syedzayyan/paper_mill_benchmark huggingface dataset:
Screening of Risk Factors for Poor Prognosis in Patients with Refractory Epilepsy Secondary to Encephalomalacia

The study was aimed at screening the independent prognostic risk factors for refractory epilepsy associated with encephalomalacia (reae).Methods.Patients with reae treated in the first people’s hospital of linping district from january 2018 to december 2019 were selected.The prognosis was represented by engel grading.Clinical data of the patients were collected, including age, sex, bmi, lesion sites, number of lesion sites, lesion size, seizure frequency, epilepsy type, and treatment methods.Independent risk factors for poor prognosis were screened by logistic regression analysis.The receiver operating characteristic curve (roc) was used to evaluate the prognostic efficacy of independent risk factors.Results.A total of 48 patients were included in this study, including 31 patients (64.58%) in the good prognosis group and 17 patients (35.42%) in the poor prognosis group.The mean age of the poor prognosis group was higher than that of the good prognosis group ( p = 0.002 ).The proportion of patients with multisite lesions in the poor prognosis group was higher than that in the good prognosis group ( p = 0.016 ).The proportion of patients with cerebral malacia lesion diameter ≥ 3 cm in the poor prognosis group was higher than that in the good prognosis group ( p = 0.002 ).The proportion of patients with attack frequency ≥ 2 times / month in the poor prognosis group was higher than in the good prognosis group ( p = 0.002 ).The proportion of patients receiving surgical treatment in the poor prognosis group was lower than that in the good prognosis group ( p &lt; 0.001 ).Age, number of lesion sites, size of encephalomalacia, and seizure frequency were independent risk factors for the prognosis of patients with reae ( or &gt; 1 , p &lt; 0.05 ).Surgical treatment was an independent protective factor associated with the prognosis of patients with reae ( or &lt; 1 , p &lt; 0.05 ).The area under the roc curve of surgical treatment was 0.83 ( p = 0.004 ).The area under the roc curve of the size of encephalomalacia was 0.72 ( p = 0.008 ).There was a positive correlation between age and size of encephalomalacia and engel grade ( r &gt; 0 , p &lt; 0.05 ).Surgical treatment was negatively correlated with engel grade ( r &lt; 0 , p &lt; 0.05 ).The number of lesion sites and seizure frequency had no significant correlation with engel ( p &gt; 0.05 ).The proportion of engel i patients treated with surgery was higher than that treated with drugs ( p = 0.001 ).The ratio of engel iii and iv patients treated with surgery was lower than that treated with medications ( p &lt; 0.05 ).Conclusion.Age, number of lesion sites, size of encephalomalacia, and seizure frequency are independent risk factors for the prognosis of patients with reae.Surgical treatment is an independent prognostic factor for patients with reae.Surgical treatment can significantly improve patient outcomes.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
S100A8/A9 Molecular Complexes Promote Cancer Migration and Invasion via the p38 MAPK Pathway in Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (npc) is one type of malignancy associated with migration and invasion through a currently unclear mechanism.We previously discovered s100a8/a9 levels were roughly elevated in the plasma of npc patients as the promising biomarkers.However, their expressions and underlying functions in npc tissues are still unknown.In the present study, we analyzed 49 npc tissues and 20 chronic pharyngitis (cp) tissues.Immunohistochemical staining was performed in different tissues and analyzed by the mann–whitney u test statistically.Transwell migration and invasion experiments were further performed to determine s100a8/a9 effects on npc.Our results showed that s100a8/a9 in npc tissues were significantly higher than those in cp tissues, closely associated with npc clinical stages.Intriguingly, exogenous s100a8/a9 protein stimulation could dramatically enhance npc migration and invasion abilities.In addition, p38 mapk pathway blockade could diminish the migration and invasion of npc cells stimulated by s100a8/a9 proteins.The downstream tumor invasion and migration associated proteins (e.g., mmp7) were also elevated in npc tissues, consistent with s100a8/a9 overexpression.Taken together, our present findings suggest that the secreted soluble inflammatory factors s100a8/a9 might promote cancer migration and invasion via the p38 mapk signaling pathway along with invasion/migration associated proteins overexpression in the tumor microenvironment of npc.This may shed light on the mechanism understanding of npc prognosis and provide more novel clues for npc diagnosis and therapy.

Journal: Bioinorganic Chemistry and Applications (2021)
Publication types: Research Article;
Role of miR-584-5p in Lipopolysaccharide-Stimulated Human Bronchial Epithelial Cell Inflammation and Apoptosis

Acute lung injury (ali)/acute respiratory distress syndrome is a common clinical syndrome characterized by respiratory failure.Micro rnas (mi rnas) are closely related to ali and acute respiratory distress syndrome.Target scan software analysis showed that mi r-584-5p can bind to the 3ʹ noncoding region of tlr4, which is involved in the occurrence and development of ali, thereby affecting the inflammatory pathway and inflammation development.Thus, we aimed to determine whether mi r-584-5p affects ali.Human bronchial epithelial (16-hbe) cells were transfected with mi r-584-5p mimics or inhibitors and then stimulated with lipopolysaccharide (lps).the cell viability, apoptosis, release of proinflammatory factors, m tor, and nf-κb pathway protein expression were evaluated respectively.Mimic584 increased, whereas inhibitor584 decreased, lps-stimulated inflammation.The protein expression of inflammatory factors was significantly increased in 16-hbe cells in the mimic584 + lps group and decreased in the inhibitor584 + lps group.Mimic584 activated m tor and the nf-κb-related proteins p65 and p-p65, whereas inhibitor584 inactivated the proteins in 16-hbe cells.Overexpression of mi r-584 significantly promoted apoptosis in lps-stimulated 16-hbe cells.There were no differences in the proliferation and cell cycle of lps-stimulated 16-hbe cells regardless of mimic584 or inhibitor584 transfection.Collectively, we demonstrated that inhibitor584 can alleviate ali-induced expression of inflammatory factors via m tor signaling and the nf-κb pathway.In conclusion, we found that inhibitor584 transfection could be a potential therapeutic strategy for ali.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;
RNF12 Promotes Glioblastoma Malignant Proliferation via Destructing RB1 and Regulating MAPK Pathway

Rnf12 has been linked to a variety of biological activities, including the control of the mdm2/p53 pathway, although its additional functions remain unclear.Rnf12 was discovered to be a new ubiquitin ligase (e3) for rb1, amongst the most frequently repressed proteins in cancer of human.Method.Cell counting kit-8 was used to detect the cell proliferation; coimmunoprecipitation was used to determine that rnf12 interacts with rb1.Xenograft studies were used to verify the results.Result.In vivo and in vitro rnf12 interacts with rb1 regardless of e3 ligase activity.The ubiquitination of rb1 by rnf12 had an effect on its stability.Rnf12 inhibits the rb1 protein and stimulates the mapk pathway, promoting the growth of gbms.Conclusion.Our findings show that rnf12 may operate as a tumour promoter by modulating the cancerous proliferation of glioblastoma by controlling the activity of a new rnf12/rb1/mapk pathway regulatory axis and that this regulatory axis might be a valuable diagnostic focus in glioblastoma.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Risk Factors for TERT Promoter Mutations with Papillary Thyroid Carcinoma Patients: A Meta-Analysis and Systematic Review

Whether tert promoter mutation is related to more aggressive clinicopathologic features and worse outcomes in papillary thyroid carcinoma patients (ptcs) is still variable and controversial.Our intention was to investigate the risk or prognostic factors that may additionally predict the tert promoter mutation doable of these lesions and new prevention techniques in ptcs.A total of 2,539 ptc patients with 11.50% tert mutation have been analyzed using revman 5.3 software in this study.The pub med and embase databases were systematically searched for works published until november 9, 2021.The following variables had been associated with an extended chance of tert promoter mutation in ptc patients: age &lt; 45 years ( md = 10.93 , 95 % ci = 7.25 – 14.61 ); gender = male ( pooled or = 1.63 , 95 % ci = 1.17 – 2.28 ); tumor size &gt; 1 cm ( md = 0.56 , 95 % ci = 0.34 – 0.77 ); lymph node metastasis ( pooled or = 1.29 , 95 % ci = 0.93 – 1.79 ); vascular invasion ( pooled or = 1.78 , 95 % ci = 0.83 – 3.84 ); extrathyroidal extension ( pooled or = 2.00 , 95 % ci = 1.32 – 3.02 ); distant metastasis ( pooled or = 1.46 , 95 % ci = 1.04 – 2.04 ); advanced tnm stage ( pooled or = 3.19 , 95 % ci = 2.28 – 4.45 ).In addition, multifocality ( pooled or = 0.67 , 95 % ci = 0.14 – 3.24 ) had no affiliation with tert promoter mutation in ptc patients.Our finding showed that age &lt; 45 years, male, tumor size &gt; 1 cm , lymph node metastasis, vascular invasion, and superior/advanced tnm stage were dangerous elements for tert promoter mutation of worse effect in ptcs while that multifocality was once negatively correlated.Tert promoter mutation is drastically associated with recurrence and ptc-related mortality.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Meta-Analysis;
Research on the Social Security and Elderly Care System under the Background of Big Data

In order to solve some of the problems of old-age care in the current society, combined with data mining technology, in-depth research on the current social security field of the elderly has been carried out.At present, the process of urbanization is accelerating.With the rapid increase of the urban population, the aging problem is becoming more and more serious.The pension model has attracted attention from all parties.Elderly care is facing serious aging problems and low quality and efficiency of elderly care services.One of the problems encountered in the development of elderly care is how to alleviate the problems caused by the aging of the population and improve the quality and level of elderly care services.The application of the smart pension model provides new ideas for solving this problem.

Journal: Mobile Information Systems (2023)
Publication types: Research Article;
Research on the Impact of Home Nursing Based on Intelligent Medical Internet of Things on the Quality of Life of Patients with Hemophilia

The purpose of this paper is to study the feasibility and economic benefits of intelligent medical internet of things (iot) systems for improving the quality of life of hemophilia patients, thereby reducing the risk of teratogenicity and disability for patients.This article selects 60 severe hemophilia patients who were followed up in our hospital from 2018 to 2019 as the research object.In the intelligent medical system, the gaussian mixture model discretization algorithm is used to preprocess patient data collection.The observation group uses the intelligent medical system to implement home nursing for the patients, and the control group uses ordinary home nursing.This paper evaluates the quality of life of the two groups of patients 6 months after the intervention, including self-care ability, transfer function, and home nursing cognitive ability.The research results show that the home nursing based on smart medical iot proposed in this paper is feasible and effective for improving the quality of life of patients.It can effectively improve the patient’s self-care ability and joint functions and has important reference value for the development of intelligent medical iot equipment.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Clinical Study;
Research on Performance Optimization Method of UAV Communication Link in Emergency Communication Environment

Ing at the problem of long average delay of traditional uav emergency communication, a performance optimization method of uav communication link based on emergency communication environment is proposed.The target tasks in the emergency communication channel are divided into different target task groups.According to the distance between the target tasks in the target task group, the symmetric matrix is constructed, all elements in the symmetric matrix are classified, and the classification results are calculated by ant colony algorithm to construct the emergency communication task scheduling model of uav.Combined with the emergency communication task scheduling model and the demand, priority, time window, and communication ability of uav emergency scheduling task, the time delay control of uav emergency communication is realized with the goal of maximizing the efficiency of uav task execution, maximizing the completion rate of uav task execution and minimizing the risk of uav delay.The experimental results show that the average delay of the three methods also increases.When the system load is 50%, the average delay of common methods is 23 ms, the average delay of traditional methods is 76 ms, the average delay of the method proposed in this paper is 26 ms, and the common average delay is the shortest.When the system load is 99%, the common methods cannot realize emergency communication scheduling due to system load overshoot, and the corresponding average delay cannot be considered, indicating that the common methods are unstable.The average delay of the method proposed in this paper is stable under different system loads and always remains below 40 ms.It is proved that compared with the traditional methods, the method proposed in this paper takes less time for uav emergency communication and has less average delay under different system loads, so it has better application value.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Research on Job Burnout Evaluation and Turnover Tendency Prediction of Knowledge Workers Based on BP Neural Network

The traditional dimission prediction method for knowledge workers does not take into account the impact of job burnout on employees’ dimission tendency, resulting in low accuracy of dimission prediction.In view of the above problems, this paper introduces the employee burnout evaluation and researches the knowledge employee burnout evaluation and turnover tendency prediction method based on bp neural network.After analyzing the influencing factors of job burnout of knowledge workers, the evaluation index system of job burnout is established.The weight of the job burnout evaluation index was determined by fuzzy hierarchy, and bp neural network model was established.Boosting method added the fusion layer of the correlation analysis of job burnout and turnover intention to the neural network model to predict the turnover intention of employees.In the method test, the accuracy rate of employee turnover tendency prediction is higher than 90%, the reliability of employee burnout evaluation is higher, and it is more helpful for human resource management.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Research on Construction and Risk Management of Operating Room Based on IoTs and Digitization

This paper introduces the background and experience of the development of a digital operating room and designs the main functions of the digital operating room based on the internet of things, the impact on medical data in hospitals, and how to build the digital operating room to cope with the huge amount of data in the “data era.” the infrastructure of the digital operating room is described, as well as how to collect and transmit medical data, how to store large amounts of medical data, and how to analyze medical data and explore its hidden data value are also described.One hundred and four surgical patients from june 2020 to june 2021 were randomly selected for the study, and they were randomly and equally divided into 52 cases each in the control group and the observation group, with the control group implementing the management of conventional care methods and the observation group implementing information technology for care management, comparing the management effects of patients in both groups.The satisfaction of patients in the observation group was significantly higher than that of the control group ( p &lt; 0.05 ).The use of information technology to ensure the quality of care in the operating room not only can help patients recover early but also can help patients relieve the psychological pressure after surgery, thus improving the doctor-patient relationship, and has a significant application effect.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Clinical Study;
Research on Classification of Primary Liver Cancer Syndrome Based on Data Mining Technology

This study is based on the analysis of the status quo of the research on liver cancer syndromes, starting with the clinical objective and true four-diagnosis information of tcm inpatients with primary liver cancer, using computer data mining technology to analyze and summarize the syndrome rules from the bottom to the top.Let the data itself show the essence of liver cancer syndrome.First, with the help of hierarchical cluster analysis, we can understand the general characteristics through the rough preliminary classification of the four-diagnosis information of liver cancer patients.Then, with the help of the emerging and mature hidden structure model analysis in recent years, through data modeling, the classification of common syndromes of liver cancer and the corresponding relationship with the four-diagnosis information are comprehensively analyzed.Finally, considering the inherent shortcomings of implicit structure and hierarchical clustering based on the assumption that there is a unique one-to-one correspondence between the four diagnostic information factors and the class (or hidden class) when classifying, we plan to use factor analysis and joint cluster analysis, as supplementary means to further explore the classification of liver cancer syndromes and the corresponding relationship with the four-diagnosis information.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Research and Analysis of Brain Glioma Imaging Based on Deep Learning

The incidence of glioma is increasing year by year, seriously endangering people’s health.Magnetic resonance imaging (mri) can effectively provide intracranial images of brain tumors and provide strong support for the diagnosis and treatment of the disease.Accurate segmentation of brain glioma has positive significance in medicine.However, due to the strong variability of the size, shape, and location of glioma and the large differences between different cases, the recognition and segmentation of glioma images are very difficult.Traditional methods are time-consuming, labor-intensive, and inefficient, and single-modal mri images cannot provide comprehensive information about gliomas.Therefore, it is necessary to synthesize multimodal mri images to identify and segment glioma mri images.This work is based on multimodal mri images and based on deep learning technology to achieve automatic and efficient segmentation of gliomas.The main tasks are as follows.A deep learning model based on dense blocks of holes, 3d u-net, is proposed.It can automatically segment multimodal mri glioma images.U-net network is often used in image segmentation and has good performance.However, due to the strong specificity of glioma, the u-net model cannot effectively obtain more details.Therefore, the 3d u-net model proposed in this paper can integrate hollow convolution and densely connected blocks.In addition, this paper also combines classification loss and cross-entropy loss as the loss function of the network to improve the problem of category imbalance in glioma image segmentation tasks.The algorithm proposed in this paper has been used to perform a lot of experiments on the bra ts2018 dataset, and the results prove that this model has good segmentation performance.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Related Factors of Cerebral Hemorrhage after Cerebral Infarction and the Effect of Atorvastatin Combined with Intensive Nursing Care

Cerebral infarction is a common neurological disease with high incidence, which is the main factor causing death and disability in adults in china.Cerebral hemorrhage transformation is a common clinical complication.High nihss score at admission, atrial fibrillation, and small artery occlusion cerebral infarction can increase the risk of cerebral infarction complicated with hemorrhage transformation.Aim.To explore the related factors of cerebral hemorrhage transformation after cerebral infarction and the value of atorvastatin calcium tablets combined with early intensive care measures.Methods.In this study, a case-control study was conducted.Sixty patients with hemorrhagic transformation after cerebral infarction admitted to the department of neurology of our hospital from january 2017 to june 2021 were selected as the observation group, and 90 patients with cerebral infarction without hemorrhagic transformation during the same period were selected as the control group.The risk factors of hemorrhagic transformation after cerebral infarction were analyzed.Results.The results of logistic regression model showed that the increased national institutes of health stroke scale (nihss) score at admission, hypertension, atrial fibrillation, toast classification of small artery occlusion, and large infarction lesions were the risk factors for hemorrhagic transformation in patients with cerebral infarction ( p &lt; 0.05 ).After 2 weeks and 4 weeks of treatment, the nihss scores of the intervention group were lower than those of the conventional group ( p &lt; 0.05 ).Nihss scores of the two groups after treatment were significantly lower than those before treatment ( p &lt; 0.05 ).After three months of treatment, the patients in the intervention group with gos score of 5 points accounted for 16.67%, and the patients with gos score of 4 points accounted for 56.67%.The patients in the conventional group with gos score of 5 points accounted for 6.67%, and the patients with gos score of 4 points accounted for 33.33%.The prognosis of the intervention group was better than that of the conventional group on the whole ( p &lt; 0.05 ).Conclusion.Patients with hypertension, large infarction lesions, high nihss score at admission, atrial fibrillation, and small artery occlusion cerebral infarction can increase the risk of bleeding transformation in patients with cerebral infarction.For patients with bleeding transformation, atorvastatin calcium tablets combined with early intensive nursing intervention has a certain value for improving the prognosis of patients.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Clinical Study;