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Purpose: This study aimed to determine the therapeutic effectiveness of different machines in intense pulsed light (IPL) treatment of meibomian gland dysfunction (MGD). Methods: 213 subjects diagnosed with MGD underwent three sessions of IPL treatment in a control (M22) treatment group or experimental (OPL-I) treatment group and were followed up three to four weeks after each session. Tear breakup time (TBUT), meibomian gland secretion scores (MGSS), meibomian gland meibum scores (MGMS), corneal fluorescein staining (CFS) scores, and the Standard Patient Evaluation of Eye Dryness (SPEED) was used to assess eye dryness signs and symptoms at baseline and follow-up visits. Results: Two machines had the same working principles except that experimental (OPL-I) group consist of a dual filter system. Both groups showed significant improvements (P ​

Abstract Fungal diseases are the main factors affecting the quality and production of vegetables. Rapid and accurate detection of pathogenic spores is of great practical significance for early prediction and prevention of diseases. However, there are some problems with microscopic images collected in the natural environment, such as complex backgrounds, more disturbing materials, small size of spores, and various forms. Therefore, this study proposed an improved detection method of GCS-YOLOv8 (Global context and CARFAE and Small detector-optimized YOLOv8), effectively improving the detection accuracy of small-target pathogen spores in natural scenes. Firstly, by adding a small target detection layer in the network, the network’s sensitivity to small targets is enhanced, and the problem of low detection accuracy of the small target is effectively improved. Secondly, Global Context attention is introduced in Backbone to optimize the CSPDarknet53 to 2-Stage FPN (C2F) module and model global context information. At the same time, the feature up-sampling module Content-Aware Reassembly of Features (CARAFE) was introduced into Neck to enhance the ability of the network to extract spore features in natural scenes further. Finally, we used an Explainable Artificial Intelligence (XAI) approach to interpret the model’s predictions. The experimental results showed that the improved GCS-YOLOv8 model could detect the spores of the three fungi with an accuracy of 0.926 and a model size of 22.8 MB, which was significantly superior to the existing model and showed good robustness under different brightness conditions. The test on the microscopic images of the infection structure of cucumber down mildew also proved that the model had good generalization. Therefore, this study realized the accurate detection of pathogen spores in natural scenes and provided feasible technical support for early predicting and preventing fungal diseases.

Abstract Background The survival benefit of venovenous extracorporeal membrane oxygenation (VV-ECMO) in adult patients with severe acute respiratory distress syndrome (ARDS) remains controversial. This study aimed to investigate the efficiency and potential prognostic factors of VV-ECMO for severe ARDS in adults by evaluating our institutional experience and results. Materials and methods This research studied ARDS patients receiving VV-ECMO between June 2011 and May 2023. The inclusion criteria were PaO2/FiO2

Modeling dynamic interactions among network components is crucial to uncovering the evolution mechanisms of complex networks. Recently, spatio-temporal graph learning methods have achieved noteworthy results in characterizing the dynamic changes of inter-node relations (INRs). However, challenges remain: The spatial neighborhood of an INR is underexploited, and the spatio-temporal dependencies in INRs’ dynamic changes are overlooked, ignoring the influence of historical states and local information. In addition, the model’s explainability has been understudied. To address these issues, we propose an explainable spatio-temporal graph evolution learning (ESTGEL) model to model the dynamic evolution of INRs. Specifically, an edge attention module is proposed to utilize the spatial neighborhood of an INR at multi-level, i.e., a hierarchy of nested subgraphs derived from decomposing the initial node-relation graph. Subsequently, a dynamic relation learning module is proposed to capture the spatio-temporal dependencies of INRs. The INRs are then used as adjacent information to improve the node representation, resulting in comprehensive delineation of dynamic evolution of the network. Finally, the approach is validated with real data on brain development study. Experimental results on dynamic brain networks analysis reveal that brain functional networks transition from dispersed to more convergent and modular structures throughout development. Significant changes are observed in the dynamic functional connectivity (dFC) associated with functions including emotional control, decision-making, and language processing.

BackgroundThe emergence of nanotechnology has injected new vigor into vaccine research. Nanovaccine research has witnessed exponential growth in recent years; yet, a comprehensive analysis of related publications has been notably absent.ObjectiveThis study utilizes bibliometric methodologies to reveal the evolution of themes and the distribution of nanovaccine research.MethodsUsing tools such as VOSviewer, CiteSpace, Scimago Graphica, Pajek, R-bibliometrix, and R packages for the bibliometric analysis and visualization of literature retrieved from the Web of Science database.ResultsNanovaccine research commenced in 1981. The publication volume exponentially increased, notably in 2021. Leading contributors include the United States, the Chinese Academy of Sciences, the “Vaccine”, and researcher Zhao Kai. Other significant contributors comprise China, the University of California, San Diego, Veronique Preat, the Journal of Controlled Release, and the National Natural Science Foundation of China. The USA functions as a central hub for international cooperation. Financial support plays a pivotal role in driving research advancements. Key themes in highly cited articles include vaccine carrier design, cancer vaccines, nanomaterial properties, and COVID-19 vaccines. Among 7402 keywords, the principal nanocarriers include Chitosan, virus-like particles, gold nanoparticles, PLGA, and lipid nanoparticles. Nanovaccine is primarily intended to address diseases including SARS-CoV-2, cancer, influenza, and HIV. Clustering analysis of co-citation networks identifies 9 primary clusters, vividly illustrating the evolution of research themes over different periods. Co-citation bursts indicate that cancer vaccines, COVID-19 vaccines, and mRNA vaccines are pivotal areas of focus for current and future research in nanovaccines. “candidate vaccines,” “protein nanoparticle,” “cationic lipids,” “ionizable lipids,” “machine learning,” “long-term storage,” “personalized cancer vaccines,” “neoantigens,” “outer membrane vesicles,” “in situ nanovaccine,” and “biomimetic nanotechnologies” stand out as research interest.ConclusionsThis analysis emphasizes the increasing scholarly interest in nanovaccine research and highlights pivotal recent research themes such as cancer and COVID-19 vaccines, with lipid nanoparticle-mRNA vaccines leading novel research directions.

Objective: In order to solve the problem of manual weighting of dragon fruit, including time-consuming, laborious and expensive, an automated weight estimation method based on machine vision and machine learning was proposed in this research. Methods: Firstly, 106 dragon fruits were weighed, recorded and photographed, and images of dragon fruits were constructed. Secondly, binary images were obtained after denoising and segmentation. Moreover, the three features of pixel area, major axis pixel length and minor axis pixel length of dragon fruits were extracted on the basis of binary images. The three features of each image and their corresponding weights were combined into a set of data, which was divided into training set and test set according to the ratio of 7∶3. Finally, the training set was input into the Gradient Boosting, Random Forest, K-Neighbors and Artificial Neural Networks machine-learning models for training, and the test sets were used for model evaluation. Results: The evaluation index of the Artificial Neural network performed well compared with other models, with R2 of 0.986 and RMSE of 13.091. Conclusion: The experimental result demonstrates that the method proposed in this research can accomplish the weight estimation of dragon fruit effectively, and meet the weight estimation requirements of dragon fruit.

We investigate the impact of industry information disclosure (IID) on audit quality in Chinese listed companies from 2010 to 2021, by constructing a staggered difference-in-differences model based on the implementation of the IID guidelines in the Shanghai and Shenzhen stock exchanges in 2013 as an exogenous shock. Audit quality is significantly improved after the implementation of the IID guidelines. We also use a parallel trend test, different measurements of key variables, propensity score matching, a placebo test and different samples, to ensure the validity of our findings. IID enhances audit quality by improving auditor independence, professionalism and audit engagement, particularly in firms with high-quality and numerous IIDs, high auditor rankings, strong auditor industry expertise, IIDs with a negative tone and low R&D investment. We demonstrate the effectiveness of the IID guidelines from the perspective of auditing.

Abstract A precise Arctic surface air temperature (SAT) dataset, that is regularly updated, has more complete spatial and temporal coverage, and is based on instrumental observations, is critically important for timely monitoring and improving understanding of the rapid change in the Arctic climate. In this study, a new monthly gridded Arctic SAT dataset dated back to 1979 was reconstructed with a deep learning method by combining surface air temperatures from multiple data sources. The source data include the observations from land station of GHCN (Global Historical Climatology Network), ICOADS (International Comprehensive Ocean-Atmosphere Data Set) over the oceans, drifting ice station of Russian NP (North Pole), and buoys of IABP (International Arctic Buoy Programme). The last two are crucial for improving the representation of the in-situ observed temperatures within the Arctic. The newly reconstructed dataset includes monthly Arctic SAT beginning in 1979 and daily Arctic SAT beginning in 2011. This dataset would represent a new improvement in developing observational temperature datasets and can be used for a variety of applications.

RNA velocity can detect the differentiation directionality by modelling sparse unspliced RNAs, but suffers from high estimation errors. Here, the authors develop a computational method called UniTVelo to reinforce the velocity estimation by introducing a unified time and a top-down model design.

Dragon fruit detection in natural environment is the prerequisite for fruit harvesting robots to perform harvesting. In order to improve the harvesting efficiency, by improving YOLOX (You Only Look Once X) network, a target detection network with an attention module was proposed in this research. As the benchmark, YOLOX-Nano network was chose to facilitate deployment on embedded devices, and the convolutional block attention module (CBAM) was added to the backbone feature extraction network of YOLOX-Nano, which improved the robustness of the model to dragon fruit target detection to a certain extent. The correlation of features between different channels was learned by weight allocation coefficients of features of different scales, which were extracted for the backbone network. Moreover, the transmission of deep information of network structure was strengthened, which aimed at reducing the interference of dragon fruit recognition in the natural environment as well as improving the accuracy and speed of detection significantly. The performance evaluation and comparison test of the method were carried out. The results showed that, after training, the dragon fruit target detection network got an AP0.5 value of 98.9% in the test set, an AP0.5:0.95 value of 72.4% and F1 score was 0.99. Compared with other YOLO network models under the same experimental conditions, on the one hand, the improved YOLOX-Nano network model proposed in this research was more lightweight, on the other hand, the detection accuracy of this method surpassed that of YOLOv3, YOLOv4 and YOLOv5 respectively. The average detection accuracy of the improved YOLOX-Nano target detection network was the highest, reaching 98.9%, 26.2% higher than YOLOv3, 9.8% points higher than YOLOv4-Tiny, and 7.9% points higher than YOLOv5-S. Finally, real-time tests were performed on videos with different input resolutions. The improved YOLOX-Nano target detection network proposed in this research had an average detection time of 21.72 ms for a single image. In terms of the size of the network model was only 3.76 MB, which was convenient for deployment on embedded devices. In conclusion, not only did the improved YOLOX-Nano target detection network model accurately detect dragon fruit under different lighting and occlusion conditions, but the detection speed and detection accuracy showed in this research could able to meet the requirements of dragon fruit harvesting in natural environment requirements at the same time, which could provide some guidance for the design of the dragon fruit harvesting robot.

IntroductionMonitoring the response after treatment of liver cancer and timely adjusting the treatment strategy are crucial to improve the survival rate of liver cancer. At present, the clinical monitoring of liver cancer after treatment is mainly based on serum markers and imaging. Morphological evaluation has limitations, such as the inability to measure small tumors and the poor repeatability of measurement, which is not applicable to cancer evaluation after immunotherapy or targeted treatment. The determination of serum markers is greatly affected by the environment and cannot accurately evaluate the prognosis. With the development of single cell sequencing technology, a large number of immune cell-specific genes have been identified. Immune cells and microenvironment play an important role in the process of prognosis. We speculate that the expression changes of immune cell-specific genes can indicate the process of prognosis.MethodTherefore, this paper first screened out the immune cell-specific genes related to liver cancer, and then built a deep learning model based on the expression of these genes to predict metastasis and the survival time of liver cancer patients. We verified and compared the model on the data set of 372 patients with liver cancer.ResultThe experiments found that our model is significantly superior to other methods, and can accurately identify whether liver cancer patients have metastasis and predict the survival time of liver cancer patients according to the expression of immune cell-specific genes.DiscussionWe found these immune cell-specific genes participant multiple cancer-related pathways. We fully explored the function of these genes, which would support the development of immunotherapy for liver cancer.

Abstract Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease. Current gold standard criteria, pulmonary function tests (PFTs) may result in underdiagnosis of potential COPD patients. Therefore, we hypothesize that the combination of high-resolution computed tomography (HRCT) and clinical basic characteristics will enable the identification of more COPD patients. Methods A total of 284 patients with respiratory symptoms who were current or former smokers were included in the study, and were further divided into 5 groups of GOLD grade I–IV and non-COPD according to PFTs. All patients underwent inspiratory HRCT scanning and low attenuation area (LAA) was measured. Then they were divided into seven visual subtypes according to the Fleischner Society classification system. Non-parametric tests were used for exploring differences in basic characteristics and PFTs between different groups of enrolled patients and visual subtypes. Binary logistic regression was to find the influencing factors that affected the patients’ outcome (non-COPD vs GOLD I-IV). The area under the receiver operating characteristic curve (AUC-ROC) was to explore the diagnostic efficacy of LAA, visual subtypes, and combined basic characteristics related to COPD for COPD diagnosis. Finally, based on the cut-off values of ROC analysis, exploring HRCT features in patients who do not meet the diagnostic criteria but clinically suspected COPD. Results With the worsening severity of COPD, the visual subtypes gradually progressed (p

Mitochondrial variants are informative endogenous barcodes for clonal substructure. Here, the authors developed a computational method MQuad to effectively detect these clonal informed mtDNA variants from single-cell RNA, DNA or ATAC sequencing data.

Active site exposure and intrinsic catalytic performance are considered important aspects of oxygen evolution reaction catalyst design. In this work, the coordination capacity of tributylphosphine is utilized to construct cationic vacancy defects on NiFe-LDH nanosheets. As-prepared defective NiFe-LDH nanosheets show not only the optimization of the exposure ability of the active site but also the intrinsic catalytic capacity is improved by construction of cationic vacancy defect to tune local electronic structure. The x-ray photoelectron spectroscopy results revealed that after reconstruction of the prepared d-NiFe-LDH, high-valence Ni and Fe can stably appear on the surface of the material. The presence of high-valence Ni and Fe is considered to be the main reason to improve the intrinsic catalytic capacity of catalysts. Finally, d-NiFe-LDH nanosheets show excellent catalytic performance (η10 = 243 mV) and remarkable long-term stability.

Rapid and accurate detection of pathogen spores is an important step to achieve early diagnosis of diseases in precision agriculture. Traditional detection methods are time-consuming, laborious, and subjective, and image processing methods mainly rely on manually designed features that are difficult to cope with pathogen spore detection in complex scenes. Therefore, an MG-YOLO detection algorithm (Multi-head self-attention and Ghost-optimized YOLO) is proposed to detect gray mold spores rapidly. Firstly, Multi-head self-attention is introduced in the backbone to capture the global information of the pathogen spores. Secondly, we combine weighted Bidirectional Feature Pyramid Network (BiFPN) to fuse multiscale features of different layers. Then, a lightweight network is used to construct GhostCSP to optimize the neck part. Cucumber gray mold spores are used as the study object. The experimental results show that the improved MG-YOLO model achieves an accuracy of 0.983 for detecting gray mold spores and takes 0.009 s per image, which is significantly better than the state-of-the-art model. The visualization of the detection results shows that MG-YOLO effectively solves the detection of spores in blurred, small targets, multimorphology, and high-density scenes. Meanwhile, compared with the YOLOv5 model, the detection accuracy of the improved model is improved by 6.8%. It can meet the demand for high-precision detection of spores and provides a novel method to enhance the objectivity of pathogen spore detection.

Abstract Introduction Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive loss of dopaminergic (DA) neurons. Accumulating evidence has shown that activation of the NLR family pyrin domain‐containing 3 (NLRP3) inflammasome is an early and cardinal feature in PD progression. Nevertheless, little is known about the effect of NLRP3 in the substantia nigra pars compacta (SNc) on DA neurodegeneration. Methods and results In the present study, we constructed NLRP3 interference sequences wrapped by lentivirus (LV3‐siNlrp3) to facilitate NLRP3 knockdown in the SNc region by intracerebral stereotactic injection. Then, we explored the effects of NLPR3 knockdown on PD pathologies via behavioral monitoring, immunohistochemistry and western blot analysis in acute 1‐methyl‐4‐phenyl‐1, 2, 3, 6‐tetrahydropyridine (MPTP) mouse model. Moreover, we performed in vitro experiments to investigate the effect of microglial NLRP3 knockdown on DA neuron survival in the context of 1‐methyl‐4‐phenylpyridinium (MPP+) stimulation. Our results demonstrated that NLRP3 knockdown in the SNc region significantly improved MPTP‐induced dyskinesia, DA neuronal loss and microglia activation in vivo. Meanwhile, knockdown of microglial NLRP3 attenuated MPP+‐induced DA neuronal damage in an indirect coculture system in which neurons were cultured in microglial conditional medium. Cumulatively, these data reveal that microglial NLRP3 located in the SNc region is detrimental to DA neurons survival, and knockdown of microglial NLRP3 is a potential strategy to rescue DA neurons in the progression of PD. Conclusions This work demonstrates the role of NLRP3 in PD pathogenesis via microglia‐neuron communication, and sheds light on targeting microglial NLRP3 to develop disease‐modifying therapy for PD.

AIM: To detect the expression of miR-486-3p in human pterygium tissue and normal conjunctival tissue and explore the possible mechanism of miR-486-3p in the development of pterygium. METHODS: Totally 69 patients 69 eyes with primary pterygium treat in Zhongnan Hospital of Wuhan University and Hankou Aier Eye Hospital from September 2018 to December 2019 were collected by excision of pterygium during surgery(experimental group). At the same time, a total of 69 patients with normal conjunctival tissue of their same eyes were taken as control group during surgery. The relative expression levels of miR-486-3p in the experimental group and the control group were quantitatively detected by RT-PCR. The Targetscan database, miWalk3.0 database and miRDB database were used to predict the potential target genes of miR-486-3p. DAVID database was used to analyse and enrich the function and pathway of the potential target genes of miR-486-3p. The String website performed an interactional analysis of the potential target genes of miR-486-3p. RESULTS: The relative expression level of miR-486-3p in the experimental group(6.183±1.366)×10-6 was significantly different from that in the control group(7.930±1.394)×10-5(P

Abstract Stem cell niche is regulated by intrinsic and extrinsic factors. In the Drosophila testis, cyst stem cells (CySCs) support the differentiation of germline stem cells (GSCs). However, the underlying mechanisms remain unclear. In this study, we found that somatic CG6015 is required for CySC maintenance and GSC differentiation in a Drosophila model. Knockdown of CG6015 in CySCs caused aberrant activation of dpERK in undifferentiated germ cells in the Drosophila testis, and disruption of key downstream targets of EGFR signaling (Dsor1 and rl) in CySCs results in a phenotype resembling that of CG6015 knockdown. CG6015, Dsor1, and rl are essential for the survival of Drosophila cell line Schneider 2 (S2) cells. Our data showed that somatic CG6015 regulates CySC maintenance and GSC differentiation via EGFR signaling, and inhibits aberrant activation of germline dpERK signals. These findings indicate regulatory mechanisms of stem cell niche homeostasis in the Drosophila testis.

The study of multi-field coupling of rocks is currently a pressing and difficult problem at present. To better analyze the interaction mechanism of rocks under of multi-field coupling, research is mainly carried out by experiment and numerical simulation. On the basis of summarizing the research and development of multi-field coupling micro-meso-macro multi-scale mechanical test equipment at home and abroad, and the developments of numerical simulation software and coupling calculation program, the development direction of rock mechanical test equipment and numerical analysis under multi field and multi-phase coupling are prospected. To study the mechanical properties of rocks under multi-field coupling, a multi-field coupling test system with different physical fields was designed by improvement through research and development. Based on the development of the test equipment, modern non-destructive detection methods, such as real-time computed tomography (CT) scanning technology, scanning electron microscopy (SEM), nuclear magnetic resonance imaging (NMRI), X-ray stereo imaging and ultrasonography, were developed. Acoustic wave technology can not only nondestructively detect the micro-structure and evolution process of rock internal pores, but also clarify the macro-relationship of rock physical fields in the multi-field coupling action of thermal-hydrological-mechanical-chemical (THMC), and further clarify the rock performance under multi-field coupling action from the perspective of a combination of micro and macro scales. With the advancement of computer technology, the development of numerical simulation software and coupling calculation program under multi-field coupling of rock has made certain progress. Especially, the development of the numerical simulation software of THMC four-field coupling interaction combined with TOUGHREACT and FLAC3D, and the multi-field coupling calculation program of Comsol docking with MATLAB provide technical supports for the development of multi-field coupling simulation of rocks. Finally, the key difficulties and future research directions of rock multi-field coupling research were discussed and analyzed, which can provide a reference for engineering practice and related problems.

Hydrogen sulfide (H2S) is regarded to be a protectant against diseases of the central nervous system and cardiovascular system. However, the mechanism by which H2S elicits neuroprotective effects in the progression of Parkinson’s disease (PD) remains unclear. To investigate the role of H2S in delaying the pathological process of PD, we used the most common sodium hydrosulfide (NaHS) as an H2S donor and established a mouse model of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/probenecid (MPTP/p) in the present study. Our results show that H2S reduced neuronal loss during the progression of PD. Notably, we found that H2S exhibited protective effects on dopaminergic neurons. Excitingly, H2S also increased the proliferation of neural stem cells in the subventricular zone. Next, we evaluated whether the neuroprotective effects of H2S on dopaminergic neurons in PD are dependent on adult nerve regeneration by treating primary adult neural stem cells cultured ex vivo with 1-methyl-4-phenylpyridine. Our results show that H2S could prevent nerve injury induced by 1-methyl-4-phenylpyridine, promote the growth of neurospheres, and promote neurogenesis by regulating Akt/glycogen synthase kinase-3β/β-catenin pathways in adult neural stem cells. These findings confirm that H2S can increase neurogenesis in an adult mouse model of PD by regulating the Akt/glycogen synthase kinase-3β/β-catenin signaling pathway. This study was approved by the Animal Care and Use Committee of Nanjing Medical University, China (IACUC Approval No. 1601153-3).

The study of multi-field coupling of rocks has been carried out for decades, including the effects of single physical field, two-field coupling, and three-field coupling of rocks. However, the occurrence environment of rock mass in deep mining of mineral resources and underground space development is very complex. Thermal–hydrological–mechanical–chemical (THMC) multi-field coupling effect will occur in rock mass under high temperature, high osmotic pressure, high stress, and complex hydrochemical environment. The multi-field coupling of rocks is not the simple superposition of multiple physical fields, but the mutual influence and action of each physical field. The research on fracture evolution, deformation mechanics mechanism, mechanical constitutive and coupling model construction was comprehensively analyzed. Based on the analysis of rock strength theory, the development of a rock multi-field coupling constitutive model and a rock creep constitutive model were obtained. There are some differences in the research focus of multi-field coupling of rocks for different industries. The multi-field coupling of rocks not only involves the development of mineral resources, oil and gas fields, geothermal resources and other resources and energy fields, but also water conservancy and hydropower engineering, alpine engineering, underground engineering, underground nuclear waste disposal, and deep buried energy storage. Under the action of high stress, seepage, high temperature and chemical action, not only will the coupling effect occur, but the physical and mechanical properties of rock itself will be affected. It is of great practical significance to analyze and study the mechanical properties of rocks under the action of multi-field coupling for preventing accidents and ensuring engineering safety. Finally, the key and difficult points of rock multi field coupling research and the direction of future research were discussed, which provides a reference for engineering practice and related problems.

Abstract Background Recently, it has been reported that miRNA is involved in pterygium, however the exact underlying mechanism in pterygium is unrevealed and require further investigation. Methods The differential expression of miRNA in pterygium was profiled using microarray and validated with quantitative real-time polymerase chain reaction (qRT-PCR). Human conjunctival epithelial cells (HCEs) were cultured and treated with transforming growth factor β (TGF-β) and epidermal growth factor (EGF) and transfected with miR-199a-3p/5p mimic and inhibitor. Markers of epithelial-mesenchymal transition (EMT) in HCEs were detected using western blot and immunohistochemistry. Cell migration ability was determined using wound healing and transwell assay, while apoptosis was determined by flow cytometry. The target genes of miR-199a were confirmed by the dual-luciferase reporter assay. Results TGF-β and EGF could induced EMT in HCEs and increase miR-199a-3p/5p but suppress target genes, DUSP5 and MAP3K11. With the occurrence of EMT, cell migration ability was enhanced, and apoptosis was impeded. Promoting miR-199a-3p/5p expression could induce EMT in HCEs without TGF-β and EGF, while suppressing miR-199a-3p/5p could inhibit EMT in TGF-β and EGF induced HCEs. In a word, TGF-β and EGF induced EMT could be regulated with miR-199a-3p/5p-DUSP5/MAP3K11 axes. The validated results in tissues showed that, compared with control conjunctival tissues, miR-199a-3p/5p were more overexpressed in pterygium, while DUSP5/MAP3K11 were lower expressed. In addition, bioinformatics analysis indicated the miR-199a-3p/5p-DUSP5/MAP3K11 was belong to MAPK signalling pathway. Conclusions TGF-β and EGF induce EMT of HCEs through miR-199a-3p/5p-DUSP5/MAP3K11 axes, which explains the pathogenesis of EMT in pterygium and may provide new targets for pterygium prevention and therapy.

Abstract Background Several studies have suggested that drug resistance in colon cancer patients with diabetes may be associated with long‐term insulin administration, which in turn decreases the survival rate. Metformin is a commonly used drug to treat diabetes but has been recently demonstrated to have a potential therapeutic effect on colon cancer. This study aimed to elucidate the underlying mechanism by which metformin reverts insulin‐induced oxaliplatin resistance in human colon cancer HCT116 cells. Methods Two colon cancer cell lines (HCT116 and LoVo) were used to verify whether the expression of insulin receptor substrate 1 (IRS‐1) could impact the half maximal inhibitory concentration (IC50) of oxaliplatin after chronic insulin treatment. The IC50 of oxaliplatin in both cell lines was measured to identify metformin sensitization to oxaliplatin. The adenosine monophosphate‐activated protein kinase (AMPK) inhibitor, namely AMPK small interfering RNA, was used to block AMPK activation to identify critical proteins in the AMPK/Erk signaling pathway. Bcl‐2 is a vital antiapoptotic protein involved in the mitochondrial apoptosis pathway. Finally, immunofluorescence and electron microscopy were performed to investigate how metformin affects the ultrastructural integrity of mitochondria. Results The IC50 of oxaliplatin in HCT116 cells was noticeably increased. After the cells were treated with metformin, oxaliplatin resistance was reversed. According to the results of the western blotting assay of vital proteins involved in the classical apoptosis pathway, cleaved caspase‐9 was noticeably upregulated, suggesting that the mitochondrial apoptosis pathway was activated. These results were verified by imaging of mitochondria using electron microscopy. The AMPK/Erk signaling pathway experiments revealed that the upregulation of Bcl‐2 induced by insulin through Erk phosphorylation was inhibited by metformin and that such inhibition could be mitigated by the inhibition of AMPK. Conclusions Insulin‐induced oxaliplatin resistance was reversed by metformin‐mediated AMPK activation. Accordingly, metformin is likely to sensitize patients with diabetes to chemotherapeutic drugs used to treat colon cancer.

The recent blackout in UK indicates that the adequacy of flexible resources is a significant factor for the stability of bulk energy system under the high integration of renewable energy. This paper proposes a planning model that incorporates various flexible resources into uncertain energy system and hence optimizes the unites' capacity and dispatch schedule. Based on Bash Game theory, the optimization capacity and dispatch schedule problems are formulated accordingly. Without setting the capacity configuration variable, the model initiatively considers the stochastic nature of RE at the planning stage. To simplify the complexity of the planning model, the problem is relaxation decoupled into two convex sub-issues, which achieves dramatic improvements in solution time. The novel model has been simulated both under IEEE-39 system and IEEE-118 system and hence the model's performance has been tested. Under the proposed model, the energy system can operate in a secure, economic and optimal state. Results demonstrate the effectiveness of the proposed method in applying to the future energy system.

Purpose: To conduct a multi-center analysis and assess the economic burden due to dry eye disease (DED) in China.Design: A retrospective and cross-sectional study.Methods: Patients (n = 598) with diagnosed DED were recruited from 3 eye centers (in central, southeast, and northeast China) from 1 January 2018 to 31 December 2018. Data were collected regarding the examination, pharmacological therapy, and non-pharmacological therapy fees. Sub-group analyses were stratified by eye center, DED severity, types of DED, number of visits to physicians, and residential area. A logistic regression analysis was conducted to investigate the variables influencing total costs.Results: The per capita costs devoted to DED at the 3 centers were 422.6, 391.3, and 265.4 USD, respectively. The costs of non-pharmacological therapy accounted the largest part in three centers (75.6, 76.4, 76.5%, respectively). Patients with severe DED sustained the largest economic burden. Patients with mixed type of DED spent the most comparing to patients with either evaporative or aqueous-deficient types of DED. Patients spent more during the first visit compared with subsequent visits. Patients living in urban areas spent significantly more than did those living in rural areas (P = 0.001). The logistics regression analysis showed that total costs were significantly influenced by DED severity, number of visits to physicians, and area of residence (beta = 2.83, 0.83, 1.48; P < 0.0001).Conclusions: DED is a chronic ocular disease that timely non-cost counseling, early diagnosis, and efficacious treatment can reduce its economic burden on patients and the society.

Abstract Evapotranspiration (ET) is the major component of the hydrology cycle. Satellites provide a convenient way for gathering information to estimate regional ET. The most widely applied method for converting the instantaneous satellite measurement to daily scale assumes that evaporative fraction (EF), defined as the ratio of ET to the available energy, is constant during the daytime. However, this method was proved to underestimate the daily ET. This study implemented a theoretically improved EF algorithm to calculate daily ET with the decoupling factor method based on the Penman‐Monteith and McNaughton‐Jarvis equations. Seven improved algorithms were developed by assuming that various parameters remain constant during the day. The satellite‐based ET estimates were compared with seven local flux tower measurements in China. The results showed that: (a) The original ET method calculated the daily evaporation more accurately than the other algorithms. However, the good fit was based on two compensating inaccuracies. Compared to the flux tower measurement, the original ET method underestimated the daily EF by 26% and overestimated the daily net radiation by 30%. (b) Six of the seven proposed algorithms underpredicted the daily ET by 30%–60%, mainly due to the inaccurate daily net radiation. (c) The algorithm that assumed that the instantaneous decoupling parameter Ω∗ was equal to its daily value method calculated EF and ET with relative errors of 8% and 10% separately when the inaccurate estimated daily net radiation was replaced by the observed flux tower data.

Cement-based materials is indispensable in the construction process, and the characteristics of cement mortar affect the quality and efficiency of construction obviously. Roof-contacted filling and dehydration in stope are two critical problems in mines in the process of mine filling, which has a very important influence on the strength of filling body. In order to enhance the work performance of cement paste backfill (CPB) and improve the work efficiency in field engineering, the mixed hydrophobic agent was mixed in the CPB slurry to improve the dewatering efficiency. The dewatering test device was designed by authors to test the dewatering efficiency of the CPB mixing different dosage of the hydrophobic agent. The rheological properties of the cement paste mixing with the hydrophobic agent were tested by the rheometer R/S plus to achieve the workability of the CPB. To analyze the influence mechanism of the hydrophobic agent on the dewatering efficiency of CPB, the density, shrinkage, water vapour permeability and capillary water absorption of the CPB specimens were measured. Considering the effect of the hydrophobic agent on the compressive strength of the hardened CPB, it can be concluded that the reasonable addition dosage of hydrophobic agent in CPB is 1% by weight. Keywords: Cemented paste backfill (CPB), Cement paste, Hydrophobic agent, Dewatering, Rheological property, Properties of hardened CPB

AIM:To explore the genetic defects and prenatal diagnosis of a Chinese family with aniridia and gestational diabetes.METHODS: We recruited a Chinese family with aniridia and gestational diabetes. Genomic DNA of the whole family individuals was extracted from the peripheral blood leukocytes. Encoding regions of the paired box 6(PAX6)gene was screened by PCR direct sequencing. Amniocentesis was carried out on the affected female at 18wk of gestation, and subsequently, genetics analysis was performed based on the result of mutation screening.RESULTS: In this study, the patients with aniridia and congenital cataract carried a heterozygous deletion mutation(c.113_129del GGCCGTGCGACATTTCC, p.Arg38ProfsTer12)in exon 5 of PAX6. One of the patients was affected with diabetes while this lady also had gestational diabetes. The result of prenatal diagnosis suggested the fetus carried the same mutation and will be affected with the aniridia, which was confirmed by postpartum follow-up.CONCLUSION: It was suggested that a reported deletion mutation in the PAX6 was identified again in a Chinese family with aniridia and congenital cataract. It contributed to more literature information for the human PAX6 allelic variant database and provided an analysis basis for prenatal diagnosis.

Rock joints have obvious acoustic emission (AE) Kaiser effect and Felicity effect under multilevel cyclic shear conditions. The TFD-20H/50J rock shear apparatus was used to carry out cyclic loading and unloading joint shear tests, and the acoustic emission parameters and frequency spectrum characteristics of the whole shearing process were analyzed. The results show that, under the cyclic loading, the shear stress-displacement curve forms several cyclic hysteresis loops, and the number of loops increases with the increase of normal stress. With the cycles increase, the shear damage gradually increases, and the Felicity ratio gradually decreases. The Felicity ratio at the final shear failure moment is about 0.94~0.99. The ratio of the RA value (rise time/amplitude) and the average frequency value (RA-AF) is used to classify the cracking mode of the joint sample. There are two AE crack signal types (tensile type and shear type) during shear damage. The peak frequency is displayed as high, medium, and low three frequency bands, which are distributed in the range of 0~35 kHz, 35~122 kHz, and 122~300 kHz, respectively. Both low-frequency and high-frequency signals account for less than 10%, and medium-frequency signals account for more than 90%. The research of the AE monitoring signals of multilevel shear behaviors can help understand the shear-friction mechanisms of rock joints.

Abstract Background Parkinson’s disease (PD) is a neurodegenerative disorder with progressive loss of dopaminergic (DA) neurons. Systemic inflammation is shown to initiate and exacerbate DA neuronal degeneration in the substantia nigra. The infiltration and transformation of immune cells from the peripheral tissues are detected in and around the affected brain regions of PD patients. Our previous studies demonstrated the crucial role that microglial Nod-like receptor protein (NLRP) 3 inflammasome plays in the pathogenesis of PD. Nevertheless, the direct linkage between peripheral inflammation and DA neuron death remains obscure. Methods In the present study, we detected the NLRP3 expressions in the midbrain, liver, and bone marrow-derived macrophages in response to 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) acute and chronic challenge. We then used a tail vein injection of Nlrp3-siRNA wrapped with lentivirus to explore the potential influence of hepatic NLRP3 inflammasome-mediated inflammation on neuronal injury in a mouse model of PD via immunohistochemistry, ELISA, and Western blotting analysis. Results We showed that siNlrp3 downregulated the NLRP3 protein expression and inhibited the activation of NLRP3 inflammasomes in mice livers. The tail vein injection of LV3-siNlrp3 reduced the liver pro-inflammatory cytokine production, which subsequently alleviated MPTP-triggered microglial activation and DA neuron loss in the midbrain. These findings indicated that inhibition of hepatic NLRP3 inflammasome weakens inflammatory cytokines spreading into the brain and delays the progress of neuroinflammation and DA neuronal degeneration. Conclusion This study gives us an insight into the direct linkage between liver inflammation and DA neuron damage in the pathogenesis of PD and provides the potential target of NLRP3 for developing novel drugs for PD therapy.

The crack initiation and propagation of 7A04 aluminum alloy in 3.5%NaCl solution at pH=1,4,7,12 during slow strain rate test (SSRT) were investigated by the method of combining phase shift with electrochemical impedance spectroscopy. The feasibility of the method was verified by electrochemical noise (EN). The results show that the more corrosive the solution is, the susceptibility of the 7A04 aluminum alloy to stress corrosion cracking is greater;in the solution at pH=1,the phase shift method shows that crack initiates at 1h and propagates at 4.5h,and the electrochemical impedance spectroscopy in situ method shows the crack initiation and propagation are discontinuous,and in stages;the EN results show that the crack initiation occurs at a certain moment among 3000-5000s and propagates obviously at a certain moment among 13500-22500s accompanying with obvious periodical current and potential noise peaks.

The shear failure of rock is a major cause of rock slope instability and consequent landslides. To determine the forming mechanism of infrasonic waves during the loss of stability of sandstone slopes, experiments were carried out using a shear loading device and an infrasonic monitoring device. In the experiments, infrasonic wave events were identified, and the characteristic parameters of infrasonic waves were extracted to analyze the features of the infrasonic wave response during the shear failure of sandstone. The study results show that: (1) the whole process of shear failure was associated with infrasound events. A normalized energy cumulative coefficient of over 0.6 and a normalized infrasound rate of over 0.89 are the key time nodes for alarming landslide; (2) with an increase in sample size, the shear resistance of the sample increases logarithmically, the total energy of infrasound events increases exponentially, and the average dominant frequency of infrasound events decreases linearly; and (3) with an increase in axial pressure, the shear of the rock increases almost linearly, the number of infrasound events increases linearly, and the average dominant frequency of infrasound events increases exponentially. The research results provide important guidance for the dynamic monitoring and evaluation of the stability of sandstone slopes and can provide a theoretical reference for landslide alarming of sandstone slopes using infrasonic waves.

Because growth environment is affected by climate change, Dacrydium pierrei resources are becoming less and less. Therefore, understanding the effects of environmental variables on seedling-sapling distributions can help gain insight into changes in population recruitment in the context of climate change. The seedling-saplings distribution and variability of Dacrydium pierrei in environmental variables at Bawangling, Hainan, China, was surveyed over a 3-year period. In addition, laboratory experiments measuring the effects of soil moisture on seedling emergence were conducted to identify seedling development characteristics; principal component analysis (PCA) and Gaussian mixture model (GMM) were used to assess how different factors influenced Dacrydium pierrei seedlings-saplings distribution. The results demonstrated that the influence degree of seedling-sapling distribution is soil temperature>litter thickness>available phosphorus>canopy density> available potassium>nitrate nitrogen; a large number of seedling-saplings occurring at altitudes 1140-1300 m; a GMM trained with a C2-L3-H4-A5-I6 combination yielded an accuracy of 72.23% in simulating seedling-saplings distribution; temperature and precipitation have strong impact on seedling-sapling distribution, with increasing soil moisture, seedling emergence shows a positive relationship. This study focuses more on developing a new method for research on the seedling-sapling distribution of Dacrydium pierrei to get reference for its adaptive management with the intense extreme climate change.

The original article [1] contains several errors.

A cable-pneumatic-muscle hybrid-driven waist rehabilitation robot is designed for human waist and gait rehabilitation training.The presented data and curves indicate that the state of motion of human torso during normal walking and the rehabilitation robotics fundamental functions are confirmed.According to these,the structure of the rehabilitation robot that employed the double parallel mechanism is designed.The cable- driven parallel mechanism is chosen to drive the human lower limb,and the pneumatic muscle（PM） is chosen to twist the human waist.The adaptability and safety of the rehabilitation robot is enhanced by synthesized the features of the two actuators.The inverse kinematics are solved by using the closed-vector-circle method,and the velocity Jacobian matrix is established.In addition,the rehabilitation robotics kinematics model and the PM element thermodynamics model are established in view of the parameters of different trainers is diverse.Then the kinematics character of cables and PM during the normal walking are obtained through numerical simulation,and the force variation trend of PM elements is also simulated to verify the feasibility of mechanism.

Hang’s mudding-off technique is a well control measure used to maintain the dynamic balance of the pressure inside a well and thus ensure safe operation when there is circulation loss in the return. Given the lack of a dynamic analysis method that reflects the principles of annulus liquid level changes in a well shaft, there has been no analytical basis for applying Hang’s mudding-off technique in practice, and as a result, the technique is typically applied as a “blind Hang”. In this study, a dynamic analysis method was employed to model well shaft leakage loss, based on actual engineering conditions under which Hang’s mudding-off technique is used, and models were developed for the effective height of the well shaft annulus liquid level in Hang’s mudding-off technique and for a safe operation time after the application of the technique. The calculation of variations in the cross-sectional area of the annulus was also addressed. The reliability of the proposed models was evaluated using calculation examples. The error in the calculated effective liquid level height was 1.22% when dynamic leakage loss was considered, and the error in the safe operation time calculation was 3.58%. These results illustrate the accuracy of the models. The analysis method proposed in this paper can be used to solve problems related to calculation of the engineering parameters involved in Hang’s mudding-off technique and averting the risks of well control safety under conditions of circulation loss in the return, thereby optimising Hang’s mudding-off technique and reducing project costs.

Although massive open online courses (MOOCs) have attracted much worldwide attention, scholars still understand little about the specific elements that students find engaging in these large open courses. This study offers a new original contribution by using a machine learning classifier to analyze 24,612 reflective sentences posted by 5,884 students, who participated in one or more of 18 highly rated MOOCs. Highly rated MOOCs were sampled because they exemplify good practices or teaching strategies. We selected highly rated MOOCs from Coursetalk, an open user-driven aggregator and discovery website that allows students to search and review various MOOCs. We defined a highly rated MOOC as a free online course that received an overall five-star course quality rating, and received at least 50 reviews from different learners within a specific subject area. We described six specific themes found across the entire data corpus: (a) structure and pace, (b) video, (c) instructor, (d) content and resources, (e) interaction and support, and (f) assignment and assessment. The findings of this study provide valuable insight into factors that students find engaging in large-scale open online courses.