bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Traditional Process Methods on the Physicochemical and Functional Properties of a Traditional Food Salt (Nikkih) Obtained from Waste Biomass Peels of Musa paradisiaca and Musa acuminate
Authors: Ngwasiri Pride Ndasi , Adanmengwi Vivian Akah , Ambindei Wilson Agwanande , Ngangmou Noumo Thierry , Fonmboh Dobgima John , Ngwabie Ngwa Martine , Ngassoum Martin Benoit , Aba Ejoh Richard
Published: December 2021

In Cameroon, agrofood waste biomass such as peels of Musa paradisiaca and Musa acuminate is being valorized using various traditional processing methods to produce a traditional functional food salt, potash, locally called nikkih. Nikkih has been reported to have varying physicochemical and functional properties, which negatively affect the quality and stability of food prepared using it. This work aims at evaluating the effect of traditional process methods on the physicochemical and functional properties of nikkih produced from these peels in view of the optimization of the process. The peels were preprocessed using two methods: boiling at 90oC before drying and direct drying of raw samples. All samples were dried and combusted to ash at varying temperatures of 250oC, 300o C, and 350oC and times of 30 min, 60 min, and 90 min. The ash obtained was dissolved in varied volumes of water, filtered to obtain the nikkih. Yellow achu soup was prepared through the dry gum method using water and read palm oil, with nikkih as emulsifier. The physicochemical and functional properties of nikkih on yellow achu soup were evaluated using standard methods. The ash yield ranged from 10.62 ± 0.12% to 7.10 ± 0.05%, with the raw samples combusted at 3000C and 2500C having the highest and lowest values respectively. The pH of nikkih ranged from 10.95 ± 0 to 12.01 ± 0.056 while potash content ranged from 32.45 ± 0.905% to 72.29 ± 1.31%, with the highest and lowest values obtained from the raw sample combusted at 2500C and the boiled samples combusted at 3500C respectively. Alkaline content ranged from 61.7 ± 0.141% to 52.8 ± 0.141%, with boiled M. acuminate combusted at 3500C having the highest value and the lowest from raw M. paradisiaca combusted at 2500C. The foaming capacity and foam stability ranged from 6.9 ± 0.01% to 16.07 ± 2.51% and from 3.20 ± 0.07% to 11.205 ± 2.39% for M. acuminate and M. paradisiaca respectively. The emulsification index ranged from 85.62 ± 0.09% to 86.67 ± 1.141% after 24 hrs and from 26.0 ± 0.94% to 27.02 ± 2.390% after 48 hrs, with the highest value from the raw M. acuminate combusted at 350oC and the lowest from that combusted at 3000C. The potash source, pretreatment method, combustion conditions, and dilution factors all had an effect on the physicochemical and functional properties of nikkih.
An Improved Simulated Annealing Particle Swarm Optimization Algorithm for Path Planning of Mobile Robots Using Mutation Particles
Authors: Lu Jianzhang , Zhang Zhihao
Published: December 2021

Artificial intelligence technology has brought tremendous changes to human life and production methods. Mobile robots, UAVs, and autonomous driving technology have gradually entered people’s daily life. As a typical issue for a mobile robot, the planning of an optimal mobile path is very important, especially in the military and emergency rescue. In order to ensure the efficiency of operation and the accuracy of the path, it is crucial for the robot to find the optimal path quickly and accurately. This paper discusses a new method and MP‐SAPSO algorithm for addressing the issue of path planning based on the PSO algorithm by combining particle swarm optimization (PSO) algorithm with the simulated annealing (SA) algorithm and mutation particle and adjusting the parameters. The MP‐SAPSO algorithm improves the accuracy of path planning and the efficiency of robot operation. The experiment also demonstrates that the MP‐SAPSO algorithm can be used to effectively address path planning issue of mobile robots.
Repetitions of Strenuous Exercise Consistently Increase Paraoxonase 1 Concentration and Activity in Plasma of Average‐Trained Men
Authors: Otocka-Kmiecik Aneta , Orłowska-Majdak Monika , Stawski Robert , Szkudlarek Urszula , Kosielski Piotr , Padula Gianluca , Gałczyński Szymon , Nowak Dariusz
Published: December 2021

Objectives. Oxidative stress, induced by physical activity, may stimulate the expression, release, and activity of certain antioxidant enzymes. We investigated the effect of three repeated bouts of strenuous exercise on paraoxonase 1 concentration (PON1c) and paraoxonase activity (PON). Methods. Eleven average‐trained healthy men (age 34.0 ± 5.2 years) performed three strenuous exercise tests on a treadmill separated by 72 hours periods of resting. PON1c, PON, ferric‐reducing activity of plasma (FRAP), lipid profile, C‐reactive protein concentration (CRP), and lactate concentration were determined in plasma. Results. Each exercise bout resulted in similar PON1c, PON, FRAP, and high‐density lipoprotein concentration (HDL‐C) increments, while PON/HDL‐C ratio remained stable in all repetitions. Percentage increments at the bout of each exercise were higher for PON1c (by 64.82% at the first, by 92.9% at the second, and by 77.02% at the third exercise) than for PON (by 6.49% at the first, 10.06% at the second, and by 12.32% at the third exercise). Association was found between preexercise PON and PON1c (r = 0.56, p = 0.029), pre‐ (r = 0.87, p = 0.00003) and postexercise HDL‐C (r = 0.6, p = 0.0002), preexercise PON and cardiovascular fitness level of participants measured as VO2max (r = 0.39, p = 0.026), and postexercise PON and lactate concentration (r = 0.44, p = 0.01). Conclusions. PON1c and PON increase during strenuous exercise, yet the effect of exercise on PON1 concentration is more pronounced. PON1 does not show tolerance to physical activity. The enzyme may provide short‐term protection from oxidative stress in each exercise bout. PON may depend on exercise load. Cardiovascular fitness levels may be associated with PON1 activity.
Compressed Sensing Image Reconstruction of Ultrasound Image for Treatment of Early Traumatic Myositis Ossificans of Elbow Joint by Electroacupuncture
Authors: Zhu Yi , Sheng Mengyuan , Ouyang Yuanming , Zhong Lichang , Liu Kun , Ge Tan , Wu Yaochi
Published: December 2021

This article conducts a retrospective analysis of 500 patients with posttraumatic elbow dysfunction admitted to our department from March 2019 to September 2020. The average time from injury to operation is 11 months (2–20 months). We adopt a personalized treatment method to completely remove the hyperplastic adhesion tissue and heterotopic ossification around the joint, remove part of the joint capsule and ligament, and release it to achieve maximum function. After the operation, an external fixator was used to stabilize the loosened elbow joint, and the patient was guided to perform rehabilitation exercises with the aid of a hinged external fixator, and celecoxib was used to prevent heterotopic ossification. Mayo functional scoring system was used to evaluate the curative effect before and after surgery. The rapid realization of ultrasound imaging under the framework of compressed sensing is studied. Under the premise of ensuring the quality of ultrasound imaging reconstruction, the theory of ultrasound imaging is improved, and a plane wave acoustic scattering ultrasound echo model is established. On this basis, the theory of compressed sensing is introduced, the mathematical model of compressed sensing reconstruction is established, and the fast iterative shrinkage thresholding algorithm (FISTA) of compressed sensing reconstruction is improved to reduce the computational complexity and the number of iterations. This article uses FISTA directly to reconstruct medical ultrasound images, and the reconstruction results are not ideal. Therefore, a simulation model of FISTA training and testing was established using the standard image library. By adding different intensities of noise to all images in the image library, the influence of noise intensity on the quality of FISTA reconstructed images is analyzed, and it is found that the FISTA model has requirements for the quality of the images to be reconstructed and the training set images. In this paper, Rob’s blind deconvolution restoration algorithm is used to preprocess the original ultrasound image. The clarity of the texture details of the restored ultrasound image is significantly improved, and the image quality is improved, which meets the above requirements. This paper finally formed a reconstruction model suitable for ultrasound images. The reconstruction strategy verified by the ultrasound images provided by the Institute of Ultrasound Imaging of a medical university has achieved a significant improvement in the quality of ultrasound images.
Effects of MicroRNA‐195‐5p on Biological Behaviors and Radiosensitivity of Lung Adenocarcinoma Cells via Targeting HOXA10
Authors: Yuan Cheng , Bai Rui , Gao Yanping , Jiang Xueping , Li Shuying , Sun Wenjie , Li Yangyi , Huang Zhengrong , Gong Yan , Xie Conghua
Published: December 2021

Objective. To explore the effects of miR‐195‐5p and its target gene HOXA10 on the biological behaviors and radiosensitivity of lung adenocarcinoma (LUAD) cells. Methods. The effects of miR‐195‐5p on LUAD cell proliferation, migration, invasion, cycle arrest, apoptosis, and radiosensitivity were investigated by in vitro experiments. The bioinformatics analysis was used to assess its clinical value and predict target genes. Double‐luciferase experiments were used to verify whether the miR‐195‐5p directly targeted HOXA10. A xenograft tumor‐bearing mouse model was used to examine its effects on the radiosensitivity of LUAD in vivo. Results. Both gain‐ and loss‐of‐function assays demonstrated that miR‐195‐5p inhibited LUAD cell proliferation, invasion, and migration, induced G1 phase arrest and apoptosis, and enhanced radiosensitivity. Double‐luciferase experiments confirmed that miR‐195‐5p directly targeted HOXA10. Downregulation of HOXA10 also inhibited LUAD cell proliferation, migration, and invasion, induced G1 phase arrest and apoptosis, and enhanced radiosensitivity. The protein levels of β‐catenin, c‐myc, and Wnt1 were decreased by miR‐195‐5p and increased by its inhibitor. Moreover, the effects of the miR‐195‐5p inhibitor could be eliminated by HOXA10‐siRNA. Furthermore, miR‐195‐5p improved radiosensitivity of LUAD cells in vivo. Conclusion. miR‐195‐5p has excellent antitumor effects via inhibiting cancer cell growth, invasion, and migration, arresting the cell cycle, promoting apoptosis, and sensitizing LUAD cells to X‐ray irradiation by targeting HOXA10. Thus, miR‐195‐5p may serve as a potential candidate for the treatment of LUAD.
Impact of Weather Predictions on COVID‐19 Infection Rate by Using Deep Learning Models
Authors: Gupta Yogesh , Raghuwanshi Ghanshyam , Ahmadini Abdullah Ali H. , Sharma Utkarsh , Mishra Amit Kumar , Mashwani Wali Khan , Goktas Pinar , Alshqaq Shokrya S. , Samson Balogun Oluwafemi
Published: December 2021

Nowadays, the whole world is facing a pandemic situation in the form of coronavirus diseases (COVID‐19). In connection with the spread of COVID‐19 confirmed cases and deaths, various researchers have analysed the impact of temperature and humidity on the spread of coronavirus. In this paper, a deep transfer learning‐based exhaustive analysis is performed by evaluating the influence of different weather factors, including temperature, sunlight hours, and humidity. To perform all the experiments, two data sets are used: one is taken from Kaggle consists of official COVID‐19 case reports and another data set is related to weather. Moreover, COVID‐19 data are also tested and validated using deep transfer learning models. From the experimental results, it is shown that the temperature, the wind speed, and the sunlight hours make a significant impact on COVID‐19 cases and deaths. However, it is shown that the humidity does not affect coronavirus cases significantly. It is concluded that the convolutional neural network performs better than the competitive model.
Mechanical Stress-Induced IGF-1 Facilitates col-I and col-III Synthesis via the IGF-1R/AKT/mTORC1 Signaling Pathway
Authors: Yan Bin , Zeng Canjun , Chen Yuhui , Huang Minjun , Yao Na , Zhang Jie , Yan Bo , Tang Jiajun , Wang Liang , Zhang Zhongmin
Published: December 2021

Mechanical stress promotes human ligamentum flavum cells (LFCs) to synthesize multitype collagens, leading to ligamentum flavum hypertrophy (LFH). However, the mechanism of mechanical stress in the formation of collagen remains unclear. Therefore, we investigated the relationship between mechanical stress and collagen synthesis in the present study. First, LFCs were isolated from 9 patients and cultured with or without mechanical stress exposure for different times. IGF-1, collagen I (col-I), and collagen III (col-III) protein and mRNA levels were then detected via ELISA and qPCR, respectively. Moreover, the activation of pIGF-1R, pAKT, and pS6 was examined by Western blot analysis. To further explore the underlying mechanism, an IGF-1 neutralizing antibody, NVP-AEW541, and rapamycin were used. IGF-1, col-I, and col-III were significantly increased in stressed LFCs compared to nonstressed LFCs. In addition, the activation of pIGF-1R, pAKT, and pS6 was obviously enhanced in stressed LFCs. Interestingly, col-I protein, col-I mRNA, col-III protein, col-III mRNA, and IGF-1 protein, but not IGF-1 mRNA, were inhibited by IGF-1 neutralizing antibody. In addition, col-I and col-III protein and mRNA, but not IGF-1, were inhibited by both NVP-AEW541 and rapamycin. Moreover, the activation of pIGF-1R, pAKT, and pS6 was reduced by the IGF-1 neutralizing antibody and NVP-AEW541, and the activation of pS6 was reduced by rapamycin. In summary, these results suggested that mechanical stress promotes LFCs to produce IGF-1, which facilitates col-I and col-III synthesis via the IGF-1R/AKT/mTORC1 signaling pathway.
An Application of Hybrid Models for Weekly Stock Market Index Prediction: Empirical Evidence from SAARC Countries
Authors: Peng Zhang , Khan Farman Ullah , Khan Faridoon , Shaikh Parvez Ahmed , Yonghong Dai , Ullah Ihsan , Ullah Farid
Published: December 2021

The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron (MLP), recurrent neural network (RNN), and autoregressive integrated moving average (ARIMA) on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA‐MLP and ARIMA‐RNN. Because of the complicated and noisy nature of financial data, we combine novel machine‐learning techniques such as MLP and RNN with ARIMA model to predict the three stock market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA‐MLP and ARIMA‐RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root‐mean‐square error and mean absolute error. Apart from this, ARIMA‐MLP outperformed the ARIMA‐RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA‐RNN beat the ARIMA‐MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time‐series forecasting.
Lifestyle in Female Teachers: Educational Intervention Based on Self‐Efficacy Theory in the South of Fars Province, Iran
Authors: Abbasi Fariba , Ghahremani Leila , Nazari Mahin , Fararouei Mohammad , Khoramaki Zakieh
Published: December 2021

Introduction. Today, improving lifestyles and promoting health are basic needs for human society. The main goal in promoting health is to achieve healthy lifestyle behaviors, and self‐efficacy is one of the factors influencing people’s lifestyle. Therefore, the impact of educational intervention based on self‐efficacy theory on improving lifestyles of the female teachers in Galledar was investigated. Method. This study was a semiexperimental study with educational intervention with a control group that was performed on 120 teachers in Galledar. Data collection tools included demographic information questionnaires, health‐promoting lifestyle questionnaires, and Sherry’s self‐efficacy questionnaire. Data were analyzed using SPSS 25 software. Result. The mean age and standard deviation of teachers in the control and intervention groups were 33.40 ± 5.68 and 32.83 ± 6.46 years, respectively. Health‐promoting lifestyle variables are significant correlation with self‐efficacy and overall lifestyle index. Six dimensions which consisted of spiritual growth and self‐actualization, health responsibility, interpersonal relationships, stress management, exercise and physical activity, and nutrition showed significant statistical differences before and after educational intervention (P = 0.001). Conclusion. Due to the sensitive role of teachers as an effective human force in the development and evolution of society and their students’ role modeling, the authorities should formulate policies, regulate educational interventions, and design strategies for promoting self‐efficacy beliefs and promoting a healthy lifestyle for all teachers. We suggest that other methods and theories of behavior change be used in future studies to promote a healthy lifestyle.
[Retracted] Enhancement of Predicting Students Performance Model Using Ensemble Approaches and Educational Data Mining Techniques
Authors: Ragab Mahmoud , Abdel Aal Ahmed M. K. , Jifri Ali O. , Omran Nahla F.
Published: December 2021

Student performance prediction is extremely important in today’s educational system. Predicting student achievement in advance can assist students and teachers in keeping track of the student’s progress. Today, several institutes have implemented a manual ongoing evaluation method. Students benefit from such methods since they help them improve their performance. In this study, we can use educational data mining (EDM), which we recommend as an ensemble classifier to anticipate the understudy accomplishment forecast model based on data mining techniques as classification techniques. This model uses distinct datasets which represent the student’s intercommunication with the instructive model. The exhibition of an understudy’s prescient model is evaluated by a kind of classifiers, for instance, logistic regression, naïve Bayes tree, artificial neural network, support vector system, decision tree, random forest, and k‐nearest neighbor. Additionally, we used set processes to evolve the presentation of these classifiers. We utilized Boosting, Random Forest, Bagging, and Voting Algorithms, which are the normal group of techniques used in studies. By using ensemble methods, we will have a good result that demonstrates the dependability of the proposed model. For better productivity, the various classifiers are gathered and, afterward, added to the ensemble method using the Vote procedure. The implementation results demonstrate that the bagging method accomplished a cleared enhancement with the DT model, where the DT algorithm accuracy with bagging increased from 90.4% to 91.4%. Recall results improved from 0.904 to 0.914. Precision results also increased from 0.905 to 0.915.
3D‐QSAR Studies of 1,2,4‐Oxadiazole Derivatives as Sortase A Inhibitors
Authors: Shakour Neda , Hadizadeh Farzin , Kesharwani Prashant , Sahebkar Amirhossein
Published: December 2021

Sortase A (SrtA) is an enzyme that catalyzes the attachment of proteins to the cell wall of Gram‐positive bacterial membrane, preventing the spread of pathogenic bacterial strains. Here, one class of oxadiazole compounds was distinguished as an efficient inhibitor of SrtA via the “S. aureus Sortase A” substrate‐based virtual screening. The current study on 3D‐QSAR was done by utilizing preparation of the structure in the Schrödinger software suite and an assessment of 120 derivatives with the crystal structure of 1,2,4‐oxadiazole which was extracted from the PDB data bank. The docking operation of the best compound in terms of pMIC (pMIC = 2.77) was done to determine the drug likeliness and binding form of 1,2,4‐oxadiazole derivatives as antibiotics in the active site. Using the kNN‐MFA way, seven models of 3D‐QSAR were created and amongst them, and one model was selected as the best. The chosen model based on q2 (pred_r2) and R2 values related to the sixth factor of PLS illustrates better and more acceptable external and internal predictions. Values of crossvalidation (pred_r2), validation (q2), and F were observed 0.5479, 0.6319, and 179.0, respectively, for a test group including 24 molecules and the training group including 96 molecules. The external reliability outcomes showed that the acceptable and the selective 3D‐QSAR model had a high predictive potential (R2 = 0.9235) which was confirmed by the Y‐randomization test. Besides, the model applicability domain was described successfully to validate the estimation of the model.
The Existence of Strong Solution for Generalized Navier-Stokes Equations withpx-Power Law under Dirichlet Boundary Conditions
Authors: Sin Cholmin
Published: December 2021

In this note, in 2D and 3D smooth bounded domain, we show the existence of strong solution for generalized Navier-Stokes equation modeling bypx-power law with Dirichlet boundary condition under the restriction3n/n+2n+2<px<2n+1/n−1. In particular, if we neglect the convective term, we get a unique strong solution of the problem under the restriction2n+1/n+3<px<2n+1/n−1, which arises from the nonflatness of domain.
Design and Construction of Multimedia Smart English Teaching Platform Based on RBF Algorithm
Authors: Li Qianbo
Published: December 2021

With the economic development in our country, there are more and more international exchanges and communications. Hence, the ability to read, write, and communicate in English is essential and very necessary. In traditional English classroom teaching, teachers are the disseminators of knowledge, whereas students only receive knowledge passively. Due to the limitation of teaching hours and the lack of teaching approaches, it is necessary to make up for the insufficiency in the teaching activities through computer technology and multimedia technology. Abundant teaching approaches can cultivate the independent inquiry ability of students, and the establishment of such an English learning platform is conducive to improving the students’ ability to make full use of the information technology. Through teaching and learning, the students can become the main entity in the English teaching, which can stimulate their enthusiasm and form a good awareness for English learning. In this paper, the radial basis function (hereinafter referred to as RBF for short) algorithm is adopted. Combined with the constructive English teaching method, practical design and construction are carried out by analyzing the concepts, principles, and application strategies of smart classroom teaching in the multimedia background. The practice has proved that the method proposed in this paper is effective and has certain research value and positive significance for the research on English teaching.
[Retracted] Physiological Index Monitoring of Wearable Sports Training Based on a Wireless Sensor Network
Authors: Lu Zhihai , Li Zhaoxiang , Zhang Lei
Published: December 2021

According to the development needs of wireless sensor networks, this paper uses the combination of embedded system and wireless sensor network technology to design a network node platform. This platform is equipped with a sports training sensor module to measure the physiological indicators of the ward in real time. The network node sends the collected physiological parameters to a remote monitoring center in real time. First, according to the generation mechanism of the physiological index signal and the characteristics of the physiological index signal, the wireless sensor network analysis and processing method are used to denoise the physiological index signal, and the wireless sensor network package is used to extract the characteristics of the physiological index, indicating different types of respiration. The energy characteristics of the sound physiological index signals are different, which verifies the feasibility of the independent component analysis method for separating the physiological index and the physiological index signal of the heart sound. Secondly, the hardware system of physiological index signal acquisition is designed, and the selection principle of the hardware unit is introduced. At the same time, the system structure of the monitor is designed, and then, the wireless sensor network sensor node is researched, the hardware of the wearable monitor system is designed, and the hardware architecture and working mode based on the single‐chip MSP430F149 are given. Finally, the wireless hardware platform includes the following main modules: sensor part, preprocessing circuit module, microprocessing module based on MSP430 low power consumption, wireless transceiver module based on RF chip CC2420, and power supply unit used to provide energy.
Asymptotically Effective Method to Explore Euler Path in a Graph
Authors: Fahad Muhammad , Ali Sikandar , Khan Mukhtaj , Husnain Mujtaba , Shafi Zeeshan , Samad Ali
Published: December 2021

Euler path is one of the most interesting and widely discussed topics in graph theory. An Euler path (or Euler trail) is a path that visits every edge of a graph exactly once. Similarly, an Euler circuit (or Euler cycle) is an Euler trail that starts and ends on the same node of a graph. A graph having Euler path is called Euler graph. While tracing Euler graph, one may halt at arbitrary nodes while some of its edges left unvisited. In this paper, we have proposed some precautionary steps that should be considered in exploring a deadlock-free Euler path, i.e., without being halted at any node. Simulation results show that our proposed approach improves the process of exploring the Euler path in an undirected connected graph without interruption. Furthermore, our proposed algorithm is complete for all types of undirected Eulerian graphs. The paper concludes with the proofs of the correctness of proposed algorithm and its computation complexity.
A Novel Effective Formulation of Bioactive Compounds for Wound Healing: Preparation, In Vivo Characterization, and Comparison of Various Postbiotics Cold Creams in a Rat Model
Authors: Golkar Nasim , Ashoori Yousef , Heidari Reza , Omidifar Navid , Abootalebi Seyedeh Narjes , Mohkam Milad , Gholami Ahmad
Published: December 2021

The wound is a break in the integrity of the skin produced by injury, illness, or operation. Wound healing is an essential dynamic biological/physiological process that occurs in response to tissue damage. The huge health, economic, and social effects of wounds on patients and societies necessitate the research to find novel potential therapeutic agents in order to promote wound healing. Postbiotics, the newest member of the biotics family, are valuable functional bioactive substances produced by probiotics through their metabolic activity, which have several beneficial properties, including immunomodulatory, anti-inflammatory, antimicrobial, and angiogenesis characteristics, resulting in acceleration of wound healing. In the current study, three topical cold cream formulations containing postbiotics obtained from Lactobacillus fermentum, Lactobacillus reuteri, or Bacillus subtilis sp. natto probiotic strains were prepared. The effectiveness and wound healing activity of the developed postbiotics cold cream formulations were investigated compared to cold cream without postbiotics and no treatment via wound closure investigation, hydroxyproline content assay, and histological assessment in 25 Sprague Dawley rats divided into five groups. Interestingly, analysis of the results revealed that all three formulations containing postbiotics significantly accelerated the wound healing process. However, in general, the Bacillus subtilis natto cold cream manifested a better wound healing property. The pleasing wound healing characteristics of the topical postbiotics cold creams through the in vivo experiment suggest that formulations containing postbiotics can be considered as a promising nominee for wound healing approaches.
MicroRNA-383-5p Regulates Oxidative Stress in Mice with Acute Myocardial Infarction through the AMPK Signaling Pathway via PFKM
Authors: Gao Linlin , Ruan Zhongbao , Chen Gecai
Published: December 2021

Objective. The purpose of this study is to explore the regulating role of microRNA-383-5p (miR-383-5p) in oxidative stress after acute myocardial infarction (AMI) through AMPK pathway via phosphofructokinase muscle-type (PFKM). Methods. We established the AMI model, and the model mice were injected with miR-383-5p agomir to study the effect of miR-383-5p in AMPK signaling pathways. The target gene for miR-383-5p was reported to be PFKM, so we hypothesized that overexpression of miR-383-5p inhibits activation of the AMPK signaling pathway. Results. In this research, we found that overexpression of miR-383-5p decreases myocardial oxidative stress, myocardial apoptosis, the expression level of PFKM malondialdehyde (MDA), and reactive oxygen species (ROS) in the myocardial tissues after AMI, and finally, AMI-induced cardiac systolic and diastolic function could be improved.Conclusion. This study demonstrated that miR-383-5p could reduce the oxidative stress after AMI through AMPK signaling pathway by targeting PFKM.
Investor Sentiment Combined with Multisource Information to Predict Stock Prices: An Analysis of China’s A-Share Market
Authors: Huang Xin , Song Huilin
Published: December 2021

Investor sentiment has been widely used in the research of the stock market, and how to accurately measure investor sentiment is still being explored. With the rise of social media, investor sentiment is no longer only influenced by macroeconomic data and news media, but also guided by We-Media and fragmented information. We take the data of China A-shares from January 2020 to December 2020 as the research object and propose a stock price prediction method that combines investor sentiment with multisource information. Firstly, the sentiment of macroeconomic data, brokerage research reports, news, and We-Media is calculated, respectively, and then the investor sentiment vector combining multisource information is obtained by the multilayer perceptron. Finally, the LSTM model is used to represent the stock time series characteristics. The results show that (1) the proposed algorithm is superior to the benchmark algorithm in terms of accuracy and F1-score, (2) investor sentiment vector can effectively measure the investment sentiment of stocks, and (3) compared with vector concatenation, multilayer perceptron can better represent investor sentiment.
A Computer‐Aided Diagnosis System Using Deep Learning for Multiclass Skin Lesion Classification
Authors: Arshad Mehak , Khan Muhammad Attique , Tariq Usman , Armghan Ammar , Alenezi Fayadh , Younus Javed Muhammad , Aslam Shabnam Mohamed , Kadry Seifedine
Published: December 2021

In the USA, each year, almost 5.4 million people are diagnosed with skin cancer. Melanoma is one of the most dangerous types of skin cancer, and its survival rate is 5%. The development of skin cancer has risen over the last couple of years. Early identification of skin cancer can help reduce the human mortality rate. Dermoscopy is a technology used for the acquisition of skin images. However, the manual inspection process consumes more time and required much cost. The recent development in the area of deep learning showed significant performance for classification tasks. In this research work, a new automated framework is proposed for multiclass skin lesion classification. The proposed framework consists of a series of steps. In the first step, augmentation is performed. For the augmentation process, three operations are performed: rotate 90, right‐left flip, and up and down flip. In the second step, deep models are fine‐tuned. Two models are opted, such as ResNet‐50 and ResNet‐101, and updated their layers. In the third step, transfer learning is applied to train both fine‐tuned deep models on augmented datasets. In the succeeding stage, features are extracted and performed fusion using a modified serial‐based approach. Finally, the fused vector is further enhanced by selecting the best features using the skewness‐controlled SVR approach. The final selected features are classified using several machine learning algorithms and selected based on the accuracy value. In the experimental process, the augmented HAM10000 dataset is used and achieved an accuracy of 91.7%. Moreover, the performance of the augmented dataset is better as compared to the original imbalanced dataset. In addition, the proposed method is compared with some recent studies and shows improved performance.
Building Virtual Scene Construction and Environmental Impact Analysis Based on Image Processing
Authors: Ying Fan , Bo Zhou
Published: December 2021

With the rapid development of computer technology, the virtual scene construction technology of image processing has gradually become a hotspot in computer research. The application of virtual scene construction technology in the construction industry is also expanding, with the intelligentization of architectural design and construction. With the rapid development of the industry, virtual technology can better provide users with diversified services and experiences. The main content of the article is as follows: (1) The article introduces image construction technology and analyzes the three-dimensional presentation of virtual technology in construction design and the diversified application of virtual technology in construction design. (2) The article introduces two virtual scene construction techniques: one is to combine the real scene obtained by taking pictures with the virtual scene by image technology processing to construct a natural virtual scene; the other is the use of geometric construction by architects. The virtual building model is drawn by the model method, and the virtual building model is thus obtained. (3) The article chooses two representative buildings as cases. The virtual platform monitors and records the movement trajectory of volunteers in the virtual environment in real time. The experimental results show that the number and shape characteristics of the escalators in the building all have a little impact on volunteers’ awareness. (4) The article sets up three control groups of normal mode, fixed skin, and variable skin. It analyzes the environmental impact of buildings from three different aspects of wind environment, thermal environment, and light environment and proposes related control measures.
Atezolizumab Treatment of Tumors with High Tumor Mutational Burden from MyPathway, a Multicenter, Open-Label, Phase IIa Multiple Basket Study
Authors: Friedman Claire F. , Hainsworth John D. , Kurzrock Razelle , Spigel David R. , Burris Howard A. , Sweeney Christopher J. , Meric-Bernstam Funda , Wang Yong , Levy Jonathan , Grindheim Jessica , Shames David S. , Schulze Katja , Patel Arisha , Swanton Charles
Published: December 2021

High tumor mutational burden (TMB-H) correlates with improved immunotherapy response. We assessed atezolizumab 1,200 mg every 3 weeks for TMB-H tumors from MyPathway (NCT02091141), a phase IIa multibasket study. One hundred twenty-one patients had advanced solid tumors with TMB ≥10 mut/Mb by any Clinical Laboratory Improvement Amendments (CLIA)–certified assay. The preplanned primary endpoint was objective response rate (ORR) in patients with TMB ≥16 mut/Mb tumors by FoundationOne TMB testing [F1(CDx)]. Patients with F1(CDx) TMB ≥10 and <16 mut/Mb were also evaluated. Ninety patients with 19 tumor types and F1(CDx) TMB ≥10 mut/Mb were efficacy evaluable. In 42 patients with F1(CDx) TMB ≥16 mut/Mb, confirmed ORR was 38.1% [16/42; 95% confidence interval (CI), 23.6–54.4], and disease control rate was 61.9% (26/42; 95% CI, 45.6–76.4) versus 2.1% (1/48; 95% CI, 0.1–11.1) and 22.9% (11/48; 95% CI, 12.0–37.3) for 48 patients with TMB ≥10 and <16 mut/Mb. Responses were observed in nine different tumor types (47%; 9/19).

Significance:

Atezolizumab monotherapy had promising, durable clinical activity across a variety of advanced solid tumor types in patients with TMB ≥16 mut/Mb tumors lacking other suitable treatment options and who were immunotherapy-naïve at enrollment, regardless of microsatellite instability status. Limited activity was observed in tumors with TMB ≥10 and <16 mut/Mb.

See related commentary by Maron and Klempner, p. 602.

This article is highlighted in the In This Issue feature, p. 587
Guideline-Directed Medical Therapy in Patients with Chronic Kidney Disease Undergoing Peripheral Vascular Intervention
Authors: Jelani Qurat-Ul-Ain , Llanos-Chea Fiorella , Bogra Pragati , Trejo-Paredes Camila , Huang Jiaming , Provance Jeremy B. , Turner Jeffrey , Anantha-Narayanan Mahesh , Sheikh Azfar Bilal , Smolderen Kim G. , Mena-Hurtado Carlos
Published: December 2021

Introduction: Guideline-directed medical therapy (GDMT) is imperative to improve cardiovascular and limb outcomes for patients with critical limb ischemia (CLI), especially amongst those at highest risk for poor outcomes, including those with comorbid chronic kidney disease (CKD). Our objective was to examine GDMT prescription rates and their variation across individual sites for patients with CLI undergoing peripheral vascular interventions (PVIs), by their comorbid CKD status. Methods: Patients with CLI who underwent PVI (October 2016–April 2019) were included from the Vascular Quality Initiative (VQI) database. CKD was defined as GFR <60 mL/min/1.73 m2. GDMT included the composite use of antiplatelet therapy and a statin, as well as an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker if hypertension was present. The use of GDMT before and after the index procedure was summarized in those with and without CKD. Adjusted median odds ratios (MORs) for site variability were calculated. Results: The study included 28,652 patients, with a mean age of 69.4 ± 11.7 years, and 40.8% were females. A total of 47.5% had CKD. Patients with CKD versus those without CKD had lower prescription rates both before (31.7% vs. 38.9%) and after (36.5% vs. 48.8%) PVI (p < 0.0001). Significant site variability was observed in the delivery of GDMT in both the non-CKD and CKD groups before and after PVI (adjusted MORs: 1.31–1.41). Discussion/Conclusion: In patients with CLI undergoing PVI, patients with comorbid CKD were less likely to receive GDMT. Significant variability of GDMT was observed across sites. These findings indicate that significant improvements must be made in the medical management of patients with CLI, particularly in patients at high risk for poor clinical outcomes.
Immunoadsorption Improves Remission Rates of Patients with Antineutrophil Cytoplasmic Antibody-Associated Vasculitis and Severe Kidney Involvement
Authors: Chu Xiaoxin , Hong Yu , Wang Yuxi , Yu Chong , Wang Lisheng , Tong Hui , Yan Jianjun , Zhang Zhonghua , Xu Gang , Yao Ying , Zeng Rui
Published: December 2021

Introduction: The role of plasma exchange in treatment of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) with severe kidney involvement is controversial. It is urgent to find effective treatments to improve prognosis of AAV patients. In this retrospective study, the outcomes of immunoadsorption (IA) onto protein A in AAV patients with severe kidney involvement were evaluated. Methods: Clinical data of 60 patients with AAV and severe kidney involvement were analyzed. Patients received cyclophosphamide or rituximab for remission induction, among which 16 were additionally treated with IA. Remission, end-stage kidney disease (ESKD), death, and relapse were compared. Results: Of 60 patients, 56 patients (93.3%) were positive for myeloperoxidase (MPO)-ANCA. At diagnosis, the estimated glomerular filtration rate and Birmingham Vasculitis Activity Score (BVAS) was 13.0 (7.7, 18.7) mL/min/1.73 m2 and 11.1 ± 3.4, respectively. After 3–17 days (mean 10.4 days) of induction treatment, the disease activity decreased more obviously in the IA group (p = 0.022) than the control group. IA showed superior over standard regimen in clearance of MPO-ANCA within 3–31 days (median 11 days) after treatment (78.4% vs. 9.3%, p = 0.005). After a median follow-up of 20.2 months, remission was achieved more quickly (p = 0.035) and higher (hazard ratio (HR) = 2.3, 95% confidence interval (CI): 1.1∼7.2, p = 0.033) in the IA group than the control group. IA therapy showed an advantage in reducing death (HR = 0.2, 95% CI: 0.1∼0.9, p = 0.032). There was no difference in developing into ESKD in both groups (HR = 0.7, 95% CI: 0.3∼2.0, p = 0.504). Multivariate Cox regression analysis indicated that early-stage remission was an independent predictor for ESKD (HR = 0.03, 95% CI: 0.003∼0.25, p = 0.001) and death (HR = 0.07, 95% CI: 0.01∼0.51, p = 0.009). Conclusion: IA treatment induces quicker and higher remission and lower mortality in AAV patients with severe kidney involvement. The early remission independently predicts the outcomes for these patients.
Identification of Novel Biomarkers in Platelets for Diagnosing Parkinson’s Disease
Authors: Zhang Lei , Shao Yiye , Tang Chunlei , Liu Zhen , Tang Dingzhong , Hu Canfang , Liang Xuelin , Hu Zhaoyang , Luo Guojun
Published: December 2021

Background: Parkinson’s disease (PD) is a common neurodegenerative disease affecting the elderly, but there is no blood test for PD diagnosis in the clinic currently. This study aimed to explore promising biomarkers in platelets (PLTs) for PD diagnosis. Methods: PLTs were isolated from whole blood samples of PD patients and healthy controls (HCs), and RNA was extracted for sequencing. RNA-seq was performed on the Illumina HiSeq platform. Results: A total of 2,221 genes with differential transcript levels (GDTLs) were identified between PD patients and HCs, 1,041 of which are upregulated genes and 1,180 of which are downregulated genes. WASH5P was the most upregulated gene and AC114491.1 was the most downregulated gene. Among the top 12 most relevant genes, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), eukaryotic elongation factor 1A (EEF1A1), and cathepsin S (CTSS) were reported to be associated with PD. Furthermore, gene ontology analysis showed that the most significant term in biological processes was neutrophil degranulation; the most enriched term in cellular components was cytoplasmic vesicle lumen; and tumor necrosis factor receptor superfamily binding was the most significant term in molecular functions. In the Kyoto Encyclopedia of Genes and Genomes enrichment analysis, inflammation-related pathway accounts for the majority. Conclusion: Our findings demonstrated WASH5P, MALAT1, EEF1A1, and CTSS may be promising biomarkers in PD, which may contribute to improving the effectiveness and accuracy of diagnosis for PD in the future.
One-Year Change in Locus of Control among People with Dementia
Authors: Halse Ingeborg , Bjørkløf Guro Hanevold , Engedal Knut , Selbæk Geir , Barca Maria Lage
Published: December 2021

Introduction: Knowledge of how perceptions of personal control change over time may provide valuable insights into how people cope with having dementia. The present study aimed to examine change in locus of control over a 12-month period in persons with dementia. Method: The study included 52 participants with dementia. Locus of control was measured with the Locus of Control of Behavior Scale (LoCB), with higher scores indicating a more external locus of control, interpreted as perceiving less personal control. A ≥5% change on the LoCB was considered clinically meaningful. We recorded sociodemographic characteristics and assessed dementia severity, cognition, ability to function independently in daily activities and physical self-maintenance, depressive symptomatology, and number of prescribed medications. Analyses were performed to examine differences between those with increases (more external) or decreases (less external) in the LoCB score after 12 months and to examine associations between baseline variables and change in the LoCB score. Results: The mean LoCB score for the total sample did not change after 12 months (baseline mean 29.33 vs. follow-up mean 30.33, p = 0.553); however, 2 subgroups emerged. Using the ≥5% cutoff revealed that the LoCB score changed for 92.3% of the sample, becoming less external (lower LoCB) for 21 participants and more external (higher LoCB) for 27 participants. At baseline, the mean LoBC score was higher in the group that became less external (33.81 vs. 24.56), p = 0.006, while this was reverse at follow-up (23.57 vs. 34.41), p = 0.001. Dementia severity and dependence in physical self-maintenance increased during the 12 months in both groups. Among those becoming more external, we also found a decline in cognition (p = 0.002), an increase in dependence in daily activities (p = 0.003), an increase in the use of prescribed medication, and a decrease in depressive symptomatology (p = 0.003). The baseline LoCB score was the only variable associated with 12-month change in LoCB scores (p = 0.001). Conclusion: Most participants showed a clinically meaningful change in locus of control after 12 months. Those with more signs of dementia progression reported a decrease in personal control but also a decrease in depressive symptoms. These findings are interesting for our understanding of coping but must be replicated with a larger sample.
Effectiveness of a Videoconferencing-Delivered Psychological Intervention for Mental Health Problems during COVID-19: A Proof-of-Concept Randomized Clinical Trial
Authors: Bryant Richard A. , Dawson Katie S. , Keyan Dharani , Azevedo Suzanna , Yadav Srishti , Tran Jenny , Rawson Natasha , Harvey Samuel
Published: December 2021

Introduction: Anxiety and depression have increased markedly during the COVID-19 pandemic. There is a lack of evidence-based strategies to address these mental health needs during the pandemic. Objective: We aim to conduct a proof-of-concept trial of the efficacy of a brief group-based psychological intervention delivered via videoconferencing for adults in Australia distressed by the pandemic. Methods: In this single-blind, parallel, randomised controlled trial, adults who screened positive for COVID-related psychological distress across Australia were randomly allocated to either a 6-session group-based program based on behavioural principles (n = 120) or enhanced usual care (EUC, n = 120). Primary outcome was total score on the Hospital Anxiety and Depression (HADS) anxiety and depression subscales assessed at baseline, 1 week posttreatment, 2 months (primary outcome time point), and 6 months after treatment, as well as secondary outcome measures of worry, sleep impairment, anhedonia, mood, and COVID-19-related stress. Results: Between May 20, 2020, and October 20, 2020, 240 patients were enrolled into the trial. Relative to EUC, at 2 months participants receiving intervention showed greater reduction on anxiety (mean difference, 1.4 [95% CI, 0.3 to 2.6], p = 0.01; effect size, 0.4 [95% CI, 0.1 to 0.7]) and depression (mean difference, 1.6 [95% CI, 0.4 to 2.8], p = 0.009; effect size, 0.4 [95% CI, 0.2 to 0.7]) scales. These effects were maintained at 6 months. There were also greater reductions of worry, anhedonia, COVID-19-related fears, and contamination fears. Conclusions: This trial provides initial evidence that brief group-based behavioural intervention delivered via videoconferencing results in moderate reductions in common psychological problems arising during the COVID-19 pandemic. This program may offer a viable and scalable means to mitigate the rising mental health problems during the pandemic.