syedzayyan/paper_mill_benchmark huggingface dataset:
MiR-129-5p Inactivates NF-iκ/iB Pathway to Block Rheumatoid Arthritis Development via Targeting BRD4

Object.Rheumatoid arthritis (ra) is an osteoarticular disease which seriously affects the motor abilities of the patients.Micro rna disorder has been confirmed as a biomarker event in ra development, and several studies have identified that mi r-129-5p is related with the progression of multiple bone diseases.The study attempted to investigate the regulation mechanism of mi r-129-5p in ra development.Methods.The abundance of mi r-129-5p was detected in the samples including normal tissues and ra tissues and cell lines including human fibroblast-like synoviocytes (h flss) and human rheumatoid arthritis fibroblast-like synoviocytes (ra-flss).The cck-8 assay, flow cytometry, transwell, and elisa were used to observe the effects of mi r-129-5p on the phenotype of ra-flss.Moreover, the potential targets of mi r-129-5p were identified with target scan and dual-luciferase reporter gene assay.Besides, the abundances of the proteins were analyzed with western blot.Results.Decreased mi r-129-5p was observed in ra tissues and cells.Increased mi r-129-5p obviously blocked the proliferation, inflammatory stress, and migration and remarkably promoted cellular apoptosis.Moreover, brd4 was confirmed as targets of mi r-129-5p, and brd4 upregulation could partly rescue the inhibition of mi r-129-5p on aggressive behaviors of ra-flss.Besides, the finding of this study also proved that upregulated mi r-129-5p could impede the nf-κb pathway via targeting brd4.Conclusion.This study suggests that mi r-129-5p suppresses the activation of nf-κb pathway to block the progression of ra via targeting brd4.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
MicroRNA-641 Inhibits Endometrial Cancer Progression via Targeting AP1G1

Micro rna-641 (mi r-641) was significantly decreased in various cancers, but its roles in endometrial cancer (ec) remain unclear.We explored the influences of mi r-641 on the ec cells.In our study, the mi r-641 expression was reduced in ec cells.Overexpression of mi r-641 inhibited viability and proliferation of hec-1a and heccl-1 cells by cck-8 and colony formation assays.Additionally, flow cytometry revealed that overexpression of mi r-641 could remarkably promote apoptosis and arrest the cell cycle at the g1 phase of hec-1a and heccl-1 cells.Besides, forced expression of mi r-641 suppressed the migration and invasion of hec-1a and heccl-1 cells as evidenced by wound healing and transwell assay.Moreover, ap1g1 was confirmed as a target gene of mi r-641 by star base prediction and dlr assay and their expressions were negatively correlated.Overexpression of ap1g1 neutralized the roles of mi r-641 mimic on the viability, proliferation, apoptosis, and migration of hec-1a and heccl-1 cells.Our findings illustrated that mi r-641 was reduced in the ec cells and ap1g1 antagonized the mi r-641 mimic-induced inhibition of the ec progression in vitro.Therefore, mi r-641 may emerge as an effective molecule for ec treatment.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;
Method of Ideological and Political Teaching Resources in Universities Based on School-Enterprise Cooperation Mode

The personalized recommendation system influences the recommendation of ideological and political teaching resources in universities, resulting in a high mae score.As a result, under the school-enterprise collaboration paradigm, this study proposes a customised recommendation approach for ideological and political teaching resources in colleges and universities.The ideological and political teaching resource bank is developed against the backdrop of the teaching paradigm that combines universities and businesses.Learners’ browsing data history is gathered to create a learning interest model for them.A hybrid collaborative filtering recommendation method was devised, and a recommendation engine was established by taste component, taking into account individualised resource recommendation needs and information entropy weight distribution mode.When compared to previous techniques, the developed customised recommendation method considerably enhances the recommendation quality of instructional resources and reduces mae by 29% and 34%, respectively.

Journal: Mathematical Problems in Engineering (2022)
Publication types: Research Article;
Management Strategy of Alzheimer’s Patients under the Medical-Care Integration Model Based on Big Data Evaluation

In the context of the era of big data, the management of alzheimer’s patients has aroused widespread concern in the society.What should the elderly and people with dementia do and how the society should accommodate these special groups have aroused heated discussions in the society.The goal of the medical‐nursing integration model is to realize the integrated model of medical care‐nursing‐rehabilitation‐old care, and to better satisfy the needs by providing medical services, rehabilitation care, and health management.The medical needs of the elderly can help the elderly maintain a healthy state; the elderly care needs can be better met through elderly care services, and the burden on families and society can be reduced.With the advancement of the medical‐care integration model, new solutions have been provided for the management of senile dementia patients.Therefore, under the medical‐care integration model, this paper managed alzheimer’s patients based on the big data algorithm based on association rules and compared it with the management of alzheimer’s patients under the traditional model, and drew the following conclusions: compared with the management satisfaction of alzheimer’s patients under the traditional model, family members and patients’ total satisfaction with nursing management under the medical‐care integration model was greatly improved; compared with the management of alzheimer’s patients under the traditional model, the incidence of adverse events in the management of alzheimer’s patients under the medical‐care integration model was greatly reduced, which was reduced to 17.6%; under the medical‐care integration model, the anxiety and depression scores of the elderly patients with dementia decreased rapidly; under the medical‐care integration model, the living ability of senile dementia patients has been greatly improved; the use of the medical‐care integration model to manage senile dementia patients has greatly improved the sleep quality, mental quality, and quality of life of senile dementia patients.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Magnetic Resonance Neuroimaging Contrast Agents of Nanomaterials

Since the early 1980s when mri imaging technology was put into clinical use, the number of mri clinical tests has steadily increased by more than 10% every year.At the same time, exogenous mri contrast agents have also been developed with the development of mri technology.However, there are still challenges in the preparation of contrast agents for magnetic resonance imaging, such as how to prepare high‐efficiency contrast agents with high stability and low biological toxicity.In order to study the contrast agent with simple preparation method, low cost, and good imaging effect, a magnetic resonance contrast agent was prepared by magnetic nanoparticles.By acting on magnetic resonance imaging detection method, and using polymer ligands to synthesize magnetic nanoparticles, experiments and tests of p(ma‐alt‐vac) polymer ligand‐modified magnetic nanoparticles were carried out.The experimental results showed that when nanoparticles containing different iron ion concentrations were incubated with dc 2.4 normal cells for 48 hours, the cell viability was still higher than 80% at concentrations up to 200 μ m.It shows that the nanoparticle has high cell activity and good biological adaptability.The transverse relaxation ( r 2 ) value of the nanoparticles in aqueous solution at 37°c and 1.5 t magnetic field is 231.1 m -1 s -1 , which is much higher than that of ptmp‐pmaa ( r 2 = 35.1 m m -1 s -1 ), which is also more than five times the relaxation of shu‐555c ( r 2 = 44 m m -1 s -1 ).It shows that the nanoparticles prepared in this paper have good effect and can be used as a contrast agent in human brain for magnetic resonance imaging.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Machine Learning-Based Intelligent Wireless Communication System for Solving Real-World Security Issues

The intelligent wireless system focuses on integrating with the advanced technologies like machine learning and related approaches in order to enhance the performance, productivity, and output.The implementation of machine learning approaches is mainly applied in order to enhance the efficient communication system, enable creation of variable node locations, support collection of data and information, analyze the pattern, and forecast so as to provide better services to the end users.The efficiency of using these technologies tend to lower the cost and support in deploying the resources effectively.The wireless network system tends to enhance the bandwidth, and the application of novel machine learning approaches supports detection of unrelated data and information and enables analysis of latency at each part of the communication channel.The study involves critically analyzing the key determinants of machine learning approaches in supporting enhanced intelligent network communication in the industries.The researchers are aimed at gathering both primary data and secondary data for the study.The respondents are chosen in the industry so that they can provide better inputs and insights related to the area of research.The key determinants considered for the study are machine learning-influenced management of hotspots, identification of critical congestion points, spectrum availability, and management.The analysis is made using spss data analysis package based on which it is noted that all the factors make major influences towards the intelligent communication, and hence machine learning supports critically in enhancing the user experience effectively.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Long-Term Outcomes of Endoscopic Intervention in the Treatment of Symptomatic Pancreas Divisum

To evaluate the efficacy and safety of endoscopic retrograde cholangiopancreatography (ercp) in the treatment of patients with symptomatic pancreas divisum (pd) and to discuss the possible risk factors of endoscopic reintervention for symptomatic pd.A total of 50 patients with symptomatic pd who underwent ercp from january 2010 to december 2019 were finally brought into study.All patients were divided into the nonage and the adult group according to their ages.Meanwhile, all patients were also divided into the intervention and the reintervention group according to times of ercp.The long-term outcome of each patient was collected during the follow-up by phone call.The total success rate of ercp was 94.7% (89/93), and the effective rate of first ercp was 58% (29/50).There were no statistical differences on the outcomes of ercp treatment between the adult and nonage group.There were 17 patients with complete pancreas divisum and 19 patients with chronic pancreatitis in the reintervention group, which were more than 6 patients and 8 patients in the intervention group ( p &lt; 0.05 ).In bivariate regression analysis, chronic pancreatitis and complete pancreas divisum might be significant risk factors for endoscopic reintervention for patients with symptomatic pd (or, 8.010, 95% ci, 1.483–43.276, p = 0.016 ; or, 8.869, 95% ci, 1.450–54.254, p = 0.018 , respectively).Ercp in treating adult and nonage patients with symptomatic pd are effective and safe.But, many patients may need endoscopic reintervention.Complete pancreas divisum and chronic pancreatitis may be risk factors of ercp reintervention for patients with symptomatic pd.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Logistics Optimization Strategy Based on Deep Neural Framework

We propose a logistics optimization method based on improved graph convolutional networks to address the current problem of low product delivery rate and untimely product delivery during the peak period of e-commerce activities.Our method can learn excellent planning strategies from previous data and can give the best logistics strategy in time during the peak logistics period, which improves the product delivery rate and delivery time of logistics and greatly enhances the return on investment.First, we add a tensor rotation module to the graph convolution layer to better capture the global features of logistics nodes.Then we add inception structures in the temporal convolution layer to build multiscale temporal convolution filters to obtain temporal information of logistics nodes in different time-aware domains and reduce arithmetic power.Finally, we cooperate with e-commerce platforms to adopt logistics data as the experimental database.The experimental results show that our method greatly accelerates the logistics planning speed, improves the product delivery rate, ensures the timely delivery of products, and increases the return on investment.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
IoT-Driven Model for Weather and Soil Conditions Based on Precision Irrigation Using Machine Learning

To feed a growing population, sustainable agriculture practices are needed particularly for irrigation.Irrigation makes use of about 85% of the world’s freshwater resources.Thus, for efficient utilization of water in irrigation, conventional irrigation practices need to either be modified or be replaced with advanced and intelligent systems deploying internet of things, wireless sensor networks, and machine learning.This article proposes intelligent system for precision irrigation for monitoring and scheduling using internet of things, long range, low-power (lo ra)-based wireless sensor network, and machine learning.The proposed system makes use of soil and weather conditions for predicting the crop’s water requirement.The use of machine learning algorithms provides the proposed system capability of the prediction of irrigation need.Dataset of soil and weather conditions captured using sensors is used with six different machine learning algorithms, and the best one giving highest efficiency in predicting the irrigation scheduling is selected.Linear discriminant analysis algorithm gives the best efficiency of 91.25% with prediction efficiency.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Innovation and Digital Construction of Cultural Tourism Industry under the Background of Big Data and Internet of Things

In recent years, the concept of the internet of everything has gradually entered all walks of life, and the combination of big data technology and the internet of everything applied to other industries has become the current trend of industrial innovation.The integration between the tourism industry and the cultural industry is an inevitable trend for the sustainable development of the tourism industry.New science and technology are constantly innovating the way of life of human beings.If the tourism industry wants to maintain a state of rapid development, it must focus on the innovative development and digital construction of cultural tourism, develop new cultural tourism products, and propose new marketing innovation models.This promotes faster and better development of the tourism industry.Based on this, this paper designs a questionnaire and uses statistical methods to analyze the data obtained by the questionnaire, summarizes the current problems in the innovation and digital construction of the cultural tourism industry, and proposes solutions in a targeted manner, in order to improve the cultural tourism industry.Healthy development provides incremental contributions.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;
Injury Prevention Effect of MRI Imaging Technology in Physical Education and Sports Training

In order to solve the problem of observing and analyzing the clinical value of mri diagnosis in patients with knee sports injury and guiding clinical targeted treatment, the author proposed a sports injury prevention method in sports training teaching based on mri image observation.This method retrospectively analyzed the imaging data of 101 patients with knee joint mri examination due to osteoarthritis, sports injury and synovitis in joint surgery, and arthroscopic exclusion of true meniscus tear, mr multisequence and multiplane scans were performed to observe the anatomical features of tgl and mfl images and the occurrence rate of the lateral meniscus “false tear sign,” and the χ 2 test was used to compare the occurrence rate of “pseudo-tear sign” between genders and sides.Experimental results show that the incidence of tgl on mri was about 67.3% (68/101), and the incidence of “pseudo-tear sign” in the anterior horn of the lateral meniscus caused by tgl was 2.9% (2/68).The overall appearance rate of mfl on mri was 91.1% (92/101), the appearance rate of plate anterior ligament (hl) was 13.9% (14/101), and the occurrence rate of “pseudo-tear sign” in the posterior horn of the lateral meniscus caused by hl was 7.1% (1/14).The occurrence rate of the posterior ligament (wl) was 77.2% (78/101), and the incidence of “pseudo-tear sign” in the posterior horn was 20.5% (16/78).According to the shape and course of tgl and mfl on mri, and the direction and position of the lateral meniscus pseudotear, combined with mri sagittal plane and coronal plane observation, it can effectively identify the true and false attributes of lateral meniscus anterior and posterior horn tears, thereby reducing unnecessary surgical treatment.

Journal: Scanning (2022)
Publication types: Research Article;
Influence of Sports Intervention Based on K-Center Algorithm on Adolescent Obesity Metabolism and Bone Quality

In order to enable obese adolescents to increase muscle content, base metabolism, etc., aerobic training is used reduce body fat and then improve body components, health physique indicators, and physical fitness.This paper adopts the current situation for research and model construction through the k-center algorithm.The results show that 10 min swimming movement increased the adolescent patients’ level of brain metabolism, and with no less than 15 min, the ci value rose to 41, the increase in brain metabolism in adolescents, and the rate of fat combustion effectively increased.It is guaranteed that physical health prevents the occurrence of obese syndrome diseases.Sports training can not only increase the skinny weight of the teen obese population but also reduce body fat content, which has a significant assistance to body type, is a high-cost performance, and has comprehensive training means.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Industrial Internet of Things Model Driven by Particle Filter and Network Communication Technology

In this paper, a better particle filter algorithm is put forth to address the issues of particle filter sample exhaustion and weight degradation.The algorithm frames the received signal and separates the signals in two steps based on the slow-varying properties of system parameters in practical applications, such as phase shift and transmission delay.In addition, the network model and energy consumption model are built while the sensor data is being collected and processed using the industrial io t’s communication mechanism and algorithm.The repeater is chosen as the node with the lowest transmission energy consumption, and the industrial field’s sensor data is gathered via the fog server node.The simulation results demonstrate that the proposed algorithm’s accuracy rate is 95.54 percent, higher than that of the comparison algorithm.The enhanced algorithm suggested in this paper can simultaneously achieve improved parameter estimation performance and achieve signal separation with low bit error rates.Additionally, the communication system and algorithm can efficiently gather the sensing information from the industrial field, and the indicators like energy consumption and the first dead node are better than other algorithms.It offers an innovative method for enhancing industrial field application.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Immune Subtype Profiling and Establishment of Prognostic Immune-Related lncRNA Pairs in Human Ovarian Cancer

This study collected immune-related genes (irgs) and used gene expression data from tcga database to construct a molecular subtype of ovarian cancer (ov) based on immune-related lnc rna gene pairs (irlnc_gps).The relationships between molecular subtypes and prognosis and clinical characteristics were further explored.Irgs were acquired from the imm port database, and round-robin pairing of immune-related lnc rnas was performed.The nmf algorithm was used to identify molecular subtypes, and the immune score of a single sample was calculated through estimate, timer, ss gsea, mcpcounter, and cibersort.The relationship between molecular subtypes and immune microenvironments was identified.A hypergeometric test was used to test the lnc rna pairs among the ov molecular subtypes (c1 and c2 subtypes).The bh method was used to screen the different lnc rna pairs, and a predictive risk model was constructed and verified.Finally, correlation analysis between the risk model, immune checkpoint genes, and chemotherapy drugs was carried out.Based on irlnc_gp to classify 373 ov samples of tcga, the samples were divided into two subtypes, and the prognosis between the subtypes showed significant differences.The c1 subtype with a poor prognosis was more related to the pathways of tumor occurrence and development.We identified 180 differential lnc rna pairs between subtypes and constructed a prognostic risk model based on 8 irlnc_gps.In the independent dataset, the distribution of subtypes in functional modules was different and highly repeatable.There were significant differences in the molecular and clinical characteristics of the subtypes and the drug sensitivity of immunotherapy/chemotherapy.In conclusion, the risk model established based on irlnc_gp can better evaluate the prognosis of ov samples and can also assess the effects of different drug treatments in the high- and low-risk groups, providing new insights and ideas for the treatment of ov.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;