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Detection of safety signals based on multiple comparisons of adverse events (AEs) between two treatments in a clinical trial involves evaluations requiring multiplicity adjustment. A Bayesian hierarchical mixture model is a good solution to this problem as it borrows information across AEs within the same System Organ Class (SOC) and modulates extremes due merely to chance. However, the hierarchical model compares only the incidence rates of AEs, regardless of severity. In this article, we propose a three-level Bayesian hierarchical non-proportional odds cumulative logit model. Our model allows for testing the equality of incidence rate and severity for AEs between the control arm and the treatment arm while addressing multiplicities. We conduct simulation study to investigate the operating characteristics of the proposed hierarchical model. The simulation study demonstrates that the proposed method could be implemented as an extension of the Bayesian hierarchical mixture model in detecting AEs with elevated incidence rate and/or elevated severity. To illustrate, we apply our proposed method using the safety data from a phase III, two-arm randomized trial. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the mechanism through which rosemary essential oil treats atopic dermatitis. A dinitrochlorobenzene (DNCB)-induced atopic dermatitis mouse model was established and treated with low (1%), medium (2%), and high (4%) doses of Rosmarinus officinalis essential oil (EORO). Serum levels of interleukin (IL)−6 and tumor necrosis factor-alpha (TNF-α) in each group were determined using enzyme-linked immunosorbent assay (ELISA). Skin tissues were stained with hematoxylin-eosin and toluidine blue. We used network pharmacology and molecular docking techniques to verify the biological activity of essential proteins and their corresponding compounds in the pathway. Gas chromatography-mass spectrometry (GC-MS) was used for metabolomics analysis and multivariate statistical analysis of mouse serum to screen differential metabolites and metabolic pathway analysis. Protein expression of p-JAK1, CD4+ cells, and IL-4 in the skin tissue was detected by immunohistochemistry analysis. Protein levels of STAT3, p-STAT3, P65, and p-P65 in damaged skin tissues were detected using western blotting. The skin of mice in the model group showed different degrees of erythema, dryness, scratches, epidermal erosion and shedding, and crusting. After treatment, the serum levels of IL-6 and TNF-α in EORO group were significantly decreased, and the expression of p-JAK1,CD4 + cells, IL-4, p-P65 / P65 and p-STAT3 / STAT3 proteins in skin tissues were decreased. EORO can effectively improve DNCB-induced AD-like skin lesions in mice by regulating the JAK/STAT/NF-κB signaling pathway, thereby reducing the production of downstream arachidonic acid metabolites, inhibiting skin inflammation, and restoring epidermal barrier function. [Display omitted] [ABSTRACT FROM AUTHOR]

The melting and crystallization behaviors, morphology, and mechanical properties of polypropylene (PP)/surface-treated calcium sulfate (CaSO4) whisker (T-CSW), β-PP/T-CSW, and β-PP/polypropylene- graft-maleic anhydride (PP-g-MAH)/T-CSW composites had been investigated via differential scanning calorimetry (DSC), wide angle X-ray diffraction (WAXD), polarized light microscopy (PLM), scanning electron microscopy (SEM), and mechanical tests. We found that T-CSW was an α-nucleating agent and increased the crystallization temperatures of PP, but PP-g-MAH and high loadings of T-CSW had weakly negative effects on the crystallization rates of PP. The T-CSW restrained the formation of β-spherulites, and the spherulitic size decreased in the composites. PP-g-MAH improved the compatibility and adhesion between T-CSW and the matrix. The notched impact strength was improved, and the tensile strength was enhanced at low levels of T-CSW, while the flexural modulus was weakened for β-PP/T-CSW and β-PP/PP-g-MAH/T-CSW composites versus PP/T-CSW composites. POLYM. COMPOS., 37:2121-2132, 2016. © 2015 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

β-Polypropylene composites containing calcium carbonate treated by titanate coupling agent (T-CaCO3) and maleic anhydride grafted PP (PP- g-MAH) were prepared by melt compounding. The crystallization, morphology and mechanical properties of the composites were investigated by means of differential scanning calorimetry, wide-angle X-ray diffraction, polarized light microscopy, scanning electron microscopy and mechanical tests. It is found that both T-CaCO3 and NT-C are able to induce the formation of β-phase, and NT-C greatly increases the β content and decreases the spherulitic size of PP. PP- g-MAH facilitates the formation of β-form PP and improves the compatibility between T-CaCO3 and PP. Izod notched impact strength of β-PP/T-CaCO3 composite is higher than that of PP/T-CaCO3 composite, indicating the synergistic toughening effect of T-CaCO3 and β-PP. Incorporation of PP- g-MAH into β-PP/T-CaCO3 composite further increases the content of β-crystal PP and improves the impact strength and tensile strength when T-CaCO3 concentration is below 5 wt%. The nonisothermal crystallization kinetics of β-PP composites is well described by Jeziorny's and Mo's methods. It is found that NT-C and T-CaCO3 accelerate the crystallization rate of PP but the influence of PP- g-MAH on crystallization rate of β-PP composite is marginal. POLYM. COMPOS., 2012. © 2012 Society of Plastics Engineers [ABSTRACT FROM AUTHOR]

Why does a beneficial treatment effect on a longitudinal biomarker not translate into overall treatment benefit on survival, when the biomarker is in fact a prognostic factor of survival? In a recent exploratory data analysis in oncology, we were faced with this seemingly paradoxical result. To address this problem, we applied a theoretically principled methodology called dynamic path analysis, which allows us to perform mediation analysis with a longitudinal mediator and survival outcome. The aim of the analysis is to decompose the total treatment effect into a direct treatment effect and an indirect treatment effect mediated through a carefully constructed mediation path. The dynamic nature of the underlying methodology enables us to describe how these effects evolve over time, which can add to the mechanistic understanding of the underlying processes. In this paper, we present a detailed description of the dynamic path analysis framework and illustrate its application to survival mediation analysis using simulated and real data. The use case analysis provides clarity on the specific exploratory question of interest while the methodology generalizes to a wide range of applications in drug development where time‐to‐event is the primary clinical outcome of interest. [ABSTRACT FROM AUTHOR]

Microwaves have the advantage of penetrating vegetation and exhibit sensitivity to properties such as vegetation water content (VWC); yet, their potential utility in the fire domain is infrequently investigated. This study elucidates the different impacts of the microwave VWC index EDVI on fire radiative energy (FRE) across various biome types and the significant predictive power for high-severity fires (defined based on FRE) in mainland Southeast Asia. While EDVI exhibits lower predictive power for high severe fires compared to the commonly used fire weather indices (e.g., FWI), an enhancement is observed when these predictors are used in combination. Either by employing EDVI or fire weather indices, the predictability of fires is found to be highest over forests and lowest over croplands. Factors such as increasing human influence and fuel limitation in croplands are likely reducing the roles of VWC and weather on fires, contributing to the lower prediction skill of EDVI and fire weather. These results indicate the usefulness of microwave VWC index in fire studies. Although fire weather presents more considerable impacts on fires, the microwave VWC index seem to still provide some complementary information in fire danger assessment. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) can be affected by cloud change, while cloud‐induced bias errors in ET change remain poorly understood. Here we evaluated seven ET data sets from satellite microwave and optical models, atmospheric reanalysis and land surface models over East Asia. Results showed that although the data sets estimated ET changes overall well under mild cloud increase, all of them had a systematic overestimation (by 73.8%–159.8%) and deteriorated capability of capturing ET change under heavy cloud increase, especially over dense vegetation with large cloud cover. Overestimated incident solar radiation under clouds contributed to the deteriorated performances of ET. Cloud‐induced change in radiation and its errors played larger role in summer ET change over densely vegetated lands, while those in air temperature and relative humidity were dominant jointly over grass and barren lands. These results can serve as a reference for improving ET models and their forcing inputs under clouds. Plain Language Summary: The change of cloud cover affects terrestrial evapotranspiration (ET), which is a fundamental process in the interaction between land and the atmosphere. ET can be estimated from satellite observations, reanalysis data sets and land surface models. Knowing the cloud‐induced errors in the estimation of ET and its drivers can be very helpful for us to improve the ET modeling under the changing cloud conditions. In this study, we evaluated seven ET data sets and their forcing data from clear sky to cloudy sky conditions over East Asia. We quantified the importance of incident radiation, air temperature and relative humidity inputs in ET data sets under cloudy sky using a machine learning algorithm. Our findings revealed that all ET data sets were overestimated systematically under heavy cloud increase. Cloud‐induced change in radiation was more important over densely vegetated lands, while air temperature and relative humidity played larger roles over grass and barren lands. The result highlights the importance of cloud effects on ET estimations. Key Points: Seven evapotranspiration (ET) data sets from satellite microwave and optical models, reanalysis and land surface models were evaluated under cloud changeAll data sets overestimated the absolute ET values and cloud‐induced changes in ET under heavy cloud increase conditionsSummer ET change under clouds was dominated by radiation in the southern dense vegetation, but by temperature and humidity in grass lands [ABSTRACT FROM AUTHOR]

Understanding the change in hydrological response due to urban dynamics is important for better flood preparedness and future sustainable urban planning. This study investigated the influence of urban land cover change on spatiotemporal changes in flood peak discharge and flood volume within a rapidly urbanizing catchment located in Beijing, China. We used Landsat satellite data ranging from 1986 to 2017 to monitor and quantify urban growth. Moreover, the Hydrological Modeling System (HEC-HMS) coupled with meteorological data was utilized to examine the impact of urban growth on hydrological responses. The results revealed that major changes in land use/cover (LULC) were detected in the urban landscape, which increased from 25.22% to 65.48% of the total catchment area, while agricultural land decreased from 64.85% to 25.28% during 1986–2017. The flood peak discharge and flood volume average of the three rainstorms events reached 7.02% and 11.93%, respectively. Furthermore, the changes in flood peak discharge and flood volume were more obvious at the sub-catchment scale. These findings indicate that urban growth enhanced the possible flooding risk in the study catchment. This study improves the understanding of the isolated impacts of urbanization on flooding and provides essential information for sustainable urban planning. [ABSTRACT FROM AUTHOR]

Rosa damascena is an ancient plant with significance in both medicine and perfumery that have a variety of therapeutic properties, including antidepressant, anti-anxiety, and anti-stress effects. Rose damascena essential oil (REO) has been used to treat depression, anxiety and other neurological related disorders in Iranian traditional medicine. However, its precise mechanism of action remains elusive. The aim of this study was to investigate the impact and mechanism underlying the influence of REO on chronic unpredictable mild stress (CUMS) rats. Gas chromatography-mass spectrometry (GC-MS) technique coupling was used to analyze of the components of REO. A CUMS rat model was replicated to assess the antidepressant effects of varying doses of REO. This assessment encompassed behavioral evaluations, biochemical index measurements, and hematoxylin-eosin staining. For a comprehensive analysis of hippocampal tissues, we employed transcriptomics and incorporated weighting coefficients by means of network pharmacology. These measures allowed us to explore differentially expressed genes and biofunctional pathways affected by REO in the context of depression treatment. Furthermore, GC-MS metabolomics was employed to assess metabolic profiles, while a joint analysis in Metscape facilitated the construction of a network elucidating the links between differentially expressed genes and metabolites, thereby elucidating potential relationships and clarifying key pathways regulated by REO. Finally, the expression of relevant proteins in the key pathways was determined through immunohistochemistry and Western blot analysis. Molecular docking was utilized to investigate the interactions between active components and key targets, thereby validating the experimental results. REO alleviated depressive-like behavior, significantly elevated levels of the neurotransmitter 5-hydroxytryptamine (5-HT), and reduced hippocampal neuronal damage in CUMS rats. This therapeutic effect may be associated with the modulation of the serotonergic synapse signaling pathway. Furthermore, REO rectified metabolic disturbances, primarily through the regulation of amino acid metabolic pathways. Joint analysis revealed five differentially expressed genes (EEF1A1 , LOC729197 , ATP8A2 , NDST4 , and GAD2), suggesting their potential in alleviating depressive symptoms by modulating the serotonergic synapse signaling pathway and tryptophan metabolism. REO also modulated the 5-HT 2 A-mediated extracellular regulated protein kinases-cAMP-response element binding protein-brain-derived neurotrophic factor (ERK-CREB-BDNF) pathway. In addition, molecular docking results indicated that citronellol, geraniol and (E,E)-farnesol in REO may serve as key active ingredients responsible for its antidepressant effects. This study is the first to report that REO can effectively alleviate CUMS-induced depression-like effects in rats. Additionally, the study offers a comprehensive understanding of its intricate antidepressant mechanism from a multi-omics and multi-level perspective. Our findings hold promise for the clinical application and further development of this essential oil. [Display omitted] • The antidepressant mechanism of action of Rosa damascena essential oil may involve the modulation of the serotonergic synapse signaling pathway, which regulates the expression relevant proteins in the ERK-CREB-BDNF pathway. • Joint transcriptomics and metabolomics analyses validated that Rosa damascena essential oil regulates the tryptophan metabolic pathway. • Rosa damascena essential oil ameliorates hippocampal neuronal damage induced by CUMS and modulates neurotransmitter levels. • The key active components in Rosa damascena essential oil responsible for its antidepressant effects may include citronellol, geraniol and (E,E)-farnesol. [ABSTRACT FROM AUTHOR]

In the context of global warming, forest fires are expected to occur more frequently and intensively, and impose more significant impacts on human society, terrestrial ecosystems, and atmosphere. Most of the existing methods in monitoring large-scale forest fire are based either on satellite visible and infrared observations or weather-based indices. This work explored the advantages of a new satellite microwave-based vegetation index in monitoring forest fire occurrence and fire intensity in Northeastern Asia and Southern China. Specifically, we used satellite observations during 2002–2011 to investigate the correlation at different temporal scales between forest fire properties (fire count, FC; fire radiative power, FRP) and the vegetation water content proxy of the Microwave Emissivity Difference Vegetation Index (EDVI) derived from the Moderate Resolution Imaging Spectroradiometer and the Advanced Microwave Scanning Radiometer-EOS on Aqua satellite. The correlations were compared to that with three weather-based indices including the Fine Fuel Moisture Code, Initial Spread Index and Fire Weather Index (FWI) to determine whether EDVI provides new independent information of forest fires. Finally, EDVI and the weather-based indices FWI were combined to establish multivariate linear regression models to estimate FC and FRP. Results show that: 1) the temporal variations of FC and total FRP are negatively correlated with EDVI using the daily and monthly observations at 1° grid and regional scales; and overall opposite annual cycles and interannual variations between FC (and total FRP) and EDVI are observed in Northeastern Asia and Southern China; 2) compared to the weather-based indices, EDVI shows higher correlation with the temperate forest fire properties in Southern China while shows weaker correlation with the forest fire properties in Northeastern Asia; and a combination of the two kind of indices is found to improve the explained variance for fire properties in both regions; 3) multivariate linear regression models based on EDVI and FWI provide better estimation of FC and FRP compared to the linear regression models based on FWI alone. To our knowledge, this is the first work that comprehensively investigates the potential application of the microwave-based vegetation water content index in forest fire count and fire intensity. [ABSTRACT FROM AUTHOR]

• A robust prospective pharmacokinetic study demonstrates an interaction between lamotrigine and coffee. • Coffee consumption decreases lamotrigine area under the curve and maximum concentration. • Cigarette use does not change lamotrigine area under the curve and maximum concentration. The objective of this analysis was to determine possible interactions between lamotrigine (LTG) and coffee or cigarette use. As part of the statistical analysis of factors influencing LTG pharmacokinetics (PK) in the Equigen chronic dose study, we collected prospective data from enrolled patients on their use of coffee and cigarettes. Subjects were part of a crossover replication study of generic LTG products with rigorous blood sampling and were instructed to not change their typical consumption of these products for the duration of the study. A total of 35 subjects were enrolled, with 33 subjects having sufficient data for analysis. Higher consumption of coffee was associated with a significantly lower area under the curve (AUC) and maximum concentration (Cmax) of lamotrigine (LTG). Higher cigarette use did not result in a significant change in AUC or Cmax. Coffee, but not cigarette use, either induces LTG metabolism or inhibits LTG absorption. [ABSTRACT FROM AUTHOR]

Because of high melting point (2300 K), rather low density (6.28g/cm3) and excellent elevated oxidation resistance (above 1600 °C), MoSi 2 have been treated to be one of the most attractive high temperature materials. However, thus a MoSi 2 materials have their intrinsic limitations, one of the worst things is it suffered from an accelerated oxidation at low temperatures (between 350 and 550 °C) which was first discovered by Fitzer in 1955 and was named PEST oxidation. The phenomena of PEST extremely hindered the application of MoSi 2 in advanced engineering and aerospace, also limited its longevity and safety. In this paper, an in-situ MoSi 2 -SiC-MoB three-phase composite was prepared by reactive infiltration process which is known as low-cost and net shape method, and after the oxidation process in 500 °C for 3 h, it was found that there is no PEST occurred anymore. And the residual bending strength of this composite will still over 68%. The reasons for overcoming PEST would be the in-situ formed MoB phase will be stiffly covered over the surface of MoSi 2 grains, and the volume expansion of SiC phase and volume contraction of MoB phase will be matched in the composite system 9.7%wt MoB/8.6%wt SiC/MoSi 2. • Overcome its intrinsic problems – PEST of MoSi 2 and its present composites. • Prepared by the most economic method. • Gained the in-situ three-phase composite with clean grain boundary. • The mechanism is volume-matched in-situ layer covering on MoSi 2 matrix. • The residual bending strength is over 66%. [ABSTRACT FROM AUTHOR]

NO x fire emissions greatly affect atmosphere and human society. The top-down NO x fire emission estimation is highly influenced by satellite fire observation performance (e.g., fire detection) by affecting the derivation of emission coefficient (EC) and fire radiative power (FRP) magnitude. However, such influence is lack of comprehensive study. Here, we developed an algorithm to evaluate such impacts in northeastern Asia using multi-source data during 2012–2019. Specifically, we extracted near-concurrent fire observations from MODIS and its successor VIIRS over their orbit-overlapping area and combined respectively with OMI NO 2 concentration to derive NO x EC. We compared EC between MODIS and VIIRS, and defined a synergetic effect index (SEI) to explore the combined effects on NO x fire emission estimation due to potentially different ECs and FRP between the two sensors. Finally, we applied EC to estimate NO x emission and made comparison between MODIS and VIIRS. Results show that: 1) both sensors derived considerably higher NO x EC for low-biomass vegetation fires (e.g., grassland fires) than other vegetation fires; however, MODIS EC is about 30% lower than VIIRS EC while similar values are derived for forest fires; 2) synergetic effects induced by different ECs and FRP magnitudes between the two sensors are more significant during fall and winter than in spring and summer; 3) annual NO x emissions based on MODIS EC are 15–23% lower than that from VIIRS EC during 2012–2019, while both are lower than the conventional bottom-up emission inventories GFED and FINN by an average of 23–44%; nevertheless, the EC-based NO x estimations presented high spatiotemporal correlation of R usually between 0.70 and 0.95 with GFED and FINN. These results reveal and quantify the critical impacts of satellite fire observation performance on EC derivation and fire emission estimation, which is helpful in reducing estimation uncertainty. [ABSTRACT FROM AUTHOR]

New β-diketone derivatives modified with glycylglycine methyl ester have been synthesized and characterized by IR, UV, 1 H NMR, 13 C NMR, Elemental analysis and single-crystal X-ray diffraction, the analytical results show that compound 1 and compound 2a exist in enamine form while compound 2b exists in aminone form. The optimized geometries and theoretical vibrational frequencies of the compounds calculated by using DFT/B3LYP with 6-31g (d, p) basis set in the ground state can well reproduce the experimental data. The results of herbicidal activity tests indicate that all the tested compounds own higher inhibition ability to monocotyledon than to dicotyledon, especially to green-bristlegrass with the inhibitory rates about 100%. Theoretical enamine–aminone tautomerism study at DFT/B3LYP/6-31g (d, p) shows that tautomerism between compound 2a and 2b is mainly caused by the proton transfer. [ABSTRACT FROM AUTHOR]

[Display omitted] Exposure to some conventional trace elements has been found to be associated with miscarriage; however, evidence for combined exposure is inconclusive. Therefore, it is important to explore the joint associations between toxic and essential trace elements and miscarriage. This cross-sectional study measured a wide range of element levels in the whole blood of pregnant women by using inductively coupled plasma mass spectrometry. The associations between individual elements and miscarriage were appraised using logistic regression model. Multi-exposure models, including Bayesian kernel machine regression (BKMR) and weighted quantile sum regression (WQS), were used to explore the mixed exposure to elements. Furthermore, grouped weighted quantile sum (GWQS) considered multiple elements with different magnitudes and directions of associations. In logistic regression, the odds ratios (ORs) with a 95% confidence interval (CI) in the highest quartiles were 5.45 (2.00, 15.91) for barium, 0.28 (0.09, 0.76) for copper, and 0.32 (0.12, 0.83) for rubidium. These exposure–outcome associations were confirmed and supplemented by BKMR, which indicated a positive association for barium and negative associations for copper and rubidium. In WQS, a positive association was found between mixed elements and miscarriage (OR: 1.71; 95% CI: 1.07, 2.78), in which barium (75.7%) was the highest weighted element. The results of GWQS showed that the toxic trace element group dominated by barium was significantly associated with increased ORs (OR: 2.71; 95% CI: 1.74, 4.38). Additionally, a negative association was observed between the essential trace element group and miscarriage (OR: 0.32; 95% CI: 0.18, 0.54), with rubidium contributing the most to the result. As a toxic trace element, barium was positively associated with miscarriage both by individual and multiple evaluations, while essential trace elements, particularly rubidium and copper, exhibited negative associations. Our findings provide significant evidence for exploring the effects of trace elements on miscarriage. [ABSTRACT FROM AUTHOR]

• A small bias in EDVI-ET is found over eight river basins using water balance method. • EDVI-ET performs a larger magnitude and higher accuracy than MOD16 over crop lands. • Cloud-induced changes in ET vary from 10% to 40% compared to clear sky conditions. • Cloud impacts are more significant for forests, savannas and crops than barrens. • EDVI-ET is most sensitive to radiation for forests, but to humidity for arid barrens. Evapotranspiration (ET) is an important component of the hydrological cycle and energy balance in a land-atmosphere system. Satellite remote sensing has been widely used to estimate regional and global ET, but most previous methods depend on optical measurements that are limited to cloud-free conditions. This makes ET estimation challenging under cloudy sky. Currently, evaluations of satellite ET estimation under various cloud conditions remain lacking at the regional scale. Owing to the ability to penetrate clouds, satellite passive microwave measurements are powerful tools for retrieving ET under clouds. This study evaluated a satellite microwave-based daily ET method under all sky conditions over the part of China between 18°N and 50°N from 2003 to 2010, using microwave emissivity difference vegetation index (EDVI) as the proxy of vegetation water content (VWC). Validations using the surface water balance method found that the estimated ET (EDVI-ET) had an overall small bias (6.18%) in eight river basins. EDVI-ET displayed consistent spatiotemporal patterns with global MOD16 ET, with high spatial correlation (R >0.71) and monthly temporal correlation (R >0.82) throughout four seasons. Their differences were also small (<0.56mmday−1) in forests, savannas, grass/shrubs, and croplands. Furthermore, cloud impacts on the regional ET were found to be significant and spatiotemporally heterogeneous. Both EDVI-ET and in-situ observations at seven flux towers indicated that cloud-induced reduction in daily ET could exceed 30% when the cloud cover increased by 60% (R2 of 0.42, fitting line slope of 0.80, p <0.001). Under increased cloud conditions in summer, the changes in net radiation dominated the ET over dense vegetation in southern China, while the roles of air temperature and humidity increased over water-stressed barrens and short vegetation in northwest China. VWC affected EDVI-ET under clouds in temperate transitional zones from flatlands to highlands. This study highlighted the importance of cloud impacts in satellite ET estimation. [ABSTRACT FROM AUTHOR]

Although satellite-based light use efficiency (LUE) model is widely used to estimate gross primary production (GPP) of terrestrial ecosystems, microwave observations have not been integrated into LUE models. This study developed a new LUE model coupled with a passive microwave vegetation index (Emissivity Difference Vegetation Index, EDVI) for daily GPP estimation. Normalized EDVI (nEDVI), an indicator of canopy-scale leaf development and biomass change, was used as a proxy of fraction of photosynthetically active radiation (FPAR). EDVI-based evaporative fraction (EDVI-EF) under all sky was used to indicate synoptic-scale water stress on LUE. 8-year in-situ measurements from seven flux tower sites (four forests, two grasslands and one croplands) of ChinaFLUX network were used to evaluate the model. We found that nEDVI-based FPAR better captured the short-term variations in daily in-situ GPP (GPP obs) than other optic-based FPAR schemes. This capability of nEDVI was more noticeable under moderate and heavy cloud cover (Frc) conditions. Validations against daily GPP obs at all sites showed that EDVI-based GPP (GPP EDVI) generated an overall small bias of −0.47 gC m−2 day−1 (−8.1%) and good Taylor score (S) of 0.86 at the daily scale. Better accuracy of GPP EDVI was found at forests sites with R2 of 0.43 to 0.73, bias of-5.29% to 3.03% and S of 0.58 to 0.78, respectively. At a tropical forest site with most frequent cloud cover, the model also well captured the variation in GPP obs from clear sky to cloudy sky (R2 of 0.93) with stable accuracies. Furthermore, the accuracy of daily GPP EDVI was found to be comparable with global satellite optic MOD17 GPP (GPP MOD17) and EC-LUE GPP (GPP ECLUE) from 8-day to yearly scales across the sites. In particular, GPP EDVI performed generally smaller bias at evergreen broadleaf forests, while both of GPP MOD17 and GPP ECLUE were overestimated, suggesting that there could be less saturation for microwave-based LUE model over dense vegetation. Although all three satellite LUE models severely underestimated GPP of crop, GPP EDVI generated lower bias (−29.8%) than GPP MOD17 (−66.8%) and GPP ECLUE (−59.5%). Overall, this study is the first attempt toward the integration of microwave-derived variables into LUE model for daily GPP estimation. The microwave-based LUE model has a potential of mapping spatiotemporally continues daily GPP under various clouds. • A LUE model coupled with microwave vegetation index (EDVI) for daily GPP estimation. • FPAR and evaporative fraction were quantified by EDVI-based schemes. • 8-year in-situ GPP from seven eddy covariance flux sites of ChinaFLUX were used. • Model performed daily GPP estimation stably under various cloud cover conditions. • Model had a better accuracy than MOD17 and EC-LUE GPP at forests and crop sites. [ABSTRACT FROM AUTHOR]