The Fifth International Conference on Biological Information and Biomedical Engineering最新文献

{"title":"Study on the Two-dimensional Sample Entropy of Sleep Apnea Based on the Hilbert-Huang Time-frequency Diagram","authors":"Lan Tang, Guanzheng Liu","doi":"10.1145/3469678.3469690","DOIUrl":"https://doi.org/10.1145/3469678.3469690","url":null,"abstract":"Sleep apnea (SA) as a common breathing disorder, has been determined to affect human physiological activities and is related to many diseases. Heart rate variability (HRV) analysis as an analysis method of the cardiac autonomic nervous system, is widely used in the study of sleep apnea. The Hilbert Huang Transform (HHT) method is composed of empirical mode decomposition (EMD) and Hilbert spectrum analysis, and is mainly used in nonlinear and non-stationary signal analysis. The two-dimensional sample entropy (SampEn2D) method can effectively analyze the irregularity of the image and evaluate the complexity of the image. We applied SampEn2D to the Hilbert-Huang time-frequency diagram to analyze the complexity of the time-frequency diagram of normal people and patients with sleep apnea. In the study, 60 electrocardiogram recordings were used for analysis, and nonlinearity SampEn2D was calculated. The SampEn2D of sleep apnea patients with different disease severity has significant differences (p<0.05), and the screening accuracy, sensitivity, and specificity reach 90%, 87.5%, and 95%, respectively. The results show that the two-dimensional sample entropy based on the Hilbert-Huang time-frequency diagram can be used to analyze the severity of sleep apnea and SA screening.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87939702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association between Baseline Serum SHBG and the Number of Retrieved Oocytes in Chinese Infertile Patients Undergoing IVF Treatment of PPOS Protocol: A Restrospective Cohort Study","authors":"Kui Fu, C. Zhang, Kai Deng","doi":"10.1145/3469678.3469708","DOIUrl":"https://doi.org/10.1145/3469678.3469708","url":null,"abstract":"This study aimed to investigate the association between the baseline circulating sex hormone binding globulin (SHBG) concentration and the number of oocytes retrieved. This retrospective cohort study included 1477 patients who underwent PPOS treatment from January 2018 to December 2019 at the reproductive centre of Shiyan Renmin Hospital, Hubei, China. We investigated the potential relationships of SHBG and the number of oocytes retrieved using piecewise linear regression and multiple logistic regression, respectively. Our results show that baseline SHBG was negatively associated with the number of oocytes retrieved (β= -0.07, 95% CI (-0.13, -0.02)) by fully adjusted linear regression. After adjusting for potential confounders, a nonlinear relationship was found between baseline SHBG and the number of oocytes retrieved (P=0.01). The number of oocytes decreased with SHBG levels above 55.4 nmol/L. A high level of SHBG (SHBG ≥ 55.4) was associated with a lower yield of oocytes (adjusted β=-0.11, (per 10 nmol/L for SHBG), 95% CI (-0.17, -0.05), p=0.0003). The relationship between baseline SHBG and the number of oocytes retrieved is nonlinear. A higher baseline SHBG level is associated with a lower yield of oocytes in PPOS cycles.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82321545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GABAergic Neuron-related DNA Methylation Modification and Chronic Pain","authors":"Qiu-ling Xu, Fengyuan Bai, Tao Liu","doi":"10.1145/3469678.3469698","DOIUrl":"https://doi.org/10.1145/3469678.3469698","url":null,"abstract":"Chronic pain is one of the major health problems in the world. Studies have shown that chronic pain is closely related to epigenetics. Chronic pain can increased the level of DNA methylation of GABAergic neurons. This article focused on the three aspects: GABAergic neurons and chronic pain, DNA methylation and chronic pain, GABAergic neuron-related DNA methylation modification and chronic pain. Discussion of the mechanism that chronic pain can increase DNA methylation of the GABAergic neuron, may be helpful for improving the clinical efficacy of chronic pain, and guiding clinical medication to improve the quality of life of patients with pain.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86826506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facile Fabrication of Cell Delivery Microrobot Using Self-rolled-up Method","authors":"Hao Li, Chengdao Piao","doi":"10.1145/3469678.3469686","DOIUrl":"https://doi.org/10.1145/3469678.3469686","url":null,"abstract":"In this paper, we propose the simple and versatile approach for fabrication of the biocompatible polymer-based microrobot for active and precise cell delivery. The typical shape of the pattern was UV cured and the patterned sheet was then immersed in the ethanol solution to weaken the adhesion with the substrate. After few hours the patterned sheet rolled inward, spontaneously, as delaminating from the substrate. The rolled-up structure was then coated with amine functionalized magnetic nanoparticles so that it can be controlled under the external magnetic field. To evaluate the locomotion ability and biocompatibility of the microrobot, various tests were conducted using electromagnetic actuation (EMA) system and cell culture experiment.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75636751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Meta-analysis: Evaluating the Effect of METTL3/METTL14 on m6A Level Based on Knockdown Samples","authors":"Yu-xin Zhang, Yuxuan Wu, Di Zhen, Kunqi Chen, Jia Meng","doi":"10.1145/3469678.3469715","DOIUrl":"https://doi.org/10.1145/3469678.3469715","url":null,"abstract":"N6-methyladenosine (m6A) is a dynamic modification regulated by the m6A enzymes prevalent on mRNA. The Mettl3 and mettl14 are two subunits of methyltransferase. Different studies have shown that knockout of the METL3 and MTEL14 genes has the potential to change methylation levels. We have therefore undertaken a meta-analysis study to assess the quality and quantity of available evidence. The focus of the research would on the effects of mRNA methylation level after the depletion of METTL3 or METTL14. R package “Metafor” was applied to output the model of random effect, the regarding risk ratios (RRs), and the 95% confidence intervals (CIs). Owing to the high heterogeneity of the overall data (I2>99%), some samples were selected and excluded to an acceptable level. Three published trials for METTL3 (Q = 12.85, I2 = 37.8%) and two for METTL4 (Q = 45.48, I2 = 82.9%) were qualified to review and analyze. Consequently, we successfully proved the correlation between the knockdown of METTL3/METTL14 and modification of methylation level.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75100190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Design of Potential Binder Protein for SARS-CoV-2 Spike RBD through A Novel Deep Neural Network Based-Protein Outpainting Algorithm","authors":"Bingya Duan, Yingfei Sun","doi":"10.1145/3469678.3469685","DOIUrl":"https://doi.org/10.1145/3469678.3469685","url":null,"abstract":"COVID-19 caused by SARS-CoV-2 is seriously endangering the health of all human beings. There is an urgent need for drugs that can inhibit the replication and propagation of the virus. Traditional macromolecular drugs have long discovery and development cycles and high experimental costs, which can't give rapid response to new viruses. Through computational protein design method, scientists have designed binder proteins with high affinity for the RBD of SARS-CoV-2 spike protein which can effectively inhibit virus replication. However, traditional computational protein design methods rely heavily on human experience and domain knowledge of protein design, and the protein design workflow is too complicated to be widely accepted and used in academia and industry. Based on previous work in the field of deep neural network protein structure prediction and protein design, we developed a novel protein outpainting method that can generate the remaining part of the protein based on a given hot spot motif and complete the entire protein. This method can generate stable protein scaffold which can support the functional hot spot motif, resulting in a protein with excellent thermal stability and developability. We tested this method in a drug discovery project with the aim of designing new SARS-CoV-2 inhibitors. Several proteins are obtained which are predicted to be stable and may have high affinity for the RBD of the SARS-CoV-2 spike protein. Although they have not been verified by wet-lab experiments, we believe that these proteins have great potential to be developed into effective drugs for the treatment of COVID-19. The protein outpainting algorithm proposed in this paper has great advantages over traditional protein design methods. It can be applied to many fields that require the design of functional proteins, such as protein drug design, enzyme de novo design, vaccine design, etc. The method will play an important role in reducing the cost of experiments, shortening the research and development period, and improving the successful rate of biological research and development.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"221 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76649862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of m6A Reader Substrate Sites Using Deep Convolutional and Recurrent Neural Network","authors":"Yuxuan Wu, Yu-xin Zhang, Ruoqi Wang, Jia Meng, Kunqi Chen, Yiyou Song, Daiyun Huang","doi":"10.1145/3469678.3469706","DOIUrl":"https://doi.org/10.1145/3469678.3469706","url":null,"abstract":"N6-methyladenosine (m6A), one of the most common post-transcriptional mRNA modifications, has been proved to correlate with multiple biological functions through the process of binding to specific m6A reader proteins. Various m6A readers exist among the genome of human beings, however, owing to the scarce wet experiments related to this topic, the binding specificity of proteins was not elucidated. Therefore, a deep learning approach combined with CNN and RNN frameworks was generated to predict the epitranscriptome-wide targets of six m6A reader proteins (YTHDF1-3, YTHDC1-2, EIF3A). Additionally, layer-wise relevance calculation was conducted to obtain each input feature contribution and tried to explain the model training process. Finally, we achieved superior performance in the classification, with an average AUROC of 0.942 in EIF3A full transcript, higher than the typical conventional machine learning algorithms (SVM) under the same condition. Moreover, we quantified the most optimal sequence length (1001bp) during the m6A reader substrate prediction. This research paves the way for further RNA methylation target prediction and functional characterization of m6A readers.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91172034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minimally Invasive Synchronous Cardiac Assisted Pump and in Vitro study","authors":"Honglong Yu, Dong Yang, Zeyang Song, Yao Xie, Q. Xie","doi":"10.1145/3469678.3469702","DOIUrl":"https://doi.org/10.1145/3469678.3469702","url":null,"abstract":"Heart failure is the end-stage manifestation of various heart diseases, which has high morbidity and mortality. Mechanical circulatory support (MCS) is a required clinical treatment method. This study developed a new MCS, minimally invasive synchronized cardiac assist pump (ISCAP). The ISCAP works in synchronization with the heart to reduce afterload and increase cardiac output. An in vitro experimental platform for simulating heart failure designed to study the effect of ISCAP. The experimental results show that compared to the Intra-aortic balloon pump (IABP), ISCAP is more effective in increasing cardiac output and reducing systolic and diastolic blood pressure, thereby having better hemodynamic parameters.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87079997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences In Acupuncture Treatment Of Dysmenorrhea Between China And Europe","authors":"F. Bai, Qiu-ling Xu, Tao Liu","doi":"10.1145/3469678.3469717","DOIUrl":"https://doi.org/10.1145/3469678.3469717","url":null,"abstract":"Dysmenorrhea is one of the most common diseases in women. Dysmenorrhea is divided into primary dysmenorrhea (PD) and secondary dysmenorrhea (SD) . The prevalence of dysmenorrhea is high. However, there is no unified treatment for dysmenorrhea at home and abroad. In this paper, the relevant literatures of acupuncture and moxibustion for dysmenorrhea in China and Europe in recent years are systematically sorted, analyzed, concluded and summarized. The purpose of this paper is to explore the differences in classification, acupoint selection, treatment methods and needle retention time between China and Europe in the treatment of dysmenorrhea by acupuncture.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85679981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Covid-19 Classification with Deep Neural Network and Belief Functions","authors":"Ling Huang, S. Ruan, T. Denoeux","doi":"10.1145/3469678.3469719","DOIUrl":"https://doi.org/10.1145/3469678.3469719","url":null,"abstract":"Computed tomography (CT) image provides useful information for radiologists to diagnose Covid-19. However, visual analysis of CT scans is time-consuming. Thus, it is necessary to develop algorithms for automatic Covid-19 detection from CT images. In this paper, we propose a belief function-based convolutional neural network with semi-supervised training to detect Covid-19 cases. Our method first extracts deep features, maps them into belief degree maps and makes the final classification decision. Our results are more reliable and explainable than those of traditional deep learning-based classification models. Experimental results show that our approach is able to achieve a good performance with an accuracy of 0.81, an F1 of 0.812 and an AUC of 0.875.","PeriodicalId":22513,"journal":{"name":"The Fifth International Conference on Biological Information and Biomedical Engineering","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78867208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}