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Abstract Hypoxic-ischemic encephalopathy (HIE) is a diffuse brain tissue injury caused by acute ischemia and hypoxia, and it is most commonly found in newborn infants but can also occur in adults. Mesenchymal stem cell (MSC) therapies have showed improved outcomes for treating HIE-induced neuronal defects. However, many key issues associated with poor cell viability and tolerance of grafted MSCs after HIE remain to be resolved. Genetic engineering could endow MSCs with more robust regenerative capacities. Our research, along with that of other scientists, has found that the expression of intracellular erythropoietin (EPO) in human umbilical cord MSCs (hUC-MSCs) increases proportionally with the duration of hypoxia exposure. Furthermore, we observed that EPO, when introduced into the EPO gene-modified hUC-MSCs, can be secreted into the extracellular space. However, the underlying mechanisms that support the neuroprotective effects of EPO-MSCs remain unclear. EPO-MSCs, hUC-MSCs, and NC-MSCs were identified by flow cytometry, osteogenic, and adipogenic differentiation assays. The oxygen-glucose deprivation (OGD)-induced SH-SY5Y cell-line was established, and five groups were set up: control, 24-h ischemia-hypoxia, co-cultured with hUC-MSCs, NC-MSCs, and EPO-MSCs after hypoxia. LEGENDplex™ multi-factor flow cytometry was used to detect the secretion of inflammatory factors in cell supernatants and cerebrospinal fluid. Chromosome-targeted excision and tagging (CUT&Tag) sequencing was applied to detect genomic H3K4me2 modifications, and conjoint analysis with transcriptome sequencing (RNA-seq) was performed. Lentiviral vector infection was used to construct SH-SY5Y cells with stable knockdown of RE1-silencing transcription factor (REST), and flow cytometry was used to detect alterations in apoptosis. Finally, the molecular mechanism underlying the neuroprotective and anti-apoptotic effects of EPO-MSCs was investigated using RNA sequencing, qRT-PCR, and western blot assays. Our results suggest that EPO-MSCs are genetically engineered to secrete significantly more EPO. EPO-MSCs treatment has anti-apoptotic properties and offers neuronal protection during ischemic-hypoxic injury. Furthermore, RNA-seq results suggest that multiple inflammation-related genes were down-regulated after EPO-MSCs treatment. Application of RNA-seq and CUT&Tag combined analysis found that the expressions of REST were significantly up-regulated. Lentiviral vector infection to construct REST knockdown SH-SY5Y failed to rescue apoptosis after hypoxia and co-culture with EPO-MSCs, and SETD2-mediated H3K36me3 protein level expression was reduced. EPO-MSCs may promote neuronal survival by affecting H3K4me2 and thus activating the expression of REST and TET3. EPO-MSCs also upregulated the modification level of SETD2-mediated H3K36me3 and regulated the expression of inflammation-related genes such as PLCG2, as well as apoptosis genes BCL2A1. To investigate the neuroprotective effects of EPO-modified hUC-MSCs and the underlying epigenetic regulatory mechanisms, this study aims to provide a theoretical foundation for the potential application of EPO gene-modified hUC-MSCs in the treatment of HIE.

Abstract Background A persistent redox state and excessive reactive species involved in carbohydrate and lipid metabolism lead to oxidative damage in the liver, however, how fasting plasma concentrations of lipids and glucose are associated with fasting blood levels of alanine transaminase (ALT) and aspartate transaminase (AST) remains to be evaluated in large-scale population. Methods A cross-sectional study with 182,971 residents aged 18 to 92 years; multidimensional stratified analyses including quantile linear regression analysis and sex stratification were adopted to improve the quality of the evidence. Results The associations between the concentrations of non-HDL-C and triglyceride and ALT levels were positive, stronger in males in each quantile of ALT levels and the coefficients expanded with increasing ALT levels at slopes of 3.610 and 5.678 in males and 2.977 and 5.165 in females, respectively. The associations between the HDL-C concentrations and ALT levels were negative, also stronger in males in each quantile and the coefficients expanded with increasing ALT levels at slopes of -7.839 in females and − 5.797 in males. The associations between glucose concentrations and ALT levels were positive, but stronger in females in each quantile and the coefficients expanded with increasing ALT levels at slopes of 1.736 in males and 2.177 in females, respectively. Similar pattern consist of relatively weaker coefficients and slops were observed between concentrations of non-HDL-C, triglyceride and glucose and AST levels. The associations between albumin concentration and concentrations of blood lipids and glucose were relatively steady across all quantiles. Conclusions The dose dependent effect between blood concentrations of lipids and glucose and liver function changes suggests that excessive carbohydrate and lipid metabolism may cause subclinical liver damage. Long term sustained primary and secondary inflammatory factors produced in the liver might be transmitted to adjacent organs, such as the heart, kidneys, and lungs, to cause and/or exacerbate pathological changes in these visceral organs.

Abstract Background Mesenchymal stem cells (MSCs) possess powerful immunomodulatory ability. This study aimed to assess the efficacy and safety of human umbilical cord-derived mesenchymal stem cells (UMSCs) in patients with ulcerative colitis (UC) and to explore the potential mechanisms. Methods This prospective, self-controlled clinical study was conducted at Henan Provincial People’s Hospital. Patients with moderate-to-severe active UC, unresponsive to traditional drugs were continuously enrolled from September 2018 to March 2023. UMSCs were administered intravenously monthly for two months at a cell dosage of 1 × 106 per kg. The primary outcome was a clinical response at 2 months. The levels of cytokines and progerin in the plasma of the patients were analyzed using enzyme-linked immunosorbent assay kits, and longitudinal data was analyzed using generalized estimation equation. Results Forty-one patients were enrolled and received UMSC therapy. At 2 months, 73.2% (30/41) of patients achieved a clinical response, and 41.5% (17/41) achieved a clinical remission. At 6 months, 2 patients were lost to follow-up; the corresponding figures were 70.0% (25/41) and 34.2% (14/41), respectively. After UMSC therapy, the Mayo score, Mayo endoscopy score, mean and maximum values of Ulcerative Colitis Endoscopic Index of Severity and Nancy index were significantly reduced compared with baseline values. Additionally, the levels of progerin and inflammatory markers, such as interleukin (IL)-1β, IL-6, IL-8, IL-12, and IL-17 A decreased, while hemoglobin, albumin, and IL-10/IL-17 A ratio increased, particularly in the response group. Multiple stepwise logistic regression analysis showed age was an independent risk factor affecting efficacy (odds ratio, 0.875 (95% confidence interval (0.787, 0.972)); the area under the receiver operating characteristic curve for age was 0.79. No serious adverse events were observed during or after UMSC therapy. Conclusion UMSCs are safe and effective for patients with UC, with age being an independent risk factor affecting efficacy. Mechanistically, UMSC treatment may ameliorate cell senescence and suppress the secretion of pro-inflammatory cytokines. Trial registration The study was retrospectively registered at www.chictr.org.cn/ (ChiCTR1900026035) on September 18, 2019.

As the reserve force and sustained driving force of the rural teacher team, rural young teachers bear the heavy responsibility of revitalizing the development of rural education. Sense of gain is the key to enhancing the professional attraction of the rural teacher profession and strengthening the education belief of rural young teachers, and it is also the fundamental guarantee for building a high-quality rural teacher team. An index system of rural young teachers' sense of gain is proposed in this study through modifying Delphi method and analytic hierarchy process. The system consists of 3 primary indicators including sense of gain in "survival guarantee", "relationship belonging" and "self-development", 7 secondary indicators including sense of gain in "material economy", "policy guarantee", "social interaction", "public culture", "social prestige", "professional growth" and "professional achievement", and 28 corresponding tertiary indicators. On this basis, this research puts forward the ways to improve rural young teachers' sense of gain: 1) improve material security, and promote differentiated teacher incentive; 2) integrate relationship belonging, and satisfy humanized social needs; 3) continue self-development, and shape rational future expectations.

The scientific goal of the Anninghe seismic array is to investigate the detailed geometry of the Anninghe fault and the velocity structure of the fault zone. This 2D seismic array is composed of 161 stations forming sub-rectangular geometry along the Anninghe fault, which covers 50 km and 150 km in the fault normal and strike directions, respectively, with ∼ 5 km intervals. The data were collected between June 2020 and June 2021, with some level of temporal gaps. Two types of instruments, i.e. QS-05A and SmartSolo, are used in this array. Data quality and examples of seismograms are provided in this paper. After the data protection period ends (expected in June 2024), researchers can request a dataset from the National Earthquake Science Data Center.

Accurate indoor 3D models are essential for building administration and applications in digital city construction and operation. Developing an automatic and accurate method to reconstruct an indoor model with semantics is a challenge in complex indoor environments. Our method focuses on the permanent structure based on a weak Manhattan world assumption, and we propose a pipeline to reconstruct indoor models. First, the proposed method extracts boundary primitives from semantic point clouds, such as floors, walls, ceilings, windows, and doors. The primitives of the building boundary are aligned to generate the boundaries of the indoor scene, which contains the structure of the horizontal plane and height change in the vertical direction. Then, an optimization algorithm is applied to optimize the geometric relationships among all features based on their categories after the classification process. The heights of feature points are captured and optimized according to their neighborhoods. Finally, a 3D wireframe model of the indoor scene is reconstructed based on the 3D feature information. Experiments on three different datasets demonstrate that the proposed method can be used to effectively reconstruct 3D wireframe models of indoor scenes with high accuracy.

Abstract Industrial defect detection is an important part of intelligent manufacturing, and Internet of things (IoT)‐based defect detection is receiving more and more attention. Although deep learning (DL) can help defect detection reduce the cost and improve the accuracy of traditional manual quality inspection, DL requires huge computational resources and is difficult to be simply deployed on IoT devices with limited computational power and memory resources. Digital signal processor (DSP) is an important IoT device with small size, high performance and low energy consumption, which has been widely used in intelligent manufacturing. In order to perform accurate defect detection on DSP, the authors proposed various optimisation strategies and then used a parallel scheme to scale the model to execute on multiple cores. The authors’ method evaluated it on Northeastern University Surface Defect Dataset, Magnetic Tile Defect Dataset, Rail Surface Defect Dataset and Silk Cylinder Defect Dataset, and the experimental results showed that the authors’ method obtains faster speeds without accuracy loss compared to running the same Convolutional Neural Networks model on a mainstream desktop CPU. This means that the authors’ method can realise efficient and accurate defect detection on IoT devices with limited computational power and memory resources, which opens up new possibilities for future development in the field of smart manufacturing.

Indoor scenes are closely related to human life and contain rich geometric and semantic information. Dividing indoor spaces from data is crucial for multiple applications, such as navigation and digital twins. However, achieving this task is challenging. Traditional indoor space division methods only represent buildings, floors, and rooms to some extent, lacking semantic descriptions of indoor elements and their spatial arrangements. To divide an indoor space more finely, a novel indoor space subdivision method is proposed in this paper. Our method leverages the flexible space subdivision framework (FSS) to categorize indoor space into free navigation subspace, object subspace, and functional subspace. To define functional subspaces, we present a taxonomy for the spatial layout patterns of common indoor elements (like tables, chairs, ceilings, walls, floors, etc.). Then, we introduce scene graphs to represent indoor 3D scenes, where each node represents an indoor element and each edge encodes the spatial relationship between the elements. Finally, a node classification network is proposed to segment indoor scene into subspaces and predicts their (semantic) functions. We select 9 buildings of Matterport3D and 6 areas in S3DIS and merge them to form our dataset for training and testing our method. Experiments yield good results with up to 90.42% accuracy and 85.28% F1-scores in overall space subdivision. Moreover, compared with the various graph node classification networks, our method has achieved the best performance in indoor space subdivisions.

Abstract Purpose Metastatic ocular and orbital melanomas are extremely rare. The clinical characteristics and standard treatments for these patients are not fully established. Materials and Methods We retrospectively analyzed patients with metastatic ocular and orbital melanoma from Fudan University Shanghai Cancer Center and Eye & ENT Hospital of Fudan University between January 2012 and May 2022. Results Overall, 51 patients with metastatic ocular and orbital melanoma were included. The most common primary sites were uvea (73%), followed by conjunctiva (22%), lacrimal sac (4%), and orbit (2%). Patients with uveal melanoma (UM) had a significantly younger age (48 vs. 68 years, p

AIM: To detect proteomic differences in tears between adenoid cystic carcinoma (ACC) and pleomorphic adenoma (PA). METHODS: Tear samples were collected from 4 patients with ACC, 5 with PA, and 4 control cases. Label-free analysis and parallel reaction monitoring (PRM) were used to screen and validate the tear proteome. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted for bioinformatics analysis. RESULTS: In total, 1059 proteins in tear samples were identified by label-free analysis. Between ACC and PA, 415 differentially expressed proteins were detected. Based on the GO annotation, enzyme regulator activity and serine-type endopeptidase inhibitor activity in the molecular function category, blood microparticle and extracellular matrix in the cellular component category, and response to nutrient levels in the biological process category were most predominant. By KEGG pathway annotation, the different proteins between ACC and PA mainly participated in complement and coagulation cascades, amoebiasis, African trypanosomiasis and cholesterol metabolism. Eight proteins with mostly significant differences were verified by PRM, and five proteins with more than 10-fold increases in ACC compared with PA, including integrin β, α-2-macroglobulin, epididymal secretory sperm binding protein Li 78p, RAB5C, and complement C5, were identified. CONCLUSION: The combined tools of label-free analysis and PRM are very effective and efficient, especially for samples such as tears. Some proteomic differences in tears between ACC and PA are identified and these protein candidates may be specific biomarkers for future exploration.

The Chang 9 oil layer deposits within Ansai District, Ordos Basin, yield considerable reserves of crude oil, yet their source remains ambiguous. This research endeavor was designed to characterize the Chang 9 crude oil and the Chang 7 and Chang 9 source rocks (SRs) of the Yan-Chang Formation via organic geochemical analysis. The results indicate that the Chang 9 crude oil exhibits a Pr/Ph ratio of 0.84–2.29 and Ga/C30H less than 0.1, implying formed in a weak reduction to weak oxidation freshwater environment. The regular sterane C27-C28-C29 configuration assumes an inversed “L” type, reflecting mixed sources and dominant terrestrial plant input. Ratios such as C2920S/20S+20R (0.54–0.6) and C29ββ/ββ+αα (0.44–0.58) indicate a mature oil stage. The depositional environment of the C7 and C9 SRs is similar, with weak oxidation to reduction conditions, and consists mainly of Type I and II organics, with a relatively higher maturity of the C9 SRs. A difference in C19/C23TT and C30D/C30H was found between the C7 and C9 SRs. The results show that the C9 crude oils have a similar C19/C23TT with the C9 SRs and similar diahopanes distribution with Class II SRs (C7 and part of the C9 SRs). Thus, the C9 crude oils most likely originate from the C9 SR mixed with the C7 SRs.

Teaching online physical education courses under the epidemic normalization plays a positive role in students’ physical fitness. In this paper, taking 308 college students of X Sports College as a research case, personalized recommendation of physical education online teaching courses is carried out through a user collaborative filtering recommendation algorithm based on fuzzy clustering and user interests. The model of sports skill action development is constructed based on the mountain peak model and hourglass model, and the exercise intensity of the initial exercise is modified according to the results of home exercise intensity adjustment to obtain a personalized home exercise program suitable for individuals. Finally, the effectiveness of the home exercise optimization program was verified through the analysis of teaching constraints and exercise effects. The results show that under the epidemic normality, the difference between the demonstration movements and the test results in the 1st, 2nd and 3rd optimized teaching phases is between ±5.86, which is closer to the value of each index of the demonstration movements, indicating that the optimization and adjustment scheme of the home exercise of the physical education network teaching course has good effects. This paper has reference value for universities to conduct online teaching and training of university physical education courses in the context of major public health emergencies.

Vitamin D deficiency is associated with various diseases such as obesity, digestive problems, osteoporosis, depression, and infections, and has therefore emerged as a topic of great interest in public healthcare. The quantitative assessment of 25-hydroxyvitamin D (25-OH VD) in human serum may accurately reflect the nutritional status of vitamin D in the human body, which is significant for the prevention and treatment of vitamin D-deficient patients. In this study, we developed an assay for quantitative detection of 25-OH VD based on the 25-OH VD monoclonal antibody (mAb), and identified the optimal process parameters. The following process settings were found to be suitable for the test strips: pH of 7.6, 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) ratio of 1:2000, and the anti-25-OH VD mAb ratio was 1:8. The equilibration time of the immune dynamic assay was 15 min. Under optimal conditions, the quantum dot nanoparticle-based fluorescent immunochromatographic assay (QDs-FICA) exhibited dynamic linear detection of 25-OH VD in PBS, from 5 ng/mL to 100 ng/mL, and the strip quantitative curve could be represented by the following regression equation: y = −0.02088 logx)+1.444 (R2 = 0.9050). The IC50 of the QDs-FICA was 39.6 ± 1.33 ng/mL. The specificity of the QDs-FICA was evaluated by running several structurally related analogues, including 25-OH VD2, 25-OH VD3, 1,25-OH2VD3, 1,25-OH2VD2, VD2, and VD3. The coefficients of variation were all below 10%. The shelf life of the test strips in this study was about 160 days at room temperature. Briefly, this study is the first to perform QDs-FICA for the rapid visual and quantitative detection of 25-OH VD, with great potential significance for clinical diagnosis of vitamin D-associated diseases.

To determine the rupture processes of big earthquakes is a fundamental problem of earthquake studies, which also supports earthquake physics research. Although the joint use of seismic, geodetic and seismicity data provides good constraints to determine the fault plane information of inland earthquakes, it is still challenging to unveil non-planar fault planes for oceanic earthquake ruptures. For complicated earthquakes, that ruptured more than one fault plane, a method to stably obtain focal mechanism changes is required to determine the fault plane information precisely. In this study, we analyze the stability and flexibility of multiple seismic methods, i.e. back-projections, multi-point-source inversion and finite fault inversion, to determine the rupture kinematics of big earthquakes, and find the stability spatial-temporal resolution and flexibility to resolve focal mechanisms that are not compatible in each single techniques. A sequential strategy is thus proposed to use back-projection results to prescribe the a priori information of multi-point-source inversion to achieve mechanism changing point source solutions with high spatial-temporal accuracy. Two strategies to connect these two techniques and other technique concerns are also discussed.

AIM: To study the clinical and pathological characteristics of the lacrimal sac lymphoma, which is rare but it is the major type of non-epithelial malignant tumor in the lacrimal sac region. METHODS: Sixty-four cases of malignant lacrimal sac tumors in our hospital from 1986 to 2020 were retrospectively reviewed. Eight cases of lacrimal sac lymphoma were carefully reviewed. RESULTS: There were five mucosal-associated lymphoid tissue (MALT) lymphomas, one diffused large B-cell lymphoma, one NK/T cell lymphoma, and one mantle cell lymphoma. All eight patients represented symptoms of epiphora with swelling in the lacrimal sac for a certain period of time and showed no signs of systemic involvement at the first time of clinical visits. They had received either chemotherapy or radiotherapy after surgery. Long-term follow-up (from 11 to 220mo) showed that, except one patient with MALT lymphoma died for unknown reasons at 104mo after surgery, the other 7 patients were all alive with no signs of local recurrence, neither in other organs. CONCLUSION: Non-epithelial malignant tumors of the lacrimal sac are rare and lymphoma is the major subtype.

The forest canopy height is a key indicator for measuring global forest carbon stocks. Spaceborne LiDAR, a satellite remote sensing technology, plays an essential role in large-scale canopy height estimations. However, there are still some problems with existing methods of the spaceborne LiDAR canopy height estimates: the retrieval accuracy is degraded by the topographic relief and vegetation cover, as well as uneven spatial distribution of mapping height uncertainties. In this paper, we investigated the possibility of fusing multimodal spaceborne LiDAR and optical images to improve these above problems. We proposed a hybrid model fusing spaceborne full-waveform and photon-counting LiDAR data with optical imagery. Specifically, our approach divided the regional extent into multiple fusion patterns based on the spatial distribution of the LiDAR footprints in an object-oriented method. We then constructed canopy height models corresponding to each pattern and finally integrated the model results using a weighting scheme considering geospatial distances. We used GEDI (full-waveform LiDAR), ICESat-2 (photon-counting LiDAR) and Sentinel-2 (optical imagery) products as the input data and validated the model accuracy in four representative biomes of global forest ecosystems (i.e., evergreen broadleaf forests, deciduous broadleaf forests, savannas and coniferous forests). The experimental results demonstrated that fusing multisource spaceborne LiDAR data and optical images can not only enhance the canopy height estimation accuracy (R2 0.65 ∼ 0.90 and RMSE 0.57 ∼ 4.15 m in four biomes) but also maintain stable accuracy under undulating slope and large vegetation cover. Moreover, the uncertainty of canopy height estimation was low (meanerror −0.20 ∼ 0.03 m) and uniformly distributed in space (stdev 0.71 ∼ 4.45 m). We also compared the performances with two other advanced canopy height models, as well as two global canopy height products, and our model showed significant advantages in each test region. Our study demonstrates the effectiveness of fusing multimodal spaceborne LiDAR data and optical imagery for canopy height estimation accuracy improvement.

With the rapid development of modern industry, the foundation soil and the underground water in some areas are severely polluted by the corrosive medium affecting the durability of foundation concrete. Sulfate corrosion is one of the major factors leading to the destruction of foundation concrete. The sulfate corrosion resistance of foundation concrete with nano-particles (nano-SiO2 and nano-CaCO3) under the action of dry-wet cycle is experimentally studied, and compared with that of plain foundation concrete. The test results indicate that, under the action of dry-wet cycle, the sulfate corrosion resistance of foundation concrete is significantly improved with the addition of nano-particles. With the increasing content of nano-particles, the sulfate corrosion resistance of foundation concrete gradually rises to its peak and then drops step by step. The sulfate corrosion resistance of foundation concrete with nano-SiO2 is superior to that of foundation concrete with the same amount of nano-CaCO3. When the content of nano-SiO2 and nano-CaCO3 is respectively 2.0 % and 1.0 % by weight of binder, the sulfate corrosion resistance of foundation concrete is the best. Because the pore structure of concrete is improved with the addition of nano-particles, as nano-SiO2 can react with Ca(OH)2 and nano-CaCO3 can react with C3A, nano-particles can significantly enhance the sulfate corrosion resistance of foundation concrete.

At present, many countries and regions around the world have entered an aging society, so the demand intelligent elderly product has begun to double. However, in the design process of intelligent elderly products, there is a lack of a set of perfect method model and evaluation criteria for the application of humanistic care factors in intelligent elderly products. To standardize the use of humanistic care factors in the design of intelligent elderly products. Firstly, this study uses grounded theory to code and analyze the humanistic care factors. Secondly, the analytic hierarchy process (AHP) and analytic network process (ANP) are used for comparative study to obtain the sensitivity priority of the application of humanistic care factors, and a new design method model is proposed. Finally, the fuzzy evaluation method is used to verify the rationality of the design method model. The study shows that the use of humanistic care factors has the greatest impact on emotion, especially in the consideration of Interactivity, followed by Color mildness and Companionship. The results are divided in the form of a hierarchical demand tower, to establish a new Humanistic-care Factors Application Hierarchical Design-model (HFAHD) for intelligent elderly products. The HFAHD can not only help designers to improve the design efficiency in the design of intelligent elderly products, but also further standardize the use of humanistic care factors in the design of intelligent elderly products. Through the combination of quantitative research and qualitative research, it is proposed to divide the use of humanistic care factors into hierarchical models to help designers better use the HFAHD. This study not only improves the design standards of intelligent elderly products, but also extends to other design fields in further research, and promotes the more rational use of humanistic care factors in design.

Abstract Background IgG4-related ophthalmic disease (IgG4ROD) is a phenotype of IgG4-related disease (IgG4RD) with ophthalmic involvement. The pathological IgG4+ plasmacyte count has only been used for diagnosis. We aimed to explore its possible clinical value in the management of IgG4ROD. Methods Fifty-five pathologically diagnosed IgG4ROD patients were included, and their clinical, pathological, serological, and radiological findings and treatment outcomes were reviewed and analyzed. The pathological IgG4+ plasmacyte counts in lesions from different anatomic sites were compared, and their association with serum IgG4 concentrations, systemic involvement, and relapse risk was analyzed. Results The patients were divided into groups according to the anatomic site of their biopsied lesions, namely, the lacrimal gland, extraocular muscle, and orbital soft tissue. No significant difference was found in the pathological IgG4+ plasma cell counts among these groups (p = 0.975). The pathological IgG4+ plasmacyte count positively correlated with the IgG4 concentration in peripheral blood (R 2 = 0.5469, p < 0.001). The serum IgG4 concentration and the pathological infiltrating IgG4+ plasmacyte count were significantly higher in patients with extraophthalmic involvement (p < 0.001 and p = 0.005, respectively). The areas under the receiver operating characteristic (ROC) curve (AUCs) of the serum IgG4 level and pathological IgG4+ plasmacyte count for identifying systemic involvement were 0.897 (p < 0.001) and 0.759 (p = 0.015), respectively. The patients with relapse had higher levels of serum IgG4, more germinal centers (GCs), and infiltrating IgG4+ plasmacytes in lesions. Multivariate Cox regression analysis revealed that a pathological IgG4+ plasmacyte count of > 150/high-power field (HPF) and an elevated serum IgG4 level of > 500 mg/dL were risk factors for relapse after steroid treatment. Conclusions Lesions from different ophthalmic sites in IgG4ROD patients have similar counts of IgG4+ and IgG+ plasmacytes. The quantity of pathological IgG4+ plasmacytes corresponded to the serum IgG4 concentration in patients with IgG4ROD and could be meaningful in identifying systemic involvement and predicting subsequent relapse.

One of the essential works of the tunnel maintenance department is to inspect and maintain the electricity transmission system (ETS). Tunnel inspection with a mobile laser system (MLS) can automate the traditionally manual surveys. In this study, we proposed a step-wise method for automatically extracting ETS in MLS data. First, in the approximate extraction stage, we used edge-based and fitting-based segmentation algorithms to remove the ground and lining, respectively. Then, in the precise extraction stage, power transmission lines were accurately extracted at the object-level using a proposed spherical-stepping-cluster algorithm, and the supporting fixtures were extracted using density information and connection characteristics. The proposed method was validated through experiments on a batch of point cloud markings with ground-truth data and comparisons with existing methods. The average F-score for the datasets was 94.2 %, indicating that this research provides a new paradigm for extracting tunnel ETS.

Trauma-induced osteonecrosis of the femoral head (TI-ONFH) is a pathological process in which the destruction of blood vessels supplying blood to the femoral head causes the death of bone tissue cells. Vascular cell adhesion molecule 1 (VCAM-1) has been shown to have potent proangiogenic activity, but the role in angiogenesis of TI-ONFH is unclear. In this work, we discovered that VCAM-1 was significantly downregulated in the bone marrow mesenchymal stem cells (BMSCs) derived from patients with TI-ONFH. Subsequently, we constructed BMSCs overexpressing VCAM-1 using a lentiviral vector. VCAM-1 enhances the migration and angiogenesis of BMSCs. We further performed mRNA transcriptome sequencing to explore the mechanisms by which VCAM-1 promotes angiogenesis. Gene ontology biological process enrichment analysis demonstrated that upregulated differentially expressed genes (DEGs) were related to blood vessel development. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that upregulated DEGs were engaged in the Apelin signaling pathway. Apelin-13 is the endogenous ligand of the APJ receptor and activates this G protein-coupled receptor. Treatment with Apelin-13 activated the Apelin signaling pathway and suppressed the expression of cellular communication network factor 2 in BMSCs. Furthermore, Apelin-13 also inhibits the migration and angiogenesis of VCAM-1-BMSCs. In summary, VCAM-1 plays an important role in vascular microcirculation disorders of TI-ONFH, which provides a new direction for the molecular mechanism and treatment of TI-ONFH.

Abstract Background The complications caused by diabetes mellitus (DM) are the focus of clinical treatment. However, little is known about diabetic enteropathy (DE) and its potential underlying mechanism. Methods Intestinal epithelial cells (IECs) and intestinal epithelial stem cells (IESCs) were harvested from BKS.Cg-Dock7m+/+Leprdb/JNju (DM) mice, and the expression of R-Spondin 3 (Rspo3) was detected by RT-qPCR, Western blotting, immunohistochemistry, and immunofluorescence. The role of Rspo3 in the abnormal differentiation of IECs during DM was confirmed by knockdown experiments. Through miRNA expression profiling, bioinformatics analysis, and RT-qPCR, we further analyzed the differentiation-related miRNAs in the IECs from mice with DM. Results Abnormal differentiation of IECs was observed in the mice with DM. The expression of Rspo3 was upregulated in the IECs from the mice with DM. This phenomenon was associated with Rspo3 overexpression. Additionally, Rspo3 is a major determinant of Lgr5+ stem cell identity in the diabetic state. Microarray analysis, bioinformatics analysis, and luciferase reporter assays revealed that microRNA (miR)-380-5p directly targeted Rspo3. Moreover, miR-380-5p upregulation was observed to attenuate the abnormal differentiation of IECs by regulating Rspo3 expression. Conclusions Together, our results provide definitive evidence of the essential role of Rspo3 in the differentiation of IECs in DM.

PurposeTo establish an easy and widely applicable prognostic prediction model for uveal melanoma (UM) based on a Chinese population.Patients and MethodsA total of 295 consecutive cases treated at the Eye & ENT Hospital of Fudan University were included as the primary cohort, and 256 cases were included in the validation cohorts from two external Caucasian databases. Clinicopathological data were collected retrospectively, and nomogram models were formulated based on multivariable analysis. The concordance index (C-index), AUC (area under the Receiver Operating Characteristic, ROC curve), and Brier score were calculated and compared.ResultsBased on the training cohort, a nomogram model was established with five relevant variables: age, tumor size, ciliary body involvement, non-spindle cell type and extra-scleral extension. The C-index was 0.737, the 3- and 5-year AUCs were 0.767 and 0.742, and the Brier scores for 3- and 5-year survival were 0.082 and 0.129, respectively, which showed superior prediction compared to that of the Tumor, Node and Metastasis staging system. The model also displayed good discrimination and calibration in the external validation cohorts. By risk stratification, patients could be divided into low- and high-risk groups, and the overall survival curves displayed significant differences in the training and validation cohorts.ConclusionOur nomogram model was simple and accurate at predicting the overall survival of patients with UM. It was established based on Asian patients and proved suitable for Caucasian patients; thus, it has a wide range of potential applications, especially for patients living in less medically developed countries and regions.

The solar energy supply system has played an increasingly substantial role in realizing nearly zero-carbon buildings. In order to overcome the impact of solar randomness on the energy supply of a distributed solar system, this paper proposes a solar tri-generation supply system which integrates a photovoltaic/thermal collector (PV/T), a heat pump (HP), and an absorption chiller (AC). The PV/T-HP integration system is adopted to provide stable heating for a building and AC. The system model is established in TRNSYS software, and its performance is evaluated based on energy, exergy, and economic aspects. The results demonstrate that the system effectively meets the load demand, with an energy efficiency of 32.98% and an exergy efficiency of 17.62%. The payback period (PP) is 7.77 years. Compared with the systems proposed in the other literature, the performance of the proposed system has a certain extent of advantage. Furthermore, the equipment and system exergy performance decline with an increase in the intensity of solar radiation. Increasing the PV/T area effectively improves the system’s profitability within the actual roof area limitation of the building. Moreover, increasing the capacity of the low-temperature heat pump after 68 kW improves the system efficiency and reduces the payback period. In summary, this paper proposes an efficient distributed solar energy system that is suitable for urban building energy supply.

The study focuses on the performance comparison of solar single-axis tracking low-concentration photovoltaic/thermal (LCPV/T) system with different axes. The axes of the single-axis tracking LCPV/T systems are arranged along the east-west (EW) axis, north-south (NS) axis, and south-east 18° (SE-18°) axis, respectively. The thermal performance of the single-axis tracking system with different axes is discussed through simulated and experimental methods. Simulation study shows that the EW tracking system receives the highest amount of radiation and produced highest electrical energy throughout the year. The experimental research demonstrates that low-concentrating technology significantly improves the performance of the system. Chiefly, the overall thermal efficiency maintains between 50%-70%, and the maximum thermal efficiency achieved in the experiment reaches 68%. The average overall efficiency and exergy efficiency of the NS axis, EW axis and SE-18° axis are 59% and 20%, 64% and 23%, 59% and 20%, respectively. Both the energy and exergy performance of the EW axis is better than the other two axes. The placement of the axis has a significant impact on the thermal and electrical performance of the LCPV/T system. Consequently, the combination of low-concentrating and single-axis tracking technologies has an excellent prospect in practical application.

Abstract The organic Rankine cycle is an effective way to recover low‐temperature waste heat, and a mixture working fluid can effectively improve the performance of the organic Rankine cycle. In order to find the best pure and mixture working fluid quickly and accurately, thirteen pure working fluids and zeotropic mixtures of two of those fluids are selected to study the performance of the organic Rankine cycle, and the net power output is selected as the objective function. Through calculation and analysis, the best pinch temperature difference and evaporation temperature are determined. By calculating the approximate net power output, we find that the parameter (k·Δs5‐1)−1, which is determined by the physical properties of a working fluid, plays an important role in the pure working fluid optimization. In addition, the condensation temperature glide and (k·Δs5‐1)−1 together determine the optimized binary zeotropic mixture. As a result, R227ea and R227ea/hexane (0.98/0.02) are shown to be the optimal pure working fluid and binary zeotropic mixture. Using this mixture resulted in a net power output of 424.63 kW, which is 29.3% higher than that of the pure working fluid R227ea.

Sentiment affects every aspect of people's lives and has strong impact on their mental health. This paper explores local users' sentiments extracted from Geo-tweets data from January to December 2016, analyzed in the spatial and temporal perspective. Because of large amount of noisy data and complicated procedure of extracting local user, a workflow is created, facilitating more researchers to reproduce, replicate or extend the procedures using similar Geo-tweet dataset. The workflow is sharing at Harvard Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/6N9VUF). Using the processed data, each tweet's sentiment is classified according to the content. Then, the overall temporal variations of total number of positive, neural, and negative sentiments are analyzed on a monthly, daily and hourly level. From a spatial perspective, the Local Indicators of Spatial Association (LISA) statistical method is employed to discover the spatial clusters. In order to explore the content of positive sentiments, this paper applies the Latent Dirichlet Allocation (LDA) model to classify the Geo-tweets with positive sentiments into different topics. Combining the geospatial information with the topics, some patterns are found which demonstrate the associations between the nature of Twitter content and the characteristics of places and users. For example, weekend events and friend and family gatherings are the time that users prefer to post positive tweets. In the western part of US, users tend to post more photos to share the great moment on Twitter than other parts of the US.

The obtainment of road condition information during driving is extremely important for a driver. However, drivers usually cannot notice multiple information at the same time, which definitely increases certain safety risks. Considering this problem, this paper designs a road information collection plus alarm system based on artificial intelligence to monitor road information. The underlying core algorithm of this system adopts the YOLO v3 network with the best comprehensive detection performance in the end-to-end network. We use this network's advantage of fast detection speed to optimize on its original basis, and propose to “copy” part of the backbone network to build an auxiliary network, which enhances its feature extraction capability. Further, we apply the attention mechanism to the feature information fusion of the auxiliary network and the backbone network, suppress the invalid information channel, and improve the network processing efficiency. Besides, the training part of the network is optimized, and the mAP (mean Average Precision) is improved by setting the scale that meets the target to be detected. Through the test, the average test accuracy of the optimized network model reaches 84.76%, and the real-time detection speed on the 2080Ti reaches 41FPS. Compared with the previous network, the detection accuracy increases by 5.43% after optimization.

BackgroundPatient portals are a safe and secure way for patients to connect with providers for video-based telepsychiatry and help to overcome the financial and logistical barriers associated with face-to-face mental health care. Due to the COVID-19 pandemic, telepsychiatry has become increasingly important to obtaining mental health care. However, financial and technological barriers, termed the “digital divide,” prevent some patients from accessing the technology needed to use telepsychiatry services. ObjectiveAs an extension to a clinic’s outreach project during COVID-19 to improve patient engagement with video-based visits through the hospital’s patient portal among adult behavioral health patients at an urban safety net hospital, we aim to assess patient preference for patient portal–based video visits or telephone-only visits and to identify the demographic variables associated with their preference. MethodsPatients in an outpatient psychiatry clinic were contacted by phone, and preference for telepsychiatry by phone or video through a patient portal, as well as device preference for video-based visits, were documented. Patient demographic characteristics were collected from the electronic medical record. ResultsA total of 128 patients were reached by phone. A total of 79 (61.7%) patients chose video-based visits, and 69.6% (n=55) of these patients preferred to access the patient portal through a smartphone. Older patients were significantly less likely to agree to video-based visits. ConclusionsAmong behavioral health patients at a safety net hospital, there was relatively low engagement with video-based visits through the hospital’s patient portal, particularly among older adults.

Soybean pubescence plays an important role in insect resistance, drought tolerance, and other stresses. Hence, a deep understanding of the molecular mechanism underlying pubescence is a prerequisite to a deeper understanding of insect resistance and drought tolerance. In the present study, quantitative trait loci (QTL) mapping of pubescence traits was performed using a high-density inter-specific linkage map of one recombinant inbred line (RIL) population, designated NJRINP. It was observed that pubescence length (PL) was negatively correlated with pubescence density (PD). A total of 10 and 9 QTLs distributed on six and five chromosomes were identified with phenotypic variance (PV) of 3.0–9.9% and 0.8–15.8% for PL and PD, respectively, out of which, eight and five were novel. Most decreased PL (8 of 10) and increased PD (8 of 9) alleles were from the wild soybean PI 342618B. Based on gene annotation, Protein ANalysis THrough Evolutionary Relationships and literature search, 21 and 12 candidate genes were identified related to PL and PD, respectively. In addition, Glyma.12G187200 from major QTLs qPL-12-1 and qPD-12-2, was identified as Ps (sparse pubescence) before, having an expression level of fivefold greater in NN 86-4 than in PI 342618B, hence it might be the candidate gene that is conferring both PL and PD. Based on gene expression and cluster analysis, three and four genes were considered as the important candidate genes of PL and PD, respectively. Besides, leaves with short and dense (SD) pubescence, which are similar to the wild soybean pubescence morphology, had the highest resistance to common cutworm (CCW) in soybean. In conclusion, the findings in the present study provide a better understanding of genetic basis and candidate genes information of PL and PD and the relationship with resistance to CCW in soybean.

With the high proportion of renewable energy connected to the grid, peak shaving demand surge, which needs to enhance the flexibility of coal power with a larger proportion to support the stable operation of the grid. At present, the capacity of the combined heat and power unit accounts for about 87 % of direct dispatching coal-fired power plants by Shandong power grid. The flexible operation ability of the combined heat and power unit is poor, and its flexible transformation is urgent. This paper summarizes the current relatively mature flexibility transformation technology of combined heat and power unit, including low pressure cylinder zero output transformation (cylinder cutting transformation), bypass load regulation, thermal energy storage and electrical energy storage transformation technology, and puts forward to encourage the flexibility transformation of in-service combined heat and power unit, and actively promote the research and application of the intelligent heating network, the integration of thermal and electricity, and the clean heating construction and clean heating technology.

This paper introduces the total heating capacity, total installed capacity, heating area change trend and unit transformation of direct regulating heating units in Shandong power grid in recent years. According to the operation data of condensing pumping units, back pressure heating units and cylinder cutting units in previous heating seasons, the heating and peak shaving performance of different types of cogeneration units of the same type, grade and grade in heating seasons are analyzed, It is convenient for the power grid dispatching department to more reasonably and orderly arrange the unit mediation plan of the province's thermal power plants according to the online situation of new energy and external power. At the same time, it is a reference for power generation enterprises to carry out flexible transformation according to the actual situation of units during the 14th Five Year Plan period, and take into account the low load peak shaving performance of units or the whole plant while increasing heating capacity.

This paper introduces the technical route of the zero output heat supply transformation of low pressure cylinders in Shandong Province, the operation after the transformation, the impact on power grid dispatching, and the constraints on the normal operation of some units after the transformation, providing technical support for power generation enterprises to accurately implement the “three transformation linkage” transformation scheme and the accurate dispatching of the power dispatching center

Surface reconstruction from a 3D point cloud is a long-standing problem in the field of computer graphics and vision, especially for point clouds that are sparse and noisy. To solve this problem, a novel method, termed LV-GCNN, that combines lossless voxelization and a graph convolutional neural network is proposed in this paper. Firstly, a lossless voxelization method for point clouds, which achieves lossless conversion from disordered point clouds to ordered volumetric maps, is proposed. Secondly, with the generated voxel, the feature pyramid is extracted through a 3D convolutional neural network. Thirdly, based on the similarity between the graph and surface mesh, the graph neural network is initialized as a unit spherical mesh. The coordinate relationship between the graph vertices and feature voxel units is used to match the corresponding hierarchical features for graph vertices. The initial spherical mesh is progressively deformed and upsampled via graph convolution and graph unpooling to achieve coarse-to-fine optimization of the surface mesh. Finally, because the deformation-based approach cannot reconstruct objects with a genus greater than zero, a genus optimization method is designed. Experiments show that the surface meshes generated by the LV-GCNN are comparable to or better than the results of state-of-the-art methods under several evaluation criteria. In addition, the reconstruction effect under different situations is discussed. Ablation experiments show the importance of several applied modules in LV-GCNN. Extra experiments show that the proposed method can achieve impressive results for point sets with diverse densities or that contain different levels of noise. The LV-GCNN results outperform other methods when the input point cloud is exceptionally sparse (256 points) or contains Gaussian noise with a standard deviation of 0.05. The chamfer distance (CD), Hausdorff distance (HD), voxel difference (VD), and depth difference (DD) of the reconstruction results of the LV-GCNN are 0.0494, 0.1457, 0.7390, and 18,402 when 256 points are used as input and are 0.0654, 0.1582, 0.6735, and 21,150 when points with noise with a standard deviation of 0.05 are used as input.

Whether for institutional investors or individual investors, there is an urgent need to explore autonomous models that can adapt to the non-stationary, low-signal-to-noise markets. This research aims to explore the two unique challenges in quantitative portfolio management: (1) the difficulty of representation and (2) the complexity of environments. In this research, we suggest a Markov decision process model-based deep reinforcement learning model including deep learning methods to perform strategy optimization, called SwanTrader. To achieve better decisions of the portfolio-management process from two different perspectives, i.e., the temporal patterns analysis and robustness information capture based on market observations, we suggest an optimal deep learning network in our model that incorporates a stacked sparse denoising autoencoder (SSDAE) and a long–short-term-memory-based autoencoder (LSTM-AE). The findings in times of COVID-19 show that the suggested model using two deep learning models gives better results with an alluring performance profile in comparison with four standard machine learning models and two state-of-the-art reinforcement learning models in terms of Sharpe ratio, Calmar ratio, and beta and alpha values. Furthermore, we analyzed which deep learning models and reward functions were most effective in optimizing the agent’s management decisions. The results of our suggested model for investors can assist in reducing the risk of investment loss as well as help them to make sound decisions.

The moment magnitude (Mw) 6.4 and 7.1 Ridgecrest earthquake sequence that occurred on July 4 and 6, 2019, ruptured a conjugate fault system within the eastern California shear zone. In addition to the ∼50 km surface ruptures, the sequence activated a series of structures with lengths ranging from 1 to 10 km, which are well illuminated by phase gradient maps of Synthetic Aperture Radar (SAR) interferograms. The deformation patterns and mechanisms of these fractures have been well studied, yet the controlling factors of their spatial distribution are less discussed, which are important for understanding how the accumulated strain is released via distributed faulting in the earthquake cycle. Here, we use multi-source SAR images to derive three-dimensional (3D) surface displacement along the main ruptures and the east–west strain across the detected small fractures caused by the 2019 Ridgecrest earthquake sequence. We find that the distribution of these fractures is related to the displacement pattern along the main rupture. Specifically, more fractures appeared in areas with larger slips normal to the main rupture as well as in the junction of the conjugated ruptures. We also conduct uniaxial loading rock experiments to evaluate the strain distribution before the samples were broken. Rock experiments show that rupturing of a conjugated fault system may produce local strain concentration along the main rupture, indicating the important role of the orthogonal faults in generating small fractures with different striking angles and deformation patterns. The 2019 Ridgecrest earthquake sequence exhibits complicated crust behaviors by rupturing an immature fault system, implying that the simple elastic rebound theory may be insufficient to model the coseismic deformation during the earthquake cycle, particularly in the zone with weak crust.

AIM: To detect how BRCA-associated protein 1 (BAP1) regulates cell migration in uveal melanoma (UM) cells. METHODS: Wound healing and transwell assays were performed to detect UM cell migration abilities. Protein chip, immunoprecipitations and surface plasmon resonance analyses were applied to identify BAP1 protein partners. Western blot and calpain activity assays were used to test the expression and function of calpastatin (CAST). RESULTS: CAST protein was confirmed as a new BAP1 protein partner, and loss of BAP1 reduced the expression and function of CAST in UM cells. The overexpression of CAST rescued the cell migration phenotype caused by BAP1 loss. CONCLUSION: BAP1 interacts with CAST in UM cells, and CAST and its subsequent calpain pathway may mediate BAP1-related cell migration regulation.

With the development of artificial intelligence technology, the demand for new digital security and privacy solutions is growing importantly. Inspired by the synaptic pruning in mammalian brains, we develop a network pruning method, called dynamic network pruning (DNP) method, which reduces the necessary number of free parameters in the convolutional neural networks. The DNP can be perfectly integrated with the gradient descent training and performed at any point, even multiple times, during training. We show that the pruning of connections (filters) is more intrinsic than the pruning of neurons (channels), and we relate the significance of filters to the dispersion of their values. With our proposed weight initialization technique, called smooth initialization (SI), unimportant filters can be easily identified based on the simple thresholds. The DNP method does not need pre-training to learn the connectivity of the network nor requires a very long time of fine-tuning to restore the performance. The DNP can also lead to better data privacy under distributed environment due to improved learning efficiency and convergency. The experiments show that our method outmatches several weight reduction methods in terms of reduction ratio and test accuracy on various models and datasets, and the generalization abilities of the pruned models are not damaged.