (pointed and regional) scales. Second, the IMERG-based standardized precipitation index (SPI) was validated and analyzed through statistical indicators. Third, a light-extreme-light drought-event process was adopted as the case study to dissect the latent performance of IMERG-based SPI in capturing the spatiotemporal variation of drought events. Our results demonstrated a sufficient consistency and small error of the IMERG precipitation data against the gauge observations with the regional mean correlation coefficient (CC) at the daily (0.7), monthly (0.93), and annual (0.86) scales for mainland China. The IMERG possessed a strong capacity for estimating intra-annual precipitation changes; especially, it performed well at the monthly scale. There was a strong agreement between the IMERG-based SPI values and gauge-based SPI values for drought monitoring in most regions in China (with CCs above 0.8). In contrast, there was a comparatively poorer capability and notably higher heterogeneity in the Xinjiang and Qinghai-Tibet Plateau regions with more widely varying statistical metrics. The IMERG featured the advantage of satisfactory spatiotemporal accuracy in terms of depicting the onset and extinction of representative drought disasters for specific consecutive months. Furthermore, the IMERG has obvious drought monitoring abilities, which was also complemented when compared with the Precipitation Estimation from the Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) 3B42V7. The outcomes of this study demonstrate that the retrospective IMERG can provide a more competent data source and potential opportunity for better drought monitoring utility across mainland China, particularly for eastern China

Quantifying multi-source uncertainties in multi-model predictions using the Bayesian model averaging scheme

This study focuses on a quantitative multi-source uncertainty analysis of multi-model predictions. Three widely used hydrological models, i.e., Xinanjiang (XAJ), hybrid rainfall–runoff (HYB), and HYMOD (HYM), were calibrated by two parameter optimization algorithms, namely, shuffled complex evolution (SCE-UA) method and shuffled complex evolution metropolis (SCEM-UA) method on the Mishui basin, south China. The input uncertainty was quantified by utilizing a normally distributed error multiplier. The ensemble simulation sets calculated from the three models were combined using the Bayesian model averaging (BMA) method. Results indicate the following. (1) Both SCE-UA and SCEM-UA resulted in good and comparable streamflow simulations. Specifically, the SCEM-UA implied parameter uncertainty and provided the posterior distribution of the parameters. (2) In terms of the precipitation input uncertainty, precision of streamflow simulations did not improve remarkably. (3) The BMA combination not only improved the precision of streamflow prediction, but also quantified the uncertainty bounds of the simulation. (4) The prediction interval calculated using the SCEM-UA-based BMA combination approach appears superior to that calculated using the SCE-UA-based BMA combination for both high flows and low flows. Results suggest that the comprehensive uncertainty analysis by using the SCEM-UA algorithm and BMA method is superior for streamflow predictions and flood forecasting

Efficacy of calcium dobesilate in treating Chinese patients with mild-to-moderate non-proliferative diabetic retinopathy (CALM-DR): protocol for a single-blind, multicentre, 24-armed cluster-randomised, controlled trial

Introduction Calcium dobesilate (CaD) has been used in the treatment of diabetic retinopathy (DR) due to its potential in protecting against retinal vascular damage. However, there is limited evidence exploring its efficacy in combating DR progression. This study is aimed at evaluating whether CaD could prevent DR progression into an advanced stage among Chinese patients with mild-to-moderate non-proliferative DR (NPDR).Methods and analysis This study is a single-blind, multicentre, cluster-randomised, controlled superiority trial. A total of 1272 patients with mild-to-moderate NPDR will be enrolled and randomly assigned at a 1:1 ratio into the control group (conventional treatment group) and the intervention group (conventional treatment plus CaD (500 mg three times per day) for 12 months). Patients will be followed at 1, 3, 6 and 12 months after randomisation and receiving treatments, with the severity of DR assessed by the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. The primary endpoint is the progression of DR during follow-up, which is defined as an increase of two or more steps in the ETDRS scale. The secondary endpoints include the concomitant changes in visual acuity, presence, number, location and type of retinal lesions, and retinal blood vessel diameter as well as the arteriovenous ratio at different visits.Ethics and dissemination Each local ethics committee (first Vote: Ethical Review Committees of Zhongda Hospital of Southeast University (2019ZDSYLL132-P01)) has approved the study. The results will be published in high impact peer-reviewed scientific journals aimed at the general reader.Trial registration numbers NCT04283162

Spatial and Temporal Variability in Precipitation Concentration over Mainland China, 1961–2017

Understanding the patterns and mechanisms of precipitation variations is important for assessing flood and drought risks and for ensuring sustainable water use. Here, we analyzed the characteristics of annual precipitation changes in eight subregions of China using the Mann&#8722;Kendall test based on daily precipitation data from 774 rain gauge stations during 1961&#8722;2017. Then, we used the monthly precipitation concentration index (PCI) and daily concentration index (CI) to analyze precipitation concentrations. The results are as follows: (1) PCI and CI in northern China generally decreased with time, indicating a uniform precipitation distribution. Notably, the annual precipitation increased significantly in Xinjiang and the Qinghai-Tibet Plateau, which could alleviate future drought. (2) PCI increased and CI decreased in the plain regions of the Yangtze River and Southeast China, exhibiting high CI values with marked increases of annual precipitation. Such heavy rainfall events combined with high rainfall concentrations could increase the flood risk. (3) A significant PCI increase and CI decrease occurred in Southwest China, where annual precipitation decreased significantly. Regular rainfall decreased notably, which could increase the likelihood of drought hazards. (4) Overall, both indices showed negative trends at most stations; precipitation distribution was generally more uniform over China. These findings improve our understanding of extreme rainfall evolution and water resource distribution over China. Furthermore, PCI and CI can serve as warning tools for disaster control and water resource management

Evolution of Hydrological Drought in Human Disturbed Areas: A Case Study in the Laohahe Catchment, Northern China

A case study on the evolution of hydrological drought in nonstationary environments is conducted over the Laohahe catchment in northern China. Using hydrometeorological observations during 1964–2009, meteorological and hydrological droughts are firstly analyzed with the threshold level method. Then, a comprehensive analysis on the changes within the catchment is conducted on the basis of hydrological variables and socioeconomic indices, and the whole period is divided into two parts: the undisturbed period (1964–1979) and the disturbed period (1980–2009). A separating framework is further introduced to distinguish droughts induced by different causes, that is, the naturalized drought and human-induced drought. Results showed that human activities are more inclined to play a negative role in aggravating droughts. Drought duration and deficit volume in naturalized conditions are amplified two to four times and three to eight times, respectively, when human activities are involved. For the two dry decades 1980s and 2000s, human activities have caused several consecutive drought events with rather long durations (up to 29 months). These results reflect the considerable impacts of human activities on hydrological drought, which could provide some theoretical support for local drought mitigation and water resources management

Evaluation and Hydrological Application of CMADS Reanalysis Precipitation Data against Four Satellite Precipitation Products in the Upper Huaihe River Basin, China

Satellite- and reanalysis-based precipitation products are important data source for precipitation, particularly in areas with a sparse gauge network. Here, five open-access precipitation products, including the newly released China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) reanalysis dataset and four widely used bias-adjusted satellite precipitation products [SPPs; i.e., Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 Version 7 (TMPA 3B42V7), Climate Prediction Center (CPC) morphing technique satellite-gauge blended product (CMORPH-BLD), Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR)], were assessed. These products were first compared with the gauge observed data collected for the upper Huaihe River basin, and then were used as forcing data for streamflow simulation by the Xin’anjiang (XAJ) hydrological model under two scenarios with different calibration procedures. The performance of CMADS precipitation product for the Chinese mainland was also assessed. The results show that: (1) for the statistical assessment, CMADS and CMORPH-BLD perform the best, followed by TMPA 3B42V7, CHIRPS, and PERSIANN-CDR, among which the correlation coefficient (CC) and root-mean-square error (RMSE) values of CMADS are optimal, although it exhibits certain significant negative relative bias (BIAS; −22.72%); (2) CMORPH-BLD performs the best in capturing and detecting rainfall events, while CMADS tends to underestimate heavy and torrential precipitation; (3) for streamflow simulation, the performance of using CMADS as input is very good, with the highest Nash-Sutcliffe efficiency (NSE) values (0.85 and 0.75 for calibration period and validation period, respectively); and (4) CMADS exhibits high accuracy in eastern China while with significant negative BIAS, and the performance declines from southeast to northwest. The statistical and hydrological evaluations show that CMADS and CMORPH-BLD have high potential for observing precipitation. As high negative BIAS values showed up in CMADS evaluation, further study on the error sources from original data and calibration algorithms is necessary. This study can serve as a reference for selecting precipitation products in data-scarce regions with similar climates and topography in the Global Precipitation Measurement (GPM) era