Search

Osteogenic differentiation of mesenchymal stem cells (MSCs) is proposed to be critical for bone tissue engineering and regenerative medicine. However, the current approach for evaluating osteogenic differentiation mainly involves immunohistochemical staining of specific markers which often can be detected at day 5–7 of osteogenic inducing. Deep learning (DL) is a significant technology for realizing artificial intelligence (AI). Computer vision, a branch of AI, has been proved to achieve high-precision image recognition using convolutional neural networks (CNNs). Our goal was to train CNNs to quantitatively measure the osteogenic differentiation of MSCs. To this end, bright-field images of MSCs during early osteogenic differentiation (day 0, 1, 3, 5, and 7) were captured using a simple optical phase contrast microscope to train CNNs. The results showed that the CNNs could be trained to recognize undifferentiated cells and differentiating cells with an accuracy of 0.961 on the independent test set. In addition, we found that CNNs successfully distinguished differentiated cells at a very early stage (only 1 day). Further analysis showed that overall morphological features of MSCs were the main basis for the CNN classification. In conclusion, MSCs differentiation detection can be achieved early and accurately through simple bright-field images and DL networks, which may also provide a potential and novel method for the field of cell detection in the near future. [ABSTRACT FROM AUTHOR]

This study explores the potential of machine learning algorithms for earthquake prediction, utilizing fluid chemical anomaly data from hot springs. Six hot springs, located within an active fault zone along the southeastern coast of China, were carefully chosen as hydrochemical monitoring sites for an extended period of two and a half years. Using this data, a prediction model integrating six algorithms was developed to forecast M ≥ 5 earthquakes in Taiwan. The model's performance was validated against recorded earthquake events, and the factors influencing its predictive capability were analyzed. Our comprehensive analysis conclusively demonstrates the superiority of machine learning algorithms over traditional statistical methods for earthquake prediction. Additionally, including sampling time in the data sets significantly improves the model's predictive performance. However, it is important to note that the model's predictive performance varies across different hot spring and indicators type, highlighting the importance of identifying optimal indicators for specific scenarios. The model parameters, including the anomaly detection rate (P) and earthquake response time threshold (M), significantly impact the model's predictive capabilities. Therefore, adjustments are needed to optimize the model's performance for practical use. Despite limitations such as the inability to differentiate pre‐earthquake anomalies from post‐earthquake anomalies and pinpoint the precise location of earthquakes, this study successfully showcases the potential of machine learning algorithms in earthquake prediction, paving the way for further research and improved prediction methods. Plain Language Summary: This study explores the potential of utilizing machine learning algorithms for earthquake prediction based on hydrothermal fluid chemical anomaly data. An earthquake prediction model integrating six machine learning algorithms was developed using continuous hot spring hydrochemical monitoring data. The model's prediction performance was validated using actual earthquake event data, and various factors influencing its predictive capability were analyzed. The results demonstrate that the machine learning algorithm's prediction performance exceeds that of traditional methods, and the selection of hot springs, indicator types, and model parameters significantly impacts the model's prediction performance. This study successfully showcased the potential of machine learning algorithms in earthquake prediction, while also indicating new avenues for further research and improvement of prediction methods. Key Points: An earthquake prediction model based on machine learning using hydrochemical data from hot springs is proposed with sufficient accuracyThe earthquake prediction accuracy of the local outlier factor algorithm outperformed the traditional statistical methodThe predictive performance of the model varies across different hot springs, indicators type, and model parameters [ABSTRACT FROM AUTHOR]

The Eastern Kunlun Fault (EKF) is situated in an area with a history of significant seismic events, yet it has witnessed a dearth of major earthquakes in recent years. This study conducted a detailed analysis of the hydrogeochemical characteristics of the springs in the EKF and their temporal variation, aiming to address the gaps in the research on the hydrogeochemistry in the region and to investigate the changes in water chemistry during the seismogenic process. In this study, the main elements, trace elements, hydrogen isotopes, oxygen isotopes, and strontium isotopes of 23 springs in the EKF were analyzed. The results indicated that the groundwater recharge in the eastern part of the Eastern Kunlun Fault Zone mainly originates from atmospheric precipitation, as supported by its isotopic characteristics. The spring water is immature, showing weak water–rock interactions. A hydrochemical analysis classified the springs into 11 main types, reflecting varying degrees of water–rock interaction. Based on measurements using quartz geothermometers, the estimated geothermal reservoir temperatures ranged from 39.6 to 120.3 °C, with circulation depths of 1.3 to 3.8 km. By means of regularly monitoring three selected springs, this study also explored the relationship between earthquakes and hot spring chemical variations. Finally, a conceptual model of hydrogeochemistry was proposed to describe the groundwater circulation in the study area. [ABSTRACT FROM AUTHOR]

Lipid metabolic reprogramming of tumor cells has been proven to play a critical role in tumor initiation and development. However, lipid metabolism in cancer‐associated fibroblasts (CAFs) has rarely been studied, particularly in CAFs of oral squamous cell carcinoma (OSCC). Additionally, the molecular mechanism by which tumor cells regulate lipid metabolism in fibroblasts is unclear. In this study, we found that phosphorylated ATP citrate lyase (p‐ACLY), a key lipid metabolic enzyme, was upregulated in OSCC CAFs. Compared to paracancerous normal fibroblasts, CAFs showed enhanced lipid synthesis, such as elevated cytosolic acetyl‐CoA level and accumulation of lipid droplets. Conversely, reduction of p‐ACLY level blocked this biological process. In addition, blocking lipid synthesis in CAFs or inhibiting fatty acid uptake by OSCC cells reduced the promotive effects of CAFs on OSCC cell proliferation, invasion, and migration. These findings suggested that CAFs are one of lipid sources required for OSCC progression. Mechanistically, AKT signaling activation was involved in the upregulation of p‐ACLY level and lipid synthesis in CAFs. Interleukin‐8 (IL8), an exocrine cytokine of OSCC cells, could activate AKT and then phosphorylate ACLY in fibroblasts. This study suggested that the IL8/AKT/p‐ACLY axis could be considered as a potential target for OSCC treatment. [ABSTRACT FROM AUTHOR]

Objectives: To compare oral adhesive bandages with the classic compression method and evaluate the clinical efficacy of this wound dressing material in improving postoperative comfort, wound healing, and hemostasis in tooth extraction. Materials and methods: The study was designed as a randomized controlled clinical trial. A total of 120 patients were recruited and randomly assigned to the study group and the control group. In the study group, oral adhesive bandages were used as wound dressing. In the control group, patients bit on cotton balls and gauze, as usual. Hemorrhage, comfort, and healing levels were evaluated at postoperative 1 h, 24 h, and 7 days. The adhesion time of the oral adhesive bandages was also recorded. Results: The average adhesion time of the oral adhesive bandages was 26.6 h. At postoperative 1 and 24 h, the hemostatic levels of the oral adhesive bandage group were significantly higher than those of the control group. The oral adhesive bandage group also reported significantly higher comfort scores than the control group. Both groups had similar healing levels and side effects. But the mean score for wound healing was slightly higher in the oral adhesive bandage group. Conclusions: Oral adhesive bandages were more effective than cotton balls and gauze in providing hemostatic and comfort effects on extraction wounds. Clinical relevance: Oral adhesive bandages possess clinical value in the management of extraction wounds. [ABSTRACT FROM AUTHOR]

Trace elements in hot-spring waters are indicators for tracing hydrochemical processes, such as the deep circulation of geothermal water, the degree of water–rock interaction, redox reactions, the contamination of shallow water by thermal water, etc. In this study, 74 hot springs in the Xianshuihe–Xiaojiang Fault Zone (XSHF-XJF) were chosen for an investigation of the geochemical characteristics of trace elements using classic geochemical tools and multivariate statistical analysis. The results indicated (1) the hot-spring waters were mainly derived from atmospheric precipitation as indicated by δD and δ18O values that generally increased with decreasing elevations; (2) the high concentrations of B, As, Fe, and Mn in the waters, as well as the values of the Water Quality Index (WQI), indicated that the water quality was spatially heterogeneous and the hot-spring waters are not entirely suitable for drinking; and (3) B/Cl ratios showed that hot springs have different reservoir sources in the XSHF and XJF, respectively. The leaching of surrounding rock during water circulation contributed predominantly to the trace elements of the study's waters. Diversity of lithology was the main factor affecting their concentrations. In addition, deep circulation controlled by the fault could influence trace-element enrichment. Our results offer a guide for the exploration and use of geothermal resources. [ABSTRACT FROM AUTHOR]

Hyaluronic acid (HA) is a glycosaminoglycan and the main component of the extracellular matrix (ECM), which has been reported to interact with its receptor CD44 to play critical roles in the self‐renewal and maintenance of cancer stem cells (CSCs) of multiple malignancies. Melatonin is a neuroendocrine hormone with pleiotropic antitumor properties. However, whether melatonin could regulate HA accumulation in the ECM to modulate the stemness of head and neck squamous cell carcinoma (HNSCC) remains unknown. In this study, we found that melatonin suppressed CSC‐related markers, such as CD44, of HNSCC cells and decreased the tumor‐initiating frequency of CSCs in vivo. In addition, melatonin modulated HA synthesis of HNSCC cells by downregulating the expression of hyaluronan synthase 3 (HAS3). Further study showed that the Fos‐like 1 (FOSL1)/HAS3 axis mediated the inhibitory effects of melatonin on HA accumulation and stemness of HNSCC in a receptor‐independent manner. Taken together, melatonin modulated HA synthesis through the FOSL1/HAS3 axis to inhibit the stemness of HNSCC cells, which elucidates the effect of melatonin on the ECM and provides a novel perspective on melatonin in HNSCC treatment. [ABSTRACT FROM AUTHOR]

The energy inside the Earth can not only be released outward through earthquakes and volcanoes but also can be used by humans in the form of geothermal energy. Is there a correlation between different forms of energy release? In this contribution, we perform detailed seismic and geothermal research in the Beijing area. The results show that the geothermal resources in Beijing belong to typical medium-low temperature geothermal resources of the sedimentary basin, and some areas are controlled by deep fault activities (e.g., Xiji geothermal well (No. 17)). The heat sources are upper mantle heat, radioactive heat in granite, and residual heat from magma cooling. The high overlap of earthquakes and geothermal field locations and the positive correlation between the injection water and earthquakes indicate that the exploitation and injection water will promote the release of the earth's energy. The energy releases are partitioned into multiple microearthquakes, avoiding damaging earthquakes (ML ≥ 5) due to excessive energy accumulation. Therefore, the exploitation of geothermal resources may be one way to reduce destructive earthquakes. Furthermore, the use of geothermal resources can also reduce the burning of fossil energy, which is of great significance in dealing with global warming. [ABSTRACT FROM AUTHOR]

Despite its ultrahigh theoretical capacity and ultralow redox electrochemical potential, the practical application of lithium metal anodes is still hampered by severe dendrite growth and unstable solid electrolyte interphase (SEI). Herein, a self‐assembled lithiophilic interface (SALI) for regulating Li electroplating behavior is constructed by introducing a meticulously synthesized Ni‐bis(dithiolene)‐based molecule (NiS4‐COOH) into a hybrid fluorinated ester‐ether electrolyte. The NiS4‐COOH molecules with carboxyl functional groups can spontaneously anchor on the Li metal surface to form a SALI, whose abundant Ni‐bis(dithiolene) sites can effectively reduce the initial Li deposition overpotential and guide the subsequent uniform Li electrodeposition. Moreover, due to the interaction between the coordination unsaturated Ni atom and the negatively charged PF6−, the NiS4‐COOH additive can significantly change the ionic coordination environment in the electrolyte, which is greatly conducive to suppressing PF6− decomposition, optimizing SEI composition and accelerating Li‐ion transfer. Consequently, the NiS4‐COOH‐modified electrolyte leads to impressive electrochemical performance of Li||LiFePO4 and Li||LiNi0.8Co0.1Mn0.1O2 batteries, delivering ultrahigh Coulombic efficiencies, considerable capacity retention, and good rate performance even at high areal active material loadings. This study presents the great potential of SALIs derived from multifunctional metal‐organic hybrid electrolyte additives toward high‐specific‐energy Li metal batteries. [ABSTRACT FROM AUTHOR]

Spatially resolved transcriptomics (SRT) is a vital technique in biology that allows for gene expression measurement at the resolution of individual spots while preserving spatial information. However, owing to technical limitations, single-spot resolution often includes data from multiple cells, leading to suboptimal results and opportunities for improvement. In this study, we propose a deep learning-based, plug-and-play method for enhancing spot resolution to obtain higher-resolution SRT data. Our approach involves training a convolutional neural network (CNN) model and introducing a shift-predict operation to obtain superresolution spots. Using a human breast cancer SRT dataset, we demonstrate that our method achieves 9 × superresolution, outperforming traditional superresolution techniques. Crucially, our method decreased the mean squared error (MSE) to 1.379 for all genes, 2.287 for tumor-related genes at 4 × superresolution, 1.866 for all genes, and 3.371 for tumor-related genes at 9 × superresolution, reflecting substantial improvements compared to the traditional approaches, including Gaussian RBF, multiquadric RBF, linear RBF, resize-predict, bilinear, and bicubic methods. Furthermore, we verify our method's effectiveness using external and simulated datasets. Our proposed method offers a substantial advancement in SRT by enabling higher-resolution gene expression data generation. By providing a deeper understanding of gene expression patterns and their underlying biological significance, this method contributes to progress in biology and medicine. [ABSTRACT FROM AUTHOR]

Objective: The laryngeal tissue carries most of the heat during inhalation injury. This study aims to explore the heat transfer process and the severity of injury inside laryngeal tissue by horizontally studying the temperature rise process at various anatomical layers of the larynx and observing the thermal damage in various parts of the upper respiratory tract. Methods: The 12 healthy adult beagles were randomly divided into four groups, and inhaled room temperature air (control group), dry hot air of 80 °C (group I), 160 °C (group II), and 320 °C (group III) for 20 min, respectively. The temperature changes of the glottic mucosal surface, the inner surface of the thyroid cartilage, the external surface of the thyroid cartilage, and subcutaneous tissue were measured every minute. All animals were immediately sacrificed after injury, and pathological changes in various parts of laryngeal tissue were observed and evaluated under a microscope. Results: After inhaling hot air of 80 °C, 160 °C and 320 °C, the increase of laryngeal temperature in each group was ΔT = 3.57 ± 0.25 °C, 7.83 ± 0.15 °C, 11.93 ± 0.21 °C. The tissue temperature was approximately uniformly distributed, and the difference was not statistically significant. The average laryngeal temperature–time curve showed that the laryngeal tissue temperature in group I and group II showed a trend of "first decrease and then increase", except that the temperature of group III directly increased with time. The prominent pathological changes after thermal burns mainly concluded necrosis of epithelial cells, loss of the mucosal layer, atrophy of submucosal glands, vasodilatation, erythrocytes exudation, and degeneration of chondrocytes. Mild degeneration of cartilage and muscle layers was also observed in mild thermal injury. Pathological scores indicated that the pathological severity of laryngeal burns increased significantly with the increase of temperature, and all layers of laryngeal tissue were seriously damaged by 320 °C hot air. Conclusions: The high efficiency of tissue heat conduction enabled the larynx to quickly transfer heat to the laryngeal periphery, and the heat-bearing capacity of perilaryngeal tissue has a certain degree of protective effect on laryngeal mucosa and function in mild to moderate inhalation injury. The laryngeal temperature distribution was in accordance with the pathological severity, and the pathological changes of laryngeal burns provided a theoretical basis for the early clinical manifestations and treatment of inhalation injury. [ABSTRACT FROM AUTHOR]

Renal cell carcinoma (RCC) is the most common form of kidney cancer in adults. Despite new therapeutic modalities, the outcomes for RCC patients remain unsatisfactory. Rho-associated coiled-coil forming protein kinase 2 (ROCK2) has previously been shown to be upregulated in RCC, and its expression was negatively correlated with patient survival. However, the precise molecular function of ROCK2 has remained unclear. Herein, using RNA-seq analysis of ROCK2 knockdown and control cells, we identified 464 differentially expressed genes, and 1287 alternative splicing events in 786-O RCC cells. Furthermore, mapping of iRIP-seq reads in 786-O cells showed a biased distribution at 5' UTR, intronic and intergenic regions. By comparing ROCK2-regulated alternative splicing and iRIP-seq data, we found 292 overlapping genes that are enriched in multiple tumorigenic pathways. Taken together, our work defined a complex ROCK2-RNA interaction map on a genomic scale in a human RCC cell line, which deepens our understanding of the molecular function of ROCK2 in cancer development. [ABSTRACT FROM AUTHOR]

In the search for precursors to earthquakes, correlation has been found between geochemical characteristics of soil gases and seismic activity. In this paper we present evidence that seismic waves can trigger emission of soil radon (Rn) and carbon dioxide (CO2). An active experiment was performed in two fault zones in China, the Annighe fault in Sichuan province and the Xiadian fault in Heibei province. An active seismic source was used to generate seismic waves at 10 m depth in wells within bedrock. Rn and CO2 detectors were placed around the wells at a distance of ∼1 m for observing the effects of the seismic waves on the emission of the gases. The observations confirm that the seismic waves have a significant and direct effect on the concentration and flux of soil radon and carbon dioxide. When the seismic events were triggered, the observed concentrations of Rn and CO2 immediately increased and reached peak values within 5–50 min and 30–60 min, with corresponding increases of Rn and CO2 concentrations by 10.5%–238.7% and 3.1%–54.1%, respectively. The measured concentrations and flux of CO2 and Rn after the passage of the seismic waves showed strong correlation, confirming the suggestion that CO2 is the carrier gas for Rn. To the best of our knowledge this is the first direct, in‐situ measurement of gas emission caused by the passage of seismic waves and provides important constraints for better understanding of geochemical earthquake precursors. Plain Language Summary: Observed geochemical properties of soil gases migrated from the deep Earth can be used to survey seismicity, volcanic activity and emission of greenhouse gases. However, due to difficulty in natural earthquake prediction, most observations on the geochemical effects linked to seismic activity are conducted after or away from naturally occurring events, with the effects normally inferred from seismic parameters. In this study, an active seismic source based on methane gaseous detonation was employed to artificially produce seismic events along two fault zones, and in‐situ measurements of concentrations and flux of radon (Rn) and carbon dioxide (CO2) were conducted. These observations showed strong correlation between concentrations and flux of CO2 and Rn after the events, in agreement with the hypothesis that CO2 is the carrier gas for Rn in tectonically active settings. Key Points: Soil CO2 and Rn emission triggered by a new type active source that excited at 10 m deep well in bedrock are observed at first timeQuantitative effect of seismicity on the concentration and flux of soil CO2 and Rn are presentedEmission of CO2 and Rn after the seismicity show strong correlation and proved that CO2 is the carrier gas for Rn [ABSTRACT FROM AUTHOR]

Studying the hydrogeochemical characteristics of hot springs provides essential geochemical information for monitoring earthquake precursors and understanding the relationship between fluids, fractures, and earthquakes. This paper investigates the hydrogeochemical characteristics of hot springs along the Tingri–Nyima Rift (TNR) in southern Tibet, a seismically active zone at the collision front of the Indian and Asian-European plates. The major elements, hydrogen, and oxygen isotopes of seven thermal springs were analyzed from July 2019 to September 2021. The findings indicate that Mount Everest's meteoric water, which has a recharge elevation of roughly 7.5–8.4 km, is the main source of recharge for the hot springs. The water samples have two main hydrochemical types: HCO3-Na and Cl-Na. The temperature of the geothermal reservoir is between 46.5 and 225.4 °C, while the circulation depth is between 1.2 and 5.0 km based on silica-enthalpy mixing models and traditional geothermometers. Furthermore, continuous measurements of major anions and cations at the Yundong Spring (T06) near Mount Everest reveal short-term (8 days) seismic precursor anomalies of hydrochemical compositions before an ML4.7 earthquake 64.36 km away from T06. Our study suggests that seismicity in the northern section of the TNR is controlled by both hydrothermal activity and tectonic activity, while seismicity in the southern section is mainly influenced by tectonic activity. In addition to magnitude and distance from the epicenter, geological forces from deep, large fissures also affect how hot springs react to seismic occurrences. A fluid circulation model is established in order to explain the process of groundwater circulation migration. The continuous hydrochemical monitoring of hot springs near Everest is critical for studying the coupling between hot springs, fractures, and earthquakes, as well as monitoring information on earthquake precursory anomalies near Everest. [ABSTRACT FROM AUTHOR]

Developing efficient cathode materials with good conductivity to restrain the shuttle effect and promote the reaction kinetics has been a key scientific issue for the development of lithium–sulfur (Li–S) batteries. Here, by means of first-principles computations, we demonstrate that the NbS2 monolayer is a promising cathode anchoring material for Li–S batteries. It has a metallic feature that improves the conductivity of sulfur and lithium polysulfides (LiPSs) and promotes the electron transfer ability. The discharge products LiPSs are strongly anchored on the NbS2 monolayer without structural distortion, which effectively alleviates the shuttle effect. Remarkably, the reductions of sulfur to soluble LiPSs are spontaneous exothermic reactions while the subsequent reductions to insoluble LiPSs are endothermic reactions with low Gibbs free energy barriers (0.09–0.18 eV) and reaction activation barriers (0.83–0.93 eV), ensuring the rapid discharge process. In addition, the barriers of Li2S decomposition and Li atom diffusion are only 0.64 and 0.18 eV, respectively, which improve the reaction kinetics in the charging process and the cycling life of batteries. These results suggest that the NbS2 monolayer can be utilized as a promising anchoring material for Li–S batteries to achieve high reversible capacity and conversion efficiency. [ABSTRACT FROM AUTHOR]

Hydrogeochemical characterization studies are regarded as an important method for determining the origin of hot springs. The major elements, trace elements, and stable isotopes of four groups of hot spring water samples and two groups of gas samples collected from the intersection of the Altyn Tagh fault zone and the East Kunlun fault belt were investigated in this study. The hot spring water temperature ranged between 6 °C and 14 °C. The water chemistry types of the hot springs were Na·Mg-Cl, Mg·Na-Cl·HCO3, Na-Cl·SO4, and Na-Cl·HCO3. The δD values ranged from −50.00% to −68.60%, while the δ18O values ranged from −6.90% to −8.60%. The hot spring water was recharged mainly by infiltrating precipitation, with a recharge elevation of 3390~3676 m. The heat storage temperature ranged from 66.7 to 164.9 °C. The circulation depth was estimated to range between 1043 and 2679 m. The strontium isotopic composition of the water samples in response to the main weathering sources comprised carbonate and sulfate. CO2 was the main component in the hot spring gas in the study region, and its content was over 95%. The 3He/4He-R/Ra relationship diagram revealed that the mantle-sourced helium from the Yitunbulake spring was 3.06%. In comparison, that from the Aiken spring was 7.38%, which indicated an intrusion of mantle-source material mixed into the hot springs in the study region. The crustal marine limestone contributed significantly to the carbon inventory of the hot spring gas samples (>75%). The dissolution of the marl aquifer resulted in the release of CO2. Carbon was primarily obtained through metamorphism and hydrothermal reactions in the basement lithologies. The Yitunbulake and Aiken hot springs are found near the intersection of the Arjin and East Kunlun fractures, where the water–rock response is relatively strong and the depth of circulation and thermal storage temperature are both high. This causes relatively high ambient pressure to be released from the deep fluid, resulting in microseismic activity in this region. The continuous observation of Aiken spring water chemistry allows for the monitoring of fracture activity in the region. The results of the study could serve as a foundation for further exploration of the relationship between geothermal water and deep faults, shallow geological formations, hydrogeological conditions, and geothermal resource development in the region. [ABSTRACT FROM AUTHOR]

Forest canopy height plays an important role in forest resource management and conservation. The accurate estimation of forest canopy height on a large scale is important for forest carbon stock, biodiversity, and the carbon cycle. With the technological development of satellite-based LiDAR, it is possible to determine forest canopy height over a large area. However, the forest canopy height that is acquired by this technology is influenced by topography and climate, and the canopy height that is acquired in complex subtropical mountainous regions has large errors. In this paper, we propose a method for estimating forest canopy height by combining long-time series Landsat images with GEDI satellite-based LiDAR data, with Fujian, China, as the study area. This approach optimizes the quality of GEDI canopy height data in topographically complex areas by combining stand age and tree height, while retaining the advantage of fast and effective forest canopy height measurements with satellite-based LiDAR. In this study, the growth curves of the main forest types in Fujian were first obtained by using a large amount of forest survey data, and the LandTrendr algorithm was used to obtain the forest age distribution in 2020. The obtained forest age was then combined with the growth curves of each forest type in order to determine the tree height distribution. Finally, the obtained average tree heights were merged with the GEDI_V27 canopy height product in order to create a modified forest canopy height model (MGEDI_V27) with a 30 m spatial resolution. The results showed that the estimated forest canopy height had a mean of 15.04 m, with a standard deviation of 4.98 m. In addition, we evaluated the accuracy of the GEDI_V27 and the MGEDI_V27 using the sample dataset. The MGEDI_V27 had a higher accuracy (R2 = 0.67, RMSE = 2.24 m, MAE = 1.85 m) than the GEDI_V27 (R2 = 0.39, RMSE = 3.35 m, MAE = 2.41 m). R2, RMSE, and MAE were improved by 71.79%, 33.13%, and 22.53%, respectively. We also produced a forest age distribution map of Fujian for the year 2020 and a forest disturbance map of Fujian for the past 32 years. The research results can provide decision support for forest ecological protection and management and for carbon sink analysis in Fujian. [ABSTRACT FROM AUTHOR]

With the rapid development of Unmanned Aerial Vehicle (UAV) technology, more and more UAVs have been used in forest survey. UAV (RGB) images are the most widely used UAV data source in forest resource management. However, there is some uncertainty as to the reliability of these data when monitoring height and growth changes of low-growing saplings in an afforestation plot via UAV RGB images. This study focuses on an artificial Chinese fir (Cunninghamia lancelota, named as Chinese Fir) young forest plot in Fujian, China. Divide-and-conquer (DAC) and the local maximum (LM) method for extracting seedling height are described in the paper, and the possibility of monitoring young forest growth based on low-cost UAV remote sensing images was explored. Two key algorithms were adopted and compared to extract the tree height and how it affects the young forest at single-tree level from multi-temporal UAV RGB images from 2019 to 2021. Compared to field survey data, the R2 of single saplings' height extracted from digital orthophoto map (DOM) images of tree pits and original DSM information using a divide-and-conquer method reached 0.8577 in 2020 and 0.9968 in 2021, respectively. The RMSE reached 0.2141 in 2020 and 0.1609 in 2021. The R2 of tree height extracted from the canopy height model (CHM) via the LM method was 0.9462. The RMSE was 0.3354 in 2021. The results demonstrated that the survival rates of the young forest in the second year and the third year were 99.9% and 85.6%, respectively. This study shows that UAV RGB images can obtain the height of low sapling trees through a computer algorithm based on using 3D point cloud data derived from high-precision UAV images and can monitor the growth of individual trees combined with multi-stage UAV RGB images after afforestation. This research provides a fully automated method for evaluating the afforestation results provided by UAV RGB images. In the future, the universality of the method should be evaluated in more afforestation plots featuring different tree species and terrain. [ABSTRACT FROM AUTHOR]

The horizontal and vertical growth of two-dimensional (2D) materials dominates their properties and applications. Vertical 2D materials have great potential in applications like high-density transistors, sensors, catalytic and energy storage. However, the controllable growth of vertical 2D materials is still challenging and the mechanism for the vertical growth is far from well understood. In this study, MoO2 nanosheets were grown on c-Al2O3 substrate using atmospheric pressure chemical vapor deposition. A transition from horizontal MoO2 nanosheets to vertical MoO2 nanofins was observed on different regions of the substrate. On the confined contact region between the substrate and the quartz boat sides, the MoO2 nanofins grew vertically, while MoO2 nanosheets grew horizontally on the other regions of the substrate. According to our specially designed confined space experiments and the available nucleation theory, the vertical growth of MoO2 nanofins was enabled by the synergistic effect of a low precursor concentration and a low carrier gas flow rate. In particular, the vertical MoO2 nanofins were mainly oriented in three directions with the interval angle of 120°, which was explained by the local minimum angle-dependent binding energies between MoO2 and Al2O3 calculated by density functional theory. Finally, the electrical conductivity of an individual vertical MoO2 nanofin was measured to be 1.9 × 105 S/m, which is among the highest in metal oxides, making it promising for non-metal electrode in batteries and supercapacitors. Our work reveals the growth mechanism of oriented vertical MoO2 nanofins, which will benefit the preparation and practical application of vertical 2D materials. [ABSTRACT FROM AUTHOR]

Photocatalytic water splitting has been regarded as a promising strategy to provide clean energy and solve the energy crisis; thus, extensive efforts have been devoted to developing highly efficient photocatalysts. Herein, based on density functional theory computations, we demonstrated that the penta-BCN monolayer is a promising photocatalyst for water splitting. The penta-BCN monolayer is semiconducting with a moderate direct band gap of 2.87 eV, and its band edge positions straddle the redox potentials of water. Remarkably, the penta-BCN monolayer also has a pronounced optical absorption in the ultraviolet and visible light regions and exhibits an ultrahigh hole mobility (∼2 × 105 cm2 V−1 s−1). These desirable properties render the penta-BCN monolayer a promising candidate for photocatalytic water splitting. [ABSTRACT FROM AUTHOR]

Metal halide perovskites, primarily used as optoelectronic devices, have not been applied for electrochemical conversion due to their insufficient stability in moisture. Herein, two bismuth‐based perovskites are introduced as novel electrocatalysts to convert CO2 into HCOOH in aqueous acidic media (pH 2.5), exhibiting a high Faradaic efficiency for HCOOH of >80 % in a wide potential range from −0.75 to −1.25 V. Their structural evolution against water was dynamically monitored by in situ spectra. Theoretical calculations further reveal that the formation of intermediate OCHO* on bismuth sites of Cs3Bi2Br9(111) play a pivotal role toward HCOOH production, which has a lower energy barrier than that on Cs2AgBiBr6(001) surfaces. Significantly, CO2 reacts with protons instead of water which can enhance CO2 reduction rate and suppress hydrogen evolution by avoiding carbonate formation in acidic electrolytes. This work paves the way for the extensive investigation of halide perovskites in aqueous systems. [ABSTRACT FROM AUTHOR]

The quality control of variants from whole-genome sequencing data is vital in clinical diagnosis and human genetics research. However, current filtering methods (Frequency, Hard-Filter, VQSR, GARFIELD, and VEF) were developed to be utilized on particular variant callers and have certain limitations. Especially, the number of eliminated true variants far exceeds the number of removed false variants using these methods. Here, we present an adaptive method for quality control on genetic variants from different analysis pipelines, and validate it on the variants generated from four popular variant callers (GATK HaplotypeCaller, Mutect2, Varscan2, and DeepVariant). FVC consistently exhibited the best performance. It removed far more false variants than the current state-of-the-art filtering methods and recalled ~51-99% true variants filtered out by the other methods. Once trained, FVC can be conveniently integrated into a user-specific variant calling pipeline. FVC is a method for calling specific gene variants from whole genome data, for potential use in clinical diagnosis and human genetics research. [ABSTRACT FROM AUTHOR]

The coupling relationship between regional seismic activity and the hydrogeochemical field provides an important theoretical basis for regional earthquake precursor exploration. The intersection area of the Red River fault zone (RRF) and the Xiaojiang fault zone (XJF) in southeast Yunnan province has become the focus area of earthquake monitoring and prediction because of its special tectonic position in China. There were 20 hot springs that were sampled and analyzed in the laboratory for major elements, including trace elements, silica, stable isotopes (δ18O and δD), and strontium isotopes, from the years 2015 to 2019. (1) The meteoric water is the main source of recharge for thermal springs in the study area, and recharged elevations ranged from 1.1 to 2 km; (2) the geothermometer method was used to estimate the region of thermal storage temperature, and its temperature ranged between 64.3 to 162.7 °C, whereas the circulation depth ranged from 1.1 to 7.2 km. Hydrochemical types were mainly controlled by aquifer lithology, in which sodium bicarbonate and sulphuric acid water gathered mainly in the RRF, while calcium bicarbonate water gathered mainly in the XJF. According to the silicon–enthalpy equation method, the temperature range and cold water mixing ratio were 97–268 °C and 61–97%, respectively; (3) the circulation depth of the RRF was deeper than that of the XJF, and it was mainly concentrated in the second segment and the fourth segment on the RRF. Most of the hot spring water was immature with a weak water–rock reaction; (4) the hot water intersections of RRF and XJF were obviously controlled by the fault and the cutting depth of granite; (5) the relationship discussed between geothermal anomaly and earthquake activity had a good correspondence with regional seismicity. The intensity of the reaction between underground hot water and the surrounding rock may lead to the change of pore pressure, and the weakening effect of groundwater on fracture may change accordingly, followed by the change in the adjustment of tectonic stress. Eventually, the difference in seismic activity was shown, implying that deep fluid has an important control action on the regional seismicity. [ABSTRACT FROM AUTHOR]

Melatonin is an endogenous hormone with various biological functions and possesses anti‐tumor properties in multiple malignancies. Immune evasion is one of the most important hallmarks of head and neck squamous cell carcinoma (HNSCC) and is closely related to tumor progression. However, as an immune modulator under physiological conditions, the roles of melatonin in tumor immunity in HNSCC remains unclear. In this study, we found that the endogenous melatonin levels in patients with HNSCC were lower than those in patients with benign tumors in head and neck. Importantly, lower melatonin levels were related to lymph node metastasis among patients with HNSCC. Moreover, melatonin significantly suppressed programmed death‐ligand 1 (PD‐L1) expression and inhibited epithelial–mesenchymal transition (EMT) of HNSCC through the ERK1/2/FOSL1 pathway in vitro and in vivo. In SCC7/C3H syngeneic mouse models, anti‐programmed death‐1 (PD‐1) antibody combined with melatonin significantly inhibited tumor growth and modulated anti‐tumor immunity by increasing CD8+ T cell infiltration and decreasing the regulatory T cell (Treg) proportion in the tumor microenvironment. Taken together, melatonin inhibited EMT and downregulated PD‐L1 expression in HNSCC through the ERK1/2/FOSL1 pathway and exerted synergistic effects with anti‐PD‐1 antibody in vivo, which could provide promising strategies for HNSCC treatment. [ABSTRACT FROM AUTHOR]

Continental regions are essential for the outgassing of deeply‐sourced helium in response to volcanic and tectonic processes. However, the helium fluxes remain largely unknown for continental collision settings such as the Tibetan Plateau. Here, we focus on hydrothermal helium degassing from the Simao block, Southeast Tibetan Plateau margin, and report flux estimates of (0.03 – 32) × 105 atoms m−2 s−1 for 3He and (3.2 – 32) × 1010 atoms m−2 s−1 for 4He, with mantle fractions of helium fluxes up to 2−3 orders of magnitude greater than those of stable continents. Geologically recent magma recharge beneath Quaternary volcanoes is proposed to account for the high mantle helium fluxes and 3He/4He up to 7.24 Ra. Active tectonics driven by the India‐Asia continental collision possibly maintained efficient release of crustal helium over geological timescales. These findings present the first flux estimates for hydrothermal helium degassing controlled by volcanic and tectonic processes in continental collision settings. Plain Language Summary: Helium (including 3He and 4He isotopes) is an element mainly outgassing from Earth's interior to the atmosphere. The fluxes and isotopic compositions of helium are critical parameters for monitoring the hazardous volcanic eruptions and earthquakes, estimating the fluxes of other volatile species (e.g., CO2 and N2) from the solid Earth, and exploring the helium resources and geothermal energy. We conducted a quantitative study on the magnitude of helium outgassing from hot springs in the Simao block of the Southeast Tibetan Plateau margin, which is located in a region influenced by the India‐Asia continental collision. The results show that the mantle and crustal helium fluxes of the Simao block are comparable to those estimated for the representative continental regions worldwide. This observation can be explained by the intrusion and degassing of mantle‐derived magmas beneath Quaternary volcanoes and efficient release of crustal helium in response to regional active tectonics. We suggest that India‐Asia continental collision zone is an important natural laboratory for studying helium degassing from solid Earth. Key Points: We report the first estimates of hydrothermal helium fluxes for continental collision settingsGeologically recent magma recharge is proposed to feed the mantle helium degassingActive tectonics driven by India‐Asia continental collision possibly maintained efficient release of crustal helium over geological timescales [ABSTRACT FROM AUTHOR]

Based on the observation of the geochemical characteristics of 19 hot springs in the Litang Fault Zone (LFZ) from 2010 to 2019, the major elements, trace elements, and stable isotopes were investigated, and a conceptual model of ground fluid circulation in the LFZ was established. The main hydrochemical type of hot spring water samples is HCO3−-Na+. The δ2H values range from −157.6‰ to −123.4‰ and δ18O values range from −24.5‰ to −15.4‰. The hot spring water in the Litang fault zone is mainly recharged by infiltrating precipitation, with a recharge elevation of 4062~6018 m. Hydrochemical types of Litang hot springs are mainly controlled by the circulation of groundwater in a deep fault system, and are related to the rock lithology of thermal reservoir and water–rock reaction areas. Hot springs in the Litang fault zone attribute to three different heat sources, belonging to three geothermal systems. The flow direction of groundwater in the LFZ is roughly from northwest to southeast along the Litang fault. The deeper the circulation depth of hot spring water on the fault, the higher the thermal reservoir temperature and the stronger the seismic activity of the segment, which is closely related to the increase in pore fluid pressure, rock weakening, and deep fluid upwelling. This study is helpful for further study on regional hydrogeological environments and provides a scientific basis for revealing geothermal fluid movement in fault zones. [ABSTRACT FROM AUTHOR]

Hypoxia is a main feature of most solid tumors, but how melanoma cells under hypoxic conditions exploit tumor microenvironment (TME) to facilitate tumor progression remains poorly understood. In this study, we found that hypoxic melanoma‐derived small extracellular vesicles (sEVs) could improve the proangiogenic capability of cancer‐associated fibroblasts (CAFs). This improvement was due to the activation of the IKK/IκB/NF‐κB signaling pathway and upregulation of CXCL1 expression and secretion in CAFs. By proteomic analysis, we verified that hypoxia could promote enrichment of chaperone HSP90 and client protein phosphorylated IKKα/β (p‐IKKα/β) in melanoma‐derived sEVs. Delivery of the HSP90/p‐IKKα/β complex by sEVs could activate the IKK/IκB/NF‐κB/CXCL1 axis in CAFs and promote angiogenesis in vitro and in vivo. Taken together, these findings deepen the understanding of hypoxic response in melanoma progression and provide potential targets for melanoma treatment. [ABSTRACT FROM AUTHOR]

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common brain diseases among children. The current criteria of ADHD diagnosis mainly depend on behavior analysis, which is subjective and inconsistent, especially for children. The development of neuroimaging technologies, such as magnetic resonance imaging (MRI), drives the discovery of brain abnormalities in structure and function by analyzing multimodal neuroimages for computer-aided diagnosis of brain diseases. This paper proposes a multimodal machine learning framework that combines the Boruta based feature selection and Multiple Kernel Learning (MKL) to integrate the multimodal features of structural and functional MRIs and Diffusion Tensor Images (DTI) for the diagnosis of early adolescent ADHD. The rich and complementary information of the macrostructural features, microstructural properties, and functional connectivities are integrated at the kernel level, followed by a support vector machine classifier for discriminating ADHD from healthy children. Our experiments were conducted on the comorbidity-free ADHD subjects and covariable-matched healthy children aged 9–10 chosen from the Adolescent Brain and Cognitive Development (ABCD) study. This paper is the first work to combine structural and functional MRIs with DTI for early adolescents of the ABCD study. The results indicate that the kernel-level fusion of multimodal features achieves 0.698 of AUC (area under the receiver operating characteristic curves) and 64.3% of classification accuracy for ADHD diagnosis, showing a significant improvement over the early feature fusion and unimodal features. The abnormal functional connectivity predictors, involving default mode network, attention network, auditory network, and sensorimotor mouth network, thalamus, and cerebellum, as well as the anatomical regions in basal ganglia, are found to encode the most discriminative information, which collaborates with macrostructure and diffusion alterations to boost the performances of disorder diagnosis. [ABSTRACT FROM AUTHOR]

Urea is an important raw material in the chemical industry and is widely used as a nitrogen source in chemical fertilizers. The current industrial urea synthesis not only requires harsh reaction conditions, but also consumes most of the NH3 obtained through artificial synthesis. The conversion of N2 and CO2 into urea through electrochemical reactions under ambient conditions represents a novel green urea synthesis method. However, the large-scale promotion of this method is limited by the lack of suitable electrocatalysts. Here, by means of density functional theory computations, we systematically study the catalytic activity of three experimentally available two-dimensional metal borides (MBenes), Mo2B2, Ti2B2, and Cr2B2 toward simultaneous electrocatalytic coupling of N2 and CO2 to produce urea under ambient conditions. According to our results, these three MBenes not only have superior intrinsic basal activity for urea formation, with limiting potentials ranging from −0.49 to −0.65 eV, but also can significantly suppress the competitive reaction of N2 reduction to NH3. In particular, 2D Mo2B2 and Cr2B2 possess superior capacity to suppress surface oxidation and self-corrosion under electrochemical reaction conditions, rendering them relatively promising electrocatalysts for urea production. Our work paves the way for the electrochemical synthesis of urea. The conversion of N2 and CO2 into urea through electrochemical reactions under ambient conditions represents a novel green urea synthesis method. Here, the authors demonstrate that two-dimensional transition metal borides can serve as effective catalysts for electrochemical urea synthesis. [ABSTRACT FROM AUTHOR]

The damage development trend of concrete with cracks in salt-freezing environment is systematically studied. The cracks are also tested in intact concrete for comparison, and crack characterization is introduced. The mass loss, the relative dynamic elastic modulus, and the change of crack width are analyzed. Results show that the crack width increases as the salt-freezing cycle progresses. Following the development trend of the cracks, concrete cracks can be divided into three categories: 0–40, 40–100, and 100–150 μm. The mass loss increases significantly, and the change of relative dynamic elastic modulus decreases in concrete with an initial crack compared with the intact concrete. When the crack width is 80 μm, a maximum mass loss rate of 0.19% and a minimum relative dynamic elastic modulus of 75.81% can be obtained. These test results prove that crack and freeze-thaw coupling can influence each other and accelerate the failure of concrete. Overall, this study can serve as a basis for the durability design and life improvement of concrete structures. [ABSTRACT FROM AUTHOR]

Background: Studies suggest Porphyromonas gingivalis (Pg) increased the incidence of oral squamous cell carcinoma (OSCC). However, fimA genotypes distribution of Pg, the origination of Pg in tissue, and its prognostic value are inconclusive. We aimed to investigate the frequency of fimA genotypes in OSCC patients, study the association between Pg and OSCC, and explore the prognostic value of Pg. Methods: The abundance of Pg in saliva from the OSCC group and the OSCC-free group was analysed by qPCR. The presence of Pg was explored in OSCC tissue and para-cancerous tissue by in situ hybridization. The frequency of fimA genotypes in saliva and OSCC tissue was determined by PCR, then PCR products were sequenced and compared. Clinical data were extracted, and patients followed up for a median period of 23 months. Clinicopathological variables were compared with the abundance of Pg using Pearson Chi-square test or Fisher's exact test. The disease-free survival (DFS) rate was calculated by Kaplan–Meier method with log-rank tests. Results: Comparing the OSCC-free group, 95 patients with OSCC showed a high abundance of Pg in saliva (P = 0.033), and OSCC tissue showed strong in situ expression of Pg compared with paired normal tissue. Patients with OSCC showed a dominant distribution of Pg with genotype I + Ib (21.1%), II (31.6%), and IV (21.1%). FimA genotypes detected in saliva were in accordance with those in OSCC tissue, there was, moreover, a significant similarity in amplified Pg fragments. Of the 94 responsive OSCC patients, the recurrence rate was 26.6% (25/94). Overabundance of Pg in saliva showed advanced pathologic staging (P = 0.008), longer disease-free time (P = 0.029) and lower recurrence rate (P = 0.033). The overabundance of Pg in saliva was associated with improved disease-free survival (P = 0.049). Conclusions: This study indicated that Pg might involve in the pathogenesis of OSCC, Pg carrying fimA I, Ib, II, and IV were prevalent genotypes in patients with OSCC, the provenance of Pg in OSCC tissue might be from the salivary microbial reservoir, and the abundance of Pg in saliva might consider as a favorable potential prognostic indicator in OSCC. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is the most common primary bone cancer characterized by an aggressive phenotype with bone destruction. The prognosis of OS patients remains unoptimistic with the current treatment strategy. Recently, osteoclasts are believed to play a crucial role in cancer bone metastasis. Thus, osteoclast could be a target both in bone destruction and cancer progression in OS. However, mechanisms governing osteoclastogenesis in OS remain poorly understood. miRNA delivered by small extracellular vesicles (sEVs) could mediate cellular communications. In this study, we investigated the effects of sEVs on osteoclastogenesis and osteoclast function, also clarified the underlying mechanism. We herein found that sEVs promoted pre-osteoclast migration, osteoclastogenesis and resorption by exposing RAW264.7 cells to sEVs derived from OS cells. Bioinformatics analysis showed that phosphatase tension homologue (PTEN), and miR-19a-3p were involved in OS progression. Overexpression of miR-19a-3p or sEVs' miR-19a-3p promoted osteoclast formation and function through PTEN/PI3K/AKT signaling pathway, while inhibition of miR-19a-3p showed the contrary results. The bone marrow macrophages (BMMs) were used to verify the results. OS mice, which were established by subcutaneous injection of OS cells, exhibited increased levels of sEVs' miR-19a-3p in blood. Moreover, micro-computed tomography (CT) and histomorphometry analysis demonstrated that OS mice exhibited osteopenia with increased number of osteoclasts. In conclusion, miR-19a-3p delivery via OS cell-derived sEVs promotes osteoclast differentiation and bone destruction through PTEN/phosphatidylinositol 3 -kinase (PI3K)/protein kinase B (AKT) signaling pathway. These findings highlight sEVs packaging of miR-19a-3p as a potential target for prevention and treatment of bone destruction and cancer progression in OS patients. And this finding provides a novel potentially therapeutic target for the bone metastasis. [ABSTRACT FROM AUTHOR]

Insulin‐like growth factor‐2 messenger RNA‐binding protein 3 (IGF2BP3) has been reported to contribute to tumorigenesis in several human cancers. However, the biological functions of IGF2BP3 in bladder cancer are poorly understood. We investigated the relation between IGF2BP3 expression and prognosis of bladder cancer patients. Cell proliferation, cell cycle and cell apoptosis assays were performed to assess IGF2BP3 functions. The results showed that IGF2BP3 was overexpressed in bladder cancer tissues compared with that in normal bladder tissues, and its higher expression was closely correlated with poor prognosis in bladder cancer patients. Overexpression of IGF2BP3 markedly promoted cell proliferation and cell cycle progression and inhibited cell apoptosis, while knockdown of IGF2BP3 notably suppressed the proliferation, promoted cell apoptosis and induced cell cycle arrest at the G0/G1 phase. Mechanistically, we revealed that IGF2BP3 promotes the activation of the JAK/STAT pathway in bladder cancer cells. Moreover, the JAK/STAT inhibitor dramatically blocked the tumour‐promoting activity of IGF2BP3. Tumour growth in vivo was also suppressed by knocking down of IGF2BP3. Hence, IGF2BP3 facilitated bladder cancer cell proliferation by activating the JAK/STAT signalling pathway. These findings suggest that IGF2BP3 exhibits an oncogenic effect in human bladder cancer progression. [ABSTRACT FROM AUTHOR]

Insulin‐like growth factor‐2 messenger RNA‐binding protein 3 (IGF2BP3) has been reported to contribute to tumorigenesis in several human cancers. However, the biological functions of IGF2BP3 in bladder cancer are poorly understood. We investigated the relation between IGF2BP3 expression and prognosis of bladder cancer patients. Cell proliferation, cell cycle and cell apoptosis assays were performed to assess IGF2BP3 functions. The results showed that IGF2BP3 was overexpressed in bladder cancer tissues compared with that in normal bladder tissues, and its higher expression was closely correlated with poor prognosis in bladder cancer patients. Overexpression of IGF2BP3 markedly promoted cell proliferation and cell cycle progression and inhibited cell apoptosis, while knockdown of IGF2BP3 notably suppressed the proliferation, promoted cell apoptosis and induced cell cycle arrest at the G0/G1 phase. Mechanistically, we revealed that IGF2BP3 promotes the activation of the JAK/STAT pathway in bladder cancer cells. Moreover, the JAK/STAT inhibitor dramatically blocked the tumour‐promoting activity of IGF2BP3. Tumour growth in vivo was also suppressed by knocking down of IGF2BP3. Hence, IGF2BP3 facilitated bladder cancer cell proliferation by activating the JAK/STAT signalling pathway. These findings suggest that IGF2BP3 exhibits an oncogenic effect in human bladder cancer progression. [ABSTRACT FROM AUTHOR]

Chemokines and their receptors show a strong relationship with poor clinical outcomes in various cancers. However, their underlying mechanisms remain to be fully elucidated. In our research, we found C‐C chemokine receptor 7 (CCR7) and its ligand chemokine ligand 21 (CCL21) were abnormally abundant in oral squamous cell carcinoma (OSCC) tissues, and CCR7 expression was correlated with poor prognosis of OSCC. After exogenous CCL21 stimulation, epithelial–mesenchymal transition (EMT) was promoted in OSCC cells, and cancer stem cell‐related markers CD133, CD44, BMI1, ALDH1A1, and OCT4 increased. The migration, invasion, tumorsphere formation, and colony formation abilities of OSCC cells were enhanced, indicating that the stemness of OSCC cells was also improved. The knockdown and overexpression of CCR7 efficiently affected the CCL21‐induced EMT and stemness of OSCC cells. When treated with CCL21, the phospho‐JAK2 and phospho‐STAT3 markedly increased. The inhibitor of the Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) significantly suppressed CCL21‐induced EMT and stemness of OSCC cells. In conclusion, CCL21/CCR7 axis regulated EMT progress and promoted the stemness of OSCC by activating the JAK2/STAT3 signaling pathway. CCL21/CCR7 might be an effective target for OSCC prevention and treatment. [ABSTRACT FROM AUTHOR]

This study is aimed at determining how oral squamous cell carcinoma (OSCC) regulates the angiogenesis of HUVECs through miR-210-3p expression and exploring the relationship among miR-210-3p, its target protein, and the possible mechanism of angiogenesis regulation. miR-210-3p expression was detected in OSCC tissues and juxta cancerous tissues (JCT), and the relationship among miR-210-3p, microvessel density (MVD), and histopathologic features was analyzed. A conditioned medium (CM) of the OSCC cell line CAL27 was collected to stimulate human umbilical vein endothelial cells (HUVECs), and the miR-210-3p levels and tube formation capability of HUVECs were measured. The target protein level of miR-210-3p was altered; then, PI3K/AKT pathway activation in HUVECs was detected. miR-210-3p was tested in exosomes separated from CAL27 CM, and the transfer of miR-210-3p from OSCC exosomes to HUVECs was verified. Then, we found that the OSCC tissues had higher miR-210-3p levels than the JCT, and miR-210-3p level was positively correlated with MVD and tumor grade. CAL27 CM was able to elevate miR-210-3p levels in HUVECs and promoted tube formation. EFNA3 was the target gene of miR-210-3p, and ephrinA3 protein level was able to influence the migration and proliferation of HUVECs. The levels of phosphorylated AKT in the HUVECs increased when ephrinA3 was downregulated, and the upregulation of ephrinA3 resulted in the suppression of the PI3K/AKT pathway. miR-210-3p was detected in exosomes isolated from the CM of CAL27 cells, and miR-210-3p level in the HUVECs was elevated after absorbing the OSCC exosomes. In conclusion, miR-210-3p was more overexpressed in OSCC tissues than in the JCT. The exosomes secreted by OSCC cells were able to upregulate miR-210-3p expression and reduce ephrinA3 expression in HUVECs and promoted tube formation through the PI3K/AKT signaling pathway. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) contains complex multiple structures. Therefore, the key problem analyzing the intrinsic properties of an HSI is how to represent the structure relationships of the HSI effectively. Hypergraph is very effective to describe the intrinsic relationships of the HSI. In general, Euclidean distance is adopted to construct the hypergraph. However, this method cannot effectively represent the structure properties of high-dimensional data. To address this problem, we propose a sparse-adaptive hypergraph discriminant analysis (SAHDA) method to obtain the embedding features of the HSI in this letter. SAHDA uses the sparse representation to reveal the structure relationships of the HSI adaptively. Then, an adaptive hypergraph is constructed by using the intraclass sparse coefficients. Finally, we develop an adaptive dimensionality reduction mode to calculate the weights of the hyperedges and the projection matrix. SAHDA can adaptively reveal the intrinsic properties of the HSI and enhance the performance of the embedding features. Some experiments on the Washington DC Mall hyperspectral data set demonstrate the effectiveness of the proposed SAHDA method, and SAHDA achieves better classification accuracies than the traditional graph learning methods. [ABSTRACT FROM AUTHOR]

Representation-based target detectors for hyperspectral imagery (HSI) have recently aroused a lot of interests. However, existing methods ignore the dictionary structure and cannot guarantee an informative and discriminative representation of test pixels for target detection. To alleviate the problem, this letter proposes a novel sparse and dense hybrid representation-based target detector (SDRD). The proposed detector adopts the idea that the relationship between the background and the target sub-dictionaries is a collaborative competition. The structure of the dictionary is discovered and preserved by learning a sparse and dense hybrid representation for test pixel. Benefitting from this, a compact and discriminative representation can be obtained to better represent the test pixel for an improved detection performance. Experimental results on several HSI data sets verify the effectiveness of SDRD in comparison with several state-of-the-art methods. [ABSTRACT FROM AUTHOR]

In view-based 3D shape recognition, extracting discriminative visual representation of 3D shapes from projected images is considered the core problem. Projections with low discriminative ability can adversely influence the final 3D shape representation. Especially under the real situations with background clutter and object occlusion, the adverse effect is even more severe. To resolve this problem, we propose a novel deep neural network, View Discerning Network, which learns to judge the quality of views and adjust their contributions to the representation of shapes. In this network, a Score Generation Unit is devised to evaluate the quality of each projected image with score vectors. These score vectors are used to weight the image features and the weighted features perform much better than original features in 3D shape recognition task. In particular, we introduce two structures of Score Generation Unit, Channel-wise Score Unit and Part-wise Score Unit, to assess the quality of feature maps from different perspectives. Our network aggregates features and scores in an end-to-end framework, so that final shape descriptors are directly obtained from its output. Our experiments on ModelNet and ShapeNet Core55 show that View Discerning Network outperforms the state-of-the-arts in terms of the retrieval task, with excellent robustness against background clutter and object occlusion. [ABSTRACT FROM AUTHOR]

The electrochemical and rust-resistant behaviors of different concentrations of carboxylic acid amine rust inhibitor on carbon steel in concrete simulated pore solution were studied by electrochemical impedance spectrums(EIS), Potentiodynamic polarization tests and wetting-drying tests. The results show that the carboxylic acid amine rust inhibitor can effectively inhibit the corrosion damage of Cl- to carbon steel and play a role in rust inhibition. With the increase of the concentration of rust inhibitor, the corresponding electrochemical impedance arc increase,the pitting potential increases, and corrosion current density is reduced, the rust area and depth of the dry and wet cycle hangs are reduced, and the rust prevention efficiency is significantly improved. [ABSTRACT FROM AUTHOR]

Aims: To compare the short-term complications between Onlay and Duckett urethroplasty and to analyze the various risk factors cause the complications. Methods: The children with hypospadias who underwent treatment with Onlay or Duckett urethroplasty from November 2014 to June 2016 were followed up. The difference in complications between the two groups was analyzed. Moreover, a single-factor ANOVA was performed to analyze the length and curvature of the penis and the length of the urethral defect. Results: 40 patients were treated by Duckett, while 54 by Onlay. In comparison to the Onlay group, the Duckett group showed the initial penile length was shorter (P = 0.044), the initial urethral defect (P = 0.024) and after the correction of chordee was longer (P < 0.001), and the initial penile curvature (P < 0.001) and after degloving (P < 0.001) was greater. Furthermore, the incidence of urethra percutaneous fistula (P = 0.041) and urethral stenosis (P < 0.001) in Duckett group was significantly higher. The analysis of risk factors showed that the age at the time of surgery, the initial penile curvature, the initial urethral defect, and the urethral defect after the correction of chordee were not correlated with the complications. The degree of penile curvature after skin degloving and urethra stenosis was significantly correlated (P = 0.019). Conclusion: The incidence of complications of urethra percutaneous fistula and urethral stenosis after 1 year of Duckett was higher than that by Onlay approach. The greater the curvature of the penis after skin degloving, the more likely the occurrence of urethral stenosis after surgery. [ABSTRACT FROM AUTHOR]

In high-resolution remote sensing image processing, segmentation is a crucial step that extracts information within the object-based image analysis framework. Because of its robustness, mean-shift segmentation algorithms are widely used in the field of image segmentation. However, the traditional implementation of these methods cannot process large volumes of images rapidly under limited computing resources. Currently, parallel computing models are generally employed for segmentation tasks with massive remote sensing images. This paper presents a parallel implementation of the mean-shift segmentation algorithm based on an analysis of the principle and characteristics of this technique. To avoid the inconsistency on the boundaries of adjacent data chunks, we propose a novel buffer-zone-based data-partitioning strategy. Employing the proposed data-partitioning strategy, two intensively computation steps are performed in parallel on different data chunks. The experimental results show that the proposed algorithm effectively improves the computing efficiency of image segmentation in a parallel computing environment. Furthermore, they demonstrate the practicality of massive image segmentation when computer resources are limited. [ABSTRACT FROM AUTHOR]