bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved Model of Product Classification Feature Extraction and Recognition Based on Intelligent Image Recognition
Authors: Gan Baiqiang , Zhang Chi
Published: August 2022

With the development of the new generation of technological revolution, the manufacturing industry has entered the era of intelligent manufacturing, and people have higher and higher requirements for the technology, industry, and application of product manufacturing. At present, some factories have introduced intelligent image recognition technology into the production process in order to meet the needs of customers' personalized customization. However, the current image recognition technology has limited capabilities. When faced with many special customized products or complex types of small batch products in the market, it is still impossible to perfectly analyze the product requirements and put them into production. Therefore, this paper conducts in-depth research on the improved model of product classification feature extraction and recognition based on intelligent image recognition: 3D modeling of the target product is carried out, and various data of the model are analyzed and recorded to facilitate subsequent work. Use the tools and the established 3D model tosimulate the parameters of the product in the real scene, and record them. Atthe same time, various methods such as image detection and edge analysis areused to maximize the accuracy of the obtained parameters, and variousalgorithms are used for cross-validation to obtain the correct rate of the obtaineddata, and the standard is 90% and above. Build a data platform, compare simulated data with display data by software and algorithm, and check by cloud computing force, so that the model data can be as close to the parameters of the real product as possible. Experimental results show that the algorithm has high accuracy and can meet the requirements of different classification prospects in actual production.
[Retracted] A Novel Protein Elicitor (PELL1) Extracted from Lecanicillium lecanii Induced Resistance against Bemisia tabaci (Hemiptera: Aleyrodidae) in Gossypium hirsutum L
Authors: Basit Abdul , Yaseen Muhammad , Babar Maham , Wang Yong , Abdulle Yusuf Ali , Qiu Dewen , Li Yunzhu , Bashir Muhammad Amjad , Shahzad Muhammad Sarmad , Farooq Hasnain , Alajmi Reem A. , Mangi David N. , Sehar Ambreen , Parveen Humaira
Published: August 2022

Protein elicitors play a key role in signaling or displaying plant defense mechanism and emerging as vital tools for biocontrol of insects. This study was aimed at the characterization of the novel protein elicitor isolated from entomopathogenic fungi Lecanicillium lecanii (V3) strain and its activity against whitefly, Bemisia tabaci, in cotton (Gossypium hirsutum L.). The sequence of purified elicitor protein showed 100% similarity with hypothetical protein LEL_00878 (Cordyceps confragosa RCEF 1005) (GenBank accession no. OAA81333.1). This novel protein elicitor has 253 amino acid residues and 762 bp with a molecular mass of 29 kDa. Their combatant protein was expressed in Escherichia coli using pET‐28a (+) plasmid. Bioassay was revealed to quantify the impact of numerous concentrations of protein (i.e., 58.32, 41.22, and 35.41 μg/ml) on the fecundity rate of B tabaci on cotton plants. Bioassay results exhibited a significant effect (P ≤ 0.001) of all the concentrations of protein on the fecundity rate of B. tabaci. In addition, the gene expression analysis found a significant upregulation of the major genes associated with salicylic acid (SA) and jasmonic acid (JA) defense pathways in elicitor protein‐treated plants. Our results showed that the potential application of novel protein elicitor derived from Lecanicillium lecanii will be used as future biointensive controlling approaches against whitefly, Bemisia tabaci.
Artificial Intelligence-Based Drug Production Quality Management Data
Authors: Yu Chenggong
Published: August 2022

As a special commodity, medicine plays a vital role in people’s healthy life. The basic effects of drugs are excitation and inhibition. Under the action of drugs, any function that can enhance or increase the function of the body’s original tissues and organs is called excitement. On the contrary, any function that can weaken or reduce the function of the original tissues and organs of the body is called inhibition. The nature of action of drugs has three aspects: regulatory function; antipathogen and antitumor; and complementary therapy. If there is a problem with the quality and safety of medicines, it is tantamount to making money and killing people. Based on artificial intelligence, this paper analyzes the current situation and improvement strategies of quality management in pharmaceutical production management enterprises and proposes how to reduce the risk of drug safety with the assistance of artificial intelligence technology. The experimental results in this paper show that the sales of heparin sodium APIs were 2.099 billion yuan, accounting for 91.6% of the operating income in 2015, when company A had not conducted a drug risk assessment in 2015. After the outbreak of drug risks, the sales in 2016 were 1.743 billion yuan, accounting for 77.1% of the operating income in 2016. After the final implementation of the measures, the sales in 2019 were 4.743 billion yuan, accounting for 329.1% of the operating income in 2016. The research method in this paper can improve the hidden safety problems of drugs more efficiently, and it can improve the profit while ensuring the safety.
An Improved Privacy Protection Algorithm for Multimodal Data Fusion
Authors: Chen Z. F. , Shuai J. J. , Tian F. J. , Li W. Y. , Zang S. H. , Zhang X. Z.
Published: August 2022

With the rapid development of Internet technology, the use and sharing of data have brought great opportunities and challenges to mankind. On the one hand, the development of data sharing and analysis technology has promoted the improvement of economic and social benefits. On the other hand, protecting private information has become an urgent issue in the Internet era. In addition, the amount and type of information data are also increasing. At present, most algorithms can only encrypt a single type of small-scale data, which cannot meet the current data environment. Therefore, it is very necessary to study the privacy protection algorithm of multimodal data fusion. To improve the security of privacy protection algorithm, combined with the idea of multimode, this paper combines the improved traditional spatial steganography algorithm LSB matching method and the improved traditional transform domain steganography algorithm DCT with AES encryption algorithm after modifying the S-box and then combines it with image stitching technology, so as to realize a safe and reliable privacy protection algorithm of multimode information fusion. The algorithm completes the hidden communication of private information, which not only ensures that the receiver can accurately recover private information in the process of information transmission but also greatly improves the security of private information transmission.
Feasibility and Safety of ERCP in the Treatment of Biliary Strictures after Liver Transplantation: With a Report of 37 Cases
Authors: Tang Fanfan , Song Jingtao , Cai Tanxing , Lei Zhao , Huang Feizhou , Hu Yina , Deng Gang
Published: August 2022

Background. Liver transplantation (LT) is an effective treatment option for patients with end-stage liver disease; biliary complications are important cause of death in posttransplant patients. Endoscopic retrograde cholangiopancreatography (ERCP) has an irreplaceable role in the diagnosis and treatment of patients with biliary tract disease. Methods. The clinical data of patients with biliary strictures (BS) after LT treated with ERCP admitted to the Third Xiangya Hospital of Central South University from September 2016 to October 2021 were reviewed; the changes in temperature, bilirubin, and albumin before and after treatment and postoperative complications were analyzed. Results. A total of 41 patients were included in the study, and biliary stents were successfully placed in 37 cases (90.2%), while 4 cases (9.8%) were unsuccessful due to complete BS. Patients with ERCP guided biliary stenting had a significant improvement in bilirubin index compared to the preoperative period (

P
<
0.05

). 27 patients (73.0%) had complete relief of symptoms after 1 ERCP-guided treatment, and 10 patients (27.0%) developed BS again at different times after the first ERCP treatment, among which 8 patients developed BS again within 1 year after the first treatment and 2 patients developed BS again after 1 year after the first treatment. The incidence of endoscopy-related adverse events was 35.14%, with no serious adverse events. Conclusion. ERCP-guided biliary stenting was an effective and safety treatment for BS after LT.
MRI Evaluation of Indomethacin Suppositories in the Prevention of Complications of Pancreatitis and Hyperamylasemia after Choledocholithiasis ERCP Based on Image Denoising Algorithm
Authors: Gao Fusheng , Zhang Chuan , Feng Yue , Zhan Yutao
Published: August 2022

Objective. To explore the value of MRI evaluation of indomethacin suppositories in the prevention of pancreatitis and hyperamylasemia in patients with common bile duct calculi after endoscopic retrograde cholangiopancreatography (ERCP) based on image denoising algorithm. Methods. A retrospective analysis in August 2020 to December 2021. Because of the common bile duct calculi hospitalized parallel ERCP operation, 89 cases of patients, according to the different postoperative treatments, were divided into group A (

n
=
44

) and group B (

n
=
45

), in which A set of separate application inhibits the pancreatic enzyme secretion after surgery drug treatment, and B group on the basis of group A linked with indole beauty Xinshuan treatment. The incidence of postoperative pancreatitis and hyperamylasemia was compared between the two groups. The levels of serum amylase were compared between the two groups. Patients in group B were diagnosed with pancreatitis by conventional MRI and MRI with denoising algorithm, respectively, and the imaging characteristics and diagnosis rate differences of the two methods were observed. ROC curve was drawn to evaluate the diagnostic efficacy of MRI denoising algorithm for postoperative pancreatitis and serum amylase level detection for hyperamylasemia. Results. The incidence of postoperative pancreatitis and hyperamylasemia in group B was significantly lower than that in group A (

P
<
0.05

). There were 6 cases of postoperative pancreatitis in group B, 2 cases (33.33%) were diagnosed by conventional MRI, and 5 cases (83.33%) were diagnosed by MRI based on denoising algorithm. Although there was no significant difference in diagnosis rate between the two methods, the number of cases of pancreatitis diagnosed by MRI based on denoising algorithm was slightly higher than that by conventional MRI. Compared with conventional MRI images, MRI images with denoising algorithm showed that the number of cases with pancreatic swelling, the number of cases with pancreatic duct/bile duct dilation, and the number of cases with abdominal effusion were all high (all

P
<
0.05

). ROC results showed that the area under the curve of MRI with denoising algorithm for the diagnosis of postoperative pancreatitis was 0.855, and the sensitivity was 89.40%. The specificity was 83.20%, and the area under the curve of serum amylase for postoperative hyperamylasemia was 0.893, the sensitivity was 89.80%, and the specificity was 85.20%, all of which had high diagnostic efficacy. Conclusion. MRI results of denoising algorithm suggest that indomethacin suppositories can effectively reduce the incidence of postoperative pancreatitis and hyperamylasemia after ERCP, which is worthy of clinical application.
Prognostic Factors of Combined Periodontal and Endodontic Lesions: A Retrospective Study
Authors: Guo Jinhong , Li Ying , Lin Xuandong , Yang Xiaomei , Shi Wei , Lu Xiaoling
Published: August 2022

Objective. This study used a retrospective method to explore the relevant factors affecting the prognosis of periodontal‐endodontic combined lesions. Methods. According to the changes of subjective feelings and clinical indicators of affected teeth, selected patients were divided into an effective group and an ineffective group. The natural conditions (age, gender, and smoking status) of the patients and various clinical indicators at the initial and follow‐up visits were collected, including the periodontal clinical indicators of the whole mouth and the clinical indicators of the affected teeth. The full‐mouth periodontal clinical indicators include periodontal probing depth (PD), clinical attachment loss (CAL), sulcus bleeding index (SBI), and simplified oral hygiene index (OHI.S); clinical indicators of affected teeth include PD, CAL, SBI, mobility (TM), clinical crown‐to‐root ratio (CR), periapical index (PAI), and number of root canals. Results. There were 74 cases of endodontic combined treatment, with a total of 86 teeth. There was no significant difference in age and gender ratio between the effective group and the ineffective group, and the proportion of smoking patients in the ineffective group was significantly higher than that in the effective group (P < 0.05). At the initial diagnosis, there was no significant difference in the clinical indicators of the whole mouth between the effective group and the ineffective group. After a combined endodontic treatment, the clinical indicators of the two groups were significantly improved (P < 0.01). There was no significant difference in other periodontal clinical indicators between the two groups. Conclusion. The prognosis of nonsurgical treatment of periodontal and periodontal combined lesions is mainly correlated to the patient’s oral hygiene maintenance, as well as the loss of attachment, the degree of loosening, the clinical crown‐to‐root ratio, the periapical index, and the number of root canals.
Study on Characteristic Raman Shift Screening Method Based on MPA for Raman Spectrum of Mine Water Inrush Source
Authors: Zhou Minghao , Dai Rongying
Published: August 2022

In the process of mine water inrush disaster prevention, accurate and rapid identification of water inrush source type is of great significance to coal mine safety production. However, traditional hydrochemical methods have shortcomings such as time-consuming and complex detection. Therefore, a new idea of identifying mine water inrush source by Raman spectroscopy is proposed. Goaf water, roof sandstone fissure water, Ordovician limestone water, Taiyuan limestone water, and surface water as well as their mixed water samples are selected as research objects, and Raman spectral data of different water samples are collected by the Raman spectroscopy system. To eliminate the influence of laser power fluctuation and spectrometer system noise in Raman spectrum acquisition, detrend correction (DC), multiplicative scatter correction (MSC), standard normal variate transformation (SNV), first derivative (FD), and mean centering (MC) were used to preprocess the raw Raman spectra. Due to the large dimension and long analysis time of Raman spectrum data, the marine predator algorithm (MPA) is used to screen the characteristic Raman shifts of the Raman spectrum of water samples, and the characteristic Raman shift information that can best characterize the mine water samples is obtained. Finally, to verify the feasibility of MPA screening the characteristic Raman shifts of Raman spectrum of mine water inrush source, the selected characteristic Raman displacement information is used as input to construct BP neural network (BP), k-nearest neighbor algorithm (KNN), support vector machine (SVM), and decision tree (DT) classification models, respectively. Experiments show that SNV has the best preprocessing effect on the raw Raman spectrum, which can effectively eliminate part of the noise in the Raman spectrum data and improve the accuracy of Raman spectrum identification. Using MPA, 226 characteristic Raman shifts can be screened from 2048 Raman data points, reducing the number of Raman shifts to 11.04%, and the modeling accuracy of characteristic Raman shift information screened by MPA is higher than that of full Raman data. In addition, the average analysis speed of BP, KNN, SVM, and DT water source identification models is 7.61 times faster than that of all Raman data. The results show that MPA is adopted to screen the characteristic Raman displacement of mine water source Raman spectrum, which can effectively reduce the redundancy of Raman spectral data and greatly improve the speed of Raman spectral analysis, which is of great significance to ensure the real-time detection of the mine water source.
The Preparation of Eco-Friendly Magnetic Adsorbent from Wild Water Hyacinth (Eichhornia crassipes): The Application for Removing Lead Ions from Industrial Wastewater
Authors: Tran Thien Khanh , Le Quang Dung , Vo Thi Muoi , Diep Minh Quang , Nguyen Thanh Duy , Huynh Hau Huu , Ly Quoc Khanh , Kim Namkeun
Published: August 2022

Water hyacinth ( Eichhornia crassipes) is a wild floating plant that can be found widely in pond or river areas. The plant grows fiercely and causes many harmful issues to the ecosystem around its covered area. This work provides a utilization method that converts wild water hyacinth to reliable magnetic biochar which can be used as a very effective adsorbent for the removal of lead ion Pb(II) in industrial wastewater. The mentioned magnetic biochar can be prepared via a modified pyrolysis process at 550°C with the support of cobalt sulfates as magnetite precursors and limited oxygen from the sweeping gas (the gas mixture ratio is 4 : 1 nitrogen/oxygen). The produced samples were hydrophobic biochar with high oxygen-containing functional groups that are suitable for the removal of inorganic contaminants. The impregnation of cobalt (II, III) oxides provided high magnetic separation performance and additional adsorption sites on the produced magnetic biochar. As indicated by the obtained result, the WHB-Co2M sample possesses a highly porous structure (0.126 cc/g), higher thermal stability (thermal durability reaches 900°C), relatively stable magnetic properties (14.74 emu/g), and a larger surface area (192 m2/g). These beneficial properties led to its suitability to serve as an adsorbent in removing lead ions in the contaminated effluent, recording 95% of removal efficiency and adsorption capacity of 67.815 mg/g. As indicated in the result, all prepared magnetic biochar samples were fitted to two-parameter (Langmuir models) and three-parameter (Sips model) isotherm models. Therefore, the adsorption process in this work could be carried out on both homogeneous and heterogeneous adsorbent surfaces. The adsorption kinetics of the removal process also was described by the pseudo-first-order, pseudo-second-order, and Elovich models to reveal the adsorption and desorption rate of the as-prepared magnetic biochar. This work indicates a successful waste refinery route of converting lignocellulosic biomass such as water hyacinth into value-added material for use as promising heavy metal adsorbents.
A Novel Defined RAS-Related Gene Signature for Predicting the Prognosis and Characterization of Biological Function in Osteosarcoma
Authors: Chen Qin , Zhou Xueliang , Jin Jianqiang , Feng Jiangbiao , Xu Zhounan , Chen Yunping , Zhao Haibo , Li Zhongchen
Published: August 2022

Background. Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents with a high incidence and poor prognosis. Activation of the RAS pathway promotes progression and metastasis of osteosarcoma. RAS has been studied in many different tumors; however, the prognostic value of RAS-associated genes in OS remains unclear. On this basis, we investigated the RAS-related gene signature and explored the intrinsic biological features of OS. Methods. We obtained RNA transcriptome sequencing data and clinical information of osteosarcoma patients from the TARGET database. RAS pathway-related genes were obtained from the KEGG pathway database. Molecular subgroups and risk models were developed using consensus clustering and least absolute shrinkage and selection operator (LASSO) regression, respectively. ESTIMATE algorithm and ssGSEA analysis were used to assess the tumor microenvironment and immune penetrance between the two groups. A comprehensive review of gene ontology (GO) and KEGG analyses revealed inherent biological functional differences between the two groups. Results. The consistent clustering showed stratification of osteosarcoma patients into two subtypes based on RAS-associated genes and provided a robust prediction of prognosis. A risk model further confirmed that RAS-related genes are the best prognostic indicators for OS patients. GO analysis showed that GDP/GTP binding, focal adhesion, cytoskeletal motor activity, and cell-matrix junctions were associated with the RAS-related model group. Furthermore, RAS signaling in osteosarcoma based on KEGG analysis was significantly associated with cancer progression, with immune function and tumor microenvironment particularly affected. Conclusion. We constructed a prognostic model founded on RAS-related gene and demonstrated its predictive ability. Then, furtherly exploration of the molecular mechanisms and immune characteristics proved the role of RAS-related gene in the dysregulation in OS.
Analysis of Velocity Measurement for Transonic Projectiles in Indoor Long Ballistic Range
Authors: Cai Rongli , Tan Linqiu , Chen Rui , Guo Quanmin , Huang Liangliang
Published: August 2022

The indoor one-kilometer projectile velocity measurement system cannot accurately identify the transonic projectile signal due to the interference signals generated by aerodynamics and other factors. To solve this problem, theoretical prediction of the projectile velocity at the transonic velocity measurement point is calculated by external ballistic numerical simulation technology based on the motion law of the center of projectile mass and the known measurement parameters of the indoor measurement system. In the measurement, a fast cross-correlation algorithm is used to process the projectile signals including interference signals and obtain velocity values at the measurement point. Then the theoretical prediction is used as the reference standard and the velocity with the smallest absolute value of the absolute error is selected as the desired measured value. A 5.8 mm rifle bullet is used to conduct an indoor one-kilometer live experiment. The results show that the relative errors between the measured value obtained by this method and the theoretical prediction are less than 1%, which eliminates the influence of interference signals and provides a new method for the accurate measurement of the transonic projectile velocity.
Construction of Primary and Secondary School Teachers’ Competency Model Based on Improved Machine Learning Algorithm
Authors: Wu JunNa
Published: August 2022

In order to quantitatively evaluate the competence of primary and secondary school teachers, a competency model of primary and secondary school teachers based on an improved machine learning algorithm is proposed. The fitting parameter analysis model of primary and secondary school teachers’ competency is constructed, and the fitting benefit degree parameter of primary and secondary school teachers’ competency is extracted based on the analysis results of reliability index parameters. The improved machine learning algorithm is used to carry out quantitative analysis and characteristic element analysis in the process of primary and secondary school teachers’ competency evaluation and determine the competency elements of the model. According to the machine learning model, the competency elements are conceptualized and classified, and the theoretical parameter analysis model of online teaching competency of primary and secondary school teachers is constructed to realize the assessment and quantitative analysis of primary and secondary school teachers’ competency. Factor analysis and reliability tests were performed using the KMO test and Bartlett test. The empirical simulation analysis results show that the reliability and accuracy of the evaluation of primary and secondary school teachers’ competence by this method are good, and the level of credibility is high.
Comparison of Early Efficacy of the Percutaneous Presuture Technique with the Femoral Artery Incision Technique in Endovascular Aortic Repair under Local Anesthesia for Uncomplicated Type B Aortic Dissection
Authors: Wu Qingsong , Jiang Debin , Lv Xiaochai , Zhang Jiaxin , Huang Rongda , Qiu Zhihuang , Chen Liangwan
Published: August 2022

Objective. To compare the efficacy of the percutaneous presuture technique (PPST) and the femoral artery incision technique (FAIT) under local anesthesia in the treatment of endovascular aortic repair (EVAR) for patients with uncomplicated type B aortic dissection (uTBAD). Method. Two hundred and ninety-five patients diagnosed with uTBAD who underwent EVAR under local anesthesia from June 2017 to December 2021 were consecutively and randomly selected for retrospective analysis. The PPST was performed in 178 cases and the FAIT was performed in 117 cases. The clinical characteristics and surgical and postoperative data from the two groups were analyzed. Results. There were no significant differences in clinical characteristics between the two groups (

p
>
0.05

). The operative time of the PPST group was significantly shorter than that of the FAIT group (46 (33, 58) versus 72 (67.5, 78.0) minutes,

p
<
0.001

), as was the operative approach procedure time (6 (4.5, 9.0) versus 38 (36.5, 43.5) minutes,

p
<
0.001

), and length of postoperative hospital stay (5.19 ± 2.26 versus 8.33 ± 3.76 days,

p
<
0.001

). There were fewer postoperative approach-related procedural complications in the PPST group than in the FAIT group (2 versus 12,

p
<
0.001

); similarly, the average frequency of postoperative wound disinfection was significantly lower in the PPST group (1.08 ± 0.39 versus 3.31 ± 0.91 times,

p
<
0.05

). Obesity was identified as an independent risk factor for postoperative approach-related procedural complications (OR, 22.26; 95% CI, 4.74–104.49;

p
<
0.001

). Conclusions. The PPST has comparable safety and efficacy to the FAIT in EVAR under local anesthesia. It can shorten the length of hospital stay, reduce operation time, lower the risk of wound-related complications, reduce the frequency of postoperative wound disinfection, and hasten postoperative recovery. It can therefore be used as a first-line surgical technique in EVAR of uTBAD under local anesthesia, especially in obese patients.
Dynamic Load Prediction Model of Electric Bus Charging Based on WNN
Authors: Zheng Chang , Peng Tao , Chao Zhang , Shasha Zhao , Xiaoyu Liu , Han Li
Published: August 2022

Electric buses have a significant penetration rate and high charging frequency and amount. Therefore, their charging load has a momentous influence on the power grid’s operation and dispatch. There are important theoretical and practical reasons to study electric bus charging load prediction; however, the intermittent and random charging behavior of buses makes it more difficult to predict charging load predictions, particularly, in real time. To accomplish this, in this paper a WNN (wavelet neural network)-based dynamic load prediction model for charging electric buses is suggested. We start by using distance and shape to group the charging load curve which, in fact, is done with spectral clustering. As a second step, we take into account a wide range of charging load-affecting variables such as temperature and time of day, in order to better train the WNN. Moreover, the charge loads for each cluster are predicted based on model parameters; subsequently, the forecast day’s total charging load is then calculated by summing the prediction results for each cluster; finally, the proposed method is validated using a real city data set. In our empirical evaluation, it has been found that, under various indicators, the proposed method’s ability to precisely forecast the charging load of electric vehicles has significantly improved. In fact, this allows for better guidance of charging user, planning, and expanding the power grid in consideration of electric vehicle charging loads.
A Novel Ferroptosis-Related Gene Signature for Prognosis Prediction in Ewing Sarcoma
Authors: Zhao Runhan , Li Zefang , Huang Yanran , Xiong Chuang , Zhang Chao , Liang Hao , Xu Jingtao , Luo Xiaoji
Published: August 2022

Ferroptosis, as a form of programmed cell death independent of apoptosis, has been demonstrated that plays a major role in tumorigenesis and cancer treatment. A comprehensive analysis of ferroptosis-related genes (FRGs) may lead to a novel choice for the treatment of Ewing sarcoma (ES). Here, 148 differentially expressed FRGs (DEFRGs) were identified between normal and ES tissue. And the GO and KEGG analyses of DEFRGs indicated that these genes were enriched in cancer and immune-related signaling pathways. Then, the GSE17679 cohort was randomly divided into train and test cohorts. Based on the train cohort, AURKA, RGS4, and RIPK1 were identified as key genes through the univariate Cox regression analysis, the random survival forest algorithm, and the multivariate Cox regression analysis and utilized to establish a prognostic FRG signature. The validation results demonstrated that the gene signature has not only excellent prediction performance and generalization ability but is also good at predicting the response of immunotherapy and chemotherapy. Subsequent analysis indicated that all 3 key genes play key roles in tumor immunity and prognosis of ES. Of these, AURKA was highly associated with EWSR1, which was verified by a single-cell dataset (GSE130019). Therefore, the 3 genes may be potential therapeutic targets for ES. At the end of this study, we also constructed an accurate nomogram that helps clinicians to assess the survival time of ES patients. In conclusion, our study constructed an excellent gene signature, which is helpful in improving the prognosis of ES patients.
Mitochondria-Associated Endoplasmic Reticulum Membranes: Inextricably Linked with Autophagy Process
Authors: Ji Chonghao , Zhang Zhanwei , Li Zechuan , She Xiao , Wang Xiaoya , Li Binyang , Xu Xin , Song Dawei , Zhang Dongjiao
Published: August 2022

Mitochondria-associated membranes (MAMs), physical connection sites between the endoplasmic reticulum (ER) and the outer mitochondrial membrane (OMM), are involved in numerous cellular processes, such as calcium ion transport, lipid metabolism, autophagy, ER stress, mitochondria morphology, and apoptosis. Autophagy is a highly conserved intracellular process in which cellular contents are delivered by double-membrane vesicles, called autophagosomes, to the lysosomes for destruction and recycling. Autophagy, typically triggered by stress, eliminates damaged or redundant protein molecules and organelles to maintain regular cellular activity. Dysfunction of MAMs or autophagy is intimately associated with various diseases, including aging, cardiovascular, infections, cancer, multiple toxic agents, and some genetic disorders. Increasing evidence has shown that MAMs play a significant role in autophagy development and maturation. In our study, we concentrated on two opposing functions of MAMs in autophagy: facilitating the formation of autophagosomes and inhibiting autophagy. We recognized the link between MAMs and autophagy in the occurrence and progression of the diseases and therefore collated and summarized the existing intrinsic molecular mechanisms. Furthermore, we draw attention to several crucial data and open issues in the area that may be helpful for further study.
Separation of Different Blogs from Skin Disease Data using Artificial Intelligence
Authors: Abdulaal Mohammed J. , Mehedi Ibrahim M. , Aljohani Abdulah Jeza , Milyani Ahmad H. , Mahmoud Mohamed , Abusorrah Abdullah M. , Jannat Rahtul
Published: August 2022

A combination of environmental conditions may cause skin illness everywhere on the earth, and it is one of the most dangerous diseases that can develop as a result. A major goal in the selection of characteristics is to produce predictions about skin disease instances in connection with influencing variables, which is one of the most important tasks. As a consequence of the widespread usage of sensors, the amount of data collected in the health industry is disproportionately large when compared to data collected in other sectors. In the past, researchers have used a variety of machine learning algorithms to determine the relationship between illnesses and other disorders. Forecasting is a procedure that involves many steps, the most important of which are the preprocessing of any scenario and the selection of forecasting features. A major disadvantage of doing business in the health industry is a lack of data availability, which is particularly problematic when data is provided in an unstructured format. Filling in missing numbers and converting between various types of data take somewhat more than 70% of the total time. When dealing with missing data in machine learning applications, the mean, average, and median, as well as the stand mechanism, may all be employed to solve the problem. Previous research has shown that the characteristics chosen for a model’s overall performance may have an influence on the overall performance of the model’s overall performance. One of the primary goals of this study is to develop an intelligent algorithm for identifying relevant traits in models while simultaneously eliminating nonsignificant attributes that have an impact on model performance. To present a full view of the data, artificial intelligence techniques such as SVM, decision tree, and logistic regression models were used in conjunction with three separate feature combination methodologies, each of which was developed independently. As a consequence of this, their accuracy, F-measure, and precision are all raised by a factor of ten, respectively. We then have a list of the most important features, together with the weights that have been allocated to each of them.
Influence of Autologous Bone Marrow Stem Cell Therapy on the Levels of Inflammatory Factors and Conexin43 of Patients with Moyamoya Disease
Authors: Zhao Liming , Li Tianxiao , Xue Bingqian , Liang Hao , Zhang Shao , Wu Ruiyu , Guo Gaochao , Gao Tao , Liu Yang , Sun Yuxue , Li Chaoyue
Published: August 2022

Moyamoya disease is a medical condition that shows the typical characteristics like continuous and chronic thickening of the walls and the contraction of the internal carotid artery; as a result, the internal diameter of the artery gets narrowed. There are six phases of the disease ranging from I to VI (moyamoya vessels completely disappear, followed by the complete blockage of the arteries). Surgery is a commonly recommended treatment for the moyamoya disease. Our research study identifies the effect of autologous bone marrow stem cell therapy (ABMSCT) on the levels of inflammatory factors and Conexin43 (Cx43) protein in patients suffering from moyamoya. In our study, we have selected 52 moyamoya patients admitted to our hospital from 30 July 2019 to 10 February 2020. The control group (CG) was treated with superficial temporal artery to a middle cerebral artery (STA-MCA) bypass + encephalo-duro-myosinangiosis (EDMS). The experimental group (Exp. Grp) was treated with ABMSC. The cerebral vascular tissue of the patients was treated with hematoxylin-eosin (HE) staining. Immunohistochemical staining was used to identify the levels of Cx43 protein. The concentrations of vascular endothelial growth factor (VEGF), inflammatory factor interleukin-6 (IL6), interleukin-1β (IL1β), tumor necrosis factor (TNFα), and anti-inflammatory factor interleukin-1β (IL1β) were determined by enzyme-linked immunosorbent assay (ELISA). We have found that after treatment of the expression of Cx43 protein, the proportions of grade IV (7.7%), grade III (311.5%), and grade II (3.8%) patients in the Exp. Grp were lower than those in the CG. The proportion of grade I patients in the Exp. Grp (77%) was higher than that in the CG (38.5%). After treatment, the inflammatory factors IL6 (0.97 ± 0.82 pg/mL), IL1β (8.33 ± 1.21 pg/mL), and TNFα (1.73 ± 0.71 pg/mL) in the Exp. Grp were lower than those in the CG. The anti-inflammatory factor IL1β (15.09 ± 4.72 pg/mL) increased in the Exp. Grp compared with the CG (11.25 ± 3.48 pg/mL) post treatment. Intracranial infection, hydrocephalus, hemiplegia, and transient neurological dysfunction in the Exp. Grp were lower than those in the CG, with statistical differences

P
<
0.05

. Our study suggests that the treatment of autologous bone marrow stem cells (ABMSC) was beneficial to balance the inflammatory response of disorders, reduce the damage of vascular tissue in the brain, and regulate tissue repair by co-acting with various inflammatory factors as compared to traditional surgery. We conclude that the involvement of Cx43 in the occurrence and development of moyamoya. We also have found that the risk factors of intracranial infection after ABMSCT were less as compared to those after conventional surgery.
[Retracted] Value of CT Radiomics and Clinical Features in Predicting Bone Metastases in Patients with NSCLC
Authors: Chen Lu , Yu Lijuan , Li Xueyan , Tian Zhanyu , Lin Xiuyan
Published: August 2022

Objective. To explore the CT radiomic features and clinical imaging features of the primary tumor in patients with nonsmall cell lung cancer (NSCLC) before treatment and their predictive value for the occurrence of bone metastases. Methods. From June 2017 to June 2021, 195 patients with NSCLC who were pathologically diagnosed without any treatment in the Cancer Hospital Affiliated to Hainan Medical College were retrospectively analyzed, and they were divided into a bone metastasis group and a nonbone metastasis group. The relationship between clinical imaging features and bone metastasis in patients was analyzed by the t‐test, rank sum test, and χ2 test. At the same time, ITK software was used to extract the radiomic characteristics of the primary tumor of the patients, and the patients were randomly divided into a training group and a validation group in a ratio of 7 : 3. The training model was validated in the validation group, and the performance of the model for predicting bone metastases in NSCLC patients was verified by the ROC curve, and a multivariate logistic regression prediction model was established based on the omics parameters extracted from the best prediction model combined with clinical image features. Results. Seven features were screened from the primary tumor by LASSO to establish a model for predicting metastasis. The area under the curve was 0.82 and 0.73 in the training and validation sets. The best omics signature and univariate analysis suggested clinical imaging factors (P < 0.05) associated with bone metastases were included in multivariate binary logistic analysis to obtain clinical characteristics of the primary tumor such as gender (OR = 0.141, 95% CI: 0.022–0.919, P = 0.04), increased Cyfra21‐1 (OR = 0.12, 95% CI: 0.018–0.782, P = 0.027), Fe content in blood (OR = 0.774, 95% CI: 0.626–0.958, P = 0.018), CT signs such as lesion homogeneity (OR = 0.052, 95% CI: 0.006–0.419, P = 0.006), pleural indentation sign (OR = 0.007, 95% CI: 0.001–0.696, P = 0.034), and omics characteristics glszm_Small Area High Gray Level Emphasis (OR = 0.016, 95% CI: 0.001–0.286, P = 0.005) were independent risk factors for bone metastasis in patients. Conclusion. The prediction model established based on radiomics and clinical imaging features has high predictive performance for the occurrence of bone metastasis in NSCLC patients.
The Protective Effect of Artesunate on LPS-Induced Acute Respiratory Distress Syndrome through Inhibiting NLRP3 Inflammasome Signaling
Authors: Cui Yifei , Weng Wenbo , Ding Qing , Su Qinghua , Wang Xiaoying
Published: August 2022

Background. Artesunate (AS) is a derivative of artemisinin that can exert anti-inflammatory effects. This study aims to explore the effect of AS on lipopolysaccharide (LPS)-induced acute respiratory distress syndrome (ARDS). Methods. The newborn mice were used for experimental ARDS model establishment by intraperitoneal injection of LPS (10 mg/kg) into mice with or without AS (20 mg/kg) pretreatment. After that, the pathological morphology of mouse lung tissue was observed by H&E staining. The content of inflammatory factors in serum was measured by ELISA and mRNA expression and lung tissue was determined by qRT-PCR. The expression of NLRP3 inflammasome and related proteins in lung tissue was confirmed by immunohistochemistry and Western blot. Results. AS treatment effectively alleviated the LPS-induced lung injury and pulmonary edema, and reduced the expression of IL-1β, IL-18, IL-6, IL-8, MCP-1, and TNF-α in serum and lung tissues of experimental ARDS mice. In addition, AS treatment reduced the expression of NLRP3, ASC, and caspase-1 in lung tissues of experimental ARDS mice. Conclusion. AS alleviated LPS-induced lung injury in ARDS mice by inhibiting the activation of NLRP3 inflammasome.
[Retracted] Predictive Significance of High‐Sensitivity C‐Reactive Protein Combined with Homocysteine for Coronary Heart Disease in Patients with Anxiety Disorders
Authors: Liu Changhe , Hua Na , Zhang Yanli , Wang Cuirong
Published: August 2022

Background. Currently, there are few studies on biomarkers for predicting coronary heart disease (CHD) with anxiety disorders. Objective. To explore risk factors and investigate the predictive value of common clinical peripheral blood indicators, such as high‐sensitivity C‐reactive protein (hs‐CRP) and homocysteine (Hcy) for CHD patients with anxiety disorders. Methods. One hundred fifty‐three hospitalized patients with chest pain as the main symptom and a Hamilton Anxiety Scale score > 14 were recruited from October 2020 to September 2021 in the hospital. Then, they were divided into an anxiety disorder with CHD group (observation group, n = 64) and a simple anxiety disorder group (control group, n = 89), according to coronary angiography (CAG) findings. Patients’ demographic and clinical messages were collected and compared. Diabetes mellitus and hypertension, body mass index (BMI), and peripheral blood interleukin‐6 (IL‐6), high‐sensitivity C‐reactive protein (hs‐CRP), homocysteine (Hcy), fibrinogen, D‐dimer, cortisol, and norepinephrine expression levels were compared. Binary logistic regression analysis screened independent risk factors of CHD patients with anxiety disorders. The effectiveness of independent risk factors in predicting CHD with anxiety disorders was analyzed using receiver operating characteristic (ROC) curves. Results. IL‐6, hs‐CRP, and Hcy levels of anxiety disorder in the CHD group were significantly higher than those in the simple anxiety disorder group. Binary multiple logistic regression analysis indicated that IL‐6, hs‐CRP, and Hcy were independent risk factors for CHD in patients with anxiety disorders. hs‐CRP and Hcy levels were positively correlated with the Gensini score. ROC curve analysis indicated that the detection of hs‐CRP or Hcy alone or the combined detection of the 2 had clinical predictive value for CHD in patients with anxiety disorders, and the area under the curve (AUC) of the combined detection of the 2 was significantly larger than that of any single factor alone (vs. hs‐CRP, P = 0.045; vs. Hcy, P = 0.045). Conclusion. IL‐6, hs‐CRP, and Hcy are related to CHD with anxiety disorders. Serum levels of the combined detection of hs‐CRP and Hcy have a high clinical predictive value for CHD in patients with anxiety disorders.
Numerical Simulation and Experimental Research on Multi-Point Forming of Aluminum Alloy Sheets Based on Ultrasonic Vibration
Authors: Li Xinqi , Hu Shicheng
Published: August 2022

In this study, the multi-point plastic forming of 2024-O aluminum alloy sheets is the research object, ultrasonic vibration-assisted forming is applied in the stamping process, a combination of ABAQUS/EXPLICITE numerical simulation and theory is used, and multi-point forming experiments are performed to verify the research. In the process of multi-point forming, the influence of ultrasonic vibration on the plastic deformation and springback of sheet metal has inspired a new idea and method for multi-point forming of sheet metal. This paper presents the following: the basic theory of multi-point stamping and ultrasonic vibration-assisted metal sheet plastic forming; a comparison of the material parameters of the multi-point stamping method with and without ultrasonic vibration; the influence of different times on the results; the changes in parameters such as stress and strain at different frequencies; and the effect of its springback.
Selecting Endophytes for Rhizome Production, Curcumin Content, Biocontrol Potential, and Antioxidant Activities of Turmeric (Curcuma longa)
Authors: Sontsa-Donhoung Alain-Martial , Bahdjolbe Marcelin , Hawaou  , Nwaga Dieudonné
Published: August 2022

Beneficial endophytes may enhance plant growth and stress tolerance. Yet, the plant health benefits of endophytes can be altered by biotic and abiotic factors and, thus, favour the inhibition of turmeric growth and curcumin production. The double petri dish method and greenhouse pot experiments were conducted to assess the biocontrol potential and impact of endophytes on the output, curcumin levels, and antioxidant activities of turmeric (Curcuma longa L.). The results showed that endophytes could control some disease‐causing plant pathogens: 52% of all isolates have an antagonistic action against Fusarium oxysporum, 43% against Pythium myriotylum, 35% against Phytophthora megakarya, and 56% against Ralstonia solanacearum in vitro. Eight months after sowing, most endophyte isolates can increase the yield of turmeric rhizomes on a sterile substrate after inoculation, with yields ranging from 42 to 105% higher than the control and 3 to 50% higher than the urea treatment. In addition, 52% endophytes isolate significantly raised curcumin levels after 8 months of culture (from 2.1 to 3.1%) compared to control (1.7%) and urea treatment (1.8%). These endophytes promote an increase in the levels of reduced glutathione (22%), total thiols (26%), and carotenoids (91%) in turmeric. The study concludes that, in general, the endophytes‐turmeric association can stimulate turmeric rhizome production, curcumin, and the antioxidant activities of the plant. They can also be used as biocontrol agents for plant pathogens.