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• A coupling mixed pixel decomposition and mixed-cell simulation methods are proposed. • The subpixel-scale impact of land use structure dynamics on future UHIs is revealed. • How the multiscale land use composition mechanisms affecting UHIs are explored. • The potential influence of UHIs on future populations is evaluated in this study. Urban heat islands (UHIs) has been proven firmly related to the land use structure. Identifying interactions between UHIs and multiple land use components is a crucial step to obtain human heat welfare information. However, few studies have predicted sub cell scale land use structure dynamics on UHIs due to the lack of subpixel simulation methods. Herein, we present an integrated framework coupling subpixel unmixing and mixed-cell simulation methods to predict fine-scale land-use structural changes. A widely used XGBoost was used to determine the optimal scale for future UHIs prediction. This framework explores how multiscale changes in land use structure will affect future UHIs intensity, taking Wuhan, China as a study area. The results reveal that most influence comes from the scale below the 330-m grid, while the fine-scale land use components of a given position show limited impact on the UHI intensity. Impervious surfaces contribute more than 55% of the importance, while bare soil and water components within the 270-m grid also significantly affect UHIs. We also find that optimizing the structure of land use components can potentially release approximately 599,000 people from high-UHI regions in the study area. [Display omitted] [ABSTRACT FROM AUTHOR]

Soil moisture (SM) and vegetation optical depth (VOD) estimates using passive microwave remote sensing at L-band (1.4 GHz) are essential for attaining a better understanding of water exchanges at the land-atmosphere interface. However, current retrieval algorithms often ignore the polarization dependence of vegetation effects. This study proposed a parameter self-calibrating framework for the multi-channel collaborative algorithm (MCCA) and presented a new SM and the first polarization-dependent VOD product based on the dual-polarized L-band observations at a fixed angle (40°) from the NASA Soil Moisture Active Passive (SMAP) mission. The parameter self-calibrating framework utilizes an information theory-based approach to obtain surface roughness and effective scattering albedo globally. Furthermore, the MCCA does not require auxiliary data for vegetation or soil moisture to constrain the retrieval process. Comparison with other SM and VOD products, such as MT-DCA version 5, DCA, SCA-H, SCA-V from SMAP Level-3 products version 8, and SMAP-IB, demonstrate analogous spatial patterns. The MCCA-derived SM exhibits the lowest unbiased root mean square deviation (ubRMSD, about 0.055 m3/m3), followed by SMAP-IB and DCA (0.061 m3/m3), with an overall Pearson's correlation coefficient of 0.744 (SMAP-IB performed best with R = 0.764) when evaluated against in-situ observations from 18 dense soil moisture networks. The MCCA generates VOD values for both vertical and horizontal polarization, demonstrating a slight polarization difference of vegetation effect at the satellite scale. Both VODs exhibit a strong linear relationship with above-ground biomass and canopy height. The polarization difference of VODs is primarily observed in densely vegetated and arid areas. • No ancillary data are used to calibrate parameters or constrain the cost function. • MCCA SM shows lower uncertainty and similar correlation compared to SMAP products. • The first SMAP VOD product that takes account of its polarization dependence. • VOD at H-polarization is greater than VOD at V-polarization over dense vegetation. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effect and mechanism of methylcrotonyl-CoA carboxylase subunit 1 (MCCA) on multidrug resistance in multiple myeloma (MM). The apoptosis kit and CCK-8 reagent were used to detect drug-induced cell apoptosis and viability. Immunoprecipitation, immunofluorescence staining, and protein structural simulation were used to detect the interaction between MCCA and Bad. Immunodeficient mice were injected with ARD cells and treated with bortezomib. Changes in tumor burden were recorded by bioluminescence imaging, and κ light chain content in the blood of mice was detected by enzyme-linked immunoassay. Patients with high MCCA expression from a primary MM dataset had superior overall survival. After treatment with different anti-MM drugs, MCCA knockdown MM (MCCA-KD) cells had higher survival rates than control knockdown (CTR-KD) cells (p < 0.05). Mechanistic studies have revealed that MCCA-KD cells had dysfunctional mitochondria with decreased Bax and Bad levels and increased Bcl-xl and Mcl-1 levels. Furthermore, that MCCA and Bad demonstrated protein–protein interactions. The half-life of Bad in MCCA-KD cells is significantly shorter than that in CTR-KD cells (7.34 vs. 2.42 h, p < 0.05). In a human MM xenograft mouse model, we confirmed that MCCA-KD tumors had a poor response to anti-MM drugs in vivo. Finally, we showed that MCCA might contribute to multidrug resistance in different human cancers, particularly in solid tumors. Our findings demonstrated a novel function of MCCA in multidrug resistance. The lack of MCCA expression promoted antiapoptotic cell signaling in MM cells. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) and vegetation optical depth (VOD) are essential variables in the terrestrial ecosystem. The multi-frequency radiometers AMSR-E and AMSR2 provide >20 years of data records, enabling the development of long-term SM and VOD products. Most of the current retrieval algorithms either only focus on SM or VOD, and generally ignore the polarization or simplify the frequency dependence of vegetation effects for reducing the unknowns and facilitating the retrieval process, limiting the synergic applicability of VOD and SM products in the soil-plant-atmosphere continuum. In this study, a new global SM and frequency- and polarization-dependent VOD product from 2002 to 2021 was developed using the multi-channel collaborative algorithm (MCCA), based on the inter-calibrated AMSR-E/2 multi-frequency passive microwave measurements. The MCCA algorithm comprehensively considers the physical relationship between multiple microwave channels and could retrieve frequency- and polarization-dependent VOD while considering the accuracy of the SM retrievals. In the overall comparison with other SM products (AMSR-ANN, CCI-passive v07.1, LPRM-C/X, JAXA) over 25 dense SM networks, MCCA achieved the best scores in terms of root mean square error (RMSE = 0.074 m3/m3), unbiased root mean square error (ubRMSE = 0.073 m3/m3) and bias (0.007 m3/m3), and presented slightly lower value of Pearson's correlation coefficient (R = 0.709) than LPRM-X (R = 0.735). For the indirect evaluation of VOD with aboveground biomass (AGB) and MODIS NDVI, the MCCA product showed the performance comparable to other products (LPRM-C/X, VODCA-C/X/Ku). MCCA-derived VODs, especially for the H-polarized VODs, exhibited smooth non-linear density distribution with AGB and high temporal correlations with MODIS NDVI over most regions of the globe. In particular, MCCA-derived VODs can physically present reasonable variations across the microwave spectrum (values of VOD increase with microwave frequency), which is superior to the LPRM and VODCA products. It is expected that the MCCA algorithm can be extended to the observations of the ongoing AMSR2 or other similar satellite missions with multi-frequency capability, such as FY-3B/C/D/F/G or the upcoming AMSR3 and CMIR missions. • A physically consistent SM product over two decades is developed using the MCCA. • MCCA-derived SM shows the best accuracy among the six AMSR SM products. • MCCA-derived VODs present reasonable variations across the microwave spectrum. • H-polarized VOD is more sensitive to vegetation in terms of biomass and greenness than V-polarized VOD. [ABSTRACT FROM AUTHOR]

[Display omitted] • We coupled a new mixed-cell CA approach and system dynamics model to forecast the ecosystem service value under three alternative scenarios. • The SD-MCCA model was demonstrated to have better performance, higher simulation accuracy and stronger robustness. • This paper employed the coefficient of sensitivity to determine the dependence of ESV on the land use variations. Land use is a crucial factor affecting ecosystem service value (ESV), and forecasting future land use changes and ESV response can guide urban planning and sustainable development decisions. However, the traditional Cellular Automata (CA) model supposes that each cell has only one land use type at each time step, neglects the mixed structure and proportional distribution of land use units, does not take into account its quantitative continuous dynamic change, and lacks the exploration of land use quantity structure and spatial pattern optimization. This study employed a novel mixed-cell cellular automata (MCCA) approach, coupled with the system dynamics (SD) model to predict the spatiotemporal pattern of land use under the natural increase scenario (NIS), economic development scenario (EDS) and ecological protection scenario (EPS) in Xi'an, China, in 2030. The equivalent coefficient method was utilized to investigate the heterogeneity distribution and sensitivity of ESV. The results demonstrated that SD-MCCA exhibited remarkable prediction accuracy and robustness. The main changes in land use in 2000–2015 were due to urban expansion, the conversion of arable land into construction land, and the conversion between grassland and arable land. The total ESV increased from 19554.36×106 CNY in 2000 to 19618.39×106 CNY under the EPS in 2030, and the contribution of climate regulation and hydrological regulation to ESV was the highest. Spatial heterogeneity of ESV revealed a certain regularity, and the high value region was chiefly concentrated in woodland and grassland with favorable ecological conditions. Land use variations under NIS and EPS improved ESV, while the ESV had a negative response to land use transformations under the EDS. This research provides a new way to identify the relationship between future land utilization scenarios and ESV, which is of great significance for the management of land resources and formulation of ecological compensation standards. [ABSTRACT FROM AUTHOR]

The current paper is the one of the few known reports that depict the influence of a distinctive morphology control chemical additive (MCCA) namely, ammonium fluoride on crystal structure and photoluminescence of Eu2+-doped BaMgAl 10 O 17 (BAM:Eu2+) nanophosphor better suited for many active displays and lighting devices. [Display omitted] • MCCAs are highly desired for tuning of morphology in BAM:Eu2+ nanophosphor. • Better crystallinity in nanophosphor could be achieved using MCCA. • BAM:Eu2+ nanophosphor exhibits intense emission compared to its bulk. In this letter, experimental results on structure and photoluminescence (PL) properties of Eu2+-doped BaMgAl 10 O 17 (BAM:Eu2+) nanophosphors modified by a distinctive morphology control chemical additive (MCCA) namely, ammonium fluoride are reported. X-ray diffraction confirmed hexagonal phase with p6 3 /mmc space group whereas, scanning electron microscopy images revealed layered rod-like morphologies for the MCCA modified BAM:Eu2+ nanophosphors. Upon excitation at 300 nm, the room-temperature PL showed enhanced emission peak at ~467 nm attributed to 4f65d1 → 4f7 transition of Eu2+ ions with (0.22, 0.17) as color coordinates. The obtained results suggest that MCCA modified BAM:Eu2+ nanophosphors would be suitable for active displays and lighting devices. [ABSTRACT FROM AUTHOR]