Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) are essential land variables for environmental monitoring and climate modeling. High resolution (<= 30 m) gap-free LAI/FAPAR products are in high demand, but frequent cloud contaminations in optical data cause substantial data gaps. To address the ill-posed nature of land surface variable inversion by leveraging time-series information instead of traditional pixel-based inversions, this study presents a temporal deep learning model that jointly estimates gap-free, 20 m/5-day LAI/FAPAR from integrated Landsat-8/9 and Sentinel-2 sequential observations, denoted as High-resolution Global LAnd Surface Satellite (Hi-GLASS) LS20 LAI/FAPAR products, part of the Hi-GLASS level 3 product suite. A hybrid Bidirectional LSTM with an attention mechanism that synergizes multiple satellite observations effectively under different cloud cover conditions was trained on representative samples derived from GLASS LAI/FAPAR and 30 m land cover data, accounting for site heterogeneity. The algorithm was directly validated against 4046 in-situ measurements from 29 validation sites, achieving an R2 of 0.79 for LAI and 0.86 for FAPAR, Root Mean Square Error (RMSE) of 1.0 for LAI and 0.155 for FAPAR. Intercomparisons with existing high and coarse resolution products showed superior continuity and accuracy. To implement the model, we constructed Landsat and Sentinel-2 Analysis Ready Data (LSARD) and generated the first 20 m gap-free LAI/ FAPAR product over China from 2018 to 2023 (www.glasss.hku.hk). We also provide a web tool on Google Colab that can calculate LAI/FAPAR for any region of interest. Unlike methods that rely solely on clear-sky pixels from a single sensor, our approach enables spatiotemporally continuous and physically consistent LAI/FAPAR estimates from multiple sensors.

The ontogeny of the brachiopod can be reflected by the shell outline, size, and their interconnections. As a representative early atrypid brachiopod group of the Edgewood-Cathay Fauna, the genus Eospirigerina survived the Late Ordovician mass extinction (LOME). Abundant E. putilla specimens were collected from the “Wulipo Bed” limestone (upper Hirnantian, Ordovician). As a typical Eospirigerina dominated Edgewood-Cathay Fauna from the upper Hirnantian (Ordovician) of northeastern Yunnan, China, the quantitative ontogenetic study of E. putilla can provide a better understanding of its palaeoecology. Using the image contour recognition, we develop an automated measuring tool, test its robustness, and measure 554 complete and silicified specimens of E. putilla. An abnormal palaeoenvironment that the E. putilla population inhabited in is suggested by the high mortality of small individuals indicated by the size-frequency histogram and survivorship curve. Using quadratic polynomial regression, the negative allometric pattern of the shell length to width in the population is recognized. Using geometric morphometrics with semi-landmarks for 51 specimens from the population, the ontogenic trends are mapped by PCA with thin-plate splines, in which the heterochronic shifts may occur from an elongate shell with relatively larger ventral cardinal area and delthyrium to wider outline and smaller beak. Such heterochronic development is possibly caused by the unstable and stressful environment immediately after the LOME.

Snow albedo is a key geophysical parameter that controls the energy exchanges between the atmosphere and Earth's surfaces and has been widely utilized in climatic and environmental change studies. However, recent studies have demonstrated that current albedo satellite products still have large uncertainties in snow-covered areas. In this study, we estimated the blue-sky shortwave albedo of snow surfaces using the eXtreme Gradient Boosting (XGBoost) algorithm with Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance values, ERA-5 land reanalysis snow parameters (e.g., snow cover, snow density and snow depth water equivalent) and in situ measurements. In the XGBoost model, the MODIS MCD43 albedo values were input as prior knowledge, and the random sample validation results showed that the R2 2 and root mean square error (RMSE) values of this model were approximately 0.953 and 0.044, respectively. The typical sites for independent validation were subjected to in situ measurements at the UPE_L, AWS5, and CA_ARB sites. Finally, the retrieved XGBoost albedo values were compared with the official NASA MODIS (MCD43, collection 6), the Global Land Surface Satellite (GLASS), and the National Oceanic and Atmospheric Administration (NOAA) Visible Infrared Imaging Radiometer Suite (VIIRS) SURFALB albedo products. The validation results indicated that the proposed approach achieved much greater accuracy (RMSE = 0.052, bias = 0.002) than did the corresponding official MODIS (RMSE = 0.087, bias =-0.033), GLASS (RMSE = 0.089, bias =-0.031) and VIIRS SURFALB albedo (RMSE = 0.100, bias =-0.032) products. The improved shortwave albedo captured the rapid temporal changes in surface snow conditions.

The root of Glehnia littoralis is used as a good traditional Chinese medicine. The aerial part of G. littoralis is often discarded as waste in China, although it is very abundant, which results in waste of resources. In order to utilize the resources, the essential oils of the aerial part and root were isolated from G. littoralis, separately named as GLA and GLR. Their phytochemical profile, antimicrobial, anti-inflammatory and antioxidant effects were investigated. The results showed that the concentrations of GLA and GLR were separately 0.933 g/kg and 1.365 g/kg, and nineteen components were identified from both oils. Among them, panaxynol was the common component with a content of 38.21% in GLA and 74.02% in GLR. GLA potently inhibited F. solani and F. incarnatum, GLR strongly suppressed S. albus. GLA and GLR reduced the production of NO, IL-1β, IL‐6, TNF-α in LPS-stimulated RAW 264.7 macrophages. This study provided a theoretical basis for the utilization of the aboveground parts of G. littoralis.

Land surface all-wave net radiation (Rn) is crucial in determining Earth's climate by contributing to the surface radiation budget. This study evaluated seven satellite and three reanalysis long-term land surface Rn products under different spatial scales, spatial and temporal variations, and different conditions. The results showed that during 2000-2018, Global Land Surface Satellite Product (GLASS)-Moderate Resolution Imaging Spectroradiometer (MODIS) performed the best (RMSE=25.54 Wm-2, bias=−1.26 Wm-2), followed by ERA5 (the fifth-generation of European Centre for Medium-Range Weather Forecast Reanalysis) (RMSE=32.17 Wm-2, bias=−4.88 Wm-2) and GLASS-AVHRR (Advanced Very-High-Resolution Radiometer) (RMSE=33.10 Wm-2, bias=4.03 Wm-2). During 1983-2018, GLASS-AVHRR and ERA5 ranked top and performed similarly, with RMSE values of 31.70 and 33.08 Wm-2 and biases of −4.56 and 3.48 Wm-2, respectively. The averaged multi-annual mean Rn over the global land surface of satellite products was higher than that of reanalysis products by about 10∼30 Wm-2. These products differed remarkably in long-term trends variations, particularly pre-2000, but no significant trends were observed. Discrepancies were more frequent in satellite data, while reanalysis products showed smoother variations. Large discrepancies were found in regions with high latitudes, reflectance, and elevation which could be attributed to input radiative components, meteorological variables (e.g., cloud properties, aerosol optical thickness), and applicability of the algorithms used. While further research is needed for detailed insights.

Vegetation, especially forest ecosystems, plays an important role in the global energy flow and material cycle. The vegetation index (VI) is an important index reflecting the dynamic change in vegetation and directly reflects the response of ecosystem to global climate change. The Greater Khingan Mountains Forest region is located in the northeast of China. It is the largest primeval forest region in China, which is well preserved and less affected by human activities. It is of great significance to study the driving mechanism of forest vegetation change for future ecological prediction and management. In this study, GIMMS NDVI data were used to explore the characteristics of nonlinear temporal and spatial variation of NDVI in the Greater Khingan Mountains and its relationship with climatic factors. Firstly, the EEMD method was used to analyze the characteristics of vegetation change in the study area from 1982 to 2015. Secondly, the relationship between vegetation change and climate was discussed by using precipitation and temperature data. The results showed that the following: (1) from 1982 to 2015, the interannual change in vegetation in the Greater Khingan Mountains presented a trend of slow fluctuation and gradual decrease (SLOPE = −0.1645/10,000, p < 0.01). (2) The spatial distribution of vegetation change had obvious geographical differences, and in the central region, the overall distribution characteristics had an obvious browning trend, and in the northwest and southeast, the distribution characteristics had a green trend. (3) The correlation analysis results of vegetation change and climate factors showed that NDVI change was significantly positively correlated with temperature and precipitation; additionally, NDVI change was more correlated with temperature with a range of 0.8–1 than precipitation. (4) The results of vegetation attribution analysis in four typical areas of the study area showed that the following: the coniferous forest area has good cold tolerance and drought tolerance, the correlation between vegetation change and climate factors (temperature, precipitation) was not the strongest, which was 0.537 and 0.828, respectively. The ecological transition area and the broad-leaved forest area, which was located at the edge of the study area, have relatively fragile ecosystems, showed a strong correlation with precipitation, and the correlation coefficients reached 0.670 and 0.632, respectively. The surface water resources provide favorable conditions for the growth of vegetation, it showed a weak correlation with precipitation, and the correlation coefficient was 0.5349.

Motivated by the lack of long-term global soil moisture products with both high spatial and temporal resolutions, a global 1 km daily spatiotemporally continuous soil moisture product (GLASS SM) was generated from 2000 to 2020 using an ensemble learning model (eXtreme Gradient Boosting – XGBoost). The model was developed by integrating multiple datasets, including albedo, land surface temperature, and leaf area index products from the Global Land Surface Satellite (GLASS) product suite, as well as the European reanalysis (ERA5-Land) soil moisture product, in situ soil moisture dataset from the International Soil Moisture Network (ISMN), and auxiliary datasets (Multi-Error-Removed Improved-Terrain (MERIT) DEM and Global gridded soil information (SoilGrids)). Given the relatively large-scale differences between point-scale in situ measurements and other datasets, the triple collocation (TC) method was adopted to select the representative soil moisture stations and their measurements for creating the training samples. To fully evaluate the model performance, three validation strategies were explored: random, site independent, and year independent. Results showed that although the XGBoost model achieved the highest accuracy on the random test samples, it was clearly a result of model overfitting. Meanwhile, training the model with representative stations selected by the TC method could considerably improve its performance for site- or year-independent test samples. The overall validation accuracy of the model trained using representative stations on the site-independent test samples, which was least likely to be overfitted, was a correlation coefficient (R) of 0.715 and root mean square error (RMSE) of 0.079 m3 m−3. Moreover, compared to the model developed without station filtering, the validation accuracies of the model trained with representative stations improved significantly for most stations, with the median R and unbiased RMSE (ubRMSE) of the model for each station increasing from 0.64 to 0.74 and decreasing from 0.055 to 0.052 m3 m−3, respectively. Further validation of the GLASS SM product across four independent soil moisture networks revealed its ability to capture the temporal dynamics of measured soil moisture (R=0.69–0.89; ubRMSE = 0.033–0.048 m3 m−3). Lastly, the intercomparison between the GLASS SM product and two global microwave soil moisture datasets – the 1 km Soil Moisture Active Passive/Sentinel-1 L2 Radiometer/Radar soil moisture product and the European Space Agency Climate Change Initiative combined soil moisture product at 0.25∘ – indicated that the derived product maintained a more complete spatial coverage and exhibited high spatiotemporal consistency with those two soil moisture products. The annual average GLASS SM dataset from 2000 to 2020 can be freely downloaded from https://doi.org/10.5281/zenodo.7172664 (Zhang et al., 2022a), and the complete product at daily scale is available at http://glass.umd.edu/soil_moisture/ (last access: 12 May 2023).

Strata equivalent to the majority of the Ordovician shallow-water sediments in South China occur in the western Yangtze region (present-day southwestern Sichuan and northeastern Yunnan, Southwest China), but remain to be properly documented largely due to their inaccessibility. Our research in the past decade has led to the recognition of spatial and temporal patterns, and hence a substantial stratigraphic revision of these rocks, with part of the results having been published in a series of papers. Here, we outline a unified and refined Ordovician stratigraphy of the region built chiefly on a summary of these new data, presenting a robust timeframe for exploring the environmental and biotic events during the Ordovician on a basin-wide scale in South China.

Introduction: Kurarinone is a potential natural compound with antitumour activity. The effect and mechanism of kurarinone against hepatocellular carcinoma (HCC) remain unclear.Method: Network pharmacology and molecular docking were applied to characterize the mechanism of kurarinone against HCC. The potential targets of kurarinone were mapped with HCC-related targets to probe the candidate proteins of kurarinone against HCC. The potential signaling pathways related to proteins were assessed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Molecular docking was performed to validate the binding energy between kurarinone and core targets. The effect and potential underlying mechanisms of kurarinone on HCC were experimentally validated in HepG2 cells.Results: There were 27 targets of kurarinone against HCC. The interleukin-17 signaling pathway was mostly enriched after pathway enrichment analysis. Molecular docking analysis revealed good affinity between kurarinone and the hub targets. Kurarinone significantly inhibited HepG2 cell viability and cell migration in a dosedependent manner. The expression levels of two proteins enriched in the interleukin-17 signaling pathway, S100 calcium binding protein A9 (S100A9) and mitogen-activated protein kinase 1 (MAPK1), were downregulated after stimulation with different concentrations of kurarinone in HepG2 cells.Conclusion: Network pharmacology along with molecular docking and experimental validation provided a useful approach for understanding the pharmacological mechanism and therapeutic drug development of kurarinone in HCC.

Ordovician chitinozoans are as yet inadequately documented from the western Yangtze Platform, South China. Here we present a systematic study on chitinozoans from a Middle–Upper Ordovician succession at Songliang of Qiaojia, northestern Yunnan, southwestern China. Altogether 34 species of 12 genera are identified from the upper Hungshihyen and the Huadan formations. The top of the Hungshihyen Formation yields typical Early and Middle Ordovician forms, for instance, Lagenochitina obeligis and Belonechitina chenjiawuensis, with the latter only known from the lower Darriwilian in South China, thus suggesting an early Darriwilian age for this interval. The chitinozoans recovered from the Huadan Formation include Lagenochitina prussica and Spinachitina fossensis, both are mainly confined in Katian and sometimes ranging into younger strata. This indicates an age younger than the middle to late Darriwilian previously determined for the Huadan Formation. However, conflicts exist in age assignment of the Huadan Formation based on chitinozoan and other evidence, and further work is required.

Purpose: To investigate the relationship between benign prostatic hyperplasia (BPH)/lower urinary tract symptoms (LUTS) and renal function in elderly men aged 80 years and older.Patients and Methods: We selected 389 elderly men aged 80-97 years with BPH/LUTS hospitalized at The Second Division of General Geriatrics, The First Affiliated Hospital of Zhengzhou University, between July 2018 and July 2020. In the cross-sectional study, patients were divided into the treatment (233 patients) and non-treatment (156 patients) groups based on whether they received treatment for BPH/LUTS. In the prospective self-case-control study, we included 129 of the non-treatment group patients who received oral BPH/LUTS medication and completed the 6-month outpatient follow-up. We compared prostate indicators and renal function in the cross-sectional study and baseline and after-treatment data in the prospective self-case-control study. Multiple linear regression analysis was performed for risk factors affecting renal function before and after BPH/LUTS treatment.Results: In the cross-sectional study, renal function was significantly better in the treatment group than in the non-treatment group. In the subgroup analysis of the prospective self-case-control study, renal function significantly improved after treatment among patients with hypertension and those with chronic kidney disease (CKD) 3a, but not in the entire cohort. Multivariable linear regression analysis showed that hypertension (beta=2.06, 95% CI 0.40 to 3.71) and CKD 3a (beta=17.16, 95% CI 15.53 to 18.79) were independent risk factors for creatinine differences before and after treatment, whereas hypertension (beta=-2.27, 95% CI -3.65 to -0.89), CKD 3a (beta=-11.93, 95% CI -13.29 to -10.58), and baseline prostate volume (beta=-0.11, 95% CI -0.20 to -0.02) were independent risk factors for estimated glomerular filtration rate differences before and after treatment.Conclusion: Treatment for moderate and severe BPH/LUTS can improve renal function in elderly patients with hypertension or CKD 3a.

华南上扬子区是奥陶纪末生物大灭绝研究的经典地区之一,但由于交通等因素,该区西缘(今昆明—西昌—成都之间)赫南特期浅水相沉积的时空分布规律仍不清楚.文章通过总结近年来的调查新成果与已发表资料,系统分析了研究区赫南特期地层划分对比和古地理,并取得一些新认识.在赫南特早期,研究区以含较凉水壳相动物群(TBF 1)的泥灰岩、灰岩发育为特色,统归入观音桥组(近岸相仅包含其下部).赫南特中期开始发生明显的相带分异:近岸一侧广泛发育一套含暖水壳相动物群(TBF 2)的生物碎屑灰岩,归于观音桥组上部,向远岸一侧相变为黑色笔石页岩(龙马溪组底部).至赫南特晚期,近岸的少数地区(如镇雄北部)以产出暖水壳相动物群(TBF 3)的粗碎屑沉积为特色,创名尾坝组;远岸一侧与前一时期类似,以龙马溪组底部黑色页岩沉积为代表.文章还通过综合已知数据,分别对区内赫南特早—中期和晚期古地理进行高精度重建.

The latest Ordovician Hirnantia Fauna is distributed worldwide including South China, but with very few records from the western margin of the Yangtze Platform. A silicified Hirnantia Fauna from the uppermost Tiezufeike Formation in the Laoga section, Butuo County, southwestern Sichuan, enriches the fauna’s record and warrants the recognition of the upper part of the Tiezufeike Formation as the Kuanyinchiao Bed. Etching bulk limestone samples from this level with acetic acid yielded 275 specimens of Dalmanella testudinaria, Plectothyrella crassicosta, and Hindella crassa. The population dynamics are analyzed for three successive populations in the section. Size-frequency histograms and survivorship curves indicate gradual improvement of the palaeoenvironments during the end of the Late Ordovician glaciation. The low-diversity brachiopod assemblages recognized in our study are assigned to the Dalmanella-Plectothyrella Community (DP Community) according to their dominant species. It is comparable with two other examples of DP communities, one from the neighboring Guizhou Province of Southwest China, and the other from the Baltica Region.

The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical land surface variable for carbon cycle modeling and ecological monitoring. Several global FAPAR products have been released and have become widely used; however, spatiotemporal inconsistency remains a large issue for the current products, and their spatial resolutions and accuracies can hardly meet the user requirements. An effective solution to improve the spatiotemporal continuity and accuracy of FAPAR products is to take better advantage of the temporal information in the satellite data using deep learning approaches. In this study, the latest version (V6) of the FAPAR product with a 250 m resolution was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and other information, as part of the Global LAnd Surface Satellite (GLASS) product suite. In addition, it was aggregated to multiple coarser resolutions (up to 0.25∘ and monthly). Three existing global FAPAR products (MODIS Collection 6; GLASS V5; and PRoject for On-Board Autonomy–Vegetation, PROBA-V, V1) were used to generate the time-series training samples, which were used to develop a bidirectional long short-term memory (Bi-LSTM) model. Direct validation using high-resolution FAPAR maps from the Validation of Land European Remote sensing Instrument (VALERI) and ImagineS networks revealed that the GLASS V6 FAPAR product has a higher accuracy than PROBA-V, MODIS, and GLASS V5, with an R2 value of 0.80 and root-mean-square errors (RMSEs) of 0.10–0.11 at the 250 m, 500 m, and 3 km scales, and a higher percentage (72 %) of retrievals for meeting the accuracy requirement of 0.1. Global spatial evaluation and temporal comparison at the AmeriFlux and National Ecological Observatory Network (NEON) sites revealed that the GLASS V6 FAPAR has a greater spatiotemporal continuity and reflects the variations in the vegetation better than the GLASS V5 FAPAR. The higher quality of the GLASS V6 FAPAR is attributed to the ability of the Bi-LSTM model, which involves high-quality training samples and combines the strengths of the existing FAPAR products, as well as the temporal and spectral information from the MODIS surface reflectance data and other information. The 250 m 8 d GLASS V6 FAPAR product for 2020 is freely available at https://doi.org/10.5281/zenodo.6405564 and https://doi.org/10.5281/zenodo.6430925 (Ma, 2022a, b) as well as at the University of Maryland for 2000–2021 (http://glass.umd.edu/FAPAR/MODIS/250m, last access 1 November 2022).

扬子台地西缘(今昆明—西昌—成都之间)晚奥陶世凯迪晚期地层的划分、对比与空间分布等方面仍存在诸多的不确定.本文综合新的研究成果和前人的资料,认为研究区这段地层可划归近岸白云岩相、近岸灰岩相、过渡混积相和远岸较深水相4个相带,并据此修订了前3个相带的地层框架,以实现与远岸较深水沉积(以临湘组和五峰组为代表)更高精度的对比.近岸白云岩相带以下部深灰色薄层硅质白云岩、上部薄至厚层白云岩夹含笔石碎屑岩为特色,以修订后的王家河坝组称之.近岸灰岩相带的该段地层下部为深灰色薄层硅质灰岩,上部为薄至厚层灰岩、白云质灰岩,常发育含笔石碎屑岩夹层,本文以修订后的铁足非克组称之.在过渡混积相带内,下部为深灰色薄层泥晶灰岩,常发育垂向管状遗迹化石,创名莲峰组;上部为灰岩与泥页岩不等厚互层,化石丰富,沿用大渡河组一名.同时,本文认为王家河坝组下段、铁足非克组下段和莲峰组均对比于临湘组;王家河坝组上段与五峰组可部分对比;铁足非克组上段和大渡河组均可与五峰组完全对比.在新的地层框架下,本文通过系统总结已有的资料,尝试对研究区凯迪晚期的古地理进行更高精度的复原.

Background and aims: The type 2 diabetes mellitus (T2DM) is a common comorbidity of chronic hepatitis C (CHC). This study intended to investigate the impact of direct-acting antiviral agents (DAAs)-induced sustained virological response (SVR) on glycometabolism in CHC patients with T2DM. Methods: We searched PubMed, Scopus, Web of Science, and Embase up to July 7th, 2021. Studies reporting the association between DAA-induced SVR and glycometabolism in diabetic patients were retained. Changes in glycated hemoglobin (HbA1c) and fasting plasma glucose (FPG) levels before DAA treatment and after SVR were conducted meta-analyses with random-effects models. Results: 1371 potentially relevant articles were screened. Our analysis included 16 studies with data for 5024 patients. A significant improvement was noted in glycemic control in SVR group, with a mean HbA1c reduction of 0.57% (95% CI: 0.46–0.69%; I=72.8%) and FPG reduction of 22.28mg/dL (95% CI: 13.35–31.21mg/dL; I=96.18%). Conversely, changes of HbA1c in non-SVR group were a mean increase of 0.03% (95% CI: -0.15–0.22%; I=68.75%). Subgroup analyses about HbA1c and FPG classified by study type both showed decline of the two indicators after SVR, and especially a reduction of HbA1c, 0.52% (95% CI: 0.39–0.65%; I=73.5%) in retrospective study subgroup and 0.70% (95% CI: 0.54–0.87%; I=36.15%) in prospective study subgroup, indicating lower heterogeneity in prospective studies. Egger’s test suggested publication bias in impact of DAAs on FPG, and no publication bias in impact on HbA1c. Sensitivity analyses confirmed robustness of the results. Conclusion: The glyco-metabolic control improved in terms of HbA1c and FPG level after DAA-induced SVR. However, further large and well-designed prospective cohort studies are still warranted and a prolonged follow-up is needed.

Surface air temperature (Ta), as an important climate variable, has been used in a wide range of fields such as ecology, hydrology, climatology, epidemiology, and environmental science. However, ground measurements are limited by poor spatial representation and inconsistency, and reanalysis and meteorological forcing datasets suffer from coarse spatial resolution and inaccuracy. Previous studies using satellite data have mainly estimated Ta under clear-sky conditions or with limited temporal and spatial coverage. In this study, an all-sky daily mean land Ta product at a 1 km spatial resolution over mainland China for 2003–2019 has been generated mainly from the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Global Land Data Assimilation System (GLDAS) dataset. Three Ta estimation models based on random forest were trained using ground measurements from 2384 stations for three different clear-sky and cloudy-sky conditions. The random sample validation results showed that the R2 and root-mean-square error (RMSE) values of the three models ranged from 0.984 to 0.986 and from 1.342 to 1.440 K, respectively. We examined the spatiotemporal patterns and land cover type dependences of model accuracy. Two cross-validation (CV) strategies of leave-time-out (LTO) CV and leave-location-out (LLO) CV were also used to evaluate the models. Finally, we developed the all-sky Ta dataset from 2003 to 2009 and compared it with the China Land Data Assimilation System (CLDAS) dataset at a 0.0625∘ spatial resolution, the China Meteorological Forcing Data (CMFD) dataset at a 0.1∘ spatial resolution, and the GLDAS dataset at a 0.25∘ spatial resolution. Validation accuracy of our product in 2010 was significantly better than other datasets, with R2 and RMSE values of 0.992 and 1.010 K, respectively. In summary, the developed all-sky daily mean land Ta dataset has achieved satisfactory accuracy and high spatial resolution simultaneously, which fills the current dataset gap in this field and plays an important role in the studies of climate change and the hydrological cycle. This dataset is currently freely available at https://doi.org/10.5281/zenodo.4399453 (Chen et al., 2021b) and the University of Maryland (http://glass.umd.edu/Ta_China/, last access: 24 August 2021). A sub-dataset that covers Beijing generated from this dataset is also publicly available at https://doi.org/10.5281/zenodo.4405123 (Chen et al., 2021a).

Hepatocellular carcinoma (HCC) is a malignant tumor without effective therapeutic drugs for most patients in advanced stages. Scutellariae Radix (SR) is a well-known anti-inflammatory and anticarcinogenic herbal medicine. However, the mechanism of SR against HCC remains to be clarified. In the present study, network pharmacology was utilized to characterize the mechanism of SR on HCC. The active components of SR and their targets were collected from the traditional Chinese medicine systems pharmacology database and the traditional Chinese medicine integrated database. HCC-related targets were acquired from the liver cancer databases OncoDB.HCC and Liverome. The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. Component-component target and protein-protein interaction networks were set up. A total of 143 components of SR were identified, and 37 of them were considered as candidate active components. Fifty targets corresponding to 29 components of SR were mapped with targets of HCC. Functional enrichment analysis indicated that SR exerted an antihepatocarcinoma effect by regulating pathways in cancer, hepatitis B, viral carcinogenesis, and PI3K-Akt signaling. The holistic approach of network pharmacology can provide novel insights into the mechanistic study and therapeutic drug development of SR for HCC treatment.