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Brassinosteroids (BRs) play vital roles in the plant life cycle and synthetic BRs are widely used to increase crop yield and plant stress tolerance. Among them are 24R-methyl-epibrassinolide (24-EBL) and 24S-ethyl-28-homobrassinolide (28-HBL), which differ from brassinolide (BL, the most active BR) at the C-24 position. Although it is well known that 24-EBL is 10% active as BL, there is no consensus on the bioactivity of 28-HBL. A recent outpouring of research interest in 28-HBL on major crops accompanied with a surge of industrial-scale synthesis that produces mixtures of active (22R,23R)-28-HBL and inactive (22S,23S)-28HBL, demands a standardized assay system capable of analyzing different synthetic "28-HBL" products. In this study, the relative bioactivity of 28-HBL to BL and 24-EBL, including its capacity to induce the well-established BR responses at molecular, biochemical, and physiological levels, was systematically analyzed using the whole seedlings of the wild-type and BR-deficient mutant of Arabidopsis thaliana. These multi-level bioassays consistently showed that 28-HBL exhibits a much stronger bioactivity than 24-EBL and is almost as active as BL in rescuing the short hypocotyl phenotype of the dark-grown det2 mutant. These results are consistent with the previously established structure–activity relationship of BRs, proving that this multi-level whole seedling bioassay system could be used to analyze different batches of industrially produced 28-HBL or other BL analogs to ensure the full potential of BRs in modern agriculture. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) with a nucleophosmin 1 (NPM1) mutation is a unique subtype of adult leukemia. Recent studies show that NPM1-mutated AML has high autophagy activity. However, the mechanism for upholding the high autophagic level is still not fully elucidated. In this study, we first identified that tumor protein p53 inducible nuclear protein 2 (TP53INP2) was highly expressed and cytoplasmically localized in NPM1-mutated AML cells. Subsequent data showed that the expression of TP53INP2 was upregulated by fat mass and obesity-associated protein (FTO)-mediated m6A modification. Meanwhile, TP53INP2 was delocalized to the cytoplasm by interacting with NPM1 mutants. Functionally, cytoplasmic TP53INP2 enhanced autophagy activity by promoting the interaction of microtubule-associated protein 1 light chain 3 (LC3) - autophagy-related 7 (ATG7) and further facilitated the survival of leukemia cells. Taken together, our study indicates that TP53INP2 plays an oncogenic role in maintaining the high autophagy activity of NPM1-mutated AML and provides further insight into autophagy-targeted therapy of this leukemia subtype. [ABSTRACT FROM AUTHOR]

Non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHBA) are the metabolites of fat mobilization initiated by negative energy balance (NEB) during the perinatal period in dairy cows, which have an adverse effect on cell physiology of various bovine cell types. The aim of this study was to explore the biological roles of NEFA and BHBA on provoking oxidative stress and inflammatory responses in bovine mammary epithelial cells (BMECs). RNA sequencing analysis showed that there are 1343, 48, and 1725 significantly differentially expressed genes (DEGs) in BMECs treated with NEFA, BHBA and their combination. GO functional analysis revealed that the DEGs were significantly enriched in "response to oxidative stress" and "inflammatory response". Further study demonstrated that NEFA and BHBA elevated the malondialdehyde (MDA) and reactive oxygen species (ROS) accumulation and reduced the total superoxide dismutase (T-SOD) and glutathione peroxidase (GSH-Px) activity to cause oxidative stress. In addition, expression of inflammatory markers (NO, TNF-α, IL-6, and IL-1β) were increased after NEFA and BHBA stimulation. Mechanistically, our data showed that NEFA and BHBA activated the MAPK signaling pathway. Collectively, our results indicate that NEFA and BHBA induce oxidative stress and inflammatory response probably via the MAPK signaling pathway in BMECs. [ABSTRACT FROM AUTHOR]

Container transportation is an important mode of international trade logistics in the world today, and its changes will seriously affect the development of the international market. For example, the COVID-19 pandemic has added a huge drag to global container logistics. Therefore, the accurate forecasting of container throughput can make a significant contribution to stakeholders who want to develop more accurate operational strategies and reduce costs. However, the current research on port container throughput forecasting mainly focuses on proposing more innovative forecasting methods on a single time series, but lacks the comparison of the performance of different basic models in the same time series and different time series. This study uses nine methods to forecast the historical throughput of the world's top 20 container ports and compares the results within and between methods. The main findings of this study are as follows. First, GRU is a method that can produce more accurate results (0.54–2.27 MAPE and 7.62–112.48 RMSE) with higher probability (85% for MAPE and 75% for RMSE) when constructing container throughput forecasting models. Secondly, NM can be used for rapid and simple container throughput estimation when computing equipment and services are not available. Thirdly, the average accuracy of machine learning forecasting methods is higher than that of traditional methods, but the accuracy of individual machine learning forecasting methods may not be higher than that of the best conventional traditional methods. [ABSTRACT FROM AUTHOR]

Elevated concentrations of non-esterified fatty acid (NEFA) induced by negative energy balance (NEB) during the transition period of dairy cows is known to be toxic for multiple bovine cell types. However, the effect of NEFA in bovine mammary epithelial cells (BMECs) remains unclear. The present study aimed to explore the role and molecular mechanism of NEFA in endoplasmic reticulum (ER) stress and the subsequent apoptosis in BMECs. The results showed that NEFA increased ER stress and activated the three unfolded protein response (UPR) signaling sub-pathways by upregulating the expression of GRP78, HSP70, XBP1, ATF6, phosphor-PERK, and phosphor-IRE1α. We also found that NEFA dose-dependently induced apoptosis in BMECs, as indicated by flow cytometry analysis and increased apoptotic gene expression. RNA-seq analysis revealed that NEFA induced apoptosis in BMECs, probably via the ATF4-CHOP axis. Mechanistically, our data showed that NEFA increased reactive oxygen species (ROS) levels, resulting in the activation of the MAPK signaling pathway. Moreover, quercetin, a well-known antioxidant, was found to alleviate ER stress-mediated apoptosis in NEFA-treated BMECs. Collectively, our results suggest that NEFA induces ER stress-mediated apoptosis, probably via the ROS/MAPK signaling pathway, as quercetin has been shown to alleviate ER stress-mediated apoptosis in NEFA-treated BMECs. [ABSTRACT FROM AUTHOR]

Featured Application: This work provides references for the selection and application of relevant solar utilization technologies on building roofs. Considering the vast areas of building rooftops and the fast development of solar utilization technologies, this paper aims to analyze the regional adaptability of solar roof utilization technologies for buildings in China. All provinces and cities in China are divided into 13 zones based on their economic development, thermal climate division, and availability of solar energy resources. Over 100 buildings are investigated, and the information of 28 buildings is analyzed to finally identify 18 typical building types. A new evaluation method is developed for both solar heating systems and solar PV. An adaptability index is developed considering the energy conservation, environment effect, and economy benefit of the systems. The developed method is used to evaluate the solar utilization technologies applied on the 18 buildings across 13 zones. The result show that the average adaptability index values for solar thermal technology and solar PV technology are 2.54 and 1.63, respectively. The solar heating system has a shorter payback time than the solar PV system for most regions of China and therefore is more favored. Recommendations on supporting policies and measures are given for policy makers with an aim to promote the utilization efficiency of building roofs. This paper provides references for the selection and application of relevant solar utilization technologies on building roofs. [ABSTRACT FROM AUTHOR]

Landslides frequently occur along the eastern margin of the Tibetan Plateau, which poses a risk to the construction, maintenance, and transportation of the proposed Dujiangyan city to Siguniang Mountain (DS) railway, China. Therefore, four advanced machine learning models, namely, the Bayesian network (BN), decision table (DTable), radial basis function network (RBFN), and stochastic gradient descent (SGD), are proposed in this study to delineate landslide susceptibility zones. First, a landslide inventory map was randomly divided into 828 (75%) samples and 276 (25%) samples for training and validation, respectively. Second, the One-R technique was utilized to analyze the importance of 14 variables. Then, the prediction capability of the four models was validated and compared in terms of different statistical indices (accuracy (ACC) and Cohen's kappa coefficient (k)) and the areas under the curve (AUC) in the receiver operating characteristic curve. The results showed that the SGD model performed best (AUC = 0.897, ACC = 80.98%, and k = 0.62), followed by the BN (AUC = 0.863, ACC = 78.80%, and k = 0.58), RBFN (AUC = 0.846, ACC = 77.36%, and k = 0.55), and DTable (AUC = 0.843, ACC = 76.45%, and k = 0.53) models. The susceptibility maps revealed that the DS railway segments from Puyang town to Dengsheng village are in high and very high-susceptibility zones. [ABSTRACT FROM AUTHOR]

High-rise buildings have a significant impact on the surrounding environment. Building-integrated solar water heating (SWH) systems are effective ways to use renewable energy in buildings. Impediments, such as security concerns, aesthetics and functionality, make it difficult to apply SWH systems in high-rise buildings. At present, only China uses SWH systems on a large scale in such buildings. What are China's experiences and lessons learned in applying SWH systems in high-rises? Are these experiences scalable to other countries? This study used a combination of field investigation, literature review and case study to summarize 36 systems that had been in operation for 1–14 years. System types, collector types, installation methods, types of auxiliary heat sources, economic performance and various basic principles were summarized. The economic performance of SWH systems in high-rise buildings was analyzed and verified by a case study in Shanghai. The results show that the installation of SWH systems in high-rise buildings is feasible and reliable. Individual household systems (61%) were more popular than centralized systems (25%) and hybrid systems account (14%). The average area of solar collectors per household was 2.17 m2/household, the average design solar fraction was 52%. Flat plate solar collectors (53%) was the most commonly used collector, while electric heating elements (89%) were the most common auxiliary heat sources for SWH systems, followed by gas water heaters and air source heat pumps. The cost of SWH systems per m2 of a building area was between 22 CNY/m2 to 75 CNY/m2. China's unique practical experience gives a reference for other countries in their efforts to make high-rise buildings more sustainable. [ABSTRACT FROM AUTHOR]

Silver powder, as the primary component of solar silver paste, significantly influences various aspects of the paste's performance, including printing, sintering, and conductivity. This study reveals that, beyond the shape and size of the silver powders, their microstructure is a critical factor influencing the performance of both silver powders and silver pastes in solar cell applications. The growth process leads to the formation of either polycrystalline aggregated silver powder or crystal growth silver powder. Analyzing the performance characteristics of these different microstructures provides guidance for selecting silver powders for silver pastes at different sintering temperatures. Polycrystalline aggregated silver powder exhibits higher sintering activity, with a sintering initiation temperature around 450 °C. The resulting silver paste, sintered at 750 °C, demonstrates a low sheet resistance of 2.92 mΩ/sq and high adhesion of 2.13 N. This silver powder is suitable for formulating silver pastes with lower sintering temperatures. The solar cell electrode grid lines have a high aspect ratio of 0.37, showing poor uniformity. However, due to the high sintering activity of the silver powder, the glass layer dissolves and deposits more silver, resulting in excellent conductivity, a low contact resistance of the silver electrode, a low series resistance of the solar cell of 1.23 mΩ, and a high photoelectric conversion efficiency of 23.16%. Crystal growth silver powder exhibits the highest tap density of 5.52 g/cm3. The corresponding silver paste shows improved densification upon sintering, especially at 840 °C, yielding a sheet resistance of 2.56 mΩ/sq and adhesion of 3.05 N. This silver powder is suitable for formulating silver pastes with higher sintering temperatures. The solar cell electrode grid lines are uniform with the highest aspect ratio of 0.40, resulting in a smaller shading area, a high fill factor of 81.59%, and a slightly higher photoelectric conversion efficiency of 23.17% compared to the polycrystalline aggregated silver powder. [ABSTRACT FROM AUTHOR]

Apart from promoting social-economic development and increasing social employment, the real estate industry in China has also brought up problems such as high energy consumption and high emissions. Scholars now focus more on energy conservation, emission reduction and sustainable development of real estate companies in their current research. The data used by this paper are three-year panel data from 2015 to 2018, with observations from 15 representative real estate companies. CO2 and green credit index are introduced as the undesirable output and the green output of real estate companies respectively. First, with the DEA model and the Malmquist index model, this paper evaluates the green productivity of real estate companies statically and dynamically. The Tobit model is then employed by the author to analyze factors that may affect green productivity. Our results indicate that (1) the green productivities of 15 Chinese real estate companies have improved by various degrees. The average green productivity rises from 0.701 in 2015 to 0.849 in 2018, indicating that the energy utilization rate of enterprises has gradually increased. From the calculation and decomposition of the Malmquist total factor productivity index, we know that technological progress is vital in improving the green productivity of real estate companies. (2) As for the influencing factors, the green productivity is positively related to factors such as policy compliance indicator P, environmental responsibility commitment indicator R, indicator of green innovation capability I, and indicator of green development information disclosure M. The asset-liability ratio on the contrary has a negative impact on green productivity. It's worth to point out that the green innovation index and green productivity is significantly correlated and the correlation coefficient can be up to 0.636, which implies that the key to improving green productivity is to increase research and development investment. [ABSTRACT FROM AUTHOR]