bluuebunny/crossref_metadata_2025 huggingface dataset:
Medicinal Inula Species: Phytochemistry, Biosynthesis, and Bioactivities
Authors: Sun Cheng-Peng , Jia Zi-Li , Huo Xiao-Kui , Tian Xiang-Ge , Feng Lei , Wang Chao , Zhang Bao-Jing , Zhao Wen-Yu , Ma Xiao-Chi
Published: February 2021

As a genus of the Asteraceae, Inula is widely distributed all over the world, and several of them are being used in traditional medicines. A number of metabolites were isolated from Inula species, and some of these have shown to possess ranges of pharmacological activities. The genus Inula contains abundant sesquiterpenoids, such as eudesmanes, xanthanes, and sesquiterpenoid dimers and trimers. In addition, other types of terpenoids, flavonoids, and lignins also exist in the genus Inula. Since 2010, more than 300 new secondary metabolites, including several known natural products that were isolated for the first time from the genus Inula. Most of them exhibited potential bioactivities in various diseases. The review aimed to summarize the advance of recent researches (2010–2020) on phytochemical constituents, biosynthesis, and pharmacological properties of the genus Inula for providing a scientific basis and supporting its application and exploitation for new drug development.
Research Advances in Protective Effects of Ursolic Acid and Oleanolic Acid Against Gastrointestinal Diseases
Authors: Shi Yajing , Leng Yufang , Liu Disheng , Liu Xin , Ren Yixing , Zhang Jianmin , Chen Feng
Published: February 2021

The intestinal tract plays an essential role in protecting tissues from the invasion of external harmful substances due to impaired barrier function. Furthermore, it participates in immunomodulation by intestinal microorganisms, which is important in health. When the intestinal tract is destroyed, it can lose its protective function, resulting in multiple systemic complications. In severe cases, it may lead to systemic inflammatory response syndrome (SIRS) and multiple organ dysfunction syndrome (MODS). Thus far, there are no curative therapies for intestinal mucosal barrier injury, other than a few drugs that can relieve symptoms. Thus, the development of novel curative agents for gastrointestinal diseases remains a challenge. Ursolic acid (UA) and its isomer, Oleanolic acid (OA), are pentacyclic triterpene acid compounds. Both their aglycone and glycoside forms have anti-oxidative, anti-inflammatory, anti-ulcer, antibacterial, antiviral, antihypertensive, anti-obesity, anticancer, antidiabetic, cardio protective, hepatoprotective, and anti-neurodegenerative properties in living organisms. In recent years, several studies have shown that UA and OA can reduce the risk of intestinal pathological injury, alleviate intestinal dysfunction, and restore intestinal barrier function. The present study evaluated the beneficial effects of UA and OA on intestinal damage and diseases, including inflammatory bowel disease (IBD) and colorectal cancer (CRC).
Topological stability and patterns of traveling wave for a micro-polar non-Newtonian fluid model
Authors: Wang Xin
Published: February 2021

A nonlinear micro-polar non-Newtonian fluid model is investigated. By the complete discrimination system for polynomial method, we give the classification of the traveling wave patterns and analysis of topological stability and dynamical behaviors. We also discuss the physical realizations and the conditions of existence of these patterns. As a result, when some of parameters are not intrinsic parameters we show that in general only two stable patterns will be observed.
What happens for the BTZ black hole solution in dilaton f(R)-gravity?
Authors: Younesizadeh Younes , Ahmed Ali Hassan , Ahmad Amir A. , Younesizadeh Feyzollah , Ebrahimkhas Morad
Published: February 2021

In this work, we obtain the black hole solutions in the dilaton [Formula: see text]-gravity (R is not considered as a constant here) and investigate their thermodynamics especially phase transition and critical behavior in the anti-de Sitter (AdS) extended phase-space. We obtain the exact Banados, Teitelboim and Zanelli (BTZ) counterpart solutions in dilaton [Formula: see text]-gravity which is the basis of our work. We also obtain the exact form of [Formula: see text] model for some solutions. In the thermodynamical analysis, we calculate the thermodynamical quantities like the temperature and entropy for these solutions and we compare them with the BTZ corresponding quantities. After that, we investigate the stability (local and global) for these obtained solutions. In the critical behavior analysis, we find that there is no evidence to show the existence of P–V criticality (like the ordinary BTZ case) in this modified gravity model except some unusual P–V behavior in the corresponding diagrams.
Iterative Approximation of Preconditioning Matrices Through Krylov-Type Solver Iterations
Authors: Kushida Noriyuki , Okuda Hiroshi
Published: February 2021

Linear equation solvers require considerable computational time in many computer simulation methods, such as the stress analysis using the finite element method (FEM), or the fluid dynamics using an implicit time integration scheme. Because of their favorable nature to modern supercomputers, Krylov-type linear equation solvers have become dominant. Krylov-type solvers are usually used with preconditioners, which accelerate the convergence of Krylov solvers, and therefore developing robust preconditioners draws attention from researchers. The basic idea of preconditioning is to transform the original system to a system which can be solved more easily by using a matrix which resembles the original system but the associated linear system can be solved without any difficulties. In this study, we propose a new methodology of constructing such a matrix by updating the matrix using the information obtained through the Krylov solver computation. More precisely, we employ the limited memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) Hessian matrix update scheme. The proposed scheme is combined with the orthogonal minimum (ORTHOMIN) residual method, which accepts a variable preconditioner. As a result of performance tests, in the best case scenario, (1) with the Matrix Market matrices, our new method combined with Algebraic Multigrid (AMG) shows the successful convergence in 12 cases out of 13 problems, whilst the conventional AMG converged only in four cases and (2) with FEM problems, we obtained [Formula: see text] acceleration in the rate of converge and [Formula: see text] in computational time over the AMG preconditioned conjugate gradient (CG) solver. With those results, our newly developed algorithm provides robustness to the conventional preconditioning, whilst the computational speed is superior to conventional ones.
Dynamics of bilateral control system with state feedback for price adjustment strategy
Authors: Zhang Meng , Zhao Yi , Song Xinyu
Published: February 2021

The price fluctuation of commodities affects their demand, and it strongly influences the development of industry and the stability of the international economy. A price-output model with two price-dependent impulses is presented in this paper to describe their mutual restrictions and the price adjustment strategies. The equilibria and dynamic properties of the impulsive-free price-output model are qualitatively analyzed, and the results show the hazard of free price fluctuation. For the price-output model with two price-dependent impulses, conditions for the existence of the order-2 periodic solution are obtained, and the orbital asymptotic stability is proved. Those results reveal the positive role of price adjustment strategies. Finally, some numerical simulations are carried out to verify the theoretical results.
Gestational long-term hypoxia induces metabolomic reprogramming and phenotypic transformations in fetal sheep pulmonary arteries
Authors: Leslie Eric , Lopez Vanessa , Anti Nana A. O. , Alvarez Rafael , Kafeero Isaac , Welsh Donald G. , Romero Monica , Kaushal Shawn , Johnson Catherine M. , Bosviel Remy , Blaženović Ivana , Song Rui , Brito Alex , La Frano Michael R. , Zhang Lubo , Newman John W. , Fiehn Oliver , Wilson Sean M.
Published: February 2021

Gestational long-term hypoxia increases the risk of myriad diseases in infants including persistent pulmonary hypertension. Similar to humans, fetal lamb lung development is susceptible to long-term intrauterine hypoxia, with structural and functional changes associated with the development of pulmonary hypertension including pulmonary arterial medial wall thickening and dysregulation of arterial reactivity, which culminates in decreased right ventricular output. To further explore the mechanisms associated with hypoxia-induced aberrations in the fetal sheep lung, we examined the premise that metabolomic changes and functional phenotypic transformations occur due to intrauterine, long-term hypoxia. To address this, we performed electron microscopy, Western immunoblotting, calcium imaging, and metabolomic analyses on pulmonary arteries isolated from near-term fetal lambs that had been exposed to low- or high-altitude (3,801 m) hypoxia for the latter 110+ days of gestation. Our results demonstrate that the sarcoplasmic reticulum was swollen with high luminal width and distances to the plasma membrane in the hypoxic group. Hypoxic animals were presented with higher endoplasmic reticulum stress and suppressed calcium storage. Metabolically, hypoxia was associated with lower levels of multiple omega-3 polyunsaturated fatty acids and derived lipid mediators (e.g., eicosapentaenoic acid, docosahexaenoic acid, α-linolenic acid, 5-hydroxyeicosapentaenoic acid (5-HEPE), 12-HEPE, 15-HEPE, prostaglandin E3, and 19(20)-epoxy docosapentaenoic acid) and higher levels of some omega-6 metabolites ( P < 0.02) including 15-keto prostaglandin E2 and linoleoylglycerol. Collectively, the results reveal broad evidence for long-term hypoxia-induced metabolic reprogramming and phenotypic transformations in the pulmonary arteries of fetal sheep, conditions that likely contribute to the development of persistent pulmonary hypertension.
Interhemispheric interactions between the right angular gyrus and the left motor cortex: a transcranial magnetic stimulation study
Authors: Baarbé Julianne , Vesia Michael , Brown Matt J. N. , Lizarraga Karlo J. , Gunraj Carolyn , Jegatheeswaran Gaayathiri , Drummond Neil M. , Rinchon Cricia , Weissbach Anne , Saravanamuttu James , Chen Robert
Published: February 2021

Goal-directed hand movements rely on the right and left angular gyri (RAG and LAG) and motor cortex (M1), yet how these brain areas functionally interact is unclear. Here, we show that RAG stimulation facilitated right hand motor output from the left M1 but inhibited indirect (I)-waves in M1. Combined RAG and LAG stimulation increased GABAB, but not GABAA, receptor-mediated inhibition in left M1. These findings highlight unique brain interactions between the RAG and left M1.
Screening and Assessment of Antimicrobial Susceptibility of Periodontopathic Bacteria in Peruvian Patients with Periodontitis: A Pilot Study
Authors: Aguilar-Luis Miguel Angel , Casas Apayco Leslie , Tinco Valdez Carmen , De Lama-Odría María del Carmen , Weilg Claudia , Mazulis Fernando , Silva-Caso Wilmer Gianfranco , Del Valle-Mendoza Juana Mercedes
Published: February 2021

Background. Severe periodontal disease is highly prevalent worldwide, affecting 20% of the population between the ages of 35 and 44 years. The etiological epidemiology in Peru is scarce, even though some studies describe a prevalence of 48.5% of periodontal disease in the general population. Periodontitis is one of the most prevalent oral diseases associated with site-specific changes in the oral microbiota and it has been associated with a socioeconomic state. This study aimed to determine the etiology and resistance profile of bacteria identified in a group of Peruvian patients with periodontal disease. Methods. Six subgingival plaque samples were collected from eight patients with severe periodontitis. Bacterial identification was carried out by an initial culture, PCR amplification, and subsequently DNA sequencing. We evaluated the antibiotic susceptibility by the disk diffusion method. Results. Variable diversity in oral microbiota was identified in each one of the eight patients. The bacterial genus most frequently found was Streptococcus spp. (15/48, 31.3%) followed by Rothia spp. (11/48, 22.9%), Actinomyces spp. (9/48, 18.8%), and Eikenella spp. (4/48, 8.3%). The most common species found was Rothia dentocariosa (8/48, 16.7%). The antimicrobial susceptibility assay varied according to the species tested; however, among all the isolates evaluated, Actinomyces naeslundii was resistant to penicillin and tetracycline; Eikenella corrodens was resistant to dicloxacillin; and Rothia dentocariosa was resistant to amoxicillin + clavulanic acid and metronidazole but also susceptible to trimethoprim-sulfamethoxazole. Conclusions. The most prevalent periodontal bacterium found in this study was Rothia dentocariosa. Specific antimicrobial therapy is required to improve the treatment outcomes of patients with periodontal disease and avoid antibiotic resistance.
Development of a Driving Cycle for Fuzhou Using K-Means and AMPSO
Authors: Zhao Minrui , Gao Hongni , Han Qi , Ge Jiaang , Wang Wei , Qu Jue
Published: February 2021

The driving cycle is a speed-to-time curve, a fundamental technique in the automotive industry, and also a basis to set standards for fuel consumption and emissions of vehicles. A driving cycle is developed based on firsthand driving data collected from fieldwork. First, bad data in the original dataset are preprocessed, the time-series standard smoothing algorithm is used to smoothen the data, and Lagrange’s interpolation is used to realize data interpolation. Next, the rules for kinematic fragment extraction are set to divide the data into kinematic fragments. Last, an evaluation system of kinematic fragment feature parameters is built. On that basis, the K-means clustering method is used to cluster the dimensionally reduced data, and the adaptive mutation particle swarm optimization (AMPSO) algorithm is employed to select the optimal fragments from candidate fragments to develop a driving cycle. The experiment result shows that the developed driving cycle can represent the kinematic features of the experiment car and provides a basis for the development of a driving cycle for Fuzhou.
Recent Fixed-Point Results forθ−Contraction Mappings in RectangularM−Metric Spaces with Supportive Application
Authors: Mudhesh Mustafa , Hammad Hasanen A. , Alsamir Habes , Arshad Muhammad , Ameer Eskandar
Published: February 2021

The goal of this manuscript is to present a new fixed-point theorem onθ−contraction mappings in the setting of rectangular M-metric spaces (RMMSs). Also, a nontrivial example to illustrate our main result has been given. Moreover, some related sequences withθ−contraction mappings have been discussed. Ultimately, our theoretical result has been implicated to study the existence and uniqueness of the solution to a nonlinear integral equation (NIE).
Effect of Short-Term Tacrolimus Exposure on Rat Liver: An Insight into Serum Antioxidant Status, Liver Lipid Peroxidation, and Inflammation
Authors: Fatima N. , Sheikh N. , Satoskar A. R. , Akhtar T. , Tayyeb A. , Ashfaq I. , Ryan N. , Ambreen S. , Jha B. K. , Oghumu S.
Published: February 2021

Tacrolimus (TAC) is an immunosuppressive drug, optimally used for liver, kidney, and heart transplant to avoid immune rejection. In retrospect, a multitude of studies have reported effects of TAC, such as nephrotoxicity, diabetes, and other complications. However, limited information is available regarding short-term exposure of TAC on the liver. Therefore, the present study was designed to unravel the effects of short-term exposure of TAC on a rat model. The animal model was established by TAC administration for 6, 12, 24, and 48 h time points. Liver histopathological changes were observed with PAS-D, reticulin stain, and immunostaining of PCNA and CK-7 coupled with glycogen quantification in a liver homogenate. TUNEL assay was performed to evaluate the DNA damage in the liver. Concentration of GSH and activities of SOD and CAT in the serum were measured to assess the antioxidant status, whereas liver tissue MDA level was measured as a biomarker of oxidative stress. Hepatic gene expression analysis of IL-10, IL-13, SOCS-2, and SOCS-3 was performed by RT-PCR. Results revealed marked changes in liver architecture of all TAC-treated groups, as evidenced by sinusoid dilation, hepatocyte derangement, glycogen deposition, and collapsed reticulin fibers. Significant increase in PCNA and CK-7 immunostaining along with the presence of TUNEL-positive cells was revealed in treatment groups as compared to the control group. Serum antioxidant enzyme status was markedly decreased, whereas the liver MDA level was increased in TAC treatment groups indicating oxidative stress induction. The gene expression profile of cytokines was significantly upregulated in treatment groups highlighting an inflammatory response. In conclusion, results of the current study propose that even a short-term TAC exposure can induce change in antioxidant status and lipid peroxidation. Therefore, these factors should be considered to avoid and minimize immunosuppression-related issues in a prolonged course of treatment.
Comprehensive Evaluation of Waterflooding Performance with Induced Fractures in Tight Reservoir: A Field Case
Authors: Feng Naichao , Chang Yuwen , Wang Zuoqian , Liang Tao , Guo Xiaofei , Zhu Yimeng , Hu Limin , Wang Yang
Published: February 2021

Whether intentionally or unintentionally, waterflooding always takes place under fracturing condition in tight reservoir because of the extremely limited water absorption ability of the formation. Recently, we proposed a novel workflow, including real-time monitoring, formation testing analysis, and dynamic production analysis, to timely and effectively identify the initiation of waterflood-induced fractures (WIFs) and characterize the waterflooding behaviors for a well group. In this paper, we further provide a supplementary study to evaluate the waterflooding performance from the well group to the field basis. The utilization factor (UF) is first estimated on the basis of injection/production data by material balance theory, which provides an overall picture of water injection efficiency every year. Then, the areal (straightforwardly showed by water cut and formation pressure distributions) and vertical sweep (includes the water absorption in injectors and water breakthrough in producers) behaviors are studied to investigate the waterflooding characteristics and residual oil distributions. Lastly, three key influence factors are detailedly discussed: sand body connectivity, WIFs, and injection and production correspondence. Combining the previous work for the single well group, and the study in this paper to field basis, one can have a better and much more comprehensive understanding of the waterflooding performance and then thus take the corresponding adjustment measurements to improve waterflooding effectiveness.
Three-Dimensional MIMO Channel Model with High-Mobility Wireless Communication Systems Using Leaky Coaxial Cable in Rectangular Tunnel
Authors: Zhang Kai , Zhang Fangqi , Zheng Guoxin , Cang Lei
Published: February 2021

With the rapid development of high-mobility wireless communication systems, e.g., high-speed train (HST) and metro wireless communication systems, more and more attention has been paid to the wireless communication technology in tunnel-like scenarios. In this paper, we propose a three-dimensional (3D) nonstationary multiple-input multiple-output (MIMO) channel model with high-mobility wireless communication systems using leaky coaxial cable (LCX) inside a rectangular tunnel over the 1.8 GHz band. Taking into account single-bounce scattering under line-of-sight (LoS) and non-line-of-sight (NLoS) propagations condition, the analytical expressions of the channel impulse response (CIR) and temporal correlation function (T-CF) are derived. In the proposed channel model, it is assumed that a large number of scatterers are randomly distributed on the sidewall of the tunnel and the roof of the tunnel. We analyze the impact of various model parameters, including LCX spacing, time separation, movement velocity of Rx, and K-factor, on the T-CF of the MIMO channel model. For HST, the results of some further studies on the maximum speed of 360 km/h are given. By comparing the T-CF between the dipole MIMO system and the LCX-MIMO system, we can see that the performance of the LCX-MIMO system is better than that of the dipole MIMO system.
Assessment of Artificial Intelligence Models for Developing Single‐Value and Loop Rating Curves
Authors: Niazkar Majid , Zakwan Mohammad
Published: February 2021

Estimation of discharge flowing through rivers is an important aspect of water resource planning and management. The most common way to address this concern is to develop stage‐discharge relationships at various river sections. Various computational techniques have been applied to develop discharge ratings and improve the accuracy of estimated discharges. In this regard, the present study explores the application of the novel hybrid multigene genetic programming‐generalized reduced gradient (MGGP‐GRG) technique for estimating river discharges for steady as well as unsteady flows. It also compares the MGGP‐GRG performance with those of the commonly used optimization techniques. As a result, the rating curves of eight different rivers were developed using the conventional method, evolutionary algorithm (EA), the modified honey bee mating optimization (MHBMO) algorithm, artificial neural network (ANN), MGGP, and the hybrid MGGP‐GRG technique. The comparison was conducted on the basis of several widely used performance evaluation criteria. It was observed that no model outperformed others for all datasets and metrics considered, which demonstrates that the best method may be different from one case to another one. Nevertheless, the ranking analysis indicates that the hybrid MGGP‐GRG model overall performs the best in developing stage‐discharge relationships for both single‐value and loop rating curves. For instance, the hybrid MGGP‐GRG technique improved sum of square of errors obtained by the conventional method between 4.5% and 99% for six out of eight datasets. Furthermore, EA, the MHBMO algorithm, and artificial intelligence (AI) models (ANN and MGGP) performed satisfactorily in some of the cases, while the idea of combining MGGP with GRG reveals that this hybrid method improved the performance of MGGP in this specific application. Unlike the black box nature of ANN, MGGP offers explicit equations for stream rating curves, which may be counted as one of the advantages of this AI model.
UPLC‐MS/MS for the Herb‐Drug Interactions of Xiao‐Ai‐Ping Injection on Enasidenib in Rats Based on Pharmacokinetics
Authors: Wang Bo-wen , Qiu Cheng-zheng , Tang Chang-qian , Zhang Jia-hui , Zhang Yi , Du Qi-guang , Feng Yi , Qiu Xiang-jun
Published: February 2021

Objective. To develop and validate a sensitive and rapid ultraperformance liquid chromatography‐tandem mass spectrometry (UPLC‐MS/MS) method for the determination of enasidenib in rat plasma and to investigate the effect of Xiao‐ai‐ping injection (XAPI) on the pharmacokinetics of enasidenib in rats. Methods. The rat plasma was precipitated with acetonitrile, enasidenib and internal standard (IS) were separated on an Acquity UPLC BEH C18 column, and acetonitrile and 0.1% formic acid were used as the mobile phase in gradient mode. Enasidenib and IS were monitored and detected by multiple reaction monitoring (MRM) using tandem mass spectrometry in positive ion mode. 12 Sprague‐Dawley (SD) rats were randomly divided into control group (group A) and experimental group (group B), 6 rats in each group. Group B was intramuscularly injected with XAPI (0.3 mL/kg) every morning, 7 days in a row. Group A was intramuscularly injected with normal saline, 7 days in a row. On the seventh day, enasidenib (10 mg/kg) was given to both groups 30 min after injection of normal saline (group A) or XAPI (group B), and the blood was collected at different time points such as 0.33, 0.67, 1, 1.5, 2, 3, 4, 6, 9, 12, 24, and 48 h. The concentration of enasidenib was detected by UPLC‐MS/MS, and the main parameters of pharmacokinetic of enasidenib were calculated using the DAS 2.0 software. Results. Under the current experimental conditions, this UPLC method showed good linearity in the detection of enasidenib. Interday and intraday precision did not exceed 10%, the range of accuracy values were from ‐1.43% to 2.76%. The results of matrix effect, extraction recovery, and stability met the requirements of FDA approval guidelines of bioanalytical method validation. The Cmax of enasidenib in the group A and the group B was (458.87 ± 136.02) ng/mL and (661.47 ± 107.32) ng/mL, t1/2 was (7.74 ± 0.91) h and (8.64 ± 0.42) h, AUC(0 − t) was (4067.24 ± 1214.36) ng·h/mL and (5645.40 ± 1046.30) ng·h/mL, AUC(0 − ∞) was (4125.79 ± 1235.91) ng·h/mL and (5759.61 ± 1078.59) ng·h/mL, respectively. The Cmax of enasidenib in group B was 44.15% higher than that in group A, and the AUC(0 − t) and AUC(0 − ∞) of enasidenib in group B were 38.80% and 39.60% higher than that in group A, respectively, and the t1/2 was prolonged from 7.74 h to 8.64 h. Conclusion. An UPLC‐MS/MS method for the determination of enasidenib in rat plasma was established. XAPI can inhibit the metabolism of enasidenib and increase the concentration of enasidenib in rats. It is suggested that when XAPI was combined with enasidenib, the herb‐drug interaction and adverse reactions should be paid attention to, and the dosage should be adjusted if necessary.
A Case of Liver Metastasis from Small Intestinal Gastrointestinal Stromal Tumor 25 Years after Surgery including Autopsy Findings
Authors: Takano Yuichi , Yamawaki Masataka , Noda Jun , Azami Tetsushi , Kobayashi Takahiro , Niiya Fumitaka , Yamamura Eiichi , Maruoka Naotaka , Gomi Kuniyo , Kuroki Yuichiro , Yamamoto Yorimasa , Norose Tomoko , Ohike Nobuyuki , Nagahama Masatsugu
Published: February 2021

Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor in the digestive tract. Recurrences may occur even after radical resection; however, recurrence later than 10 years after surgery is rare. We report a case of GIST with recurrence of liver metastasis 25 years after surgery. A 56-year-old man complained of sudden epigastric pain and was transferred to the emergency department. He had undergone partial resection of the small intestine for leiomyosarcoma 25 years previously. Abdominal computed tomography showed multiple liver tumors with massive hemorrhage. Ultrasound-guided percutaneous biopsy was performed for the 15-mm hepatic tumor in segment 2. Pathological findings revealed proliferation of spindle-shaped atypical cells, and immunostaining for c-kit and CD34 was both positive; the patient was therefore diagnosed with GIST. He then underwent chemotherapy for 7 years but died of multiple organ failure due to GIST. Autopsy revealed GIST occupying the entire liver with peritoneal dissemination, and minute lung metastases that could not be identified by CT were also detected. This case is interesting in considering the recurrence of GIST, and we will report it together with the literature review.
Maternal Serum Cytokine Concentrations in Healthy Pregnancy and Preeclampsia
Authors: Spence Toni , Allsopp Philip J. , Yeates Alison J. , Mulhern Maria S. , Strain J. J. , McSorley Emeir M.
Published: February 2021

The maternal immune response is essential for successful pregnancy, promoting immune tolerance to the fetus while maintaining innate and adaptive immunity. Uncontrolled, increased proinflammatory responses are a contributing factor to the pathogenesis of preeclampsia. The Th1/Th2 cytokine shift theory, characterised by bias production of Th2 anti-inflammatory cytokine midgestation, was frequently used to reflect the maternal immune response in pregnancy. This theory is simplistic as it is based on limited information and does not consider the role of other T cell subsets, Th17 and Tregs. A range of maternal peripheral cytokines have been measured in pregnancy cohorts, albeit the changes in individual cytokine concentrations across gestation is not well summarised. Using available data, this review was aimed at summarising changes in individual maternal serum cytokine concentrations throughout healthy pregnancy and evaluating their association with preeclampsia. We report that TNF-α increases as pregnancy progresses, IL-8 decreases in the second trimester, and IL-4 concentrations remain consistent throughout gestation. Lower second trimester IL-10 concentrations may be an early predictor for developing preeclampsia. Proinflammatory cytokines (TNF-α, IFN-γ, IL-2, IL-8, and IL-6) are significantly elevated in preeclampsia. More research is required to determine the usefulness of using cytokines, particularly IL-10, as early biomarkers of pregnancy health.
Prediction of miRNA‐Disease Association Using Deep Collaborative Filtering
Authors: Wang Li , Zhong Cheng
Published: February 2021

The existing studies have shown that miRNAs are related to human diseases by regulating gene expression. Identifying miRNA association with diseases will contribute to diagnosis, treatment, and prognosis of diseases. The experimental identification of miRNA‐disease associations is time‐consuming, tremendously expensive, and of high‐failure rate. In recent years, many researchers predicted potential associations between miRNAs and diseases by computational approaches. In this paper, we proposed a novel method using deep collaborative filtering called DCFMDA to predict miRNA‐disease potential associations. To improve prediction performance, we integrated neural network matrix factorization (NNMF) and multilayer perceptron (MLP) in a deep collaborative filtering framework. We utilized known miRNA‐disease associations to capture miRNA‐disease interaction features by NNMF and utilized miRNA similarity and disease similarity to extract miRNA feature vector and disease feature vector, respectively, by MLP. At last, we merged outputs of the NNMF and MLP to obtain the prediction matrix. The experimental results indicate that compared with other existing computational methods, our method can achieve the AUC of 0.9466 based on 10‐fold cross‐validation. In addition, case studies show that the DCFMDA can effectively predict candidate miRNAs for breast neoplasms, colon neoplasms, kidney neoplasms, leukemia, and lymphoma.
Profiles of Innate Immune Cell Infiltration and Related Core Genes in Psoriasis
Authors: Gong Xiaoting , Wang Wei
Published: February 2021

Psoriasis is an inflammatory skin disease with substantial morbidity. Numerous patients with psoriasis experience recurrence after therapy. The underlying mechanism about psoriasis is still not fully understood. Some evidences suggest that innate immunity may play an unexpected and important role in active severe psoriasis. In this work, the deconvolution algorithm CIBERSORT was conducted to identify the infiltration of innate immune cells and related core genes in psoriatic plaque. Datasets from the Gene Expression Omnibus, including skin samples from 405 psoriasis patients and 91 healthy donors, were downloaded for analysis. Considerable differences of the innate immune cell composition were uncovered between psoriatic plaque and control skin. Results revealed that γδ T cells, resting NK cells, M0 macrophages, M1 macrophages, activated dendritic cells, and neutrophils were significantly increased in psoriatic skin, while resting mast cells and active NK cells were significantly decreased. Moreover, the proportion of M0 macrophages or resting mast cells was found to be associated with disease severity. Spearman correlation analysis suggests that RORC and S100A12 genes were related to disease severity, while genes including S100A12, CLEC4C, IL‐19, AIM2, IL‐17F, and PPARGC1A were correlated with biologic treatment response. In conclusion, this work displays innate immune status in psoriatic skin and provides novel clues for clinical decisions and mechanism study.
Size Effects of Closed Encounter Ag Nanoshell Pairs for SERS Application
Authors: Zhao Zhiguo , Liu Wenwen , Zhao Junfeng , Dong Xiaoyan , Li Caiqiong , Zhu Pengcheng , Yu Xinxiang , Dai Han
Published: February 2021

Closed encounter Ag nanoshell pairs with remarkable improved plasmonic light enhancement in their gaps have been attracting much attention in the production of sensitivity SERS substrates. This work demonstrates the size effects of Ag nanoshell pairs on obtaining higher light intensity in their gaps. It is found that very complex light intensity changes occur in the gaps of Ag nanoshell pairs with their diameter enlargements (

diameters
>
100

 nm). By the calculation of scattering efficiency and electric field vectors, the size-related light intensity changes in the gaps have been revealed and been concluded systematically. This work fills in the gaps of application of nanoshell pairs with larger sizes in SERS detectors and could guide the design of some other Ag nanoshell pair-based optical devices.
Special Distribution of Crude Oil in the Lucaogou Formation in Jimusaer Sag and Genetic Analysis of Its Physical Difference
Authors: Wang Ming , Liu Shiju , Li Ji , Gao Gang , Mi Julei , Li Erting
Published: February 2021

The shale oil of the Lucaogou Formation in the Jimusaer Sag of the Junggar Basin was divided into two sweet spots for exploration and development. Crude oil in the upper and lower sweet spots comes from the upper and lower source rocks. After years of exploration, it has been found that the crude oil in the lower sweet spot has worse physical properties than that of the upper sweet spot. In this study, through the physical and geochemical analysis of crude oil in the upper and lower sweet spots, combined with the organic petrological observation of the upper and lower source rocks, the cause of the poor physical properties of the crude oil in the lower sweet spot has been identified. n-Alkanes in the saturated hydrocarbons of crude oil in the upper and lower sweet were complete while odd-to-even predominance was evident, indicating that the poor physical properties of the crude oil are unrelated to biodegradation. In addition, the correlation between the biogenic parameters and the physical properties of crude oil was analyzed, finding that the difference in crude oil is mainly related to the composition of biogenic precursors of upper and lower source rocks. Combined with organic petrological observation, the lower source rock was found to be rich in telalginite (green algae), which is therefore the primary reason for the difference in physical properties. In comparing results from the characteristics of crude oil biomarkers from both the upper and lower sweet spots, crude oils in the upper sweet spot are similar to each other, indicating that the enrichment of crude oil has experienced a certain migration. In contrast, the differences in biomarkers between the crude oils of the lower sweet spot were relatively large and changed regularly with depth, suggesting the self-generated and self-stored characteristics of crude oil enrichment. At the same time, it was found that the crude oil in the lower sweet spot is also affected by the maturity of adjacent source rocks under the condition of a consistent parent material source. Overall, it was determined that the lower the maturity of source rocks, the poorer the physical property of the crude oil produced.
An Improved Double Channel Long Short-Term Memory Model for Medical Text Classification
Authors: Liang Shengbin , Chen Xinan , Ma Jixin , Du Wencai , Ma Huawei
Published: February 2021

There are a large number of symptom consultation texts in medical and healthcare Internet communities, and Chinese health segmentation is more complex, which leads to the low accuracy of the existing algorithms for medical text classification. The deep learning model has advantages in extracting abstract features of text effectively. However, for a large number of samples of complex text data, especially for words with ambiguous meanings in the field of Chinese medical diagnosis, the word-level neural network model is insufficient. Therefore, in order to solve the triage and precise treatment of patients, we present an improved Double Channel (DC) mechanism as a significant enhancement to Long Short-Term Memory (LSTM). In this DC mechanism, two channels are used to receive word-level and char-level embedding, respectively, at the same time. Hybrid attention is proposed to combine the current time output with the current time unit state and then using attention to calculate the weight. By calculating the probability distribution of each timestep input data weight, the weight score is obtained, and then weighted summation is performed. At last, the data input by each timestep is subjected to trade-off learning to improve the generalization ability of the model learning. Moreover, we conduct an extensive performance evaluation on two different datasets: cMedQA and Sentiment140. The experimental results show that the DC-LSTM model proposed in this paper has significantly superior accuracy and ROC compared with the basic CNN-LSTM model.
Risk Assessment of a Cryogenic Globe Valve by Using Combined Group Decision and Fuzzy Comprehensive Evaluation
Authors: Lu Yi , Zheng Jianming , Zhao Chen , Ren Gang
Published: February 2021

When using the risk priority number method to perform a criticality analysis of the failure modes of mechanical products, different subjective factors exist on the part of experts regarding the severity level (S), occurrence probability level (O), and failure modes. The estimation of the detection difficulty level (D) is different, which causes the problem of inaccurate evaluation of the criticality of failure modes. This study proposes a harm analysis method that combines group decision-making and fuzzy comprehensive evaluation. The similarity and difference between an individual expert and the group are used in group decision-making to assign the weight of the expert, thus reducing the influence of subjective factors on the evaluation results. On the basis of the fuzzy comprehensive evaluation method, the weight of three risk elements (S, O, and D) is determined, and a hazard ranking of the interval obtained by group decision-making is performed. The CA (criticality analysis) improvement method is used to analyze the hazard posed by low-temperature shut-off valves. Results indicate that this method can effectively assess the weak links of the low-temperature shut-off valves and improve the accuracy of the hazard evaluation in comparison with the risk priority coefficient method.
The Cost-Effectiveness of Lenvatinib in the Treatment of Advanced or Unresectable Hepatocellular Carcinoma from a Canadian Perspective
Authors: Meyers Brandon M. , Vogel Arndt , Marotta Paul , Kavan Petr , Kamboj Laveena , Pan Janice , Geadah Marc , Trueman David , Sabapathy Suthakar
Published: February 2021

Lenvatinib is an oral multikinase inhibitor indicated for the first-line treatment of unresectable hepatocellular carcinoma (uHCC). In the Phase III REFLECT trial, lenvatinib was noninferior in the primary endpoint of overall survival versus sorafenib, the only systemic therapy funded in Canada prior to the introduction of lenvatinib. Lenvatinib also demonstrated statistically significant improvement compared to sorafenib in secondary endpoint progression-free survival, time to progression, and objective response rate. The aim of this analysis was to estimate the cost-effectiveness of lenvatinib versus sorafenib for the first-line treatment of patients with uHCC from a Canadian perspective. A cost-utility analysis was conducted using partitioned survival modelling, with health states representing progression-free disease, progressed disease, and death. Health effects were measured using quality-adjusted life years (QALYs), and costs were represented in Canadian dollars. Clinical inputs were derived from the REFLECT trial, with outcomes extrapolated using parametric survival models. EQ-5D data collected in REFLECT were used to determine health state utility values, and estimates of resource use came from a survey of clinicians. The model predicted incremental costs of-$5,021 and incremental QALYs of 0.17, making lenvatinib dominant over sorafenib. The model demonstrates lenvatinib to be a cost-effective use of resources versus sorafenib in Canada for the treatment of uHCC. Overall costs are lower compared with sorafenib, while health benefits are greater, with modelled progression-free and overall survival extended by 4.1 and 2.6 months in the lenvatinib arm, respectively.
Finite Element Analysis of RC Beams by the Discrete Model and CBIS Model Using LS‐DYNA
Authors: Yang Seung H. , Woo Kwang S. , Kim Jeong J. , Ahn Jae S.
Published: February 2021

There are several techniques to simulate rebar reinforced concrete, such as smeared model, discrete model, embedded model, CLIS (constrained Lagrange in solid) model, and CBIS (constrained beam in solid) model. In this study, however, the interaction between the concrete elements and the reinforcement beam elements is only simulated by the discrete model and CBIS (constrained beam in solid) model. The efficiency and accuracy comparisons are investigated with reference to the analysis results by both models provided by LS‐DYNA explicit finite element software. The geometric models are created using LS‐PrePost, general purpose preprocessing software for meshing. The meshed models are imported to LS‐DYNA where the input files are then analyzed. Winfrith and CSCM concrete material options are employed to describe the concrete damage behavior. The reinforcement material model is capable of isotropic and kinematic hardening plasticity. The load versus midspan deflection curves of the finite element models correlate with those of the experiment. Under the conditions of the same level of accuracy, the CBIS model is evaluated to have the following advantages over the discrete model. First, it has the advantage of reducing the time required for FE modeling; second, saving computer CPU time due to a reduction in total number of nodes; and third, securing a good aspect ratio of concrete elements.
Stochastic Differential Game-Based Malware Propagation in Edge Computing-Based IoT
Authors: Miao Li , Li Shuai
Published: February 2021

Internet of Things (IoT) has played an important role in our daily life since its emergence. The applications of IoT cover from the traditional devices to intelligent equipment. With the great potential of IoT, there comes various kinds of security problems. In this paper, we study the malware propagation under the dynamic interaction between the attackers and defenders in edge computing-based IoT and propose an infinite-horizon stochastic differential game model to discuss the optimal strategies for the attackers and defenders. Considering the effect of stochastic fluctuations in the edge network on the malware propagation, we construct the Itô stochastic differential equations to describe the propagation of the malware in edge computing-based IoT. Subsequently, we analyze the feedback Nash equilibrium solutions for our proposed game model, which can be considered as the optimal strategies for the defenders and attackers. Finally, numerical simulations show the effectiveness of our proposed game model.
Neural Network-Based Finite-Time Fault-Tolerant Control for Spacecraft without Unwinding
Authors: Tan Chao , Xu Guodong , Dong Limin , Zhao Han , Li Jun , Zhang Sai
Published: February 2021

In this paper, we focus on solving the problems of inertia-free attitude tracking control for spacecraft subject to external disturbance, unknown inertial parameters, and actuator faults. The robust control architecture is designed by using the rotation matrix and neural networks. In the presence of external disturbance and parametric uncertainties, a fault-tolerant control (FTC) scheme synthesized with the minimum-learning-parameter (MLP) algorithm is proposed to improve the reliability of the system when unknown actuator faults occur. These methods are developed based on backstepping to ensure that finite-time convergence is achievable for the entire closed-loop system states with low computational complexity. The validity and advantage of the designed controllers are highlighted by using Lyapunov-based analysis. Finally, the simulation results demonstrate the satisfactory performance of the developed controllers.
Development and Validation of Machine Learning–based Model for the Prediction of Malignancy in Multiple Pulmonary Nodules: Analysis from Multicentric Cohorts
Authors: Chen Kezhong , Nie Yuntao , Park Samina , Zhang Kai , Zhang Yangming , Liu Yuan , Hui Bengang , Zhou Lixin , Wang Xun , Qi Qingyi , Li Hao , Kang Guannan , Huang Yuqing , Chen Yingtai , Liu Jiabao , Cui Jian , Li Mingru , Park In Kyu , Kang Chang Hyun , Shen Haifeng , Yang Yingshun , Guan Tian , Zhang Yaxiao , Yang Fan , Kim Young Tae , Wang Jun
Published: February 2021

Purpose:

Nodule evaluation is challenging and critical to diagnose multiple pulmonary nodules (MPNs). We aimed to develop and validate a machine learning–based model to estimate the malignant probability of MPNs to guide decision-making.

Experimental Design:

A boosted ensemble algorithm (XGBoost) was used to predict malignancy using the clinicoradiologic variables of 1,739 nodules from 520 patients with MPNs at a Chinese center. The model (PKU-M model) was trained using 10-fold cross-validation in which hyperparameters were selected and fine-tuned. The model was validated and compared with solitary pulmonary nodule (SPN) models, clinicians, and a computer-aided diagnosis (CADx) system in an independent transnational cohort and a prospective multicentric cohort.

Results:

The PKU-M model showed excellent discrimination [area under the curve; AUC (95% confidence interval (95% CI)), 0.909 (0.854–0.946)] and calibration (Brier score, 0.122) in the development cohort. External validation (583 nodules) revealed that the AUC of the PKU-M model was 0.890 (0.859–0.916), higher than those of the Brock model [0.806 (0.771–0.838)], PKU model [0.780 (0.743–0.817)], Mayo model [0.739 (0.697–0.776)], and VA model [0.682 (0.640–0.722)]. Prospective comparison (200 nodules) showed that the AUC of the PKU-M model [0.871 (0.815–0.915)] was higher than that of surgeons [0.790 (0.711–0.852), 0.741 (0.662–0.804), and 0.727 (0.650–0.788)], radiologist [0.748 (0.671–0.814)], and the CADx system [0.757 (0.682–0.818)]. Furthermore, the model outperformed the clinicians with an increase of 14.3% in sensitivity and 7.8% in specificity.

Conclusions:

After its development using machine learning algorithms, validation using transnational multicentric cohorts, and prospective comparison with clinicians and the CADx system, this novel prediction model for MPNs presented solid performance as a convenient reference to help decision-making.