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The use of biomass-based glycerol to produce chemicals with high added value is of great significance for solving the problem of glycerol surplus and thus reducing the production cost of biodiesel. The production of 1,2-propanediol (abbreviated as 1,2-PDO) and 1,3-propanediol (abbreviated as 1,3-PDO) via the hydrogenolysis of glycerol is one of the most representative and highest-potential processes for the comprehensive utilization of biomass-based glycerol. Glycerol hydrogenolysis may include several parallel and serial reactions (involving broken C–O and C–C bonds), and therefore, the catalyst is a key factor in improving the rate of glycerol hydrogenolysis and the selectivities of the target products. Over the past 20 years, glycerol hydrogenolysis has been extensively investigated, and until now, the developments of catalysts for glycerol hydrogenolysis have been active research topics. Non-precious metals, including Cu, Ni, and Co, and some precious metals (Ru, Pd, etc.) have been used as the active components of the catalysts for the hydrogenolysis of glycerol to 1,2-PDO, while precious metals such as Pt, Rh, Ru, Pd, and Ir have been used for the catalytic conversion of glycerol to 1,3-PDO. In this article, we focus on reviewing the research progress of the catalyst systems, including Cu-based catalysts and Pt-, Ru-, and Pd-based catalysts for the hydrogenolysis of glycerol to 1,2-PDO, as well as Pt-WOx-based and Ir-ReOx-based catalysts for the hydrogenolysis of glycerol to 1,3-PDO. The influence of the properties of active components and supports, the effects of promoters and additives, and the interaction and synergic effects between active component metals and supports are also examined. [ABSTRACT FROM AUTHOR]

Soil salinization has become a major environmental factor severely threatening global food security. The application of porous minerals could significantly ameliorate soil fertility and promote plant productivity under salt stress conditions. However, the effects of porous minerals on improving the salt resistance of grain crops in coastal saline soils is not fully studied. In this work, the shoot growth and grain yield of wheat plants grown in coastal saline fields, respectively amended with the four naturally available porous minerals, diatomite, montmorillonite, bentonite and zeolite, were assessed. The application of porous minerals, especially zeolite, significantly improved the biomass and grain yield of wheat plants under saline conditions, as demonstrated by the augmented plant fresh mass (14.8~61.2%) and increased seed size (3.8~58.8%) and number (1.4~57.5%). Soil property analyses exhibited that porous-mineral amendment decreased soil sodium content and sodium absorption ratio, and increased soil nutrients in both the rhizosphere and nonrhizosphere of wheat plants. Further quantitative-PCR and 16S high-throughput sequencing analysis revealed that porous-mineral application also remarkably increased the abundance of bacterial 16S rRNA (0.8~102.4%) and fungal 18S rRNA (89.2~209.6%), and altered the composition of the soil microbial community in the rhizosphere of wheat. Our findings suggest that zeolite could be used as an ideal salt soil amendment, and the changes in soil properties and microorganisms caused by the application of porous minerals like zeolite improved the salt resistance of wheat plants in coastal saline land, leading to increased shoot growth and seed production. [ABSTRACT FROM AUTHOR]

The discharge process has undergone major changes in many river basins throughout the world as a result of the simultaneous influences of global climate change and human activity. Flow duration curves (FDCs) are crucial indicators of river basins' hydrological processes. However, it is challenging to compare FDCs in a quantitative way. This study will identify the best function with which to fit the flow duration curve in a semi-arid region of North China, so as to quantify the FDC, and parameterize the function of the FDC of the region in order to describe the FDCs of ungauged basins. In this work, six small- and medium-sized catchments in North China are selected as the study area, and three functions, i.e., log normal, generalized Pareto and H2018 functions, were chosen to fit the FDC at nineteen hydrological stations. The relationship between the parameters of the FDC and the basin characteristics, such as the climatic factors and geographical features, were analyzed. A regression formula of the parameters of the FDC function was established, and its spatial and temporal distributions were examined. Based on the evaluation of four indicators, the Nash–Sutcliffe efficiency, the root mean square relative error, the logarithmic Nash efficiency coefficient and the coefficient of determination, the results demonstrate that the H2018 function can match FDCs the best. Through the annual runoff, annual precipitation, precipitation in summer, potential evapotranspiration, catchment area, mean elevation, length of the main channel and maximum flow frequency, the parameters of a, b, and k in the H2018 function can be formulated. The regression formula constructed in this study can obtain a regional flow duration curve with satisfactory performance, which provides a reference for the validation of remote-sensing-based runoff data in ungauged regions. [ABSTRACT FROM AUTHOR]

Determining the nutrient requirements of industrial hemp to increase the yield requires quantifying variations in soil nutrients and enzyme activities in different growth stages, along with relevant soil microbial response. This study investigated the effects of different growth stages of industrial hemp on rhizosphere soil nutrients, enzyme activities, and microbial communities. The results showed that with the increase in the growth stages, the pH and available phosphorus (AP) decreased, while the soil organic matter (SOM), available nitrogen (AN), and available potassium (AK) increased substantially, indicating that the demand for nutrients of industrial hemp was constantly changing. Proteobacteria, Acidobacteria, Ascomycota, and Basidiomycota were found to be the keystone taxa to adapt to the nutrient requirements of industrial hemp at different growth stages by regulating soil enzyme activity. Furthermore, using the redundancy analysis and Spearman's correlation analysis, we found that microbial taxonomic composition was related to the variations in AN, AP, and pH. In general, we emphasized that the interaction between industrial hemp and soil is closely related to the growth stage, which increases plant adaptability and growth because of the change of soil microorganisms. [ABSTRACT FROM AUTHOR]

The electrochemical performance of supercapacitors using porous carbon as electrodes is strongly affected by the fabrication process of carbon material. KOH is commonly used as an activator combined with urea as a nitrogen dopant. However, the roles of KOH and urea in pore structure configuration and the electrochemical behavior of porous carbon electrodes are still ambiguous. Herein, the optimum porous carbon is obtained when KOH and urea are used simultaneously. KOH is used as a pore-forming substance, whereas urea is employed as a nitrogen source for the nitrogen doping of porous carbon, which increases its defect sites while reducing the graphitization degree. More importantly, urea also expands pores as a pore-enlarging agent, inducing interconnected porous structures. As a result, a hierarchical porous structure is formed and ascribed to the synergistic effect of KOH and urea, and the specific surface area reached 3282 m2 g−1 for sample PC800-4. The specific capacitance is 319 F g−1 at 0.5 A g−1 with excellent cycling stability over 2500 cycles. Furthermore, the symmetric supercapacitor reaches an excellent energy density of 11.6 W h kg−1 under 70.0 W kg−1 in a 6 M KOH electrolyte. Our work contributes to the rational designation of the porous carbon structure for supercapacitor applications. [ABSTRACT FROM AUTHOR]

In this study, a fractal dimension-based method has been developed to compute the visual complexity of the heterogeneity in the built environment. The built environment is a very complex combination, structurally consisting of both natural and artificial elements. Its fractal dimension computation is often disturbed by the homogenous visual redundancy, which is textured but needs less attention to process, so that it leads to a pseudo-evaluation of visual complexity in the built environment. Based on human visual perception, the study developed a method: fractal dimension of heterogeneity in the built environment, which includes Potts segmentation and Canny edge detection as image preprocessing procedure and fractal dimension as computation procedure. This proposed method effectively extracts perceptually meaningful edge structures in the visual image and computes its visual complexity which is consistent with human visual characteristics. In addition, an evaluation system combining the proposed method and the traditional method has been established to classify and assess the visual complexity of the scenario more comprehensively. Two different gardens had been computed and analyzed to demonstrate that the proposed method and the evaluation system provide a robust and accurate way to measure the visual complexity in the built environment. [ABSTRACT FROM AUTHOR]

TiH2-basd powder metallurgy (PM) is one of the effective ways to prepared high temperature titanium alloy. To study the thermomechanical behavior of near-α titanium alloy and proper design of hot forming, isothermal compression test of TiH2-based PM near-α type Ti-5.05Al-3.69Zr-1.96Sn-0.32Mo-0.29Si (Ti-1100) alloy was performed at temperatures of 1123–1323 K, strain rates of 0.01-1 s−1, and maximum deformation degree of 60%. The hot deformation characteristics of alloy were analyzed by strain hardening exponent (n), strain rate sensitivity (m), and processing map, along with microstructure observation. The flow stress revealed that the difference in softening/hardening behavior at temperature of 1273–1323 K and the strain rate of 1 s−1 compared to the lower deformation temperature and strain rate. The strain hardening exponents at temperatures of 1123 K are all negative under all strain rates, and the most severe flow softening with minimum value of n was observed at 1123 K and 1 s−1. The strain rate sensitives showed that the peak region with m value greater than 0.5 generally appeared in the high temperature range of 1273–1323 K, while strain rate sensitivity at low temperature behaved differently with strain rates. The processing map developed for strain of 0.6 exhibited high power dissipation efficiency at high temperatures of 1273–1323 K and a low strain rate of 0.01 s−1, due to microstructure evolution of β phase. The decrease of strain rate at 1323 K resulted in the formation of globularization of α lamellae. The instability domain of flow behavior was identified in the temperature range of 1123–1173 K and at the strain rate higher than 0.01 s−1 reflecting the localized plastic flow and adiabatic shear banding, and inhomogenous microstructure. The variation of power dissipation energy (η) slope with strain demonstrated that the power dissipation mechanism during hot deformation has been changed from temperature-dependent to microstructure-dependent with the increase of temperature for the alloy deformed at 0.1 s−1. Eventually, the optimum processing range to deform the material is at 1273–1323 K and a strain rate range of 0.01–0.165 s−1 (ln ε ˙ = −4.6–−1.8). [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has made assessing vaccine efficacy more challenging. Besides neutralizing antibody assays, systems vaccinology studies use omics technology to reveal immune response mechanisms and identify gene signatures in human peripheral blood mononuclear cells (PBMCs). However, due to their low proportion in PBMCs, profiling the immune response signatures of dendritic cells (DCs) is difficult. Here, we develop a predictive model for evaluating early immune responses in dendritic cells. We establish a THP-1-derived dendritic cell (TDDC) model and stimulate their maturation in vitro with an optimal dose of attenuated yellow fever 17D (YF-17D). Transcriptomic analysis reveals that type I interferon (IFN-I)-induced immunity plays a key role in dendritic cells. IFN-I regulatory biomarkers (IRF7, SIGLEC1) and IFN-I-inducible biomarkers (IFI27, IFI44, IFIT1, IFIT3, ISG15, MX1, OAS2, OAS3) are identified and validated in vitro and in vivo. Furthermore, we apply this TDDC approach to various types of vaccines, providing novel insights into their early immune response signatures and their heterogeneity in vaccine recipients. Our findings suggest that a standardizable TDDC model is a promising predictive approach to assessing early immunity in DCs. Further research into vaccine efficacy assessment approaches on various types of immune cells could lead to a systemic regimen for vaccine development in the future. [ABSTRACT FROM AUTHOR]

High speed and heavy loads have become more prevalent in the traction power supply system recently. To ensure system operating stability, better power quality, and sufficient power capacity, improvements are needed over the conventional traction system. Inspired by the concept of a microgrid (MG), an AC co-phase traction MG system was proposed. Substations were connected to the traction grid as distributed generators operate in islanded mode. Droop control was adopted as the primary control to stabilize the system's operating frequency and voltage. Considering the operating features of the substation and locomotive load, a de-centralized secondary control strategy was proposed for AC co-phase traction MG system operation with enhanced resiliency. The proposed control strategy could increase system stability and prevent circulation currents between substations. Moreover, the proposed de-centralized coordination between substations does not rely on communication, which promotes the system's "plug-and-play" functionality. Stability analysis was undertaken and the proposed controller was proved to be exponentially stable. The dynamic response of the proposed controller was validated using comprehensive case studies in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic caused by SARS-CoV-2 highlighted the importance of reliable detection methods for disease control and surveillance. Optimizing detection antibodies by rational screening antigens would improve the sensitivity and specificity of antibody-based detection methods such as colloidal gold immunochromatography. In this study, we screened three peptide antigens with conserved sequences in the N protein of SARS-CoV-2 using bioinformatical and structural biological analyses. Antibodies that specifically recognize these peptides were prepared. The epitope of the peptide that had the highest binding affinity with its antibody was located on the surface of the N protein, which was favorable for antibody binding. Using the optimal antibody that can recognize this epitope, we developed colloidal gold immunochromatography, which can detect the N protein at 10 pg/mL. Importantly, this antibody could effectively recognize both the natural peptide antigen and mutated peptide antigen in the N protein, showing the feasibility of being applied in the large-scale population testing of SARS-CoV-2. Our study provides a platform with reference significance for the rational screening of detection antibodies with high sensitivity, specificity, and reliability for SARS-CoV-2 and other pathogens. [ABSTRACT FROM AUTHOR]

The accurate segmentation and quantification of retinal fluid in Optical Coherence Tomography (OCT) images are crucial for the diagnosis and treatment of ophthalmic diseases such as age-related macular degeneration. However, the accurate segmentation of retinal fluid is challenging due to significant variations in the size, position, and shape of fluid, as well as their complex, curved boundaries. To address these challenges, we propose a novel multi-scale feature fusion attention network (FNeXter), based on ConvNeXt and Transformer, for OCT fluid segmentation. In FNeXter, we introduce a novel global multi-scale hybrid encoder module that integrates ConvNeXt, Transformer, and region-aware spatial attention. This module can capture long-range dependencies and non-local similarities while also focusing on local features. Moreover, this module possesses the spatial region-aware capabilities, enabling it to adaptively focus on the lesions regions. Additionally, we propose a novel self-adaptive multi-scale feature fusion attention module to enhance the skip connections between the encoder and the decoder. The inclusion of this module elevates the model's capacity to learn global features and multi-scale contextual information effectively. Finally, we conduct comprehensive experiments to evaluate the performance of the proposed FNeXter. Experimental results demonstrate that our proposed approach outperforms other state-of-the-art methods in the task of fluid segmentation. [ABSTRACT FROM AUTHOR]

Soil temperature directly affects the germination of seeds and the growth of crops. In order to accurately predict soil temperature, this study used RF and MLP to simulate shallow soil temperature, and then the shallow soil temperature with the best simulation effect will be used to predict the deep soil temperature. The models were forced by combinations of environmental factors, including daily air temperature (Tair), water vapor pressure (Pw), net radiation (Rn), and soil moisture (VWC), which were observed in the Hejiashan watershed on the Loess Plateau in China. The results showed that the accuracy of the model for predicting deep soil temperature proposed in this paper is higher than that of directly using environmental factors to predict deep soil temperature. In testing data, the range of MAE was 1.158–1.610 °C, the range of RMSE was 1.449–2.088 °C, the range of R2 was 0.665–0.928, and the range of KGE was 0.708–0.885 at different depths. The study not only provides a critical reference for predicting soil temperature but also helps people to better carry out agricultural production activities. [ABSTRACT FROM AUTHOR]

Owing to the harsh downhole environments, poor dispersion of silica at high salinity and high temperature can severely restrict its application as the nano-plugging agent in shale gas exploitation. The objective of this study is to improve salt tolerance and thermal stability of silica. Herein, silica was successfully functionalized with an anionic polymer (p SPMA) by SI-ATRP (surface-initiated atom transfer radical polymerization), named SiO2-g-SPMA. The grafted pSPMA brushes on silica provided sufficient electrostatic repulsion and steric repulsion for stabilizing silica in a harsh environment. The modified silica (SiO2-g-SPMA) had excellent colloidal stability at salinities up to 5.43 M NaCl (saturated brine) and standard API brine (8 wt% NaCl + 2 wt% CaCl2) for 30 days at room temperature. Simultaneously, the SiO2-g-SPMA was stable at 170 °C for 24 h as well as stable in weakly alkali environment. Furthermore, the plugging performance of SiO2-g-SPMA in water-based drilling fluids for low permeate reservoir reached to 78.25% when adding a small amount of 0.5 wt% SiO2-g-SPMA, which effectively hindered the water invasion into formation and protected the reservoir. [ABSTRACT FROM AUTHOR]

Irrigation water is the main type of water consumption in the Yanqi Basin irrigation district of Xinjiang, which is an oasis-type irrigation district in the arid region of Northwest China. With the continuous expansion of cultivated areas, there is an increasing demand for irrigation water, resulting in an irrigation efficiency paradox and the phenomenon of "the more water-saving, the more water-scarce". In this study, the water balance method and the improved IWMI (International Water Management Institute) water balance method were used with remote sensing and statistical data from 1980 to 2020 to analyze the changes in the irrigation water supply, consumption, and loss for improvement in irrigation water use efficiency (IWUE) in the Yanqi Basin. The results showed that there was an upward trend in the cultivated land area in the irrigation district of Yanqi Basin, as monitored with remote sensing from 1980 to 2020, and the values from the remote sensing data were higher than those from the yearbooks. According to the remote sensing data, the arable land area in the irrigation district increased from 1672 km2 in 1980 to 2494 km2 in 2020, thus showing a trend of expansion. The traditional water use efficiency in the irrigation district showed an increasing trend. The lowest value for the field water-use coefficient was 0.70 in 1998, and it exceeded to 0.81 from 2009 to 2020. The canal water-use coefficient was as low as 0.50 in 1998 and increased from 0.54 in 2009 to 0.82 in 2020. The irrigation water-use coefficient increased from 0.35 in 1998 to 0.68 in 2020, with a general upward trend. In this study, the water consumption ratio indicator DFg (depleted fraction), determined using the improved water balance method, increased from 0.8390 in 1980 to 0.8562 in 2020, although it showed an overall decreasing trend, and the average was 0.8436. Cultivated land's actual irrigation water consumption per unit area reached the highest value of 8.41 × 106 m3/hm2/a in 2011 and the minimum value of 4.01 × 106 m3/hm2/a in 2020, and from 1980 to 2020 it showed a decreasing trend, while the total water diversion showed an increasing trend due to the continuous expansion of arable land. From 1980 to 2020, water diversion into the irrigation district changed from 1.214 km3 to 1.000 km3, and it reached a maximum of 1.593 km3 in 2000; water diversion into the irrigation district showed an overall upward trend. The positive impact of the post-2000 water conservation phase with the adaptation of water-saving irrigation technology was clear, as the findings showed an increase in IWUE in the Yanqi Basin irrigation district. These results provide a theoretical basis for breaking the paradox of irrigation efficiency, which can be used in the water resource management of irrigation districts. [ABSTRACT FROM AUTHOR]

Due to its low conduction loss, hence high current ratings, as well as low cost, Silicon Insulated Gate Bipolar Transistor (Si IGBT) is widely used in high power applications. However, its switching frequency is generally low because of relatively large switching losses. Silicon carbide Metal-Oxide-Semiconductor Field-Effect Transistor (SiC MOSFET) is much more superior due to their fast switching speed, which is determined by the internal parasitic capacitance instead of the stored charges, like the IGBT. By the combination of SiC MOSFET and Si IGBT, this paper presents a novel series hybrid switching method to achieve IGBT's dynamic switching loss reduction by switching under Zero Voltage Hard Current (ZVHC) turn-on and Zero Current Hard Voltage (ZCHV) turn-off conditions. Both simulation and experimental results of IGBT are carried out, which shows that the soft switching of IGBT has been achieved both in turn-on and turn-off period. Thus 90% turn-on loss and 57% turn-off loss are reduced. Two different IGBTs' test results are also provided to study the modulation parameter's effect on the turn-off switching loss. Furthermore, with the consideration of voltage and current transient states, a new soft switching classification is proposed. At last, another improved modulation and Highly Efficient and Reliable Inverter Concept (HERIC) inverter are given to validate the effectiveness of the device level hybrid soft switching method application. [ABSTRACT FROM AUTHOR]

Mucin1 (MUC1) is abnormally glycosylated and overexpressed in a variety of epithelial cancers and plays a critical role in tumor progression. MUC1 has received remark attention as an oncogenic molecule and is considered a valuable tumor target for immunotherapy, while many monoclonal antibodies (mAbs) targeting MUC1-positive cancers in clinical studies lack satisfactory results. It would be highly desirable to develop an effective therapy against MUC1-expressing cancers. In this study, we constructed a novel T cell-engaging bispecific antibody (BsAb) targeting MUC1 and CD3 with the Fab-ScFv-IgG format. A high quality of MUC1-CD3 BsAb can be acquired through a standard method. Our study suggested that this BsAb could specifically bind to MUC1- and CD3-positive cells and efficiently enhance T cell activation, cytokine release, and cytotoxicity. Furthermore, our study demonstrated that this BsAb could potently redirect T cells to eliminate MUC1-expressing tumor cells in vitro and significantly suppress MUC1-positive tumor growth in a xenograft mouse model. Thus, T cell-engaging MUC1/CD3 BsAb could be an effective therapeutic approach to combat MUC1-positive tumors and our MUC1/CD3 BsAb could be a promising candidate in clinical applications for the treatment of MUC1-positive cancer patients. [ABSTRACT FROM AUTHOR]

Mycotoxins are the toxic secondary metabolites produced by fungi and they are a worldwide public health concern. A VHH antibody (or nanobody) is the smallest antigen binding entity and is produced by heavy chain only antibodies. Compared with conventional antibodies, VHH antibodies overcome many pitfalls typically encountered in clinical therapeutics and immunodiagnostics. Likewise, VHH antibodies are particularly useful for monitoring mycotoxins in food and feedstuffs, as they are easily genetic engineered and have superior stability. In this review, we summarize the efforts to produce anti-mycotoxins VHH antibodies and associated assays, presenting VHH as a potential tool in mycotoxin analysis. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) are lipid bound particles derived from their original cells, which play critical roles in intercellular communication through their cargoes, including protein, lipids, and nucleic acids. According to their biogenesis and release pathway, EVs can be divided into three categories: apoptotic vesicles (ApoVs), microvesicles (MVs), and small EVs (sEVs). Recently, the role of EVs in oral disease has received close attention. In this review, the main characteristics of EVs are described, including their classification, biogenesis, biomarkers, and components. Moreover, the therapeutic mechanism of EVs in tissue regeneration is discussed. We further summarize the current status of EVs in pulp/periodontal tissue regeneration and discuss the potential mechanisms. The therapeutic potential of EVs in pulp and periodontal regeneration might involve the promotion of tissue regeneration and immunomodulatory capabilities. Furthermore, we highlight the current challenges in the translational use of EVs. This review would provide valuable insights into the potential therapeutic strategies of EVs in dental pulp and periodontal regeneration. [ABSTRACT FROM AUTHOR]

Non-syndromic cleft lip with or without cleft palate (NSCL/P) is a complex disease with a strong genetic component. More than 40 loci have been identified to be associated with the risk of NSCL/P by genome-wide association studies (GWASs), but the majority of these variants are mapped to non-coding regions of the genome. Expression quantitative trait locus (eQTL) studies have increasingly been integrated with GWASs to identify target genes for these non-coding variants. In this study, we generated a unique, lip-specific eQTL dataset from 40 NSCL/P patients. A total of 5158 eQTL SNPs (eSNPs) -689 eQTL genes were identified after multiple corrections. Then, we integrated nominal eQTL SNPs with NSCL/P risk SNPs and identified 243 variants associated with the expression of 18 genes in lip tissues. Functional annotation analysis indicated that these risk eSNPs were significantly enriched in transcription regulation and chromatin open regions on the genome. These susceptible genes were enriched in cell fate determination, the pluripotency of stem cells, and Wnt signaling pathways. Finally, 8 of the 18 susceptible genes were differentially expressed in NSCL/P case-control studies. In summary, we have generated a unique lip-specific eQTL resource and identified multiple associations for NSCL/P risk loci, which should inform functional studies of NSCL/P biology. [ABSTRACT FROM AUTHOR]

Skeletal Class III malocclusion with maxillary deficiency is a severe maxillofacial disease with unclear pathogenic mechanisms. We recruited a Han Chinese family who was clinically diagnosed with skeletal Class III malocclusion and maxillary deficiency. Using whole exome sequencing, a missense variant in ADAMTS2 (NM_014244: c.3506G>T: p.G1169V) was identified and predicted as deleterious by in silico tools. We also found ADAMTS2 variants associated with deficient maxillary development in a cohort. ADAMTS2 expression in HEK293 cells showed significant decrease due to the variant, which was also consistent in dental pulp stem cells from the proband and a healthy control. In the adamts2-knockdown zebrafish model, the length and width of the ethmoid plate, as well as the length of the palatoquadrate became significantly shorter than the control group (p < 0.001), while there was no significant difference in the length and width of the mandible. The expression of Sox3, which was required in early embryonic craniofacial development, was significantly downregulated in the adamts2-knockdown zebrafish embryos. Bioinformatic and cellular studies showed that the decreased expression of ADAMTS2 may inhibit downstream ErbB signaling pathway transduction and restrain subsequent osteogenesis in human adult mesenchymal stromal cells. Collectively, these data showed that ADAMTS2 (c.3506G>T: p.G1169V) may confer susceptibility to risk of skeletal Class III malocclusion with maxillary deficiency. [ABSTRACT FROM AUTHOR]

Simple Summary: The findings of predictive and diagnostic systems in cancer are an intriguing topic for physicians and the oncologic community. Computer-aided decision (CAD) is vital for breast cancer diagnosis. It aids in higher accuracy and early, reliable diagnosis. To achieve such aims, diverse imaging modalities have been used and decision-making was facilitated by artificial intelligence and machine learning models. High-fidelity automated breast lesion finding, along with their corresponding radiomic feature biomarkers, can be delivered by a trained model. In this study, the potential impact of a machine learning model for detecting breast lesions and various radiomic biomarkers are examined. This study presents a model that automatically segments and extracts radiomics and can enable the clinical practice to find breast lesions while performing diagnosis concurrently. Automated medical data analysis demonstrated a significant role in modern medicine, and cancer diagnosis/prognosis to achieve highly reliable and generalizable systems. In this study, an automated breast cancer screening method in ultrasound imaging is proposed. A convolutional deep autoencoder model is presented for simultaneous segmentation and radiomic extraction. The model segments the breast lesions while concurrently extracting radiomic features. With our deep model, we perform breast lesion segmentation, which is linked to low-dimensional deep-radiomic extraction (four features). Similarly, we used high dimensional conventional imaging throughputs and applied spectral embedding techniques to reduce its size from 354 to 12 radiomics. A total of 780 ultrasound images—437 benign, 210, malignant, and 133 normal—were used to train and validate the models in this study. To diagnose malignant lesions, we have performed training, hyperparameter tuning, cross-validation, and testing with a random forest model. This resulted in a binary classification accuracy of 78.5% (65.1–84.1%) for the maximal (full multivariate) cross-validated model for a combination of radiomic groups. [ABSTRACT FROM AUTHOR]

Herein, we prepared CoO nanozymes with three types of enzyme catalytic activities for the first time, which have SOD-like, CAT-like, and POD-like catalytic activities. This is the first study to report the preparation of CoO nanoparticles with three types of enzyme catalytic activities by the one-pot method. By modifying the surface of CoO nanozymes with a carboxyl group, its biocompatibility enhanced, so it can be used in the field of life sciences. In vitro cytotoxicity and anti-H2O2-induced ROS experiments proved that CoO nanozymes can protect HaCaT cells against ROS and cytotoxicity induced by H2O2. In addition, an atopic dermatitis (AD) mouse model was established by topical application of MC903, which verified the anti-inflammatory effect of CoO nanozymes on the AD mouse model. Traditional drugs for the treatment of AD, such as dexamethasone, have significant side-effects. The side-effects include skin burns, telangiectasias, and even serious drug dependence. CoO nano-enzymes have a low cytotoxicity and its multiple enzyme-like catalytic activities can effectively protect cells and tissues in ROS environments, which proves that CoO nano-enzymes have high application potential in the field of anti-inflammation. [ABSTRACT FROM AUTHOR]

This research aimed to explore how Strychnine (Str) ion-pair compounds affect the in vitro transdermal process. In order to prevent the influence of different functional groups on skin permeation, seven homologous fatty acids were selected to form ion-pair compounds with Str. The in vitro permeation fluxes of the Str ion-pair compounds were 2.2 to 8.4 times that of Str, and Str-C10 had the highest permeation fluxes of 42.79 ± 19.86 µg/cm2/h. The hydrogen bond of the Str ion-pair compounds was also confirmed by Fourier Transform Infrared (FTIR) Spectroscopy, Nuclear Magnetic Resonance (NMR) Spectroscopy and molecular simulation. In the process of molecular simulation, the intercellular lipid and the viable skin were represented by ceramide, cholesterol and free fatty acid of equal molar ratios and water, respectively. It was found by the binding energy curve that the Str ion-pair compounds had better compatibility with the intercellular lipid and water than Str, which indicated that the affinity of Str ion-pair compounds and skin was better than that of Str and skin. Therefore, it was concluded that Str ion-pair compounds can be distributed from the vehicle to the intercellular lipid and viable skin more easily than Str. These findings broadened our knowledge about how Str ion-pair compounds affect the transdermal process. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading causes of death globally. A variety of phenolic compounds display preventative and therapeutic effects against cancers. Green teas are rich in phenolics. Catechins are the most dominant phenolic component in green teas. Studies have shown that catechins have anticancer activity in various cancer models. The anticancer activity of catechins, however, may be compromised due to their low oral bioavailability. Nanodelivery emerges as a promising way to improve the oral bioavailability and anticancer activity of catechins. Research in this area has been actively conducted in recent decades. This review provides the molecular mechanisms of the anticancer effects of catechins, the factors that limit the oral bioavailability of catechins, and the latest advances of delivering catechins using nanodelivery systems through different routes to enhance their anticancer activity. [ABSTRACT FROM AUTHOR]

Herein, we prepared CoO nanozymes with three types of enzyme catalytic activities for the first time, which have SOD-like, CAT-like, and POD-like catalytic activities. This is the first study to report the preparation of CoO nanoparticles with three types of enzyme catalytic activities by the one-pot method. By modifying the surface of CoO nanozymes with a carboxyl group, its biocompatibility enhanced, so it can be used in the field of life sciences. In vitro cytotoxicity and anti-H2O2-induced ROS experiments proved that CoO nanozymes can protect HaCaT cells against ROS and cytotoxicity induced by H2O2. In addition, an atopic dermatitis (AD) mouse model was established by topical application of MC903, which verified the anti-inflammatory effect of CoO nanozymes on the AD mouse model. Traditional drugs for the treatment of AD, such as dexamethasone, have significant side-effects. The side-effects include skin burns, telangiectasias, and even serious drug dependence. CoO nano-enzymes have a low cytotoxicity and its multiple enzyme-like catalytic activities can effectively protect cells and tissues in ROS environments, which proves that CoO nano-enzymes have high application potential in the field of anti-inflammation. [ABSTRACT FROM AUTHOR]

The high mutation rate of the influenza A virus hemagglutinin segment poses great challenges to its long-term effective testing and subtyping. Our conserved sequence searching method achieves high-specificity conserved sequences on H1–H9 subtypes. In addition, PCR experiments show that primers based on conserved sequences can be used in influenza A virus HA subtyping. Conserved sequence-based primers are expected to be long-term, effective subtyping tools for influenza A virus HA. [ABSTRACT FROM AUTHOR]

As an important part of a micro-compressed air energy storage system, the scroll expander directly affects the efficiency of the whole energy storage system. The effects of resistance on the efficiency of scroll expander caused by inlet structure and size are discussed with theory analysis and experimental methods in this paper. Micro-compressed air energy storage system has aroused widespread attention because of its pollution-free, high flexibility, in the community, remote areas power supply. Comprehensive experimental work with the selections of different size and structure of the air inlet of the scroll expander was performed with the cutting angle of air inlet chamber of the scroll expander. The results of the experiments are discussed on how exergy efficiency and inlet flow of the scroll expander were affected resulting from the cutting angles dissected. The results show that a maximum value exists for exergy efficiency of the scroll expander. Therefore, the exergy efficiency of the scroll expander can be effectively improved by enlarging the air inlet port dimension and modifying the size of air chamber. [ABSTRACT FROM AUTHOR]

Nanomaterials can enhance interactions with stem cells for tissue regeneration. This study aimed to investigate the biological effects of tricalcium silicate nanoparticle-containing cement (Biodentine™) during or after setting on stem cells from human exfoliated deciduous teeth (SHED) to mimic clinically relevant situations in which materials are adapted. Specimens were divided into four groups depending on the start of extraction time (during (3, 6 and 12 min) or after setting (24 h)) and extracted in culture medium for 24 h for further physicochemical and biological analysis. After cell viability in serially diluted extracts was evaluated, odontogenic differentiation on SHED was evaluated by ARS staining using nontoxic conditions. A physicochemical analysis of extracts or specimens indicated different Ca ion content, pH, and surface chemistry among groups, supporting the possibility of different biological functionalities depending on the extraction starting conditions. Compared to the 'after setting' group, all 'during setting' groups showed cytotoxicity on SHED. The during setting groups induced more odontogenic differentiation at the nontoxic concentrations compared to the control. Thus, under clinically simulated extract conditions at nontoxic concentrations, Biodentine™ seemed to be a promising odontoblast differentiating biomaterial that is helpful for dental tissue regeneration. In addition, to simulate clinical situations when nanoparticle-containing cement is adjusted, biological effects during setting need to be considered. [ABSTRACT FROM AUTHOR]

Increased expression of trefoil factor 3 (TFF3) has been reported in colorectal carcinoma (CRC), being correlated with distant metastasis and poor clinical outcomes. Amongst the CRC subtypes, mesenchymal (CMS4) CRC is associated with the worst survival outcome. Herein, the functional roles of TFF3 and the pharmacological inhibition of TFF3 by a novel specific small molecule TFF3 inhibitor—2-amino-4-(4-(6-fluoro-5-methylpyridin-3-yl)phenyl)-5-oxo-4H,5H-pyrano[3,2-c]chromene-3-carbonitrile (AMPC) in CMS4 CRC was explored. Forced expression of TFF3 in CMS4 CRC cells promoted cell proliferation, cell survival, foci formation, invasion, migration, cancer stem cell like behaviour and growth in 3D Matrigel. In contrast, siRNA-mediated depletion of TFF3 or AMPC inhibition of TFF3 in CMS4 CRC cells decreased oncogenic behaviour as indicated by the above cell function assays. AMPC also inhibited tumour growth in vivo. The TFF3-stimulated oncogenic behaviour of CMS4 CRC cells was dependent on TFF3 activation of the p44/42 MAPK (ERK1/2) pathway. Furthermore, the forced expression of TFF3 decreased the sensitivity of CMS4 CRC cells to 5-fluorouracil (5-FU); while depleted TFF3 expression enhanced 5-FU sensitivity in CMS4 CRC cells. 5-FU treatment induced TFF3 expression in CMS4 CRC cells. AMPC, when used in combination with 5-FU in CMS4 CRC cells exhibited a synergistic inhibitory effect. In summary, this study provides functional evidence for TFF3 as a therapeutic target in CMS4 CRC. [ABSTRACT FROM AUTHOR]

Dose-dependent toxicity and acquired resistance are two major challenges limiting the efficacious treatment of mammary carcinoma (MC) with doxorubicin. Herein, we investigated the function of Trefoil Factor 3 (TFF3) in the sensitivity and acquired resistance of estrogen receptor positive (ER+) MC cells to doxorubicin. Doxorubicin treatment of ER+MC cells increased TFF3 expression. The depletion of TFF3 by siRNA or inhibition with a small molecule TFF3 inhibitor (AMPC) synergistically enhanced the efficacy of doxorubicin in ER+MC through the suppression of doxorubicin-induced AKT activation and enhancement of doxorubicin-induced apoptosis. Elevated expression of TFF3 and increased activation of AKT were also observed using a model of acquired doxorubicin resistance in ER+MC cells. AMPC partially re-sensitized the doxorubicin resistant cells to doxorubicin-induced apoptosis. Indeed, doxorubicin resistant ER + MC cells exhibited increased sensitivity to AMPC as a single agent compared to doxorubicin sensitive cells. In vivo, AMPC attenuated growth of doxorubicin sensitive ER+MC xenografts whereas it produced regression of xenografts generated by doxorubicin resistant ER+MC cells. Hence, TFF3 inhibition may improve the efficacy and reduce required doses of doxorubicin in ER+MC. Moreover, inhibition of TFF3 may also be an effective therapeutic strategy to eradicate doxorubicin resistant ER+MC. [ABSTRACT FROM AUTHOR]