bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross talk between LAM cells and fibroblasts may influence alveolar epithelial cell behavior in lymphangioleiomyomatosis
Authors: Clements Debbie , Miller Suzanne , Babaei-Jadidi Roya , Adam Mike , Potter S. Steven , Johnson Simon R.
Published: December 2021

Lymphangioleiomyomatosis (LAM) is a female-specific cystic lung disease in which tuberous sclerosis complex 2 (TSC2)-deficient LAM cells, LAM-associated fibroblasts (LAFs), and other cell types infiltrate the lungs. LAM lesions can be associated with type II alveolar epithelial (AT2) cells. We hypothesized that the behavior of AT2 cells in LAM is influenced locally by LAFs. We tested this hypothesis in the patient samples and in vitro. In human LAM lung, nodular AT2 cells show enhanced proliferation when compared with parenchymal AT2 cells, demonstrated by increased Ki67 expression. Furthermore, nodular AT2 cells express proteins associated with epithelial activation in other disease states including matrix metalloproteinase 7, and fibroblast growth factor 7 (FGF7). In vitro, LAF-conditioned medium is mitogenic and positively chemotactic for epithelial cells, increases the rate of epithelial repair, and protects against apoptosis. In vitro, LAM patient-derived TSC2 null cells cocultured with LAFs upregulate LAF expression of the epithelial chemokine and mitogen FGF7, a potential mediator of fibroblast-epithelial cross talk, in a mechanistic target of rapamycin (mTOR)-dependent manner. In a novel in vitro model of LAM, ex vivo cultured LAM lung-derived microtissues promote both epithelial migration and adhesion. Our findings suggest that AT2 cells in LAM display a proliferative, activated phenotype and fibroblast accumulation following LAM cell infiltration into the parenchyma contributes to this change in AT2 cell behavior. Fibroblast-derived FGF7 may contribute to the cross talk between LAFs and hyperplastic epithelium in vivo, but does not appear to be the main driver of the effects of LAFs on epithelial cells in vitro.
Effects of airway smooth muscle contraction and inflammation on lung tissue compliance
Authors: Boucher Magali , Henry Cyndi , Khadangi Fatemeh , Dufour-Mailhot Alexis , Tremblay-Pitre Sophie , Fereydoonzad Liah , Brunet David , Robichaud Annette , Bossé Ynuk
Published: December 2021

There are renewed interests in using the parameter K of Salazar–Knowles’ equation to assess lung tissue compliance. K either decreases or increases when the lung’s parenchyma stiffens or loosens, respectively. However, whether K is affected by other common features of respiratory diseases, such as inflammation and airway smooth muscle (ASM) contraction, is unknown. Herein, male C57BL/6 mice were treated intranasally with either saline or lipopolysaccharide (LPS) at 1 mg/kg to induce pulmonary inflammation. They were then subjected to either a multiple or a single-dose challenge with methacholine to activate ASM to different degrees. A quasi-static pressure-driven partial pressure-volume (P-V) maneuver was performed before and after methacholine. The Salazar–Knowles’ equation was then fitted to the deflation limb of the P-V loop to obtain K, as well as the parameter A, an estimate of lung volume (inspiratory capacity). The fitted curve was also used to derive the quasi-static elastance (Est) at 5 cmH2O. The results demonstrate that LPS and both methacholine challenges increased Est. LPS also decreased A, but did not affect K. In contradistinction, methacholine decreased both A and K in the multiple-dose challenge, whereas it decreased K but not A in the single-dose challenge. These results suggest that LPS increases Est by reducing the open lung volume (A) and without affecting tissue compliance (K), whereas methacholine increases Est by decreasing tissue compliance with or without affecting lung volume. We conclude that lung tissue compliance, assessed using the parameter K of Salazar–Knowles’ equation, is insensitive to inflammation but sensitive to ASM contraction.
Changes in the spatiotemporal pattern of spontaneous activity across a cortical column after noise trauma
Authors: Parameshwarappa V. , Pezard L. , Noreña A. J.
Published: December 2021

The present study investigates the effects of acute and chronic noise trauma on the laminar pattern of spontaneous activity in the primary auditory cortex. Our study is first to report that noise trauma alters the sequence of cortical column activation during ongoing activity. In particular, we show that the supragranular layer becomes a major input recipient and the synaptic activity in the infragranular layers is enhanced.
BDNF polymorphism and interhemispheric balance of motor cortex excitability: a preliminary study
Authors: Dubbioso Raffaele , Pellegrino Giovanni , Ranieri Federico , Di Pino Giovanni , Capone Fioravante , Dileone Michele , Iodice Rosa , Ruggiero Lucia , Tozza Stefano , Uncini Antonino , Manganelli Fiore , Di Lazzaro Vincenzo
Published: December 2021

BDNF Val66Met polymorphism might influence interhemispheric balance of motor cortex excitability. Specifically, Val/Val carriers display higher excitability of the left compared with the right primary motor cortex, whereas Met carriers do not show any significant corticomotor excitability imbalance. These preliminary results are relevant to understanding aberrant interhemispheric excitability and excitation/inhibition balance in neurological disorders.
Increased upper-limb sensory attenuation with age
Authors: Parthasharathy Manasa , Mantini Dante , Orban de Xivry Jean-Jacques
Published: December 2021

Forces generated externally (by the environment on the participant) and internally (by the participant on her/his body) are not perceived with the same intensity. Internally generated forces are perceived less intensely than externally generated ones. This difference in force sensation has been shown to be higher in elderly participants when the forces were applied on the fingers because of their impaired proprioception. Here we replicated this finding for the arm but suggest that it is unlikely to be linked to impaired proprioception.
Evaluation of Motor Complications in Parkinson’s Disease: Understanding the Perception Gap between Patients and Physicians
Authors: Ogura Hiromu , Nakagawa Ryoko , Ishido Miwako , Yoshinaga Yoko , Watanabe Jun , Kurihara Kanako , Hayashi Yuka , Nagaki Koichi , Mishima Takayasu , Fujioka Shinsuke , Tsuboi Yoshio
Published: December 2021

Background. Patients with Parkinson’s disease (PD) receiving levodopa treatment often report motor complications including wearing-off (WO), dyskinesia, and morning akinesia. As motor complications are associated with a decrease in patients’ quality of life (QoL), it is important to identify their occurrence and commence immediate management. This study investigated whether differences in the perception of motor complications exist between patients and their physicians in routine clinical practice. Methods. After an Internet-based screening survey, questionnaires were distributed to physicians and their patients in Japan. The 9-item Wearing-Off Questionnaire (WOQ-9) was used to objectively assess the presence of WO; patients with WOQ-9 scores ≥2 were considered to have WO. McNemar’s test was used to compare physician assessment versus WOQ-9 scores, patient self-awareness versus physician assessment, and patient self-awareness versus WOQ-9, separately. Morning akinesia and dyskinesia were assessed by both physician assessment and patient self-awareness with McNemar’s test. QoL was assessed using the 8-item Parkinson’s Disease Questionnaire (PDQ-8) with the Wilcoxon rank-sum test. Results. A total of 235 patients with PD and their 92 physicians participated in this survey. A significant discordance was observed between the WOQ-9 and physician assessment of WO (67.2% vs 46.0%;

p
<
0.0001

). Furthermore, patient self-awareness of WO was 35.3% (

p
=
0.0004

, vs physician). Morning akinesia (patient, 58.7%; physician, 48.9%;

p
=
0.0032

), dyskinesia (patient, 34.0%; physician, 23.4%;

p
=
0.0006

), and bodily discomfort (patient, 25.0; physician, 0.0;

p
=
0.0102

) of QoL were underrecognized by physicians. Conclusions. This study investigated differences in the perception of WO between patients with PD and their physicians in routine clinical practice and highlighted that patients have a low awareness of the symptoms of WO compared with physician assessments and WOQ-9. Conversely, morning akinesia, dyskinesia, and bodily discomfort were underrecognized by physicians.
Robust Adaptive Self‐Structuring Neural Network Bounded Target Tracking Control of Underactuated Surface Vessels
Authors: Liu Haitao , Lin Jianfei , Yu Guoyan , Yuan Jianbin
Published: December 2021

This paper studies the target‐tracking problem of underactuated surface vessels with model uncertainties and external unknown disturbances. A composite robust adaptive self‐structuring neural‐network‐bounded controller is proposed to improve system performance and avoid input saturation. An extended state observer is proposed to estimate the uncertain nonlinear term, including the unknown velocity of the tracking target, when only the measurement values of the line‐of‐sight range and angle can be obtained. An adaptive self‐structuring neural network is developed to approximate model uncertainties and external unknown disturbances, which can effectively optimize the structure of the neural network to reduce the computational burden by adjusting the number of neurons online. The input‐to‐state stability of the total closed‐loop system is analyzed by the cascade stability theorem. The simulation results verify the effectiveness of the proposed method.
[Retracted] A Robust and Novel Approach for Brain Tumor Classification Using Convolutional Neural Network
Authors: Tazin Tahia , Sarker Sraboni , Gupta Punit , Ayaz Fozayel Ibn , Islam Sumaia , Monirujjaman Khan Mohammad , Bourouis Sami , Idris Sahar Ahmed , Alshazly Hammam
Published: December 2021

Brain tumors are the most common and aggressive illness, with a relatively short life expectancy in their most severe form. Thus, treatment planning is an important step in improving patients’ quality of life. In general, image methods such as computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound images are used to assess tumors in the brain, lung, liver, breast, prostate, and so on. X‐ray images, in particular, are utilized in this study to diagnose brain tumors. This paper describes the investigation of the convolutional neural network (CNN) to identify brain tumors from X‐ray images. It expedites and increases the reliability of the treatment. Because there has been a significant amount of study in this field, the presented model focuses on boosting accuracy while using a transfer learning strategy. Python and Google Colab were utilized to perform this investigation. Deep feature extraction was accomplished with the help of pretrained deep CNN models, VGG19, InceptionV3, and MobileNetV2. The classification accuracy is used to assess the performance of this paper. MobileNetV2 had the accuracy of 92%, InceptionV3 had the accuracy of 91%, and VGG19 had the accuracy of 88%. MobileNetV2 has offered the highest level of accuracy among these networks. These precisions aid in the early identification of tumors before they produce physical adverse effects such as paralysis and other impairments.
Compressed Firmware Classification Based on Extra Trees and Doc2Vec
Authors: Qiu Jing , Geng Xiaoxu , Sun Guanglu
Published: December 2021

Firmware formats vary from vendor to vendor, making it difficult to track which vendor or device the firmware belongs to, or to identify the firmware used in an embedded device. Current firmware analysis tools mainly distinguish firmware by static signatures in the firmware binary code. However, the extraction of a signature often requires careful analysis by professionals to obtain it and requires a significant investment of time and effort. In this paper, we use Doc2Vec to extract and process the character information in firmware, combine the file size, file entropy, and the arithmetic mean of bytes as firmware features, and implement the firmware classifier by combining the Extra Trees model. The evaluation is performed on 1,190 firmware files from 5 router vendors. The accuracy of the classifier is 97.18%, which is higher than that of current approaches. The results show that the proposed approach is feasible and effective.
Gender Was Associated with Depression but Not with Gastrointestinal Dysfunction in Patients with Parkinson’s Disease
Authors: Xiao-ling Qin , Yin-zhen Du , Xue-kui Liu , Xue Li , Gang Cheng , Zai-li Li , Dian-shuai Gao
Published: December 2021

Objective. To investigate the association between gender and gastrointestinal (GI) dysfunctions, as well as gender and other motor symptoms/nonmotor symptoms, in a sample of PD patients. Methods. 186 patients with PD were recruited into this study and divided into male PD group (M-PD) and female PD group (FM-PD). Demographic and PD-related clinical information of the participants were collected by the same neurologist. PD patients were objectively assessed by a spectrum of rating scales of motor symptoms and nonmotor symptoms (including GI dysfunctions). The data were analyzed by SPSS 20 statistical software. Results. Totally 95 cases (51.08%) were in the M-PD group and 91 cases (48.92%) in the FM-PD group. There were no significant differences in age, BMI, and lifestyles between the two groups (P > 0.05). Males had higher educational level (P = 0.002). Females were more likely to have early satiety and loss of appetite (P = 0.025, P = 0.001). There were no significant differences in LED disease duration, age of motor symptoms onset, types of motor symptoms onset, location of motor symptoms onset, and phenotype of motor symptoms between the two groups (P > 0.05). Females had significantly higher UPDRS-III and HAMD scores than males (P = 0.037, P = 0.034). There were no significant differences in PQSI, ESS, RLS, RBD, HAMA, HAMD, and MoCA scores between the two groups. Gender was associated with HAMD (OR = 0.682, P = 0.019). Conclusions. Gender is a risk factor for depression, but not for GI dysfunctions in patients with PD.
Preconditioned Conjugate Gradient Algorithm‐Based 2D Waveform Inversion for Shallow‐Surface Site Characterization
Authors: Guan Jianbo , Li Yu , Liu Guohua
Published: December 2021

The full‐waveform inversion (FWI) of a Love wave has become a powerful tool for shallow‐surface site characterization. In classic conjugate gradient algorithm‐ (CG) based FWI, the energy distribution of the gradient calculated with the adjoint state method does not scale with increasing depth, resulting in diminished illumination capability and insufficient model updating. The inverse Hessian matrix (HM) can be used as a preprocessing operator to balance, filter, and regularize the gradient to strengthen the model illumination capabilities at depth and improve the inversion accuracy. However, the explicit calculation of the HM is unacceptable due to its large dimension in FWI. In this paper, we present a new method for obtaining the inverse HM of the Love wave FWI by referring to HM determination in inverse scattering theory to achieve a preconditioned gradient, and the preconditioned CG (PCG) is developed. This method uses the Love wave wavefield stress components to construct a pseudo‐HM to avoid the huge calculation cost. It can effectively alleviate the influence of nonuniform coverage from source to receiver, including double scattering, transmission, and geometric diffusion, thus improving the inversion result. The superiority of the proposed algorithm is verified with two synthetic tests. The inversion results indicate that the PCG significantly improves the imaging accuracy of deep media, accelerates the convergence rate, and has strong antinoise ability, which can be attributed to the use of the pseudo‐HM.
Wireless Pressure Sensor Assisted Orthopedic Nursing Effectiveness Evaluation
Authors: Wang Qiufang , Shen Yumei
Published: December 2021

This paper combines flexible pressure sensing technology, wireless sensor network, and cloud platform technology to design and manufacture a medical miniature pressure sensor and its supporting system. The problem of noninvasive monitoring of the syndrome encountered in the clinic is used for real‐time monitoring and auxiliary diagnosis of the disease. Different from the current clinical use of “puncture” to measure intrafascial pressure, this system focuses on the noninvasive monitoring of compartment syndrome, using medical tape to paste a flexible microsensing unit on the injured area. The flexible sensor unit can measure the pressure here in real time and then can know the pressure in the fascia chamber. The flexible pressure sensor unit combines with the subsequent flexible circuit to send the measured data to the data in real time through wireless communication. The data aggregation node transmits the collected data to the upper computer through serial communication, and the upper computer software processes and stores the data and uploads it to the cloud server. In this experiment, it was observed that the concentrations of Ca and P showed the same fluctuating trend. With the gradual progress of the stretch, the concentrations of Ca and P increased with the increase in time, reaching approximately at the end of the extension. The peak value indicates that the osteoclast activity is enhanced at this time, the bone matrix is largely destroyed, and the Ca and P in the matrix are released into the serum in a large amount, thereby increasing the serum concentration. After the distraction ceases, it enters the healing period of the callus. At this time, the concentrations of Ca and P decrease with the increase in time and gradually reach a stable level, indicating that the osteoblast activity is enhanced at this time, the bone matrix begins to rebuild, and the Ca and P gradually increase. The deposited bone matrix gradually forms new bone and finally reaches a balance. Since the speed of extension in each experimental group is inconsistent, the time required to reach the same extension length is also inconsistent, so that the peak time is also inconsistent. After plotting the stress difference (△F) before and after stretching against time and speed, it is found that the relationship is linear. However, these two variables affect △F at the same time, so they cannot be isolated. Based on this, this subject uses multiple regression equations to fit the three relationships of stress difference (△F), time, and speed. In the process of distraction osteogenesis, with each distraction, the bone stress presents a trend from high to low. And as the stretch progresses, the measured stress value increases linearly at the same time point every day.
Remote-Sensing Image Tile-Level Annotation Based on Discriminative Features and Expressive Visual Word Descriptors
Authors: Xue Jiaming , Xiong Shun , Men Chaoguang , Liu Zhiming , Liu Yongmei
Published: December 2021

Remote-sensing images play a crucial role in a wide range of applications and have been receiving significant attention. In recent years, great efforts have been made in developing various methods for intelligent interpretation of remote-sensing images. Generally speaking, machine learning-based methods of remote-sensing image interpretation require a large number of labeled samples and there are still not enough annotated datasets in the field of remote sensing. However, manual annotation of remote-sensing images is usually labor-intensive and requires expert knowledge and the accuracy of annotation results is relatively low. The goal of this paper is to propose a novel tile-level annotation method of remote-sensing images to obtain remote-sensing datasets which are well-labeled and contain accurate semantic concepts. Firstly, we use a set of images with defined semantic concepts to represent the training set and divide them into several nonoverlapping regions. Secondly, the color features, texture features, and spatial features of each region are extracted, and discriminative features are obtained by the weight optimization feature fusion method. Then, the features are quantized into visual words by applying a density-based clustering center selection method and an isolated feature point elimination method. And the remote-sensing images can be represented by a series of visual words. Finally, the LDA model is used to calculate the probabilities of semantic categories for each region. The experiments are conducted on remote-sensing images which demonstrate that our proposed method can achieve good performance on remote-sensing image tile-level annotation. The implications of our research can obtain annotated datasets with accurate semantic concepts for intelligent interpretation of remote-sensing images.
A Study of Two‐Way Short‐ and Long‐Term Memory Network Intelligent Computing IoT Model‐Assisted Home Education Attention Mechanism
Authors: Ma Suling
Published: December 2021

This paper analyzes and collates the research on traditional homeschooling attention mechanism and homeschooling attention mechanism based on two‐way short‐ and long‐term memory network intelligent computing IoT model and finds the superiority of two‐way short‐ and long‐term memory network intelligent computing IoT model. The two‐way short‐ and long‐term memory network intelligent computing IoT model is improved and an improved deep neural network intelligent computing IoT is proposed, and the improved method is verified based on discrete signal homeschooling classification experiments, followed by focusing on the application research of the two‐way short‐ and long‐term memory network intelligent computing IoT model‐assisted homeschooling attention mechanism. Learning based on neural network, human behavior recognition method combining spatiotemporal networks, a homeschooling method integrating bidirectional short‐ and long‐term memory networks and attention mechanisms is designed. The visual attention mechanism is used to add weight information to the deep visual features extracted by the convolutional neural network, and a new feature sequence incorporating salient attention weights is output. This feature sequence is then decoded using an IndRNN independent recurrent neural network to finally classify and decide on the homeschooling category. Experiments on the UCF101 dataset demonstrate that the incorporation of the attention mechanism can improve the ability of the network to classify. The attention mechanism can help the intelligent computing IoT model discover key features, and the self‐attention mechanism can effectively capture the internal features of homeschooling and optimize the feature vector. We propose the strategy of combining the self‐attention mechanism with a bidirectional short‐ and long‐term memory network to solve the family education classification problem and experimentally verify that the intelligent computing IoT model combined with the self‐attention mechanism can more easily capture the interdependent features in family education, which can effectively solve the family education problem and further improve the family education classification accuracy.
Prevalence and Trajectory of COVID-19-Associated Hypercoagulability Using Serial Thromboelastography in a South African Population
Authors: van Blydenstein Sarah Alexandra , Menezes Colin Nigel , Miller Nicole , Johnson Naomi , Pillay Bavinash , Jacobson Barry F. , Omar Shahed
Published: December 2021

Introduction. The coagulation abnormalities resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been attributed to inflammation and subsequent cytokine storm. Thromboelastography (TEG) is a point-of-care test used to assess clot formation and degradation in whole blood and is an indicator of the overall real-time coagulopathic state of the patient. Methods. A single-centre, prospective, observational cohort study was conducted in South Africa, analysing the coagulation patterns of 41 patients with hypoxia related to SARS-CoV-2 using serial thromboelastography (TEG) on admission, after 48 hours, and at resolution of hypoxia/day 10. Results: Two-thirds (n = 26) were women. The median age was 61 (IQR 50–67), and the majority (88%) were Black patients. Almost half (22) of the patients were critically ill and ventilated, with median SOFA and SAPS2 scores of 3 and 22 (IQR2-4 and 18–30), respectively. The prevalence of hypercoagulability was 0.54 (95% CI 0.46–0.62), whilst 29/41 (0.71, CI 0.64–0.78)) met the definition of hypofibrinolysis. Differences between the hypercoagulable (HC) and non-hypercoagulable groups remained apparent at 48 hours after anticoagulation. At this time point, the K time was significantly lower (

p

 ˂ 0,01), and the α-angle (

p

 ˂ 0,01) and maximum amplitude (MA) (

p

 ˂ 0,01) were significantly higher in the HC cohort. At resolution of hypoxia, or day 10, only MA was significantly higher in the hypercoagulable group compared to the non-hypercoagulable group (p = 0.01). The initial impairment in fibrinolysis (Ly30), α angle, and MA were significantly associated with mortality, with p values of 0.006, 0.031, and 0.04, respectively. Conclusions. In this South African population, hypercoagulability was a highly prevalent phenomenon in COVID-19 disease. It was typified by hypofibrinolysis and a persistently elevated MA, despite anticoagulation therapy.
VX765, a Specific Caspase‐1 Inhibitor, Alleviates Lung Ischemia Reperfusion Injury by Suppressing Endothelial Pyroptosis and Barrier Dysfunction
Authors: Wu Siyi , Li Zhao , Ye Mengling , Liu Chunxia , Liu Hao , He Xiaojing , Qin Yi , Liang Fangte , Pan Linghui , Lin Fei
Published: December 2021

Lung ischemia reperfusion injury (LIRI) is a complex pathophysiological process with high morbidity and mortality. An important pathophysiological characteristic of LIRI is endothelial barrier dysfunction, although the mechanism involved in this process remains unclear. VX765, a specific caspase‐1 inhibitor, has been shown to have a protective effect against several diseases including sepsis, atherosclerosis, and glial inflammatory disease. The objective of this study was to determine whether VX765 had a protective effect in LIRI. The results showed that lung ischemia/reperfusion (I/R) and oxygen/glucose deprivation and reoxygenation (OGD/R) induced endothelial pyroptosis and barrier dysfunction characterized by an inflammatory response. Treatment with VX765 successfully alleviated I/R‐ and OGD/R‐induced endothelial pyroptosis and barrier dysfunction by inhibiting caspase‐1 in vivo and in vitro. In conclusion, these findings showed that VX765 provided effective protection against lung I/R‐induced endothelial pyroptosis and barrier dysfunction.
Hepatoprotective Effects of (−) Epicatechin in CCl4-Induced Toxicity Model Are Mediated via Modulation of Oxidative Stress Markers in Rats
Authors: Alkinani Khadijah B. , Ali Ehab M. M. , Al-Shaikh Turki M. , Awlia Khan Jalaluddin A. , Al-naomasi Tahani M. , Ali Soad S. , Abduljawad Asaad A. , Mosa Osama F. , Zafar Tariq A.
Published: December 2021

Objective. (−) Epicatechin (EP) is a naturally occurring antioxidant flavonoid found in some green plants. The current study was designed to evaluate the potential role of antioxidant mechanisms in the hepatoprotective properties of EP using the carbon tetrachloride (CCl4)-induced acute liver injury model. Materials and Methods. Rats (n = 7 per group) were divided into five groups including control group, (−) epicatechin group (20 mg·kg−1 body weight), CCl4 group (1 mL−1 body weight), CCl4-EP treatment group, and CCl4-silymarin (SILY) group. The levels of enzymes including hepatic malondialdehyde (MDA), glutathione (GSH), catalase (CAT), glutathione S-transferase (GST), nitric oxide synthase (NOS), glutathione peroxidase (GPx), and cytochrome P450 (CYP450) were analyzed via enzyme-linked immunosorbent assay (ELISA). Histological studies were performed on all groups to assess the regenerative effects of test sample and compare it with the control group. Results. Test compound EP and standard drug silymarin (SILY) considerably reduced liver function enzyme levels in the blood, which were raised by CCl4 administration, and increased serum albumin and total protein (TP) concentrations. The hepatic malondialdehyde (MDA) level was considerably declined, whereas glutathione (GSH), catalase (CAT), glutathione S-transferase (GST), nitric oxide synthase (NOS), glutathione peroxidase (GPx), and cytochrome P450 (CYP450) levels were upregulated in the EC-treated groups. The hepatoprotective results of the study were further confirmed via the histological assessments, which indicated a regeneration of the damaged hepatic tissue in treated rats. Conclusions. The results of this study revealed a significant protective efficacy of EP against CCl4-induced liver injury, which was potentially mediated via upregulation of antioxidant enzymes and direct scavenging effects of the compound against free radicals.
Network Pharmacology and Molecular Docking Analyses of Mechanisms Underlying Effects of the Cyperi Rhizoma-Chuanxiong Rhizoma Herb Pair on Depression
Authors: Shi Yanan , Chen Mingqi , Zhao Zehua , Pan Juhua , Huang Shijing
Published: December 2021

Objective. We aimed to investigate the mechanisms underlying the effects of the Cyperi Rhizoma-Chuanxiong Rhizoma herb pair (CCHP) against depression using a network pharmacology approach. Methods. A network pharmacology approach, including screening of active compounds, target prediction, construction of a protein-protein interaction (PPI) network, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and molecular docking, molecular dynamics (MD) simulations, and molecular mechanics Poisson–Boltzmann surface area (MMPBSA), were used to explore the mechanisms of CCHP against depression. Results. Twenty-six active compounds and 315 and 207 targets of CCHP and depression, respectively, were identified. The PPI network suggested that AKT1, IL-6, TP53, DRD2, MAPK1, NR3C1, TNF, etc., were core targets. GO enrichment analyses showed that positive regulation of transcription from RNA polymerase II promoter, plasma membrane, and protein binding were of great significance. Neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway, dopaminergic synapse, and mTOR signaling pathway were important pathways. Molecular docking results revealed good binding affinities for the core compounds and core targets. MD simulations and MMPBSA validated that quercetin can stably bind to 6hhi. Conclusions. The effects of CCHP against depression involve multiple components, targets, and pathways, and these findings will promote further research on and clinical application of CCHP.
5G Multimedia Precision Marketing Based on the Improved Multisensor Node Collaborative Filtering Recommendation Algorithm
Authors: Si Kai , Zhou Min , Qiao Yingfang
Published: December 2021

The rapid development of web technology has brought new problems and challenges to the recommendation system: on the one hand, the traditional collaborative filtering recommendation algorithm has been difficult to meet the personalized recommendation needs of users; on the other hand, the massive data brought by web technology provides more useful information for recommendation algorithms. How to extract features from this information, alleviate sparsity and dynamic timeliness, and effectively improve recommendation quality is a hot issue in the research of recommendation system algorithms. In view of the lack of an effective multisource information fusion mechanism in the existing research, an improved 5G multimedia precision marketing based on an improved multisensor node collaborative filtering recommendation algorithm is proposed. By expanding the input vector field, the features of users’ social relations and comment information are extracted and fused, and the problem of collaborative modelling of these two kinds of important auxiliary information is solved. The objective function is improved, the social regularization term and the internal regularization term in the vector domain are analysed and added from the perspective of practical significance and vector structure, which alleviates the overfitting problem. Experiments on a large number of real datasets show that the proposed method has higher recommendation quality than the classical and mainstream baseline algorithm.
Efficacy and Safety of Chuanxiong Qingnao Granule in Patients with Migraine: A Randomized, Double-Blind, Placebo-Controlled Trial
Authors: Li Yi-Fan , Hu Hui-Min , Wang Bo-Ning , Zhang Yi , Liu Xing , Mao Peng , Fan Bi-Fa
Published: December 2021

Objective. To evaluate the efficacy and safety of Chuanxiong Qingnao Granule (CQG) to treat migraine. Method. This study was a randomized, double-blind, placebo-controlled trial. All migraineurs were recruited and randomly assigned into a treatment group treated with CQG and a control group treated with a placebo. The whole research process included a 4-week baseline, 12-week intervention, and 12-week follow-up. The primary outcome was responder rate, defined as the percentage of migraineurs with 50% or more reduction in the frequency of migraine attack during treatment and posttreatment period compared with the baseline. The secondary outcomes were the number of migraine days, migraine attack frequency, visual analogue scale (VAS), Fatigue Severity Scale (FSS), Hamilton Depression Scale (HAMD), and Migraine Disability Assessment (MIDAS). Results. A total of 346 migraineurs completed the research and were included in the intention-treatment analyses. The response rates differed significantly between the treatment group and the control group (71.5% vs. 12.1% at week 12 and 83.1% vs. 3.4% at week 24). Attack frequency, days of headache attack, VAS, FSS, HAMD, and MIDAS decreased at week 12 in both groups with more reduction in the treatment group (

P
<
0.001

). No severe adverse events were observed in this trial. Conclusion. Chuanxiong Qingnao Granule can significantly improve headache symptoms in patients with migraine while improving disability, fatigue, and depression with a good safety profile.
Digital Media Art Communication Based on Wireless Cooperative Routing with Minimum Energy Consumption
Authors: Song Shuli
Published: December 2021

Wireless cooperative routing algorithm transmits the data collected in the target area to users, so that users can obtain monitoring information timely and accurately. In the traditional low‐power adaptive clustering hierarchical routing protocol, the process of building clusters is random, the resources of nodes are not fully utilized, the node death speed is fast, the network life cycle is short, and the performance is not stable enough. In addition, the route maintenance process is cumbersome and will occupy a lot of bandwidth. In order to solve the problems of real‐time transmission of digital media art communication data and network lifetime optimization, a wireless cooperative routing algorithm based on minimum energy consumption is proposed. The facts of transmission strength consumption, node residual strength, and minimal information transmission extension are analyzed, a new weight feature is proposed, and a multipath statistics routing scheme is developed by using the usage of the minimal strength consumption. All digital media art propagation sensor nodes transmit data to sink nodes along multiple transmission paths. Simulation results show that the algorithm can prolong the network lifetime, reduce and balance the node energy consumption, reduce the data transmission delay, reduce the energy consumption of wireless cooperative routing based on the minimum energy consumption by 64.5%, and increase the number of compressed images by 182%.
Experimental and Numerical Simulation of Coal Rock Impact Energy Index Based on Peridynamics
Authors: He Feng , Ren Tianjiao , Yang Song , Bian Hongjie
Published: December 2021

In response to the increasing severity of the rock burst phenomenon and its relatively difficult prediction, peridynamics and indoor uniaxial compression experiments were used to calculate the changes of the internal elastic energy (t) and impact energy (c) for different rock masses during a loading process from an energy perspective. Two traditional indices for judging rock burst tendency—the rock elastic deformation energy index (WET) and the rock impact energy index (WCF)—were combined to define a new actual impact energy index (W) to more accurately determine the occurrence tendency of rock bursts. The LAMMPS software was used to simulate the internal energy changes of rock materials under pressure, and the results were compared with experimental results for verification. The results were as follows: (1) in the uniaxial compression experiments of different specimens, fine sandstone had the strongest impact resistance, followed by coarse sandstone, mudstone, bottom coal seam, and top coal seam, and the obtained material properties provide a reference for predicting the rock bursts of various rock types in practical engineering. (2) The values calculated using the actual impact energy index (W) and the simulation value were 1.75 and 1.77, respectively, which corresponded to a lower error than when the rock impact energy index (WCF) and the rock elastic deformation energy index (WET) were used individually. Thus, this index can better predict the rock burst. (3) The simulated specimen was subjected to a gradual increase in the internal stored elastic energy during compression, which gradually decreased after the ultimate compressive strength was exceeded. The degree of impact damage formed after macroscopic crushing occurred depended on its residual energy.
Relationship between High Expression of Kaiso Protein and Poor Prognosis of Lung Cancer and the Regulation Mechanism of Malignant Phenotype of Lung Cancer Cells
Authors: Zhu Shasha , Zhou Ning , Ding Ning , Li Shanshan , Liu Xiaoxing , Ren Guangming , Li Qingling , Zhou Min
Published: December 2021

In this study, Kaiso was discovered to be a unique member of the POZ-zinc fingers family of transcription factors, which has been implicated in the genesis and progression of cancer. Although there is still some debate, Kaiso is believed to be implicated in the development of human cancer. It should be noted that there is minimal evidence available on the therapeutic relevance of nuclear Kaiso in lung cancer in humans. Histone or DNA modifications that control gene activity outside of the underlying sequence are examples of epigenetic alternations. Epigenetic alterations are heritable but reversible. Human illness, such as lung cancer, is often related to epigenetic dysregulation. In preclinical and clinical studies, epigenetic-targeted therapy has shown significant therapeutic promise for solid tumours and has been used in the treatment of haematological malignancies using different medicines targeting epigenetic regulators. It is important to note that the abnormal activities of Kaiso enzymes in tumour growth are summarised below and the development of inhibitors or medicines targeting epigenetic enzyme regulation is highlighted.
Software Knowledge Entity Relation Extraction with Entity-Aware and Syntactic Dependency Structure Information
Authors: Tang Mingjing , Li Tong , Wang Wei , Zhu Rui , Ma Zifei , Tang Yahui
Published: December 2021

Software knowledge community contains a large scale of software knowledge entities with complex structure and rich semantic relations. Semantic relation extraction of software knowledge entities is a critical task for software knowledge graph construction, which has an important impact on knowledge graph based tasks such as software document generation and software expert recommendation. Due to the problems of entity sparsity, relation ambiguity, and the lack of annotated dataset in user-generated content of software knowledge community, it is difficult to apply existing methods of relation extraction in the software knowledge domain. To address these issues, we propose a novel software knowledge entity relation extraction model which incorporates entity-aware information with syntactic dependency information. Bidirectional Gated Recurrent Unit (Bi-GRU) and Graph Convolutional Networks (GCN) are used to learn the features of contextual semantic representation and syntactic dependency representation, respectively. To obtain more syntactic dependency information, a weight graph convolutional network based on Newton’s cooling law is constructed by calculating a weight adjacency matrix. Specifically, an entity-aware attention mechanism is proposed to integrate the entity information and syntactic dependency information to improve the prediction performance of the model. Experiments are conducted on a dataset which is constructed based on texts of the StackOverflow and show that the proposed model has better performance than the benchmark models.
Variable-Order Fractional Diffusion Model-Based Medical Image Denoising
Authors: Abirami A. , Prakash P. , Ma Y.-K.
Published: December 2021

Fractional differential models are playing a vital role in many applications such as diffusion, probability potential theory, and scattering theory. In this study, the variable-order space and time fractional diffusion model is employed for denoising the medical images. The finite difference approach is implemented to find the numerical solution of the proposed model. Convergence and stability of the numerical method are presented. The experimental outcomes of the variable-order model are analyzed with those of the fractional and integer-order diffusion models. It was noticed that the peak signal-to-noise ratio (PSNR) value is increased considerably for the proposed model.
Diagnostic Value of Prenatal Ultrasound Parameters and Esophageal Signs in Pouch and Lower Thoracic Segment in Fetuses with Esophageal Atresia
Authors: Feng Wenjun
Published: December 2021

In order to investigate the diagnostic value of prenatal ultrasound parameters and signs of pouch and lower thoracic esophagus in the fetus with esophageal atresia (EA), the prenatal ultrasound data of 35 EA fetuses (observation group) confirmed by autopsy after induced labor or postnatal surgery and imaging examination in our hospital from May 2019 to May 2021 were retrospectively analyzed and compared with 35 normal postnatal fetuses (control group). General information and prenatal ultrasound parameters of the two groups, including head circumference (HC), abdominal circumference (AC), double parietal diameter (BPD), fetal body weight (EFW), and signs (small or unmanifested gastric vesicles, amniotic fluid, neck or upper chest pouch, lower chest esophagus not visible), were analyzed using logistic regression. The logistic multifactor regression model for EA diagnosis was established, and the diagnostic value for EA was analyzed. As a result, the HC, AC, and EFW of the observation group were lower than those of the control group, the gastric bubbles were small or not displayed, the amniotic fluid was more, and the signs of neck or upper chest pouch and lower chest esophagus were not visible in the observation group (

P
<
0.05

). Logistic regression analysis showed that decreased ultrasound parameters HC, AC, EFW, small or no gastric bubble, amniotic fluid, neck or upper chest pouch, and no visible signs of lower chest esophagus were all risk factors for EA (

P
<
0.05

). And in the prenatal ultrasound diagnostic model of EA was established, logistic

P

=
−
19.851
+
HC
×
0.384
+
AC
×
0.682
+
EFW
×
0.695
+
small
 
or
 
no
 
gastric
 
vesicle
×
3.747
+
amniotic
 
fluid
×
3.607
+
cervical
 
or
 
upper
 
chest
 
sac
×
4.104
+
invisible
 
lower
 
thoracic
 
esophagus
×
4.623

.When logistic

P

>
0.468

, AUC was 0.891,

χ
2

was 7.764, diagnostic sensitivity was 91.24%, and specificity was 79.22%. To draw a conclusion, prenatal ultrasound parameters and signs are of great value in the diagnosis of EA. Independent influencing factors of EA include small or no HC, AC, EFW and gastric vesicles, polyhydramnios, neck or upper chest pouch, and invisible lower thoracic esophagus. Logistic multifactor regression model has a high coincidence rate for the prenatal diagnosis of EA, providing a basis for clinical decision-making.
Water Pollution Prediction Based on Deep Belief Network in Big Data of Water Environment Monitoring
Authors: Liang Li
Published: December 2021

Aiming at the problems that the traditional water quality prediction model is generally not high in prediction accuracy and robustness, a water pollution prediction using deep learning in water environment monitoring big data is proposed. Objective. To optimize and improve the prediction accuracy of the water quality prediction model. Firstly, in the water environment monitoring system, the Internet of Things big data technology is used to accurately sense and monitor the real-time data of sewage treatment equipment and sewage quality. Then, the deep belief network (DBN) is used to build the water pollution prediction model, and the collected sewage treatment data is analyzed to predict the water quality status. Finally, particle swarm optimization algorithm is used to dynamically optimize the number of hidden layer neural units and learning rate in the DBN prediction model, which makes the prediction results more scientific and accurate. Based on the sampling data of Shanghai Jinze Reservoir, the proposed model is experimentally analyzed. The results show that the probability of accurate location of the pollution source is not less than 70%. And under the two indicators of chemical oxygen demand and biological oxygen demand, the root mean square error and correlation coefficient are 3.073, 0.9892 and 1.958, 0.9565, respectively, which are better than other comparison models.
Experimental Investigation on the Propagation of Hydraulic Fractures through Coal‐Rock Interfaces
Authors: Wu Pengfei , Wang Jianlong , Luo Xiaofei , Mo Rujun , Hu Yaoqing , He Wei
Published: December 2021

Although hydraulic fracturing has been one of the primary stimulation methods for coal‐bed methane (CBM) exploration, it is difficult to be applied in soft and low‐permeability coal seams due to the instability of wells in such geological structures. In order to solve the problem, an idea of indirect fracturing is proposed, that is, fractures are initiated in stable and hard rocks and then propagated to coal seams in which crack networks can be formed. To verify the feasibility of such an approach, the true triaxial hydraulic fracturing experiments were conducted using two‐dimensional and three‐dimensional coal‐rock combination samples, respectively. This study investigates the fracture patterns, pressure variation, and fracture morphology. The results show that in the process of fracture propagation from sandy mudstones to coals, the strain energy release rate in the sandy mudstones is 10.69∼25.53 times greater than that in the coal. When the fracture has a tendency to deflect toward the lower strength coal strata, under the condition of large K2/K1, the deflection criterion will be met first and the fracture will deflect and grow into the coal strata. In addition, the complex crack network can be generated when the hydrofracture intersects the coal‐rock interface and the fracture pattern is analyzed.