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Abstract To study borehole deformation under non-uniform horizontal principal stress in the deep strata, a prediction method for horizontal principal stress was developed based on the morphological parameters of boreholes, the deformation trajectory equation for the standard circular borehole was derived based on elasticity theory, and the morphological characteristics of boreholes were analyzed. Additionally, a quantitative relationship between the geometric parameters of elliptical boreholes and horizontal principal stress was established. Subsequently, uniaxial tests on borehole deformation were conducted to verify elliptical deformation under non-uniform horizontal principal stress. A combined deductive, experimental, and numerical simulation approach to borehole deformation analysis was adopted, and the impact factors of borehole deformation were obtained. The results indicated as following: (1) the deformation morphology of borehole under non-uniform horizontal principal stress was elliptical; (2) for the given lithology, the greater the difference in horizontal principal stress, the greater were the ellipticity and elliptical deformation of borehole; (3) for given stress background, rock strength was inversely proportional to ellipticity. Additionally, the smaller the Young’s modulus and compressive strength, the larger was the Poisson’s ratio and the larger was the ellipticity. For example, the ellipticity of mudstone and coal was greater than that of limestone and sandstone; (4) with an increase in load, the displacement of borehole wall exhibited three stages: initial micro-deformation, accelerated deformation, and stable deformation; (5) horizontal principal stress can be calculated by using the morphological parameters (long and short axes) of an elliptical hole. Furthermore, a horizontal principal stress method theory can be developed based on the morphological parameters of boreholes. The results of our study can provide new ideas and methods for the measurement of in situ stress in deep boreholes and a theoretical basis for the development of equipment for measuring elliptical boreholes.

Abstract Patients with multiple myeloma (MM) are likely to achieve poor therapeutic response when organs are involved. We produced anti‐B‐cell maturation antigen (BCMA) chimeric antigen receptor (CAR)‐T cells, which are in a trial for patients with relapsed/refractory MM. One enrolled patient developed severe heart failure, highly suspected as light chain cardiac amyloidosis. He exhibited increased N‐terminal pro‐brain natriuretic peptide with a peak of 32 299 ng/mL and heart failure with an ejection fraction of 30%. Anti‐BCMA CAR‐T cells were administered following lymphodepletion. The patient achieved cardiac response within 1 week with a decrease in N‐terminal pro‐brain natriuretic peptide by 80%, an increase in ejection fraction from 30% to 56%, and a haematological response with negative minimal residual disease at 1 month and a complete response at 1 year. To date, this patient has maintained good health without heart failure or haematological relapse. Herein, we show the efficacy of anti‐BCMA CAR‐T cells in patients with MM and severe heart failure.

Topological building extraction in remote sensing images is vital for city planning, disaster assessment, and other real-world applications. To meet the requirements of real-world applications, existing building extraction approaches predict topological building by vectorization of binary building masks using multiple refinement stages, leading to complex methodology and poor generalization. To tackle this issue, we propose a topological building extraction approach by directly predicting serialized vertices of each building instance. We observe that the order of serialized vertices from one building is inherently bidirectional, which can be clockwise or counterclockwise. By this new observation, the proposed method learns serialized vertices for each building supervised by the bidirectional constraint. Moreover, we design a cross-scale feature fusion module to obtain building representations with rich spatial and context information, facilitating the following serialized vertex prediction. Besides, a merge strategy is adopted to generate the final topological building from serialized vertices of two directions (clockwise and counterclockwise). Experiments are conducted on three building benchmarks to evaluate the effectiveness of our proposed method. Finally, extensive results show that the proposed approach outperforms state-of-the-art methods highlighting its superiority.

Glioma is the leading cancer of the central nervous system (CNS). The efficacy of glioma treatment is significantly hindered by the presence of the blood-brain barrier (BBB) and blood-brain tumour barrier (BBTB), which prevent most drugs from entering the brain and tumours. Hence, we established a novel drug delivery nanosystem of brain tumour-targeting that could self-assemble the method using an amphiphilic Zein protein isolated from corn. Zein's amphiphilicity prompted it to self-assembled into NPs, efficiently containing TMZ. This allowed us to investigate temozolomide (TMZ) for glioblastoma (GBM) treatment. To construct TMZ-encapsulated NPs (TMZ@RVG-Zein NPs), the NPs' Zein was clocked to rabies virus glycoprotein 29 (RVG29). To verify that the NPs could penetrate the BBB and precisely target and kill the GBM cancer cell line, in vitro studies were performed. The process of NPs penetrating cancer cell membranes was investigated using enzyme-linked immunosorbent assays (ELISAs) to measure the expressions of nicotinic acetylcholine receptors (nAChRs) on the U87 cell line. Therefore, effective targeted brain cancer treatment is possible by forming NP clocks, a cell-penetrating natural Zein protein with an RVG29. These NPs can penetrate the blood-brain barrier (BBB) and enter the glioblastoma (U87) cell line to release TMZ. These NPs have a distinct cocktail of biocompatibility and brain-targeting abilities, making them ideal for involving brain diseases.

Abstract Currently, there are no in-situ methods to quantify drilling-vibration response characteristics of different lithologies. Here, we quantified the vibration responses of four lithologies (limestone, sandstone, coal, and mudstone) using a combination of theoretical deduction and numerical simulation. First, a drilling-vibration model of a particular rock was established, and the differential equations of motion and vibration responses to rock/drill bit interactions with the formation were derived. Next, finite-element simulation was adopted to simulate the rock/drill-bit interactions of the four lithologies. Finally, the Hilbert–Huang transform (HHT) was applied to extract characteristic waveforms, frequency bands, peak frequencies, and marginal spectra of vibration signals. Simulations revealed that the highest and lowest vibration responses were observed in limestone and mudstone, respectively. Vibration acceleration was proportional to the Young's modulus of rocks, whereas vibration displacement and velocity were inversely proportional to Young's modulus, compressive strength, and density. Based on the HHT results, among the four lithologies, vibration responses had the largest characteristic frequency segments and peak frequencies in limestone (28.1–34.6 kHz and 33.4 kHz, respectively), whereas those of mudstone were the smallest (15.6–21.3 kHz and 19.6 kHz, respectively). The results of this study provide a theoretical basis for establishing an identification method and expert knowledge database of lithology based on drilling-vibration responses.

Abstract Aim To explore the relationship between the serum sodium level on admission and all‐cause mortality in HF patients. Design A single‐center retrospective cohort study. Methods Patients hospitalized with HF at the Heart Failure Center, Fuwai Hospital, from November 2008 to November 2018 were enrolled. Results A total of 3649 patients were included, and the mean sodium level was 137.19 ± 4.36 mmol/L, with a range from 115.6 to 160.9 mmol/L. During a median follow‐up of 1101 days, mortality occurred in 1413 (38.7%) hospital survivors. After adjustment for age, sex, and other potential confounders, patients with sodium levels

AbstractThe aim of this study is to demonstrate a method for improving the solubility and relative bioavailability of artemisinin using a self-emulsifying drug delivery system (SEDDS). The self-emulsifying drug load, solubility, and emulsifying time were used as the evaluation indices, based on a solubility test and a ternary phase diagram. Optimal Mixture Design in Design-Expert software was used to optimize the prescription of the artemisinin SEDDS. By determining the water distribution coefficient in vitro, combined with the drug concentration–time curve in vivo, a comparison was made of the relative oral bioavailability of the artemisinin SEDDS and the crude drug. The optimal prescription ratio of oleic acid polyethylene glycol glyceride, polyoxyethylene hydrogenated castor oil, and diethylene glycol monoethyl ether in the artemisinin SEDDS was 0.5:0.2:0.3 (wt/wt/wt), with a drug loading capacity of 41.556 mg/g, a solubility of 1.997 mg/mL, and a self-emulsification time of 214 s. The optimal prescription was transparent, slightly yellow, and oil-like. The average loading capacity of artemisinin was 41.912 mg/g, the emulsification time was 231 s, the average particle size was 128.0 nm, the average Zeta potential was –4.29 mV, and the solubility of artemisinin SEDDS in water was 1.997 mg mL–1. It is 33.85 times of the solubility of artemisinin in water, which achieves the purpose of increasing the solubility of artemisinin. The comparison of the oil/water distribution coefficient of the artemisinin SEDDS with that of the crude drug in vitro showed that SEDDS could improve the permeability of artemisinin and promote the absorption in vivo, and the relative bioavailability of the SEDDS agent was at least 1.47 times higher than that of the crude drug. The artemisinin SEDDS could significantly improve the solubility and relative bioavailability of artemisinin.

Building detection from panchromatic (PAN) and multispectral (MS) images is an essential task for many practical applications. In this article, a dual-stream asymmetric fusion network is proposed, named DAFNet. DAFNet can achieve effective information fusion at the feature level. It obtains better building detection performance from the following three perspectives: a two-stream network structure is designed to guarantee the ability to extract information from PAN and MS images; an asymmetric feature fusion module is proposed to fuse features efficiently and concisely; and two consistency regularization losses, i.e., PAN information preservation loss and cross-modal semantic consistency loss are applied to further explore the consistency between features for better fusion. The experiments are conducted on a challenging building detection dataset collected from GaoFen-2 satellite images. Comprehensive evaluations on 12 popular detection methods demonstrate the superiority of our DAFNet compared with the existing state-of-the-art fusion methods. We reveal that feature-level fusion is more suitable for building detection from PAN-MS images.

This research aims to combine the pursuit of literacy cultivation with a focused investigation into the evidence of game-based teaching (GBT). To achieve this, the study employs a mixed-methods approach including the interview method, Delphi method, and network hierarchical analysis (ANP) to analysis Expert opinions and construct a comprehensive GBT evaluation index system. The results indicated that a comprehensive GBT evaluation index system is comprised of five primary indicators: teaching objectives, game-based teaching methods, teaching content, game-based teaching processes, and game-based teaching characteristics. Additionally, there are 19 secondary indicators, such as objective content, game presentation, context construction, and flow experience. This study expects to effectively capture the unique attributes of game-based classes and to assist teachers in improving the design of GBT activities in practical applications.

Abstract Aims Mildly dilated cardiomyopathy (MDCM) was characterized as a subset of dilated cardiomyopathy (DCM) with systolic dysfunction and modest ventricular dilatation, of which the prognostic studies were limited. We aimed to compare the prognostic value of the N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) and high‐sensitivity C‐reactive protein (hs‐CRP) between MDCM and DCM. Methods and results We retrospectively included hospitalized patients diagnosed with DCM and a left ventricular ejection fraction ≤ 50% at Fuwai Hospital from 2006 to 2017. MDCM was defined as left ventricular end‐diastolic diameter index (LVEDDi) ≤ 33 mm/m2 in males and ≤34 mm/m2 in females. A total of 640 patients (median age 49 years, 24.8% female) were included in this study. At baseline, 110 cases (17%) were categorized as MDCM and 529 cases (83%) as DCM. Of 282 patients who had follow‐up echocardiograms ≥ 6 months, 7 MDCM patients (11.1%) evolved to DCM and 70 DCM patients (32.0%) recovered to MDCM by the change of LVEDDi. Compared with DCM, patients with baseline MDCM had lower composite risks of all‐cause mortality, heart transplantation, and heart failure rehospitalization [adjusted hazard ratio (HR) 0.63, 95% confidence interval (CI) 0.43–0.93, P = 0.019]. Both hs‐CRP and NT‐proBNP were independently associated with the composite endpoint in the overall cohort (hs‐CRP: adjusted HR 1.07, 95% CI 1.00–1.15, P = 0.036; NT‐proBNP: adjusted HR 1.11, 95% CI 1.02–1.22, P = 0.019). After a propensity‐score matching between MDCM and DCM, higher NT‐proBNP (above the median) was significantly associated with the outcome in DCM patients (HR 1.83, 95% CI 1.05–3.20, P = 0.034), but not in MDCM patients (HR 1.54, 95% CI 0.76–3.11, P = 0.227). On the contrary, higher hs‐CRP (above the median) showed prognostic value for adverse events in MDCM patients (HR 3.19, 95% CI 1.52–6.66, P = 0.002), but not in DCM patients (HR 1.04, 95% CI 0.61–1.79, P = 0.88). Conclusions In patients with MDCM, although no evidence suggested the prognostic role of NT‐proBNP, higher level of hs‐CRP was associated with outcome, supporting the use of hs‐CRP in risk stratification for patients with MDCM.

Abstract Background The aim of the present study is to increase the solubility of dihydroartemisinin (DHA) using the self-emulsifying drug delivery system (SEDDS). Methods We first conducted solubility test and ternary phase diagram, then, in order to optimize the formulation of the DHA self-emulsifying agent, the design mixture method was selected in the design expert software. Next, optimal prescription validation and preliminary formulation evaluation were conducted. By comparing the oil–water partition coefficient in vitro, the improvement of the in vivo osmotic absorption of DHA via self-emulsification was evaluated. Results The optimal prescription ratio of oleic acid polyethylene glycol glyceride, polyoxyethylene hydrogenated castor oil, and diethylene glycol monoethyl ether in the DHA self-emulsifying preparation = 0.511:0.2:0.289 (w/w/w), with a drug-loading capacity of 26.3634 mg/g, solubility of 2.5448 mg/ml, and self-emulsification time of 230 s. The solubility self-emulsification was approximately 20.52 × higher in DHA than in the crude drug. The self-emulsification could improve DHA permeability and promoting in vivo DHA absorption. Conclusion The DHA SEDDS could significantly improve DHA solubility and in vivo absorption.

Abstract Background Hypertrophic cardiomyopathy with extreme hypertrophy, biventricular obstruction and diffuse myocardial fibrosis complicated by myocardial infarction in the absence of obstructive coronary artery disease (MINOCA) is a rare phenotype. Evidence and guideline recommendations are still lacking for a treatment strategy. Case presentation Emergency coronary angiography was performed in a 38-year-old man with a 2-year history of nonobstructive hypertrophic cardiomyopathy (HCM) presenting with acute myocardial infarction. The coronary angiogram yielded no stenotic lesions but showed a diffusely dilated left descending artery with slow blood flow. All evidence from biomarker analysis, electrocardiography, echocardiography, and imaging supported the diagnosis of acute myocardial infarction in the left ventricular anterior wall. The echocardiogram demonstrated severe interventricular and apical hypertrophy, severe left ventricular outflow tract obstruction and mild right ventricular outflow tract obstruction. Cardiac magnetic resonance imaging showed a concentric morphological subtype of HCM with diffuse late gadolinium enhancement in the left ventricle. Extended septal myectomy was performed 1 month later, and the patient recovered well. Conclusions Hypertrophic obstructive cardiomyopathy with acute myocardial infarction is an indication for coronary angiography. Septal reduction surgery could be performed cautiously in HCM patients with extreme hypertrophy, biventricular obstruction and diffuse myocardial fibrosis complicated by MINOCA to improve the patient’s symptoms.

Abstract Herba Epimedii, as a traditional Chinese herb, is divided into large and small flower taxa, and can invigorate sexuality and strengthen muscles and bones. Herba Epimedii is rich in flavonoids, which largely contribute to its medicinal benefits. In our previous studies, we have found that the flavonoids content was much more in small than large flower taxa. To further identify molecular mechanisms of flavonoids metabolism in Herba Epimedii, combined metabolome and transcriptomic analyses were performed to profile leaves and flowers. Association analysis revealed that the expression of genes involved in flavonoid biosynthesis showed significant differences between small and large flower taxa. Eleven flavonols significantly increased in small compared to large flower taxa. Moreover, genes encoding O-methyltransferase played crucial roles in flavonoids metabolism by an integrated analysis. Taken together, these data highlight the breeding tendency of small flower taxa to improve the quality of Herba Epimedii.

Abstract Background The present study intends to optimize the processing technology for the wine-processing of Rhizoma Coptidis, using alkaloids as indicators. Method In the present study, the Box–Behnken design method was adopted to optimize the processing technology for Rhizoma Coptidis, using the alkaloid component quantities as the index. 100 g of Rhizoma Coptidis slices and 12.5 g of Rhizoma Coptidis wine were used. After full mixing, box-Behnken design method was used to optimize the processing time, processing temperature and processing time of coptis chinensis by taking alkaloid content as index. After mixing well, these components were fried in a container at 125 °C for 6 min and exhibited good parallelism. Results The content of alkaloids in coptis chinensis was the highest after roasting at 125 °C for 6 min. The characteristic components were berberine hydrochloride, and the relative content was about 15.96%. And showed good parallelism. The effective components of Rhizoma Coptidis were primarily alkaloids. Conclusion The optimized processing technology for Rhizoma Coptidis is good.

Although the use of incentives has been widely recognized as an effective project management tool, its application still needs specific exploration. Existing research on incentives mainly focuses on intra-organizational incentives, lacking systematic research with empirical evidence from the perspective of the inter-organizational level. To fill this research gap, this study conducted an in-depth investigation into the application and impacts of inter-organizational incentives by studying a typical case of a hydropower project. In this case, a series of innovative inter-organizational incentives, involving a multiple contractual incentive scheme concerning schedule, quality, safety, as well as environmental performance, is applied. Using a mixed methodology that included a document review, a questionnaire survey, and interviews, this case study revealed that inter-organizational incentives could effectively help promote goal alignment, stimulate cooperative inter-organizational relationships, and improve project performance. This research developed a novel classification of inter-organizational incentives and emphasized the importance of non-contractual and informal incentives, which were ignored in previous research. The results further highlight that while incentivized organizations generally value incentives according to their monetary intensity, their prioritization of goals is determined by various factors. Therefore, to achieve project goal alignment, the optimization of incentive schemes should comprehensively consider a variety of influencing factors rather than merely focusing on monetary intensity. These findings will help both academic researchers and industrial practitioners design and execute effective inter-organizational incentives for superior project performance, especially for those projects that pursue high sustainable performance with safety and environmental performance included.

Cervical cancer is the most prevalent gynecological tumor among women worldwide. Although the incidence and mortality of cervical cancer have been declining thanks to the wide-scale implementation of cytological screening, it remains a major challenge in clinical treatment. High viability is one of the leading causes of the chemotherapeutic resistance in cervical cancers. Formin-binding protein 1 (FNBP1) could stimulate F-actin polymerization beneath the curved plasma membrane in the cell migration and endocytosis, which had previously been well defined. Here, FNBP1 was also demonstrated to play a crucial role in cervical cancer cell survival, and the knockdown of which could result in the attenuation of FAK/PI3K/AKT signaling followed by significant apoptotic accumulation and proliferative inhibition. In addition, the epidermal growth factor (hrEGF) abrogated all the biological effects mediated by the silencing of FNBP1 except for the cell adhesion decrease. These findings indicated that FNBP1 plays a key role in maintaining the activity of focal adhesion kinase (FAK) by promoting cell adhesion. The activated FAK positively regulated downstream PI3K/AKT/mTOR signaling, which is responsible for cell survival. Promisingly, FNBP1 might be a potential target against cervical cancer in combination therapy.

Abstract Objective To investigate the prognostic value of elevated urinary albumin concentration (UAC) in hospitalized acute decompensated heart failure (ADHF) patients. Methods We measured UAC at baseline in 1818 hospitalized ADHF patients who were admitted to our Heart Failure Center. All patients were followed up for a median period of 937.5 days. The primary endpoint was a composite of all‐cause death or heart transplantation (HTx) or left ventricular assist device (LVAD) implantation. Results In total, 41.5% of ADHF patients had albuminuria (UAC ≥ 20 mg/L). The median value of UAC was 15.5 mg/L. A total of 679 patients died or underwent HTx/LVAD during follow‐up. The median UAC was significantly lower in non‐HTx/LVAD survivors (14.3 mg/L) than in those who died or underwent HTx/LVAD (18.0 mg/L, P

A geometric equation of borehole deformation under stress was deduced based on the basic theory of elasticity. Subsequently, we established the quantitative relationship between the in situ stress and geometrical parameters of borehole deformation. Furthermore, we proposed an in situ stress prediction model based on borehole deformation. Additionally, numerical simulations of borehole morphology in different lithologies under in situ stress were conducted to analyze the deformation effect. Logging parameters that are sensitive to the shear wave time difference, such as longitudinal wave time difference, density, and natural gamma radiation, were selected for training using an artificial neural network (ANN) to predict the shear wave time difference. The results demonstrated that 1) combining the theoretical derivation and numerical simulation, the borehole geometry under stress was quasi-elliptic, and 2) compared with the existing shear wave time difference curve, the predicted geometry by the ANN was consistent with the actual geometry. Consequently, compared with the tested data from acoustic emission, the overall error of the in situ stress predicted using the new method was less than 9.2%. Moreover, the accuracy of the coal seam was the highest, wherein the average errors of the maximum and minimum horizontal principal stresses were 2.01 and 2.56%, respectively, which confirms the feasibility of the proposed method.

Tripterygium hypoglaucum (Levl.) Hutch (THH) is the source plant of a traditional Chinese medicine named Kunmingshanhaitang, which was first recorded in Compendium of Materia Medica. Like Tripterygium wilfordii Hook f. (TWH), THH is also widely used in the treatment of various autoimmune diseases, such as systemic lupus erythematosus, rheumatoid arthritis and psoriasis. The therapeutic effect of THH is closely related to its special compound composition. By now, about 300 compounds have been isolated and identified from THH, including sesquiterpenoids, diterpenoids, triterpenoids, flavonoids, lignans, alkaloids, fatty acids, steroids and others. Further studies found that many compounds originated from THH showed a wide range of biological activities, such as immunosuppression, anti-inflammatory, antitumor, neuroprotection and the others. It is worth noting that THH belongs to the toxic traditional Chinese medicine, commonly known as gut-break grass. Although there have been a lot of studies on the toxic doses of some extracts or isolated compounds of THH, their mechanism remains unclear. Further study on the structure and function relationship of each active and/or toxic compound, analysis of their unique mechanism of action or toxicity mechanism, and exploration of its detoxification methods and new clinical uses will contribute to its better use for human health. In order to better explore the pharmaceutical potential of THH, this paper systematically reviewed its traditional uses, botany, phytochemistry, pharmacology, pharmacokinetics, toxicology and detoxification, which is convenient for further understanding and research.

Scutellariae and Coptidis compose a classical drug pair applied in clinical practice to dispel heat, dryness, and dampness, and they are also precipitation compatible drug pairs. With modern technology, Scutellaria-Coptis is mostly prepared by decocting its components separately, while in the traditional method, it is predominantly prepared as a combined decoction. The present study investigated the effects and mechanisms of separate and combined application of Scutellaria-Coptis decoction on ulcerative colitis (UC) in mice induced by the administration of dextran sulfate sodium (DSS). Changes in body weight, colon length, and Disease Activity Index scores were also evaluated. Hematoxylin and eosin staining and other methods were used to evaluate the overall condition of animals in each group. Intestinal microflora was analyzed using 16S rRNA sequencing, while colon inflammation and antioxidant capacity were evaluated based on the levels of interleukin-6 (IL-6), IL-10, IL-1β, tumor necrosis factor-α, superoxide dismutase, malondialdehyde, and reduced glutathione. The results revealed that Scutellaria-Coptis significantly relieved colon inflammation in mice, and the combined decoction of Scutellaria-Coptis exerted a significant effect on UC. Notably, the protective effect of Scutellaria-Coptis against colon inflammation was weakened when the antibiotic mixture was partially consumed by the gut microbiota. The results of 16S rRNA sequencing showed that the group treated with combined decoction of Scutellaria-Coptis exhibited a higher intestinal microbial diversity and intestinal flora composition than the separated decoction group. Treatment of mice with UC by administering Scutellaria-Coptis decoction through intestinal flora removal (ABX) and fecal microbial transplantation (FMT) was closely associated with intestinal flora composition. In conclusion, Scutellaria-Coptis can relieve UC with an excellent effect especially when taken as a combined decoction, alleviating colon inflammation incurred by intestinal microbes to a certain extent.

Pansharpening aims at fusing a low-resolution multispectral (MS) image and a high-resolution (HR) panchromatic (PAN) image acquired by a satellite to generate an HR MS image. Many deep learning based methods have been developed in the past few years. However, since there are no intended HR MS images as references for learning, almost all of the existing methods downsample the MS and PAN images and regard the original MS images as targets to form a supervised setting for training. These methods may perform well on the down-scaled images; however, they generalize poorly to the full-resolution images. To conquer this problem, we design an unsupervised framework that is able to learn directly from the full-resolution images without any preprocessing. The model is built based on a novel generative multiadversarial network. We use a two-stream generator to extract the modality-specific features from the PAN and MS images, respectively, and develop a dual discriminator to preserve the spectral and spatial information of the inputs when performing fusion. Furthermore, a novel loss function is introduced to facilitate training under the unsupervised setting. Experiments and comparisons with other state-of-the-art methods on GaoFen-2, QuickBird, and WorldView-3 images demonstrate that the proposed method can obtain much better fusion results on the full-resolution images. Code is available. [Online]. Available: https://github.com/zhysora/PGMAN.

Objective: In recent years, research on microRNAs (miRNAs) associated with coronary artery disease (CAD) has attracted considerable attention. However, findings of these studies on the validity of circulating miRNAs in CAD diagnosis are controversial. A meta-analysis was therefore conducted to determine the potential value of miRNAs as biomarkers in CAD diagnosis. Methods: Relevant documents on miRNAs expression levels in the diagnosis of CAD were searched and collected from Pubmed, Embase, and Web of Science. They were collected from the time of inception of the database till January 31, 2020. A meta-analysis was conducted using Stata14.0 software. Forest maps were studied and a comprehensive evaluation of the diagnostic value of the expression levels of mRNAs in CAD was conducted using statistical indicators such as the summary receiver operating characteristic curve. Results: Overall, 14 studies were included, with 38 data sets, involving 29 miRNAs with 846 cases and 898 controls. The meta-analysis revealed that the average sensitivity and specificity of miRNAs for CAD diagnosis were 0.80 (0.75–0.84) and 0.78 (0.75–0.81), respectively. The positive likelihood, negative likelihood, and diagnostic odds ratios were 3.7 (3.1–4.4), 0.26 (0.21–0.33), and 14 (10–21), respectively, and the area under the curve was 0.85 (0.82–0.88). Subgroup analysis revealed that the accuracy in the Asian population was higher than that in the non-Asian population. Multiple miRNAs may be more diagnostically accurate than single miRNAs. MiRNAs in whole blood were more accurate than those in plasma, serum, and peripheral blood mononuclear cells. The diagnostic performance of the quantitative real-time polymerase chain reaction group was better than that of the qPCR group. Conclusion: According to our study, miRNAs may be a new, non-invasive diagnostic tool for the diagnosis of CAD. As a screening tool in clinical practice, it has potential diagnostic value and is worthy of clinical promotion. Considering the number and quality of the studies included in this meta-analysis, the above conclusion requires more quality research to verify it.

BackgroundSeveral studies have investigated the effect of direct oral anticoagulants (DOACs) in Latin American patients with atrial fibrillation (AF), but the results remain controversial. Therefore, we aimed to compare the efficacy and safety of DOACs vs. warfarin in Latin American patients with AF.MethodsWe systematically searched the PubMed and Embase databases until November 2021 for studies that compared the effect of DOACs vs. warfarin in Latin patients with AF. Adjusted hazard ratios (HRs) and 95% CIs were pooled by a random-effects model using an inverse variance method.ResultsFour post-hoc analyses of randomized clinical trials (RCTs) involving 42,411 DOACs and 29,270 warfarin users were included. In Latin American patients with AF, for the effectiveness outcomes, the use of DOACs compared with warfarin was significantly associated with decreased risks of stroke or systemic embolism (SSE) (HR = 0.78; 95%CI.64–0.96), stroke (HR = 0.75; 95%CI.57–0.99), hemorrhagic stroke (HR = 0.14; 95%CI.05–0.36), all-cause death (HR = 0.89; 95% CI.80–1.00), but not ischemic stroke and cardiovascular death. For the safety outcomes, compared with warfarin, the use of DOACs was associated with reduced risks of major or non-major clinically relevant (NMCR) bleeding (HR = 0.70; 95% CI.57–0.86), major bleeding (HR = 0.70; 95%CI.53–0.92), intracranial hemorrhage (ICH) (HR = 0.42; 95%CI.24–0.74), or any bleeding (HR = 0.70;95% CI.62–0.78), but not gastrointestinal bleeding. In non-Latin American patients with AF, for the effectiveness outcomes, the use of DOACs compared with warfarin was significantly associated with decreased risks of SSE (HR = 0.87; 95%CI.75–1.00), hemorrhagic stroke (HR = 0.41; 95%CI.28–0.60), cardiovascular death (HR = 0.87; 95% CI.81–0.94), all-cause death (HR = 0.90; 95% CI.85–0.94). Conversely, the risk of myocardial infarction increased (HR = 1.34; 95% CI 1.13–1.60), but not ischemic stroke. For the safety outcomes, compared with warfarin, the use of DOACs was associated with reduced risks of major or NMCR bleeding (HR = 0.75; 95%CI.61–0.92), major bleeding (HR = 0.76; 95%CI.63–0.92), ICH (HR = 0.42; 95%CI.36–0.52), and any bleeding (HR = 0.81; 95% CI.71–0.92), but not gastrointestinal bleeding.ConclusionCurrent pooled data from the four post-hoc analyses of RCTs suggested that compared with warfarin, DOACs appeared to have significant reductions in SSE, stroke, hemorrhagic stroke, all-cause death, major or NMCR bleeding, major bleeding, ICH, and any bleeding, but comparable risks of ischemic stroke, cardiovascular death, and gastrointestinal bleeding in Latin American patients with AF. DOACs appeared to have significant reductions in SSE, hemorrhagic stroke, all-cause death, cardiovascular death, major or NMCR bleeding, major bleeding, ICH, and any bleeding, and increased the risk of myocardial infarction, but comparable risks of stroke, ischemic stroke, and gastrointestinal bleeding in non-Latin American patients with AF.

In this study, the effects of different processing techniques on the chemical components of Raphani Semen (RS) were evaluated. An established high-performance liquid chromatography (HPLC) method was adopted for the simultaneous determination of glucoraphanin, sinapine thiocyanate, raphanin, and erucic acid in the fried products of Raphani Semen to evaluate the chemical changes during frying processing as well as optimize the best frying technology of Raphani Semen. Then, the chemical components in the fried Raphani Semen were identified by ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). A total of 54 compounds in processed Raphani Semen were identified by UPLC-Q-TOF-MS. The results showed that the content of glucoraphanin and sinapine thiocyanate was the highest in the fried products at 130°C for 10 min, and the effect of “Enzyme Killing and Glycosides Preserving” was the best. Therefore, this condition was chosen as the best frying technology of Raphani Semen. This study provided a more scientific basis for evaluation of the quality of Raphani Semen fried products and optimization of the frying technology of Raphani Semen.

Chinese vernacular fiction is characterized by a simulated storytelling mode through which the narrator manipulates narration and facilitates interaction with the reader. There is little research on the representation of this distinctive Chinese narrative mode across languages and cultures. Recently scholars in translation studies have begun to focus on how different types and levels of voice are represented in translated texts. The present article investigates how the overt voice of the simulated storyteller characterizing the Chinese vernacular narrative style is represented in three complete English translations of a Chinese classic entitled Shuihu Zhuan . The article includes a comparative study of how the storyteller-narrator manifests his narrative voice through storytelling formulae and rhetorical narratorial questions and more importantly, on how the storyteller-narrator’s voice has been rendered by different translators. Besides, by relating the reproduction of narrative voice to translatorship, it shows that the professional role and status of each translator influence their strategy-making as to whether, and to what extent, the narrative voice of the source text should be reconstructed.

The technology of microseismic monitoring, the first step of which is event recognition, provides an effective method for giving early warning of dynamic disasters in coal mines, especially mining water hazards, while signals with a low signal-to-noise ratio (SNR) usually cannot be recognized effectively by systematic methods. This paper proposes a wavelet scattering decomposition (WSD) transform and support vector machine (SVM) algorithm for discriminating events of microseismic signals with a low SNR. Firstly, a method of signal feature extraction based on WSD transform is presented by studying the matrix constructed by the scattering decomposition coefficients. Secondly, the microseismic events intelligent recognition model built by operating a WSD coefficients calculation for the acquired raw vibration signals, shaping a feature vector matrix of them, is outlined. Finally, a comparative analysis of the microseismic events and noise signals in the experiment verifies that the discriminative features of the two can accurately be expressed by using wavelet scattering coefficients. The artificial intelligence recognition model developed based on both SVM and WSD not only provides a fast method with a high classification accuracy rate, but it also fits the online feature extraction of microseismic monitoring signals. We establish that the proposed method improves the efficiency and the accuracy of microseismic signals processing for monitoring rock instability and seismicity.

Computerized pupillary light reflex assessment devices (CPLRADs) may serve as an effective screening tool for glaucomatous optic neuropathy, since they can dynamically detect abnormal pupillary responses from a novel sequence of light stimuli and functionally-shaped stimuli. The aim of this study was to systematically evaluate the current state of advanced CPLRADs and accuracy of application in detecting glaucoma. An electronic literature search of PubMed, MEDLINE, and Embase from database inception to December 2019 was performed. Studies that reported data on the use of computer-aided pupillometry with monocular and/or binocular monitoring in glaucoma patients were included. Two review authors independently conducted the study selection and extracted study data. A total of twenty-five studies were included in this review; eight studies with a total of 829 subjects were included in this meta-analysis. Data were pooled using a random-effect model, since the significant heterogeneity (P < 0.1, I2> 50%). Our meta-analysis of eight studies showed reasonably high summary sensitivity and specificity estimates of 0.81 (95% CI 0.73–0.89) and 0.83 (95% CI: 0.75–0.91), respectively. Simpler monochromatic devices, such as PupilmetrixTM PLR60, generally performed as well as or slightly better than more complex chromatic devices. This review suggests that CPLRADs may facilitate direct clinical decision making for glaucoma diagnosis and evaluation, and may provide a deeper understanding of the pathomechanism of glaucoma.

The dynamic process of membrane fouling was characterized during relatively long-term (30 d) continuous nanofiltration (NF) of a real wastewater secondary effluent, with the roles of organic, inorganic and biological foulants quantified via statistical analyses. The analyses were based on time-series data of physical properties (morphology, roughness, hydrophilicity and charge), chemical compositions (X-ray and infrared responses) and biomass (adenosine triphosphate, ATP) on the membrane surface during fouling evolution. The individual and interactive contributions of organic factor (typical functional groups), inorganic factor (Ca as a representative) and biological factor (ATP amount) to fouling were quantified via multiple linear regression coupled with variance partitioning analysis. About 78% of the variance of filtration resistance can be explained by these factors, among which 16% was contributed by individual effect of organics (via e.g. physical adsorption), 21% by organic-inorganic binary effect (in the form of e.g. Ca-complex), 13% by organic-biological binary effect (organics as the nutrient/product of microorganisms), and 24% by organic-inorganic-biological ternary interaction. Organic matter was universally involved in these effects. The interrelations among fouling factors, foulant layer properties and filtration time were comprehensively explored via redundancy analysis, which clearly delineated the fouling evolution into three major stages: Stage I (0–1 d) for initial fouling mainly due to rapid organic adsorption; Stage II (1–10 d) mainly for the gradual growth of Ca-organic combined fouling; and Stage III (10–30 d) for the eventual maturation of biofouling. These may provide foundations for a targeted fouling control based on foulant type or fouling stage. Keywords: Nanofiltration, Membrane fouling, Dynamic evolution, Synergistic effect, Statistical analysis

Several studies have reported the preventive or therapeutic effect of curcuminoids on chronic heart failure (CHF), but their application was limited due to low solubility and bioavailability. Our previous study indicates that self-emulsifying drug delivery system (SEDDS) improves the solubility and bioavailability of curcuminoids. Thus, the aim of this work was to investigate whether SEDDS could improve preventive effect of curcuminoids on CHF in rats. CHF model was were established by coronary artery ligation. Ninety rats were randomly and averagely divided into sham, model, low- or high-dose suspension or SEDDS of curcuminoids (66.68 or 266.68 mg/kg) groups. Hemodynamic indices were recorded by multipurpose polygraph. Serum oxidative indices, B-type natriuretic peptide (BNP) and heart weight index were determined by kits and electronic balance. Myocardial infarct area, ventricular dilatation degree and collagen volume fraction of myocardial interstitium were analyzed by Masson staining, picric acid and sirius red staining, light microscopy and image analysis system. Myocardial histopathology was observed by hematoxylin and eosin staining, Masson staining and light microscopy. Reduction of ventricular pump function, increase of BNP level and heart weight index, myocardial lipid peroxidation damage, myocardial infarction, myocardial fibrosis, and cardiac enlargement were detected or observed in model group relative to those in sham group. After treatment with suspension or SEDDS of curcuminoids, the above-mentioned pathological changes were obviously reversed relative to those in model group. Meanwhile, the ameliorative effect of SEDDS of curcuminoids was markedly better than that of suspension of curcuminoids. This work provides a valuable reference from pharmacodynamics for development of curcuminoids pharmaceutics. Keywords: Curcuminoids, Self-emulsifying drug delivery system, Chronic heart failure, Ventricular pump function, Lipid peroxidation damage

Facial aging simulation is one of the most challenging issues in automatic machine based face analysis, where the most essential requirements are (i) human identity should remain stable in texture synthesis and (ii) the texture synthesised is expected to accord with human cognitive perception in aging. In this study, the authors propose a tensor completion based method to transform the simulation task to a standard matrix completion one. To protect human dependent characteristics during texture synthesis, the proposed method processes the two major components, i.e. identity and age, in different channels. Furthermore, they incorporate prior information in such a process, assuming that the textures of different subjects in the same age group are similar and similar looking people tend to age in similar ways, and the metric learning technique is adopted to measure the similarity between identities so that the faces that have the highest similarities with the one in the test image are assigned bigger weights in texture generation. In addition, shape deformation is also considered to make the synthesised images more natural. Experimental results achieved on the FG‐NET database demonstrate the effectiveness of the proposed method.

Peroxisomes can be frequently found in proximity to other subcellular organelles such as the endoplasmic reticulum (ER), mitochondria or lysosomes. The tail-anchored protein ACBD5 was recently identified as part of a tethering complex at peroxisome-ER contact sites, interacting with the ER resident protein VAPB. Contact site disruption was found to significantly increase peroxisome motility, apparently interfering with intracellular positioning systems. Unlike other somatic cells, neurons have to distribute organelles across relatively long distances in order to maintain their extraordinary cellular polarity. Using confocal live imaging microscopy in cultured hippocampal neurons we observed that peroxisomes and mitochondria show a strikingly similar motility with approximately 10% performing microtubule-driven long range movements. In order to investigate if ER contacts influence overall peroxisome motility and cellular distribution patterns, hippocampal neurons were transfected with plasmids encoding ACBD5 to stimulate peroxisome-ER interactions. Overexpression of ACBD5 reduced peroxisomal long range movements in the neurites of the hippocampal cells by 70%, implying that ER attachment counteracts microtubule-driven peroxisome transport, while mitochondrial motility was unaffected. Moreover, the analyses of peroxisome distribution in fixed neurons unveiled a significant redistribution of peroxisomes towards the periphery of the perikaryon underneath the plasma membrane and into neurites, where peroxisomes are frequently found in close proximity to mitochondria. Surprisingly, further analysis of peroxisome and VAPB distribution upon ACBD5 expression did not reveal a substantial colocalization, implying this effect may be independent of VAPB. In line with these findings, expression of an ACBD5 variant unable to bind to VAPB still altered the localization of peroxisomes in the same way as the wild-type ACBD5. Thus, we conclude, that the VAPB-ACBD5 facilitated peroxisome-ER interaction is not responsible for the observed organelle redistribution in neurons. Rather, we suggest that additional ACBD5-binding proteins in neurons may tether peroxisomes to contact sites at or near the plasma membrane of neurons.

Video‐based face recognition has attracted much attention and made great progress in the past decade. However, it still encounters two main problems, which are efficiently representing faces in frames and sufficiently exploiting temporal–spatial constraints between frames. The authors investigate the existing real‐time features for face description, and compare their performance. Moreover, a novel approach is proposed to model temporal–spatial information which is then combined with real‐time features to further enforce the consistent constraints between frames to improve the recognition performance. The experiments are validated on three video face databases and the results demonstrate that temporal–spatial cues combined with the most powerful real‐time features largely improve the recognition rate.

Automatic extraction of ground objects is fundamental for many applications of remote sensing. It is valuable to extract different kinds of ground objects effectively by using a general method. We propose such a method, JointNet, which is a novel neural network to meet extraction requirements for both roads and buildings. The proposed method makes three contributions to road and building extraction: (1) in addition to the accurate extraction of small objects, it can extract large objects with a wide receptive field. By switching the loss function, the network can effectively extract multi-type ground objects, from road centerlines to large-scale buildings. (2) This network module combines the dense connectivity with the atrous convolution layers, maintaining the efficiency of the dense connection connectivity pattern and reaching a large receptive field. (3) The proposed method utilizes the focal loss function to improve road extraction. The proposed method is designed to be effective on both road and building extraction tasks. Experimental results on three datasets verified the effectiveness of JointNet in information extraction of road and building objects.

In this paper, the change detection of Multi-Spectral (MS) remote sensing images is treated as an image segmentation issue. An unsupervised method integrating histogram-based thresholding and image segmentation techniques is proposed. In order to overcome the poor performance of thresholding techniques for strongly overlapped change/non-change signals, a Gaussian Mixture Model (GMM) with three components, including non-change, non-labeling and change, is adopted to model the statistical characteristics of the different images between two multi-temporal MS images. The non-labeling represents the pixels that are difficult to be classified. A random walk based segmentation method is applied to solve this problem, in which the different images are modeled as graphs and the classification results of GMM are imported as the labeling seeds. The experimental results of three remote sensing image pairs acquired by different sensors suggest a superiority of the proposed approach comparing with the existing unsupervised change detection methods.

sST2 has been shown to be a risk predictor in heart failure (HF). Our aim was to explore the characteristics and prognostic value of soluble ST2 (sST2) in hospitalized Chinese patients with HF.We consecutively enrolled 1528 hospitalized patients with HF. Receiver operating characteristic (ROC) and multivariable Cox proportional hazards analysis were used to assess the prognostic values of sST2. Adverse events were defined as all-cause death and cardiac transplantation. During a median follow-up of 19.1 months, 325 patients experienced adverse events. Compared with patients free of events, sST2 concentrations were significantly higher in patients with events (P55.6 ng/mL) independently predicted events in comparison to the lowest quartile (≤25.2 ng/mL) when adjusted by multivariable model. In ROC analysis, the area under the curve for sST2 was not different from that for NT-proBNP in short and longer term. Over time, sST2 also improved discrimination and reclassification of risk beyond NT-proBNP.sST2 is a strong independent risk predictor in Chinese patients hospitalized with HF and can significantly provide additional prognostic value to NT-proBNP in risk prediction.

Characterizations of up to date information of the Earth’s surface are an important application providing insights to urban planning, resources monitoring and environmental studies. A large number of change detection (CD) methods have been developed to solve them by utilizing remote sensing (RS) images. The advent of high resolution (HR) remote sensing images further provides challenges to traditional CD methods and opportunities to object-based CD methods. While several kinds of geospatial objects are recognized, this manuscript mainly focuses on buildings. Specifically, we propose a novel automatic approach combining pixel-based strategies with object-based ones for detecting building changes with HR remote sensing images. A multiresolution contextual morphological transformation called extended morphological attribute profiles (EMAPs) allows the extraction of geometrical features related to the structures within the scene at different scales. Pixel-based post-classification is executed on EMAPs using hierarchical fuzzy clustering. Subsequently, the hierarchical fuzzy frequency vector histograms are formed based on the image-objects acquired by simple linear iterative clustering (SLIC) segmentation. Then, saliency and morphological building index (MBI) extracted on difference images are used to generate a pseudo training set. Ultimately, object-based semi-supervised classification is implemented on this training set by applying random forest (RF). Most of the important changes are detected by the proposed method in our experiments. This study was checked for effectiveness using visual evaluation and numerical evaluation.