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ObjectiveTo identify HBV-related genes (HRGs) implicated in osteoporosis (OP) pathogenesis and develop a diagnostic model for early OP detection in chronic HBV infection (CBI) patients.MethodsFive public sequencing datasets were collected from the GEO database. Gene differential expression and LASSO analyses identified genes linked to OP and CBI. Machine learning algorithms (random forests, support vector machines, and gradient boosting machines) further filtered these genes. The best diagnostic model was chosen based on accuracy and Kappa values. A nomogram model based on HRGs was constructed and assessed for reliability. OP patients were divided into two chronic HBV-related clusters using non-negative matrix factorization. Differential gene expression analysis, Gene Ontology, and KEGG enrichment analyses explored the roles of these genes in OP progression, using ssGSEA and GSVA. Differences in immune cell infiltration between clusters and the correlation between HRGs and immune cells were examined using ssGSEA and the Pearson method.ResultsDifferential gene expression analysis of CBI and combined OP dataset identified 822 and 776 differentially expressed genes, respectively, with 43 genes intersecting. Following LASSO analysis and various machine learning recursive feature elimination algorithms, 16 HRGs were identified. The support vector machine emerged as the best predictive model based on accuracy and Kappa values, with AUC values of 0.92, 0.83, 0.74, and 0.7 for the training set, validation set, GSE7429, and GSE7158, respectively. The nomogram model exhibited AUC values of 0.91, 0.79, and 0.68 in the training set, GSE7429, and GSE7158, respectively. Non-negative matrix factorization divided OP patients into two clusters, revealing statistically significant differences in 11 types of immune cell infiltration between clusters. Finally, intersecting the HRGs obtained from LASSO analysis with the HRGs identified three genes.ConclusionThis study successfully identified HRGs and developed an efficient diagnostic model based on HRGs, demonstrating high accuracy and strong predictive performance across multiple datasets. This research not only offers new insights into the complex relationship between OP and CBI but also establishes a foundation for the development of early diagnostic and personalized treatment strategies for chronic HBV-related OP.

The high-temporal-resolution monitoring of key management nodes in cotton management via agricultural remote sensing is vital for field cotton macro-statistics, particularly for predicting cotton production and obtaining comprehensive data. This study examines Shihezi, Xinjiang as a case study, utilizing Sentinel-1 and Sentinel-2 data from 2019 to 2021. Three machine learning models(RF, SVM, and CART) were employed to extract annual crop classification area rasters, monitor weekly cultivation progress, and monitor abandoned cropland during the cultivation period. The results demonstrate that the random forest model has produced satisfactory results in gridded extraction for cotton classification areas, achieving the producer's accuracy of the cotton category reached 98.5%, and the kappa coefficient is 0.947. Cotton cultivated in 2021 began is a week later than in 2020, yet exhibited a faster cultivate speed. The proportion of abandoned cotton fields in the study area rose in 2020 compared to 2019. The methodology presented in this study has a certain reference value for exploring the monitoring of continuous changes in crops over the years and macro-monitoring of important activities in the entire growth cycle.

Background: Osteosarcoma (OSA) is the most prevalent form of malignant bone tumor in children and adolescents, producing osteoid and immature bone. Numerous high quality studies have been published in the OSA field, however, no bibliometric study related to this area has been reported thus far. Therefore, the present study retrieved the published data from 2000 to 2022 to reveal the dynamics, development trends, hotspots and future directions of the OSA. Methods: Publications regard to osteogenic sarcoma and prognosis were searched in the core collection on Web of Science database. The retrieved publications were analyzed by publication years, journals, categories, countries, citations, institutions, authors, keywords and clusters using the two widely available bibliometric visualization tools, VOS viewer (Version 1.6.16), Citespace (Version 6.2. R1). Results: A total of 6260 publications related to the current topic were retrieved and analyzed, revealing exponential increase in the number of publications with an improvement in the citations on the OSA over time, in which China and the USA are the most productive nations. Shanghai Jiao Tong University, University of Texas System and Harvard University are prolific institutions, having highest collaboration network. Oncology Letters and Journal of Clinical Oncology are the most productive and the most cited journals respectively. The Wang Y is a prominent author and articles published by Bacci G had the highest number of citations indicating their significant impact in the field. According to keywords analysis, osteosarcoma, expression and metastasis were the most apparent keywords whereas the current research hotspots are biomarker, tumor microenvironment, immunotherapy and DNA methylation. Conclusion: Our findings offer valuable information for researchers to understand the current research status and the necessity of future research to mitigate the mortality of the OS patients.

Abstract Patients with single ventricle defects undergoing the Fontan procedure eventually face Fontan failure. Long-term cavopulmonary assist devices using rotary pump technologies are currently being developed as a subpulmonary power source to prevent and treat Fontan failure. Low hydraulic resistance is a critical safety requirement in the event of pump failure (0 RPM) as a modest 2 mmHg cavopulmonary pressure drop can compromise patient hemodynamics. The goal of this study is therefore to assess the passive performance of a viscous impeller pump (VIP) we are developing for Fontan patients, and validate flow simulations against in-vitro data. Two different blade heights (1.09 mm vs 1.62 mm) and a blank housing model were tested using a mock circulatory loop (MCL) with cardiac output ranging from 3 to 11 L/min. Three-dimensional flow simulations were performed and compared against MCL data. In-silico and MCL results demonstrated a pressure drop of < 2 mmHg at a cardiac output of 7 L/min for both blade heights. There was good agreement between simulation and MCL results for pressure loss (mean difference − 0.23 mmHg 95% CI [0.24–0.71]). Compared to the blank housing model, low wall shear stress area and oscillatory shear index on the pump surface were low, and mean washout times were within 2 s. This study demonstrated the low resistance characteristic of current VIP designs in the failed condition that results in clinically acceptable minimal pressure loss without increased washout time as compared to a blank housing model under normal cardiac output in Fontan patients.

The vision-based recognition and localization system plays a crucial role in the unmanned harvesting of aquatic vegetables. After field investigation, factors such as illumination, shading, and computational cost have become the main difficulties restricting the identification and positioning of Brasenia schreberi. Therefore, this paper proposes a new lightweight detection method, YOLO-GS, which integrates feature information from both RGB and depth images for recognition and localization tasks. YOLO-GS employs the Ghost convolution module as a replacement for traditional convolution and innovatively introduces the C3-GS, a cross-stage module, to effectively reduce parameters and computational costs. With the redesigned detection head structure, its feature extraction capability in complex environments has been significantly enhanced. Moreover, the model utilizes Focal EIoU as the regression loss function to mitigate the adverse effects of low-quality samples on gradients. We have developed a data set of Brasenia schreberi that covers various complex scenarios, comprising a total of 1500 images. The YOLO-GS model, trained on this dataset, achieves an average accuracy of 95.7%. The model size is 7.95 MB, with 3.75 M parameters and a 9.5 GFLOPS computational cost. Compared to the original YOLOv5s model, YOLO-GS improves recognition accuracy by 2.8%, reduces the model size and parameter number by 43.6% and 46.5%, and offers a 39.9% reduction in computational requirements. Furthermore, the positioning errors of picking points are less than 5.01 mm in the X direction, 3.65 mm in the Y direction, and 1.79 mm in the Z direction. As a result, YOLO-GS not only excels with high recognition accuracy but also exhibits low computational demands, enabling precise target identification and localization in complex environments so as to meet the requirements of real-time harvesting tasks.

Background: Endovascular aneurysm repair with four-vessel fenestrated endovascular aneurysm repair (fEVAR) or branched endovascular aneurysm repair (bEVAR) currently represent the forefront of minimally invasive complex aortic aneurysm repair. This study sought to use patient-specific computational flow simulation (CFS) to assess differences in postoperative hemodynamic effects associated with fEVAR vs bEVAR. Methods: Patients from two institutions who underwent four-vessel fEVAR with the Cook Zenith Fenestrated platform and bEVAR with the Jotec E-xtra Design platform were retrospectively selected. Patients in both cohorts were treated for paravisceral and extent II, II, and V thoracoabdominal aortic aneurysms. Three-dimensional finite element volume meshes were created from preoperative and postoperative computed tomography scans. Boundary conditions were adjusted for body surface area, heart rate, and blood pressure. Pulsatile flow simulations were performed with equivalent boundary conditions between preoperative and postoperative states. Postoperative changes in hemodynamic parameters were compared between the fEVAR and bEVAR groups. Results: Patient-specific CFS was performed on 20 patients (10 bEVAR, 10 fEVAR) with a total of 80 target vessels (40 renal, 20 celiac, 20 superior mesenteric artery stents). bEVAR was associated with a decrease in renal artery peak flow rate (−5.2% vs +2.0%; P < .0001) and peak pressure (−3.4 vs +0.1%; P < .0001) compared with fEVAR. Almost all renal arteries treated with bEVAR had a reduction in renal artery perfusion (n = 19 [95%]), compared with 35% (n = 7) treated with fEVAR. There were no significant differences in celiac or superior mesenteric artery perfusion metrics (P = .10-.27) between groups. Time-averaged wall shear stress in the paravisceral aorta and branches also varied significantly depending on endograft configuration, with bEVAR associated with large postoperative increases in renal artery (+47.5 vs +13.5%; P = .002) and aortic time-averaged wall shear stress (+200.1% vs −31.3%; P = .001) compared with fEVAR. Streamline analysis revealed areas of hemodynamic abnormalities associated with branched renal grafts which adopt a U-shaped geometry, which may explain the observed differences in postoperative changes in renal perfusion between bEVAR and fEVAR. Conclusions: bEVAR may be associated with subtle decreases in renal perfusion and a large increase in aortic wall shear stress compared with fEVAR. CFS is a novel tool for quantifying and visualizing the unique patient-specific hemodynamic effect of different complex EVAR strategies. Clinical Relevance: This study used patient-specific CFS to compare postoperative hemodynamic effects of four-vessel fenestrated endovascular aneurysm repair (fEVAR) and branched endovascular aneurysm repair (bEVAR) in patients with complex aortic aneurysms. The findings indicate that bEVAR may result in subtle reductions in renal artery perfusion and a significant increase in aortic wall shear stress compared with fEVAR. These differences are clinically relevant, providing insights for clinicians choosing between these approaches. Understanding the patient-specific hemodynamic effects of complex EVAR strategies, as revealed by CFS, can aid in future personalized treatment decisions, and potentially reduce postoperative complications in aortic aneurysm repair.

Gut microbiota can coordinate with different tissues and organs to maintain human health, which derives the concept of the gut-X axis. Conversely, the dysbiosis of gut microbiota leads to the occurrence and development of various diseases, such as neurological diseases, liver diseases, and even cancers. Therefore, the modulation of gut microbiota offers new opportunities in the field of medicines. Antibiotics, probiotics or other treatments might restore unbalanced gut microbiota, which effects do not match what people have expected. Recently, nanomedicines with the high targeting ability and reduced toxicity make them an appreciative choice for relieving disease through targeting gut-X axis. Considering this paradigm-setting trend, the current review summarizes the advancements in gut microbiota and its related nanomedicines. Specifically, this article introduces the immunological effects of gut microbiota, summarizes the gut-X axis-associated diseases, and highlights the nanotherapeutics-mediated treatment via remolding the gut-X axis. Moreover, this review also discusses the challenges in studies related to nanomedicines targeting the gut microbiota and offers the future perspective, thereby aiming at charting a course toward clinic.

This study introduces a novel methodology for the dynamic extraction of information on cotton growth in terms of height utilizing the DJI Zenmuse L1 LiDAR sensor mounted onto a DJI Matrice 300 RTK Unmanned Aerial Vehicle (UAV), aimed at enhancing the precision and efficiency of growth monitoring within the realm of precision agriculture. Employing the Progressive TIN Densification (PTD) and Cloth Simulation Filter (CSF) algorithms, combined with Kriging interpolation, we generated Canopy Height Models (CHMs) to extract the cotton heights at two key agricultural sites: Zengcheng and Tumxuk. Our analysis reveals that the PTD algorithm significantly outperforms the CSF method in terms of accuracy, with its R2 values indicating a superior model fit for height extraction across different growth stages (Zengcheng: 0.71, Tumxuk: 0.82). Through meticulous data processing and cluster analysis, this study not only identifies the most effective algorithm for accurate height extraction but also provides detailed insights into the dynamic growth patterns of cotton varieties across different geographical regions. The findings highlight the critical role of UAV remote sensing in enabling large-scale, high-precision monitoring of crop growth, which is essential for the optimization of agricultural practices such as precision fertilization and irrigation. Furthermore, the study demonstrates the potential of UAV technology to select superior cotton varieties by analyzing their growth dynamics, offering valuable guidance for cotton breeding and cultivation.

Calmodulin (CaM) and Calmodulin-like (CML) genes are the primary families of Calcium (Ca2+) sensors which are found to be involved in response to various stresses. Some genes involved in Ca2+ signal transduction have been genome-wide characterized in various species. However, the detailed identification, characterization, and expression profilings of ZmCaM and ZmCML genes in maize remain poorly understood, especially in the response to drought stress. In this study, a total of 7 ZmCaMs and 46 ZmCMLs are identified in maize and unevenly located on 10 chromosomes. ZmCaM and ZmCML proteins are divided into 9 groups. Protein structures analysis shows that the EF-hand motif number of ZmCaMs/ZmCMLs ranges from 3 to 4 and 2 to 4, respectively. A large number of cis-regulatory elements are found in the promoter regions of ZmCaM and ZmCML genes. ZmCaM and ZmCML genes display highly diversified tissue-specific expression patterns. Furthermore, ZmCaM2, ZmCML3, ZmCML6, ZmCML8, ZmCML19, ZmCML24, ZmCML27, ZmCML28, ZmCML36, ZmCML39, and ZmCML40 are induced significantly under drought stress through RNA-seq data and RT-qPCR. Taken together, these results will help to understand the critical roles of ZmCaM and ZmCML genes played in drought resistance and provide valuable candidate genes that could be used to develop drought-resistant maize.

Abstract Background Four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR) allows comprehensive assessment of pulmonary artery (PA) flow dynamics. Few studies have characterized longitudinal changes in pulmonary flow dynamics and right ventricular (RV) recovery following a pulmonary endarterectomy (PEA) for patients with chronic thromboembolic pulmonary hypertension (CTEPH). This can provide novel insights of RV and PA dynamics during recovery. We investigated the longitudinal trajectory of 4D flow metrics following a PEA including velocity, vorticity, helicity, and PA vessel wall stiffness. Methods Twenty patients with CTEPH underwent pre-PEA and > 6 months post-PEA CMR imaging including 4D flow CMR; right heart catheter measurements were performed in 18 of these patients. We developed a semi-automated pipeline to extract integrated 4D flow-derived main, left, and right PA (MPA, LPA, RPA) volumes, velocity flow profiles, and secondary flow profiles. We focused on secondary flow metrics of vorticity, volume fraction of positive helicity (clockwise rotation), and the helical flow index (HFI) that measures helicity intensity. Results Mean PA pressures (mPAP), total pulmonary resistance (TPR), and normalized RV end-systolic volume (RVESV) decreased significantly post-PEA (P

Insertions–deletions (InDels) are the second most abundant molecular marker in the genome and have been widely used in molecular biology research along with simple sequence repeats (SSR) and single-nucleotide polymorphisms (SNP). However, InDel variant mining and marker development usually focuses on a single type of dimorphic InDel, which does not reflect the overall InDel diversity across the genome. Here, we developed Omni InDels for maize, soybean, and rice based on sequencing data and genome assembly that included InDel variants with base lengths from 1 bp to several Mb, and we conducted a detailed classification of Omni InDels. Moreover, we screened a set of InDels that are easily detected and typed (Perfect InDels) from the Omni InDels, verified the site authenticity using 3,587 germplasm resources from 11 groups, and analyzed the germplasm resources. Furthermore, we developed a Multi-InDel set based on the Omni InDels; each Multi-InDel contains multiple InDels, which greatly increases site polymorphism, they can be detected in multiple platforms such as fluorescent capillary electrophoresis and sequencing. Finally, we developed an online database website to make Omni InDels easy to use and share and developed a visual browsing function called “Variant viewer” for all Omni InDel sites to better display the variant distribution.

The spectrum confocal displacement sensor is an innovative type of photoelectric sensor. The non-contact advantages of this method include the capacity to obtain highly accurate measurements without inflicting any harm as well as the ability to determine the object’s surface contour recovery by reconstructing the measurement data. Consequently, it has been widely used in the field of three-dimensional topographic measuring. The spectral confocal displacement sensor consists of a light source, a dispersive objective, and an imaging spectrometer. The scanning mode can be categorized into point scanning and line scanning. Point scanning is inherently present when the scanning efficiency is low, resulting in a slower measurement speed. Further improvements are necessary in the research on the line-scanning type. It is crucial to expand the measurement range of existing studies to overcome the limitations encountered during the detection process. The objective of this study is to overcome the constraints of the existing line-swept spectral confocal displacement sensor’s limited measuring range and lack of theoretical foundation for the entire system. This is accomplished by suggesting an appropriate approach for creating the optical design of the dispersive objective lens in the line-swept spectral confocal displacement sensor. Additionally, prism-grating beam splitting is employed to simulate and analyze the imaging spectrometer’s back end. The combination of a prism and a grating eliminates the spectral line bending that occurs in the imaging spectrometer. The results indicate that a complete optical pathway for the line-scanning spectral confocal displacement sensor has been built, achieving an axial resolution of 0.8 μm, a scanning line length of 24 mm, and a dispersion range of 3.9 mm. This sensor significantly expands the range of measurements and fills a previously unaddressed gap in the field of analyzing the current stage of line-scanning spectral confocal displacement sensors. This is a groundbreaking achievement for both the sensor itself and the field it operates in. The line-scanning spectral confocal displacement sensor’s design addresses a previously unmet need in systematic analysis by successfully obtaining a wide measuring range. This provides systematic theoretical backing for the advancement of the sensor, which has potential applications in the industrial detection of various ranges and complicated objects.

DLD is a key gene involved in “cuproptosis,” but its roles in tumor progression and immunity remain unclear. Exploring the potential mechanisms and biological roles of DLD may provide new insights for therapeutic strategies for tumors. In the present study, we analyzed the role of DLD in a variety of tumors by using several bioinformatic tools. The results showed that compared with normal tissues, tumor tissues representing multiple cancers showed significant differential expression of DLD. High DLD expression was associated with a good prognosis in BRCA, KICH, and LUAD. Conversely, high expression levels of DLD were detrimental to patient prognosis in many other tumors, such as COAD, KIRC, and KIRP. In addition, the associations of DLD with infiltrating immune cells, genetic alterations and methylation levels across cancers were assessed. Aberrant expression of DLD was positively correlated with most infiltrating immune cells, especially neutrophils. The DLD methylation level was significantly decreased in COAD, LIHC, and LUSC but significantly increased in BRCA. DLD had the highest mutation rate (6.04%) in ESCA. In LUSC, patients with genetic alterations in DLD showed a poorer prognosis. At the single-cell level, the roles of DLD in regulating cancer-associated biological functions, such as metastasis, inflammation, and differentiation, were explored. Afterward, we further investigated whether several disease-associated genes could be correlated with DLD. GO enrichment analysis indicated that DLD-related genes were mainly associated with mitochondria-related cellular components, aerobic respiration and the tricarboxylic acid cycle. Finally, the correlations between DLD expression and immunomodulatory genes, immune checkpoints, and sensitivity to some antitumor drugs were investigated. It is worth noting that DLD expression was positively correlated with immune checkpoint genes and immunomodulatory genes in most cancers. In conclusion, this study comprehensively analyzed the differential expression, prognostic value and immune cell infiltration-related function of DLD across cancers. Our results suggest that DLD has great potential to serve as a candidate marker for pancancer prognosis and immunotherapy and may provide a new direction for cancer treatment development.

Abstract Background Osteonecrosis of the femoral head (ONFH) is a common disabling disease with considerable social and economic impacts. Although extensive studies related to ONFH have been conducted in recent years, a specific bibliometric analysis on this topic has not yet been performed. Our study attempted to summarize the comprehensive knowledge map, development landscape, and future directions of ONFH research with the bibliometric approach. Methods All publications concerning ONFH published from 2001 to 2020 were identified from Web of Science Core Collection. Key bibliometric indicators were calculated and evaluated using CiteSpace, VOSviewer, and the online bibliometric analysis platform. Results A total of 2594 publications were included. Our analysis revealed a significant exponential growth trend in the annual number of publications over the past 20 years (R 2 = 0.9663). China, the USA, and Japan were the major contributors both from the quality and quantity points of view. Correlation analysis indicated that there was a high positive correlation between the number of publications and gross domestic product (r = 0.774), and a moderate positive correlation between publications and demographic factor (r = 0.673). All keywords were categorized into four clusters including Cluster 1 (etiology and risk factors study); Cluster 2 (basic research and stem cell therapy); cluster 3 (hip-preserving study); and Cluster 4 (hip replacement study). Stem cell therapy-related research has been recognized as an important research hotspot in this field. Several topics including exosomes, autophagy, biomarkers, osteogenic differentiation, microRNAs, steroid-induced osteonecrosis, mesenchymal stem cells, double-blind, early-stage osteonecrosis, and asymptomatic osteonecrosis were considered as research focuses in the near future. Conclusion Over the past two decades, increasing attention has been paid to global ONFH-related research. Our bibliometric findings provide valuable information for researchers to understand the basic knowledge structure, identify the current research hotspots, potential collaborators, and future research frontiers in this field.

Plant height is a crucial phenotypic trait that plays a vital role in predicting cotton growth and yield, as well as in estimating biomass in cotton plants. The accurate estimation of canopy height from single-flight LiDAR data remains a formidable challenge in current high-density cotton cultivation patterns, where dense foliage obstructs the collection of bare soil terrain, particularly after flowering. The existing LiDAR-based methods for cotton height estimation suffer from significant errors. In this study, a new method is proposed to compensate for the canopy height estimation by using the canopy laser interception rate. The ground points are extracted by the ground filtering algorithm, and the interception rate of the laser per unit volume of the canopy is calculated to represent the canopy density and compensate for the cotton height estimation. The appropriate segmented height compensation function is determined by grouping and step-by-step analysis of the canopy laser interception rate. Verified by 440 groups of height data measured manually in the field, the results show that the canopy laser interception compensation mechanism is of great help in improving the estimation accuracy of LiDAR. R2 and RMSE reach 0.90 and 6.18 cm, respectively. Compared with the estimation method before compensation, R2 is increased by 13.92%, and RMSE is reduced by 49.31%. And when the canopy interception rate is greater than 99%, the compensation effect is more obvious, and the RMSE is reduced by 62.49%. This research result can significantly improve the height estimation accuracy of UAV-borne for high planting density cotton areas, which is helpful to improve the efficiency of cotton quality breeding and match genomics data.

While fluorescent organic materials have many potential as well as proven applications and so have attracted significant attention, pyridine–olefin conjugates remain a less studied subset of such systems. Herein, therefore, we report on the development of the straightforward syntheses of pyridin-1(2H)-ylacrylates and the outcomes of a study of the effects of substituents on their fluorescent properties. Such compounds were prepared using a simple, metal-free and three-component coupling reaction involving 2-aminopyridines, sulfonyl azides and propiolates. The fluorescent properties of the ensuing products are significantly affected by the positions of substituents on the cyclic framework, with those located in central positions having the greatest impact. Electron-withdrawing groups tend to induce blue shifts while electron-donating ones cause red shifts. This work highlights the capacity that the micro-modification of fluorescent materials provides for fine-tuning their properties such that they may be usefully applied to, for example, the study of luminescent materials.

Chromite is a strategic mineral resource for many countries, and chromite deposit occurrences are widespread in the ultramafic rocks of the Yarlung Zangbo ophiolite belt, particularly in the harzburgite unit of the mantle section. Conducting field surveys in complex and poorly accessible terrain is challenging, expensive, and time-consuming. Remote sensing is an advanced method of achieving modern geological work and is a powerful technical means of geological research and mineral exploration. In order to delineate outcrops of chromite-bearing mantle peridotite, the present research study integrates seven image-enhancement techniques, including optimal band combination, decorrelation stretching, band ratio, independent component analysis, principal component analysis, minimum noise fraction, and false color composite, for the interpretation of Landsat8 OLI and WorldView-2 satellite data. This integrated approach allows the effective discrimination of chromite-containing peridotite outcrops in the Luobusa area, Tibet. The interpretation results derived from these integrated image-processing techniques were systematically verified in the field and formed the basis of the feature selection process of different lithologies supported by the support vector machine algorithm. Furthermore, the distribution range of the ferric contamination anomaly is detected through the de-interference abnormal principal component thresholding technique, which shows a high spatial matching relationship with mantle peridotite. This is the first study to utilize Landsat8 OLI and WorldView-2 remote sensing satellite data to explore the largest chromite deposit in China, which enriches the research methods for the chromite deposits in the Luobusa area. Accordingly, the results of this investigation indicate that the integration of information extracted from image-processing algorithms using remote sensing data could be a broadly applicable tool for prospecting chromite ore deposits associated with ophiolitic complexes in mountainous and inaccessible regions such as Tibet’s ophiolitic zones.

The power consumption and the opto-electric noise of organic photo-detectors are the challenges for large-scale detecting and imaging applications to surpass. This article presents a new device concept of organic heterojunction PIN channel for photo-transistor. The presence of the channel's heterostructure enables rectifying capability and effective control of defect density, which leads to low power consumption (0.12 to 7.5 nW) and low dynamic noise (4.5 × 1013 Jones detectivity). Significantly, through adopting the highly efficient Perovskite Quantum Dots as intrinsic sensing core, the device exhibits high responsivity up to 7190 A/W. As we demonstrate a large-scale 10 × 20 imaging array with integrated photo-transistor, the output signals are read-out and rebuilt by I-V converting amplifier with analog-to-digital circuit and numerical computation method to visualize the functionality of the system.

Background: The durability of fenestrated endovascular aneurysm repair (fEVAR) has been threatened by thrombotic complications. In the present study, we used patient-specific computational fluid dynamic (CFD) simulation to investigate the effect of the endograft diameter on hemodynamics after fEVAR and explore the hypothesis that diameter-dependent alterations in aortic hemodynamics can predict for thrombotic events. Methods: A single-institutional retrospective study was performed of patients who had undergone fEVAR for juxtarenal aortic aneurysms. The patients were stratified into large diameter (34-36 mm) and small diameter (24-26 mm) endograft groups. Patient-specific CFD simulations were performed using three-dimensional paravisceral aortic models created from computed tomographic images with allometrically scaled boundary conditions. Aortic time-averaged wall shear stress (TAWSS) and residence time (RT) were computed and correlated with future thrombotic complications (eg, renal stent occlusion, development of significant intraluminal graft thrombus). Results: A total of 36 patients (14 with a small endograft and 22 with a large endograft) were included in the present study. The patients treated with large endografts had experienced a higher incidence of thrombotic complications compared with small endografts (45.5% vs 7.1%; P = .016). Large endografts were associated with a lower postoperative aortic TAWSS (1.45 ± 0.76 dynes/cm2 vs 3.16 ± 1.24 dynes/cm2; P < .001) and longer aortic RT (0.78 ± 0.30 second vs 0.34 ± 0.08 second; P < .001). In the large endograft group, a reduction >0.39 dynes/cm2 in aortic TAWSS demonstrated discriminatory power for thrombotic complications (area under the receiver operating characteristic curve, 0.77). An increased aortic RT of ≥0.05 second had similar accuracy for predicting thrombotic complications (area under the receiver operating characteristic curve, 0.78). The odds of thrombotic complications were significantly higher if patients had met the hemodynamic threshold changes in aortic TAWSS (odds ratio, 7.0; 95% confidence interval, 1.1-45.9) and RT (odds ratio, 8.0; 95% confidence interval, 1.13-56.8). Conclusions: Patient-specific CFD simulation of fEVAR in juxtarenal aortic aneurysms demonstrated significant endograft diameter-dependent differences in aortic hemodynamics. A postoperative reduction in TAWSS and an increased RT correlated with future thrombotic events after large-diameter endograft implantation. Patient-specific simulation of hemodynamics provides a novel method for thrombotic risk stratification after fEVAR. : Clinical Relevance: The durability of fenestrated endovascular aneurysm repair (fEVAR) has been threatened by thrombotic complications. Using patient-specific computational flow simulation, the present retrospective study of 36 patients with juxtarenal aortic aneurysms treated with fEVAR identified several endograft diameter-dependent changes in aortic hemodynamics associated with thrombotic complications. A postoperative reduction in aortic wall shear stress and increased particle residence time correlated with the development of intraluminal graft thrombus and renal stent occlusion in patients treated with large diameter (>34 mm) endografts. These computationally estimated hemodynamic parameters could provide a novel method for patient-specific risk stratification for adverse events after fEVAR.

Background: Ultrasound-triggered sonodynamic therapy (SDT), as a non-invasive approach, has attracted considerable attention in a wide variety of malignant tumors and other diseases. Over the past 2 decades, the number of scientific publications on SDT has increased rapidly. However, there is still a lack of one comprehensive report that summarizes the global research trends and knowledge landscapes in the field of SDT in detail. Thus, we performed a bibliometric analysis on SDT from 2000 to 2021 to track the current hotspots and highlight future directions.Methods: We collected publications on SDT research from the Web of Science Core Collection database. The annual number of publications and citations, major contributors, popular journals, international collaborations, co-cited references and co-occurrence keywords were analyzed and visualized with CiteSpace, VOSviewer, and R-bibliometrix.Results: A total of 701 publications were included. The annual publication output increased from 5 in 2000 to 175 in 2021, and the average growth rate was 18.4%. China was the most productive country with 463 documents (66.05%), and Harbin Medical University was the most prolific institution (N = 73). Ultrasound in Medicine and Biology published the most papers related to SDT. Materials Science, and Chemistry were the research areas receiving the most interest. All the keywords were divided into four different clusters including studies on mechanisms, studies on drug delivery and nanoparticles, studies on cancer therapy, as well as studies on ultrasound and sonosensitizers. In addition to nanomaterials-related studies including nanoparticles, mesoporous silica nanoparticles, nanosheets, liposomes, microbubble and TiO2 nanoparticle, the following research directions such as immunogenic cell death, metal-organic framework, photothermal therapy, hypoxia, tumor microenvironment, chemodynamic therapy, combination therapy, tumor resistance, intensity focused ultrasound, drug delivery, and Staphylococcus aureus also deserve further attention and may continue to explode in the future.Conclusion: SDT has a bright future in the field of cancer treatment, and nanomaterials have increasingly influenced the SDT field with the development of nano-technology. Overall, this comprehensive bibliometric study was the first attempt to analyze the field of SDT, which could provide valuable references for later researchers to better understand the global research trends, hotspots and frontiers in this domain.

This paper explores the effects of fucoidan on the frequency of diarrhea, colon morphology, colon antioxidant status, cytokine content, short-chain fatty acids, and microflora of cecal contents in early weaned lambs in order to provide a reference for the intestinal health of young ruminants. Fucoidan is a natural active polysaccharide extracted from kelp and other large brown algae. It has many biological effects, such as improving immunity, nourishing the stomach and intestines, and anti-tumor properties. This study investigated the effects of fucoidan supplementation in milk replacer on the large intestine's ability to act as an intestinal barrier in weaned lambs. With six duplicate pens and one lamb per pen, a total of 24 weaned lambs (average starting body weight of 7.32 ± 0.37 kg) were randomly assigned to one of four milk replacer treatments. Four concentrations of fucoidan supplementation (0, 0.1, 0.3, and 0.6% dry matter intake) were employed to investigate the effects of fucoidan on cecal fermentation and colon microbial organization. The test period lasted 37 days (1 week before the test and 1 month after the test), and lamb cecal contents and colon organization were collected for examination. In addition, the fecal status of all lambs was observed and recorded daily, allowing us to calculate the incidence of diarrhea in weaned lambs. The findings demonstrated that fucoidan may significantly increase the concentration of short-chain fatty acids (propionic acid and butyric acid) in the cecal digesta of weaned lambs. In weaned lambs, 16S rDNA testing showed that fucoidan at 0.3–0.6% (dry matter intake) was beneficial for boosting the variety of the intestinal bacteria and modifying the relative abundance of a few bacterial strains. In addition, fucoidan enhanced colon antioxidant and immune functions and decreased the diarrhea rate to relieve weaning stress. This result demonstrates that milk replacer supplementation with fucoidan contributes to the improvement in the large intestinal health of weaned lambs.

Osteosarcoma (OS) is one of the most prevalent primary bone tumors at all ages of human development. The objective of our study was to develop a model of Cuproptosis-Related Genes (CRGs) for predicting prognosis in OS patients. All datasets of OS patients were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database and Gene Expression Omnibus (GEO) database. We obtained the gene set (81 CRGs) related to cuproptosis by accessing the database and previous literature. All the CRGs were analyzed by univariate COX regression, least absolute shrinkage and selection operator (LASSO) COX regression analysis to screen for CRGs associated with prognosis in OS patients. Then these CRGs were used to construct a prognostic signature, which was further verified by independent cohort (GSE21257) and clinical correlation analysis. Afterward, to identify underlying mechanisms, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for the high-risk group by using the GSEA method. The association between the prognostic signature and 28 types of immune infiltrating cells in the tumor microenvironment was assessed. Ultimately, Lipoic Acid Synthetase (LIAS) (HR=0.632, P=0.004), Lipoyltransferase 1 (LIPT1) (HR=0.524, P=0.011), BCL2 Like 1 (BCL2L1/BCL-XL) (HR=0.593, P=0.022), and Pyruvate Dehydrogenase Kinase 1 (PDK1) (HR=0.662, P=0.025) were identified. Subsequently, they were used to calculate the risk score and build a prognostic model. In the training cohort, risk score (HR=1.878, P=0.003) could be considered as an independent prognostic factor, and OS patients with high-risk scores showed lower survival rates. Biological pathways related to substance metabolism and transport were enriched. There were significant differences in immune infiltrating cells in the tumor microenvironment. All in all, The CRGs signature is related to the tumor immune microenvironment and could be used as a credible predictor of the prognostic status in OS patients.

BackgroundCentral nervous system tumor (CNST) is one of the most complicated and lethal forms of human tumors with very limited treatment options. In recent years, growing evidence indicates that oncolytic virotherapy (OVT) has emerged as a promising therapeutic strategy for CNSTs. And a considerable amount of literature on OVT-CNSTs has been published. However, there are still no studies summarizing the global research trends and hotspots of this field through a bibliometric approach. To fulfill this knowledge gap, bibliometric analysis was conducted based on all publications relating to OVT-CNSTs since 2000s.MethodsWe searched the Web of Science Core Collection for all relevant studies published between 2000 and 2022. Four different tools (online analysis platform, R-bibliometrix, CiteSpace and VOSviewer) were used to perform bibliometric analysis and network visualization, including annual publication output, active journals, contribution of countries, institutions, and authors, references, as well as keywords.ResultsA total of 473 articles and reviews were included. The annual number of publications on OVT-CNSTs showed a significant increasing trend. Molecular Therapy and Cancer Research were the most active and co-cited journals, respectively. In terms of contributions, there is no doubt that the United States occupied a leading position with the most publications (n=307, 64.9%) and the highest H-index (57). The institution and author that contributed the largest number of publications were Ohio State University and Chiocca EA, respectively. As can be seen from citation analysis, the current studies mainly focused on preclinical and phase I/II clinical results of various oncolytic virus for CNSTs treatment. Keywords co-occurrence and burst analysis revealed that the following research topics including immunotherapy, T-cells, tumor microenvironment, vaccine, blood-brain-barrier, checkpoint inhibitors, macrophage, stem cell, and recurrent glioblastoma have been research frontiers of this field and also have great potential to continue to be research hotspots in the future.ConclusionThere has been increasing attention on oncolytic viruses for use as CNSTs therapeutics. Oncolytic immunotherapy is a topic of great concern in this field. This bibliometric study provides a comprehensive analysis of the knowledge base, research hotspots, development perspective in the field of OVT-CNSTs, which could become an essential reference for scholars in this area.

In recent years, ferroptosis has become a research hotspot in programmed cell death. Since the concept of ferroptosis was proposed, a growing number of articles have been published on this topic. Nevertheless, to our knowledge, these ferroptosis-related publications that have received a great deal of attention have not been quantitatively evaluated. In this study, we analyzed the top 100 most influential articles over the past decade through a bibliometric method to characterize the research status and trends in this field. Web of Science Core Collection was searched to identify relevant studies. After being manually screened, the top 100 most cited studies with original data were identified and analyzed. Bibliometric software including VOSviewer and R-Bibliometrix were used to perform visualization analysis. The citation frequency for the top 100 selected articles ranged from 135 to 3603 (326.6 citations on average). These articles originated from 25 countries/regions, with more than half originating from the United States and China. The most frequently nominated author was Stockwell BR from the Columbia University, and of the top 100 articles, 19 listed his name. Three core journals were Nature, Cell and Proceedings of the National Academy of Sciences of the United States of America. In addition to term of ferroptosis, these terms or phrases including cell death, cancer cell, GPX4, pathway, inhibitor, mechanism, iron, lipid peroxidation, resistance, erastin, sorafenib, P53, reactive oxygen species, necroptosis, apoptosis, glutathione peroxidase, ACSL4, autophagy, and SLC7A11 appeared more frequently in the top 100 articles. Overall, although much progress has been made, the research on ferroptosis is still at an early stage. The current attention in this field mainly focuses on potential regulatory mechanism and pathways including key ferroptosis-related genes/molecules, oxidant and antioxidant system, ferroptosis-inducing agents or nanomedicine for cancer therapy, as well as the role of ferroptosis in non-neoplastic disorders. Meanwhile, combination therapeutic strategies targeting ferroptosis in radiotherapy or immunotherapy also deserve further attention.

An oxidant-free and highly efficient synthesis of phenolic quinazolin-4(3H)-ones was achieved by simply stirring a mixture of 2-aminobenzamides, sulfonyl azides, and terminal alkynes. The intermediate N-sulfonylketenimine underwent two nucleophilic additions and the sulfonyl group eliminated through the power of aromatization. The natural product 2-(4-hydroxybenzyl)quinazolin-4(3H)-one can be synthesized on a large scale under mild conditions with this method.

BackgroundDiabetes mellitus (DM) have become seriously threatens to human health and life quality worldwide. As a systemic metabolic disease, multiple studies have revealed that DM is related to metabolic bone diseases and always induces higher risk of fracture. In view of this, the links between bone metabolism (BM) and DM (BMDM) have gained much attention and numerous related papers have been published. Nevertheless, no prior studies have yet been performed to analyze the field of BMDM research through bibliometric approach. To fill this knowledge gap, we performed a comprehensive bibliometric analysis of the global scientific publications in this field.MethodsArticles and reviews regarding BMDM published between 2000 and 2021 were obtained from the Web of Science after manually screening. VOSviewer 1.6.16, CiteSpace V 5.8.R3, Bibliometrix, and two online analysis platforms were used to conduct the bibliometric and visualization analyses.ResultsA total of 2,525 documents including 2,255 articles and 270 reviews were retrieved. Our analysis demonstrated a steady increasing trend in the number of publications over the past 22 years (R2 = 0.989). The United States has occupied the leading position with the largest outputs and highest H-index. University of California San Francisco contributed the most publications, and Schwartz AV was the most influential author. Collaboration among institutions from different countries was relatively few. The journals that published the most BMDM-related papers were Bone and Osteoporosis International. Osteoporosis and related fractures are the main bone metabolic diseases of greatest concern in this field. According to co-cited references result, “high glucose environment,” “glycation end-product” and “sodium-glucose co-transporter” have been recognized as the current research focus in this domain. The keywords co-occurrence analysis indicated that “diabetic osteoporosis,” “osteoarthritis,” “fracture risk,” “meta-analysis,” “osteogenic differentiation,” “bone regeneration,” “osteogenesis,” and “trabecular bone score” might remain the research hotspots and frontiers in the near future.ConclusionAs a cross-discipline research field, the links between bone metabolism and diabetes mellitus are attracting increased attention. Osteoporosis and related fractures are the main bone metabolic diseases of greatest concern in this field. These insights may be helpful for clinicians to recognize diabetic osteopenia and provide more attention and support to such patients.

A growing body of research has illuminated that photodynamic therapy (PDT) serves as an important therapeutic strategy in oncology and has become a hot topic in recent years. Although numerous papers related to cancer PDT (CPDT) have been published, no bibliometric studies have been conducted to summarize the research landscape, and highlight the research trends and hotspots in this field. This study collected 5,804 records on CPDT published between 2000 and 2021 from Web of Science Core Collection. Bibliometric analysis and visualization were conducted using VOSviewer, CiteSpace, and one online platform. The annual publication and citation results revealed significant increasing trends over the past 22 years. China and the United States, contributing 56.24% of the total publications, were the main driving force in this field. Chinese Academy of Sciences was the most prolific institution. Photodiagnosis and Photodynamic Therapy and Photochemistry and Photobiology were the most productive and most co-cited journals, respectively. All keywords were categorized into four clusters including studies on nanomaterial technology, clinical applications, mechanism, and photosensitizers. “nanotech-based PDT” and “enhanced PDT” were current research hotspots. In addition to several nano-related topics such as “nanosphere,” “nanoparticle,” “nanomaterial,” “nanoplatform,” “nanomedicine” and “gold nanoparticle,” the following topics including “photothermal therapy,” “metal organic framework,” “checkpoint blockade,” “tumor microenvironment,” “prodrug” also deserve further attention in the near future.

We recently demonstrated the reduction of the unified continuum and variational multiscale formulation to a computationally efficient fluid-structure interaction (FSI) formulation via three modeling assumptions pertaining to the vascular wall. Similar to the coupled momentum method introduced by Figueroa et al., the resulting semi-discrete formulation yields a monolithically coupled FSI system posed in an Eulerian frame of reference with only a minor modification of the fluid boundary integral. To achieve uniform second-order temporal accuracy and user-controlled high-frequency algorithmic damping, we adopt the generalized-α method for uniform temporal discretization of the entire coupled system. In conjunction with a fully consistent, segregated predictor multi-corrector algorithm preserving the block structure of the incompressible Navier-Stokes equations in the implicit solver’s associated linear system, a three-level nested block preconditioner is adopted for improved representation of the Schur complement. In this work, we apply our reduced unified continuum formulation to an appropriately prestressed patient-specific abdominal aortic aneurysm and investigate the effects of varying spatial distributions of wall properties on hemodynamic and vascular wall quantities of interest.

Objective: This study aimed to develop an accessible patient-specific computational flow modelling pipeline for evaluating the hemodynamic performance of fenestrated endovascular aneurysm repair (fEVAR), with the hypothesis that computational flow modelling can detect aortic branch hemodynamic changes associated with fEVAR graft implantation. Methods: Patients who underwent fEVAR for juxtarenal aortic aneurysms with the Cook ZFEN were retrospectively selected. Using open-source SimVascular software, preoperative and postoperative visceral aortic anatomy was manually segmented from computed tomography angiograms. Three-dimensional geometric models were then discretized into tetrahedral finite element meshes. Patient-specific pulsatile in-flow conditions were derived from known supraceliac aortic flow waveforms and adjusted for patient body surface area, average resting heart rate, and blood pressure. Outlet boundary conditions consisted of three-element Windkessel models approximated from physiologic flow splits. Rigid wall flow simulations were then performed on preoperative and postoperative models with the same inflow and outflow conditions. We used SimVascular's incompressible Navier-Stokes solver to perform blood flow simulations on a cluster using 72 cores. Results: Preoperative and postoperative flow simulations were performed for 10 patients undergoing fEVAR with a total of 30 target vessels (20 renal stents, 10 mesenteric scallops). Postoperative models required a higher mean number of mesh elements to reach mesh convergence (3.2 ± 1.8 × 106 vs 2.6 ± 1.1 × 106; P = .005) with a longer mean computational time (10.3 ± 6.3 hours vs 7.8 ± 3.5 hours; P = .04) compared with preoperative models. fEVAR was associated with small but statistically significant increases in mean peak proximal aortic arterial pressure (140.3 ± 11.0 mm Hg vs 136.9 ± 8.7 mm Hg; P = .02) and peak renal artery pressure (131.6 ± 14.8 mm Hg vs 128.9 ± 11.8 mm Hg; P = .04) compared with preoperative simulations. No differences were observed in peak pressure in the celiac, superior mesenteric, or distal aortic arteries (P = .17-.96). When measuring blood flow, the only observed difference was an increase in peak renal flow rate after fEVAR (17.5 ± 3.8 mL/s vs 16.9 ± 3.5 mL/s; P = .04). fEVAR was not associated with changes in the mean pressure or the mean flow rate in the celiac, superior mesenteric, or renal arteries (P = .06-.98). Stenting of the renal arteries did not induce significant changes time-averaged wall shear stress in the proximal renal artery (23.4 ± 8.1 dynes/cm2 vs 23.2 ± 8.4 dynes/cm2; P = .98) or distal renal artery (32.7 ± 13.9 dynes/cm2 vs 29.6 ± 11.8 dynes/cm2; P = .23). In addition, computational visualization of cross-sectional velocity profiles revealed low flow disturbances associated with protrusion of renal graft fabric into the aortic lumen. Conclusions: In a pilot study involving a selective cohort of patients who underwent uncomplicated fEVAR, patient-specific flow modelling was a feasible method for assessing the hemodynamic performance of various two-vessel fenestrated device configurations and revealed subtle differences in computationally derived peak branch pressure and blood flow rates. Structural changes in aortic flow geometry after fEVAR do not seem to affect computationally estimated renovisceral branch perfusion or wall shear stress adversely. Additional studies with invasive angiography or phase contrast magnetic resonance imaging are required to clinically validate these findings. (JVS–Vascular Science 2021;2:53-69.) Clinical Relevance: Using a computational flow modelling for assessing the hemodynamic performance of fenestrated endovascular aneurysm repair (fEVAR), this real-world, patient-specific study included 10 participants and found that structural changes in aortic flow geometry after fEVAR did not seem to adversely impact estimated renal or visceral branch perfusion metrics (eg, peak and mean arterial pressure and flow rates) or wall shear stress. These findings overall support the ongoing clinical use of commercially available fEVAR devices for repair of juxtarenal aortic aneurysms, and provides a computational framework for future evaluation of fEVAR configurations in a preoperative or postoperative settings.

Background Despite favorable outcomes of surgical pulmonary artery (PA) reconstruction, isolated proximal stenting of the central PAs is common clinical practice for patients with peripheral PA stenosis in association with Williams and Alagille syndromes. Given the technical challenges of PA reconstruction and the morbidities associated with transcatheter interventions, the hemodynamic consequences of all treatment strategies must be rigorously assessed. Our study aims to model, assess, and predict hemodynamic outcomes of transcatheter interventions in these patients. Methods and Results Isolated proximal and “extensive” interventions (stenting and/or balloon angioplasty of proximal and lobar vessels) were performed in silico on 6 patient‐specific PA models. Autoregulatory adaptation of the cardiac output and downstream arterial resistance was modeled in response to intervention‐induced hemodynamic perturbations. Postintervention computational fluid dynamics predictions were validated in 2 stented patients and quantitatively assessed in 4 surgical patients. Our computational methods accurately predicted postinterventional PA pressures, the primary indicators of success for treatment of peripheral PA stenosis. Proximal and extensive treatment achieved median reductions of 14% and 40% in main PA systolic pressure, 27% and 56% in pulmonary vascular resistance, and 10% and 45% in right ventricular stroke work, respectively. Conclusions In patients with Williams and Alagille syndromes, extensive transcatheter intervention is required to sufficiently reduce PA pressures and right ventricular stroke work. Transcatheter therapy was shown to be ineffective for long‐segment stenosis and pales hemodynamically in comparison with published outcomes of surgical reconstruction. Regardless of the chosen strategy, a virtual treatment planning platform could identify lesions most critical for optimizing right ventricular afterload.

Abstract Background Cold stress is one of the primary environmental factors that affect plant growth and productivity, especially for crops like Brassica napus that live through cold seasons. Till recently, although a number of genes and pathways involved in B. napus cold response have been revealed by independent studies, a genome-wide identification of the key regulators and the regulatory networks is still lack. In this study, we investigated the transcriptomes of cold stressed semi-winter and winter type rapeseeds in short day condition, mainly with the purpose to systematically identify the functional conserved transcription factors (TFs) in cold response of B. napus. Results Global modulation of gene expression was observed in both the semi-winter type line (158A) and the winter type line (SGDH284) rapeseeds, in response to a seven-day chilling stress in short-day condition. Function analysis of differentially expressed genes (DEGs) revealed enhanced stresses response mechanisms and inhibited photosynthesis in both lines, as well as a more extensive inhibition of some primary biological processes in the semi-winter type line. Over 400 TFs were differentially expressed in response to cold stress, including 56 of them showed high similarity to the known cold response TFs and were consistently regulated in 158A and SGDH284, as well as 25 TFs which targets were over-represented in the total DEGs. A further investigation based on their interactions indicated the critical roles of several TFs in cold response of B. napus. Conclusion In summary, our results revealed the alteration of gene expression in cold stressed semi-winter and winter ecotype B. napus lines and provided a valuable collection of candidate key regulators involved in B. napus response to cold stress, which could expand our understanding of plant stress response and benefit the future improvement of the breed of rapeseeds.

Four metal-ceramic composite coatings were prepared by laser cladding (LC) using Hastelloy C-276, nano-TiC and micro-TiB2 as raw materials to improve the surface properties and extend the service life of 316L stainless steel. The microstructure and mechanical properties were analyzed by metallographic microscopy, scanning electron microscopy (SEM), x-ray diffraction (XRD), Vickers hardness experiments, and friction and wear testing. The TiC and TiB2 phases were detected in the coating, exhibiting homogenous distribution as their content increased. As a result, the strengthening effect of the coating was enhanced, improving microhardness relative to that of the 316L substrate. The wear test revealed that the Hastelloy coating exhibited poor wear resistance, but the addition of TiC and TiB2 particles improved the wear resistance by reducing the wear rate. The lowest average coefficient and wear rate were attained at 50% and 70% ceramic contents, respectively. However, abundant hard particles on the surface easily fell off during the wear, which further impeded the surface degradation and increased the friction coefficient.

As an important factor determining the competitiveness of raw cotton, cotton fiber quality has received more and more attention. The results of traditional detection methods are accurate, but the sampling cost is high and has a hysteresis, which makes it difficult to measure cotton fiber quality parameters in real time and at a large scale. The purpose of this study is to use time-series UAV (Unmanned Aerial Vehicle) multispectral and RGB remote sensing images combined with machine learning to model four main quality indicators of cotton fibers. A deep learning algorithm is used to identify and extract cotton boll pixels in remote sensing images and improve the accuracy of quantitative extraction of spectral features. In order to simplify the input parameters of the model, the stepwise sensitivity analysis method is used to eliminate redundant variables and obtain the optimal input feature set. The results of this study show that the R2 of the prediction model established by a neural network is improved by 29.67% compared with the model established by linear regression. When the spectral index is calculated after removing the soil pixels used for prediction, R2 is improved by 4.01% compared with the ordinary method. The prediction model can well predict the average length, uniformity index, and micronaire value of the upper half. R2 is 0.8250, 0.8014, and 0.7722, respectively. This study provides a method to predict the cotton fiber quality in a large area without manual sampling, which provides a new idea for variety breeding and commercial decision-making in the cotton industry.

Estimating plant physiological indicators with remote sensing technology is critical for ensuring precise field management. Compared with other remote sensing platforms, low-altitude unmanned aerial vehicles (UAVs) produce images with high spatial resolution that can be used to clearly identify vegetation. However, the information of UAV image data is relatively complex and difficult to analyze, which is the main problem limiting its large-scale use at present. In order to monitor plant physiological indexes from the multi-spectral data, a new method based on machine learning is studied in this paper. Using UAV for deriving the absorption coefficients of plant canopies and whole leaf area, this paper quantifies the effects of plant physiological indicators such as the soil and plant analyzer development (SPAD) value, whole leaf area, and dry matter accumulation on the relationship between the reflectance spectra. Nine vegetation indexes were then extracted as the sensitive vegetation indexes of the rice physiological indicators. Using the SVM model to predict the SPAD value of the plant, the mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and symmetric mean absolute percentage error (SMAPE) values of the model were 1.90, 1.38, 0.13, 0.86, and 4.13, respectively. The results demonstrate that the rice plants display a considerable biochemical and spectral correlation. Using SVM to predict the SPAD value has a better effect because of a better adaptation and a higher accuracy than other models. This study suggests that the multi-spectral data acquired using UAV can quickly estimate field physiological indicators, which has potential in the pre-visual detection of SPAD value information in the field. At the same time, it can also be extended to the detection and inversion of other key variables of crops.

Abstract Background Drought is one of the most serious factors limiting plant growth and production. Sheepgrass can adapt well to various adverse conditions, including drought. However, during germination, sheepgrass young seedlings are sensitive to these adverse conditions. Therefore, the adaptability of seedlings is very important for plant survival, especially in plants that inhabit grasslands or the construction of artificial grassland. Results In this study, we found a sheepgrass MYB-related transcription factor, LcMYB2 that is up-regulated by drought stress and returns to a basal level after rewatering. The expression of LcMYB2 was mainly induced by osmotic stress and was localized to the nucleus. Furthermore, we demonstrate that LcMYB2 promoted seed germination and root growth under drought and ABA treatments. Additionally, we confirmed that LcMYB2 can regulate LcDREB2 expression in sheepgrass by binding to its promoter, and it activates the expression of the osmotic stress marker genes AtDREB2A, AtLEA14 and AtP5CS1 by directly binding to their promoters in transgenic Arabidopsis. Conclusions Based on these results, we propose that LcMYB2 improves plant drought stress tolerance by increasing the accumulation of osmoprotectants and promoting root growth. Therefore, LcMYB2 plays pivotal roles in plant responses to drought stress and is an important candidate for genetic manipulation to create drought-resistant crops, especially during seed germination.

Background: Rheumatoid arthritis is a chronic disabling disease characterized by chronic inflammation, articular cartilage destruction, and reduced bone mass. Multiple studies have revealed that the development of osteoporosis in rheumatoid arthritis (RA; ORA) patients could be led to a reduced quality of life and increased healthcare costs. Nevertheless, no attempt has been made to analyze the field of ORA research with the bibliometric method. This study aimed to provide a comprehensive overview of the knowledge structure and theme trends in the field of ORA research from a bibliometric perspective.Methods: Articles and reviews regarding ORA from 1998 to 2021 were identified from the Web of Science database. An online bibliometric platform, CiteSpace, and VOSviewer software were used to generate visualization knowledge maps including co-authorship, co-citation, and co-occurrence analysis. SPSS, R, and Microsoft Excel software were used to conduct curve fitting and correlation analysis, and to analyze quantitative indicators, such as publication and citation counts, h-index, and journal citation reports.Results: A total of 1,081 papers with 28,473 citations were identified. Publications were mainly concentrated in North America, Western Europe, and Eastern Asia. Economic strength is an important factor affecting scientific output. The United States contributed the most publications (213) with the highest h-index value (46) as of September 14, 2021. Diakonhjemmet Hospital and professor Haugeberg G were the most prolific institution and influential authors, respectively. Journal of Rheumatology was the most productive journal concerning ORA research. According to the burst references, “anti-citrullinated protein antibodies” and “preventing joint destruction” have been recognized as the hot research issues in the domain. The keywords co-occurrence analysis identified “teriparatide,” “interleukin-6,” “Wnt,” and “vertebral fractures” as the important future research directions.Conclusion: This was the first bibliometric study comprehensively summarizing the trends and development of ORA research. Our findings could offer practical sources for scholars to understand the key information in this field, and identify the potential research frontiers and hot directions in the near future.

The site-specific management of cotton fields is necessary for evaluating the growth status of cotton and generating a defoliation prescription map. The traditional assessment method of pests and diseases is based on spot surveys and manual participation, which is time-consuming, labor-intensive, and lacks high-quality results. The RGB and multispectral images acquired by drones equipped with sensors provide the possibility to quickly and accurately obtain the overall data for a field. In this study, we obtained RGB and multispectral remote sensing images to calculate the spectral index of the target area. At the same time, ground survey data were obtained by tracking and investigating the defoliation rate of cotton after spraying. With the help of data analysis methods, such as univariate linear regression, multiple linear regression models, neural network models, etc., a cotton defoliation effect monitoring model based on UAV remote sensing images was constructed. The results show that the BP neural network based on the VARI, VDVI, RSI, NGRDI, NDVI index has an R2 value of 0.945 and RMSE value of 0.006. The R2 values of the multiple linear regression model are 0.844 based on the RSI and NGRDI indexes and RSI and VARI indexes. Additionally, based on the model, the cotton defoliation of the whole farmland was evaluated, and the spray prescription map of the UAV sprayer was obtained.

Abstract Background The formation of natural colored fibers mainly results from the accumulation of different anthocyanidins and their derivatives in the fibers of Gossypium hirsutum L. Chalcone synthase (CHS) is the first committed enzyme of flavonoid biosynthesis, and anthocyanidins are transported into fiber cells after biosynthesis mainly by Anthocyanidin reductase (ANR) and Leucoanthocyanidin reductase (LAR) to present diverse colors with distinct stability. The biochemical and molecular mechanism of pigment formation in natural colored cotton fiber is not clear. Results The three key genes of GhCHS, GhANR and GhLAR were predominantly expressed in the developing fibers of colored cotton. In the GhCHSi, GhANRi and GhLARi transgenic cottons, the expression levels of GhCHS, GhANR and GhLAR significantly decreased in the developing cotton fiber, negatively correlated with the content of anthocyanidins and the color depth of cotton fiber. In colored cotton Zongxu1 (ZX1) and the GhCHSi, GhANRi and GhLARi transgenic lines of ZX1, HZ and ZH, the anthocyanidin contents of the leaves, cotton kernels, the mixture of fiber and seedcoat were all changed and positively correlated with the fiber color. Conclusion The three genes of GhCHS, GhANR and GhLAR were predominantly expressed early in developing colored cotton fibers and identified to be a key genes of cotton fiber color formation. The expression levels of the three genes affected the anthocyanidin contents and fiber color depth. So the three genes played a crucial part in cotton fiber color formation and has important significant to improve natural colored cotton quality and create new colored cotton germplasm resources by genetic engineering.

The purpose of this study was to evaluate the effects of fucoidan supplementation on serum biochemical parameters, small intestinal barrier function, and cecal microbiota of weaned goat kids. A total of 60 2-month-old weaned castrated male goat kids (Chuanzhong black goat) were used in this 30-day experiment. The goat kids were randomly divided into four groups: a control group (CON) fed the basal diet, and three other groups supplemented with 0.1%, 0.3%, and 0.5% fucoidan in the basal diet (denoted as F1, F2, and F3 groups, respectively). The results indicated that dietary fucoidan supplementation decreased (p < 0.05) the activity of lactate dehydrogenase (LDH) and the content of glucose (GLU) as measured on day 15. As measured on day 30, dietary fucoidan increased (p < 0.05) the content of total protein (TP) and decreased the activity of aspartate aminotransferase (AST), and supplementation with 0.3% and 0.5% fucoidan decreased (p < 0.05) the activity of LDH. Dietary fucoidan decreased (p < 0.05) the content of D-lactic acid (D-LA) and the activity of diamine oxidase (DAO). Dietary fucoidan increased (p < 0.05) the activity of catalase (CAT) in the duodenum. Dietary 0.3% and 0.5% fucoidan enhanced (p < 0.05) the activity of glutathione peroxidase (GSH-Px) in the ileum, the activity of total superoxide dismutase (T-SOD) in the jejunum and ileum, and the activity of CAT in the ileum. Dietary 0.3% and 0.5% fucoidan reduced the contents of malondialdehyde (MDA) in the duodenum, jejunum, and ileum and the content of hydrogen peroxide (H2O2) in the duodenum. Dietary fucoidan increased (p < 0.05) the content of secretory immunoglobulin A (sIgA) in the duodenum. Supplementation of 0.3% and 0.5% fucoidan upregulated (p < 0.05) the gene expression of ZO-1 and claudin-1 in the duodenum, jejunum, and ileum, and dietary supplementation of 0.3% and 0.5% fucoidan upregulated (p < 0.05) the gene expression of occludin in the jejunum and ileum. The 16S rRNA high-throughput sequencing results showed that at the phylum level, dietary fucoidan increased (p < 0.05) the abundance of Bacteroidetes while decreasing (p < 0.05) the abundance of Firmicutes. At the genus level, dietary 0.3% and 0.5% fucoidan increased (p < 0.05) the abundances of Unspecified_Ruminococcaceae, Unspecified_Bacteroidale, Unspecified_Clostridiales, and Akkermansia. In conclusion, dietary fucoidan supplementation had positive effects on intestinal permeability, antioxidant capacity, immunity function, tight junctions, and the cecal microflora balance in weaned goat kids.

A copper catalyzed tandem CuAAC/ring cleavage/[4+2] annulation reaction of terminal ynones, sulfonyl azides, and imines has been developed to synthesize the functionalized oxazines under mild conditions. Particularly, the intermediate N-sulfonyl acylketenimines undergo cycloaddition of an inverse electron demand Diels–Alder reaction with imines and a series of 1,3-oxazine derivatives were obtained successfully in good yields.

Plants have evolved a series of sophisticated defense mechanisms to help them from harm. Ethylene Response Factor (ERF) plays pivotal roles in plant immune reactions, however, its underlying mechanism in maize with a defensive function to Exserohilum turcicum (E. turcicum) remains poorly understood. Here, we isolated and characterized a novel ERF transcription factor, designated ZmERF061, from maize. Phylogenetic analysis revealed that ZmERF061 is a member of B3 group in the ERF family. qRT-PCR assays showed that the expression of ZmERF061 is significantly induced by E. turcicum inoculation and hormone treatments with salicylic acid (SA) and methyl jasmonate (MeJA). ZmERF061 was proved to function as a nucleus-localized transcription activator and specifically bind to the GCC-box element. zmerf061 mutant lines resulted in enhanced susceptibility to E. turcicum via decreasing the expression of ZmPR10.1 and ZmPR10.2 and the activity of antioxidant defense system. zmerf061 mutant lines increased the expression of the SA signaling-related gene ZmPR1a and decreased the expression of the jasmonic acid (JA) signaling-related gene ZmLox1 after infection with E. turcicum. In addition, ZmERF061 could interact with ZmMPK6-1. These results suggested that ZmERF061 plays an important role in response to E. turcicum and may be useful in genetic engineering breeding.

Gibberellin-dioxygenases genes plays important roles in the regulating plant development. However, Gibberellin-dioxygenases genes are rarely reported in maize, especially response to gibberellin (GA). In present study, 27 Gibberellin-dioxygenases genes were identified in the maize and they were classified into seven subfamilies (I-VII) based on phylogenetic analysis. This result was also further confirmed by their gene structure and conserved motif characteristics. And gibberellin-dioxygenases genes only occurred segmental duplication that occurs most frequently in plants. Furthermore, the gibberellin-dioxygenases genes showed different tissue expression pattern in different tissues and most of the gibberellin-dioxygenases genes showed tissue specific expression. Moreover, almost all the gibberellin-dioxygenases genes were significantly elevated in response to GA except for ZmGA2ox2 and ZmGA20ox10 of 15 gibberellin-dioxygenases genes normally expressed in leaves while 10 and 11 gibberellin-dioxygenases genes showed up and down regulated under GA treatment than that under normal condition in leaf sheath. In addition, we found that ZmGA2ox1, ZmGA2ox4, ZmGA20ox7, ZmGA3ox1 and ZmGA3ox3 might be potential genes for regulating balance of GAs which play essential roles in plant development. These findings will increase our understanding of Gibberellin-dioxygenases gene family in response to GA and will provide a solid base for further functional characterization of Gibberellin-dioxygenases genes in maize.

The purpose of this study was to evaluate the effects of fucoidan dietary supplementation on growth performance, organs’ relative weight, serum anti-oxidation markers, immune function indices and intestinal morphology in weaned kids. A total of 60 2-month-old weaned castrated male kids (Chuanzhong black goat) were used for this 30-day experiment and randomly allocated to four groups. The control group (CON) fed a basal diet, while the other three groups were provided with the same diet further supplemented with fucoidan at 0.1%, 0.3% or 0.5%, namely, F1, F2 and F3 groups, respectively. The results indicated that dietary fucoidan supplementation significantly increased (p < 0.05) the activity of catalase (CAT) when compared to the CON group on day 15. Moreover, the addition of fucoidan at 0.3% and 0.5% significantly increased (p < 0.05) the activities of glutathione peroxidase (GSH-Px) and total superoxide dismutase (T-SOD). On day 30, dietary fucoidan supplementation significantly reduced (p < 0.05) the feed conversion rate (FCR), contents of tumor necrosis-α (TNF-α), interleukin-1β (IL-1β) and interleukin-6 (IL-6), while it significantly increased (p < 0.05) the activity of total superoxide dismutase (T-SOD), the content of immunoglobulin G (IgG) and the villus height (VH) of the duodenum. Moreover, dietary 0.3% and 0.5% fucoidan supplementation significantly increased (p < 0.05) the villus height (VH) of the jejunum and ileum and significantly reduced (p < 0.05) the crypt depth (CD) of ileum. In conclusion, dietary fucoidan had positive effects on growth performance, serum anti-oxidation, immune function and intestinal morphology of weaned kids.

The ethylene response factor (ERF) plays a crucial role in plant innate immunity. However, the molecular function of ERF in response to Exserohilum turcicum (E. turcicum) remains unknown in maize. In this study, a novel ERF gene, designated as ZmERF105, was firstly isolated and characterized. The ZmERF105 protein contains an APETALA2/ETHYLENE RESPONSIVE FACTOR (AP2/ERF) domain and a conserved LSPLSPHP motif in its C-terminal region. ZmERF105 protein was exclusively localized to the nucleus. ZmERF105 expression responded to E. turcicum treatment. Yeast one-hybrid and transcription activity assays revealed that ZmERF105 is an activator of transcription and binds to GCC-box elements. Over-expression of ZmERF105 was shown to increase maize resistance against E. turcicum, and erf105 mutant lines displayed opposite phenotype. Moreover, the activities of superoxide dismutase (SOD) and peroxidase (POD) in the ZmERF105 over-expression lines were markedly higher than in the wild-type maize lines (WT) after infection with E. turcicum, and were compromised in the erf105 mutant lines. Simultaneously, ZmERF105 over-expression lines enhanced the expression of several pathogenesis-related (PR) genes, including ZmPR1a, ZmPR2, ZmPR5, ZmPR10.1, and ZmPR10.2 after infection with E. turcicum. In contrast, the expression of PR genes was reduced in erf105 mutant lines. Our work reveals that ZmERF105 as a novel player of the ERF network and positively regulates the maize resistance response to E. turcicum.

Alloy steel components can be subjected to serious damage from a variety of conditions during the industrial production procedures, such as wear and fracture failure. Therefore, the preparation of gradient-reinforced layers on the surface of the alloy steel was considered an effective technique to improve the performance. Along these lines, a 40Cr alloy steel, which was commonly used in industry, was systematically investigated in this work. The nano TiC ceramic material was selected in the hard phase. In this work, continuous-wave laser was used to fabricate gradient reinforced layers, which provided a technical reference for the development of protective reinforcement layers for alloy steels with excellent mechanical properties. A dense structure was formed inside the nano TiC gradient reinforced layer, which has a lower friction coefficient (0.25) and wear loss weight (23 mg). The height of the surface material loss under a heavy load wear environment (187 μ m) was lower than that of a bare 40Cr alloy steel sample (1116 μ m). The impact energy of the nano TiC gradient reinforced layer (75.27 J cm ^−2 ) was higher than that of a bare 40Cr alloy steel sample (15.25 J cm ^−2 ). Both the wear behavior and impact toughness strengthening mechanism of the nano TiC gradient reinforced layer were revealed.

Abstract Background MADS-box genes are categorized into A, B, C, D and E classes and are involved in floral organ identity and flowering. Sheepgrass (Leymus chinensis (Trin.) Tzvel) is an important perennial forage grass and adapts well to many adverse environments. However, there are few studies on the molecular mechanisms of flower development in sheepgrass, especially studies on MADS-domain proteins. Results In this study, we cloned 11 MADS-box genes from sheepgrass (Leymus chinensis (Trin.) Tzvel), and phylogenetic analysis of the 11 genes with their homologs revealed that they are divided into nine subclades. Tissue-specific expression profile analysis showed that most of these MADS-box genes were highly expressed in floral organs. LcMADS1 and LcMADS3 showed higher expression in the stamen than in the other tissues, and LcMADS7 showed high expression in the stamen, glume, lemma and palea, while expression of LcMADS2, LcMADS9 and LcMADS11 was higher in vegetative organs than floral organs. Furthermore, yeast two-hybrid analyses showed that LcMADS2 interacted with LcMADS7 and LcMADS9. LcMADS3 interacted with LcMADS4, LcMADS7 and LcMADS10, while LcMADS1 could interact with only LcMADS7. Interestingly, the expression of LcMADS1 and LcMADS2 were significantly induced by cold, and LcMADS9 was significantly up-regulated by NaCl. Conclusion Hence, we proposed that LcMADS1, LcMADS2, LcMADS3, LcMADS7 and LcMADS9 play a pivotal role in sheepgrass sexual reproduction and may be involved in abiotic stress responses, and our findings provide useful information for further exploration of the functions of this gene family in rice, wheat and other graminaceous cereals.

Development of novel anticancer therapeutic candidates is one of the key challenges in medicinal chemistry. Podophyllotoxin and its derivatives, as a potent cytotoxic agent, have been at the center of extensive chemical amendment and pharmacological investigation. Herein, a new series of podophyllotoxin-N-sulfonyl amidine hybrids (4a–4v, 5a–5f) were synthesized by a CuAAC/ring-opening procedure. All the synthesized podophyllotoxins derivatives were evaluated for in vitro cytotoxic activity against a panel of human lung (A-549) cancer cell lines. Different substituents’, or functional groups’ antiproliferative activities were discussed. The –CF3 group performed best (IC50: 1.65 μM) and exhibited more potent activity than etoposide. Furthermore, molecular docking and dynamics studies were also conducted for active compounds and the results were in good agreement with the observed IC50 values.

With the continuous development of intelligent product interaction technology, the facial expression design of virtual images on the interactive interface of intelligent products has become an important research topic. Based on the current research on facial expression design of existing intelligent products, we symmetrically mapped the PAD (pleasure–arousal–dominance) emotion value to the image design, explored the characteristics of abstract expressions and the principles of expression design, and evaluated them experimentally. In this study, the experiment of PAD scores was conducted on the emotion expression design of abstract expressions, and the data results were analyzed to iterate the expression design. The experimental results show that PAD values can effectively guide designers in expression design. Meanwhile, the efficiency and recognition accuracy of human communication with abstract expression design can be improved by facial auxiliary elements and eyebrows.

N-Sulfonyl amidines are developed from a Cu-catalyzed three-component reaction from sulfonyl hydrazines, terminal alkynes and sulfonyl azides in toluene at room temperature. Particularly, the intermediate N-sulfonylketenimines was generated via a CuAAC/ring-opening procedure and took a nucleophilic addition with the weak nucleophile sulfonyl hydrazines. In addition, the stability of the product was tested by a HNMR spectrometer.