IET Systems Biology最新文献

{"title":"Variable structure robust controller design for blood glucose regulation for type 1 diabetic patients: A backstepping approach","authors":"Mohamadreza Homayounzade","doi":"10.1049/syb2.12032","DOIUrl":"10.1049/syb2.12032","url":null,"abstract":"<p>Diabetes mellitus type 1 occurs when <math>\u0000 <mrow>\u0000 <mi>β</mi>\u0000 <mo>-</mo>\u0000 </mrow></math>cells in the pancreas are destroyed by the immune system. As a result, the pancreas cannot produce adequate insulin, and the glucose enters the cells to produce energy. To elevate the glycaemic concentration, sufficient amount of insulin should be taken orally or injected into the human body. Artificial pancreas is a device that automatically regulates the level of body insulin by injecting the requisite amount of insulin into the human body. A finite-time robust feedback controller based on the Extended Bergman Minimal Model is designed here. The controller is designed utilizing the backstepping approach and is robust against the unknown external disturbance and parametric uncertainties. The stability of the system is proved using the Lyapunov theorem. The controller is exponentially stable and hence provides the finite-time convergence of the blood glucose concentration to its desired magnitude. The effectiveness of the proposed control method is shown through simulation in MATLAB/Simulink environment via comparisons with previous studies.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 6","pages":"173-183"},"PeriodicalIF":2.3,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/38/c9/SYB2-15-173.PMC8675804.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39163460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-stage neural network prediction of chronic kidney disease","authors":"Hongquan Peng,&nbsp;Haibin Zhu,&nbsp;Chi Wa Ao Ieong,&nbsp;Tao Tao,&nbsp;Tsung Yang Tsai,&nbsp;Zhi Liu","doi":"10.1049/syb2.12031","DOIUrl":"10.1049/syb2.12031","url":null,"abstract":"<p>Accurate detection of chronic kidney disease (CKD) plays a pivotal role in early diagnosis and treatment. Measured glomerular filtration rate (mGFR) is considered the benchmark indicator in measuring the kidney function. However, due to the high resource cost of measuring mGFR, it is usually approximated by the estimated glomerular filtration rate, underscoring an urgent need for more precise and stable approaches. With the introduction of novel machine learning methodologies, prediction performance is shown to be significantly improved across all available data, but the performance is still limited because of the lack of models in dealing with ultra-high dimensional datasets. This study aims to provide a two-stage neural network approach for prediction of GFR and to suggest some other useful biomarkers obtained from the blood metabolites in measuring GFR. It is a composite of feature shrinkage and neural network when the number of features is much larger than the number of training samples. The results show that the proposed method outperforms the existing ones, such as convolutionneural network and direct deep neural network.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 5","pages":"163-171"},"PeriodicalIF":2.3,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/71/55/SYB2-15-163.PMC8675857.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39038177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constraint-based models for dominating protein interaction networks","authors":"Adel A. Alofairi,&nbsp;Emad Mabrouk,&nbsp;Ibrahim E. Elsemman","doi":"10.1049/syb2.12021","DOIUrl":"10.1049/syb2.12021","url":null,"abstract":"&lt;p&gt;The minimum dominating set (MDSet) comprises the smallest number of graph nodes, where other graph nodes are connected with at least one MDSet node. The MDSet has been successfully applied to extract proteins that control protein–protein interaction (PPI) networks and to reveal the correlation between structural analysis and biological functions. Although the PPI network contains many MDSets, the identification of multiple MDSets is an NP-complete problem, and it is difficult to determine the best MDSets, enriched with biological functions. Therefore, the MDSet model needs to be further expanded and validated to find constrained solutions that differ from those generated by the traditional models. Moreover, by identifying the critical set of the network, the set of nodes common to all MDSets can be time-consuming. Herein, the authors adopted the minimisation of metabolic adjustment (MOMA) algorithm to develop a new framework, called maximisation of interaction adjustment (MOIA). In MOIA, they provide three models; the first one generates two MDSets with a minimum number of shared proteins, the second model generates constrained multiple MDSets (&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;-MDSets), and the third model generates user-defined MDSets, containing the maximum number of essential genes and/or other important genes of the PPI network. In practice, these models significantly reduce the cost of finding the critical set and classifying the graph nodes. Herein, the authors termed the critical set as the &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;-critical set, where &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; is the number of MDSets generated by the proposed model. Then, they defined a new set of proteins called the &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;-critical set, where each node belongs to &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; MDSets. This set has been shown to be as important as the &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;-critical set and contains many essential genes, transcription factors, and protein kinases as the &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;-critical set. The &lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;-critical set can be used to extend the search for drug target proteins. Based on the performance of the MOIA mod","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 5","pages":"148-162"},"PeriodicalIF":2.3,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675806/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38959855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long non-coding RNAs and their targets as potential biomarkers in breast cancer","authors":"Maryam Khalid,&nbsp;Rehan Zafar Paracha,&nbsp;Maryum Nisar,&nbsp;Sumaira Malik,&nbsp;Salma Tariq,&nbsp;Iqra Arshad,&nbsp;Amnah Siddiqa,&nbsp;Zamir Hussain,&nbsp;Jamil Ahmad,&nbsp;Amjad Ali","doi":"10.1049/syb2.12020","DOIUrl":"10.1049/syb2.12020","url":null,"abstract":"Abstract Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease‐specific biomarkers. Recently, long non‐coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post‐transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co‐expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co‐expressed lncRNAs and their cis‐ and trans‐regulating mRNA targets which include RP11‐108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 5","pages":"137-147"},"PeriodicalIF":2.3,"publicationDate":"2021-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38982766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bifurcation analyses and potential landscapes of a cortex-basal ganglia-thalamus model.","authors":"Chenri Yan,&nbsp;Quansheng Liu,&nbsp;Yuanhong Bi","doi":"10.1049/syb2.12018","DOIUrl":"https://doi.org/10.1049/syb2.12018","url":null,"abstract":"<p><p>The dynamics of cortical neuronal activity plays important roles in controlling body movement and is regulated by connection weights between neurons in a cortex-basal ganglia-thalamus (BGCT) loop. Beta-band oscillation of cortical activity is closely associated with the movement disorder of Parkinson's disease, which is caused by an imbalance in the connection weights of direct and indirect pathways in the BGCT loop. In this study, the authors investigate how the dynamics of cortical activity are modulated by connection weights of direct and indirect pathways in the BGCT loop under low dopamine levels through bifurcation analyses and potential landscapes. The results reveal that cortical activity displays rich dynamics under different connection weights, including one, two, or three stable steady states, one or two stable limit cycles, and the coexistence of one stable limit cycle with one stable steady state or two stable ones. For a low dopamine level, cortical activity exhibits oscillation for larger connection weights of direct and indirect pathways. The stability of these stable dynamics is explored by the potential landscapes.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 3","pages":"101-109"},"PeriodicalIF":2.3,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675854/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38880590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State Feedback and Synergetic controllers for tuberculosis in infected population.","authors":"Muhammad Bilal,&nbsp;Iftikhar Ahmad,&nbsp;Sheraz Ahmad Babar,&nbsp;Khurram Shahzad","doi":"10.1049/syb2.12013","DOIUrl":"https://doi.org/10.1049/syb2.12013","url":null,"abstract":"<p><p>Tuberculosis (TB) is a contagious disease which can easily be disseminated in a society. A five state Susceptible, exposed, infected, recovered and resistant (SEIRs) epidemiological mathematical model of TB has been considered along with two non-linear controllers: State Feedback (SFB) and Synergetic controllers have been designed for the control and prevention of the TB in a population. Using the proposed controllers, the infected individuals have been reduced/controlled via treatment, and susceptible individuals have been prevented from the disease via vaccination. A mathematical analysis has been carried out to prove the asymptotic stability of proposed controllers by invoking the Lyapunov control theory. Simulation results using MATLAB/Simulink manifest that the non-linear controllers show fast convergence of the system states to their respective desired levels. Comparison shows that proposed SFB controller performs better than Synergetic controller in terms of convergence time, steady state error and oscillations.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 3","pages":"83-92"},"PeriodicalIF":2.3,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25547612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pathway-based protein–protein association network to explore mechanism of α-glucosidase inhibitors from Scutellaria baicalensis Georgi against type 2 diabetes","authors":"Le Wang,&nbsp;Wenbo Diwu,&nbsp;Nana Tan,&nbsp;Huan Wang,&nbsp;Jingbo Hu,&nbsp;Bailu Xu,&nbsp;Xiaoling Wang","doi":"10.1049/syb2.12019","DOIUrl":"10.1049/syb2.12019","url":null,"abstract":"<p>Natural products have been widely used in the treatment of type 2 diabetes (T2D). However, their mechanisms are often obscured due to multi-components and multi-targets. The authors constructed a pathway-based protein–protein association (PPA) network for target proteins of 13 α-glucosidase inhibitors (AGIs) identified from <i>Scutellaria baicalensis</i> Georgi (<i>SBG</i>), designed to explore the underlying mechanisms. This network contained 118 nodes and 1167 connections. An uneven degree distribution and small-world property were observed, characterised by high clustering coefficient and short average path length. The PPA network had an inherent hierarchy as <i>C(k)∼k</i>^−0.71. It also exhibited potential weak disassortative mixing pattern, coupled with a decreased function <i>Knn</i> (<i>k</i>) and negative value of assortativity coefficient. These properties indicated that a few nodes were crucial to the network. PGH2, GNAS, MAPK1, MAPK3, PRKCA, and MAOA were then identified as key targets with the highest degree values and centrality indices. Additionally, a core subnetwork showed that chrysin, 5,8,2′-trihydroxy-7-methoxyflavone, and wogonin were the main active constituents of these AGIs, and that the serotonergic synapse pathway was the critical pathway for <i>SBG</i> against T2D. The application of a pathway-based protein–protein association network provides a novel strategy to explore the mechanisms of natural products on complex diseases.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 4","pages":"126-135"},"PeriodicalIF":2.3,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38909022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of noise and time delay on E2F's expression level in a bistable Rb-E2F gene’s regulatory network","authors":"John Billy Kirunda,&nbsp;Lijian Yang,&nbsp;Lulu Lu,&nbsp;Ya Jia","doi":"10.1049/syb2.12017","DOIUrl":"10.1049/syb2.12017","url":null,"abstract":"<p>The bistable Rb-E2F gene regulatory network plays a central role in regulating cellular proliferation-quiescence transition. Based on Gillespie's chemical Langevin method, the stochastic bistable Rb-E2F gene’s regulatory network with time delays is proposed. It is found that under the moderate intensity of internal noise, delay in the Cyclin E synthesis rate can greatly increase the average concentration value of E2F. When the delay is considered in both E2F-related positive feedback loops, within a specific range of delay (3-13)<math>\u0000 <mrow>\u0000 <mtext>hr</mtext>\u0000 </mrow></math>, the average expression of E2F is significantly increased. Also, this range is in the scope with that experimentally given by Dong et al. [65]. By analysing the quasi-potential curves at different delay times, simulation results show that delay regulates the dynamic behaviour of the system in the following way: small delay stabilises the bistable system; the medium delay is conducive to a high steady-state, making the system fluctuate near the high steady-state; large delay induces approximately periodic transitions between high and low steady-state. Therefore, by regulating noise and time delay, the cell itself can control the expression level of E2F to respond to different situations. These findings may provide an explanation of some experimental result intricacies related to the cell cycle.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 4","pages":"111-125"},"PeriodicalIF":2.3,"publicationDate":"2021-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/14/dc/SYB2-15-111.PMC8675803.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38894037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Weighted gene co expression network analysis (WGCNA) with key pathways and hub-genes related to micro RNAs in ischemic stroke","authors":"Xiang Qu,&nbsp;Shuang Wu,&nbsp;Jinggui Gao,&nbsp;Zhenxiu Qin,&nbsp;Zhenhua Zhou,&nbsp;Jingli Liu","doi":"10.1049/syb2.12016","DOIUrl":"10.1049/syb2.12016","url":null,"abstract":"<p>Ischemic stroke (IS) is one of the major causes of death and disability worldwide. However, the specific mechanism of gene interplay and the biological function in IS are not clear. Therefore, more research into IS is necessary. Dataset GSE110993 including 20 ischemic stroke (IS) and 20 control specimens are used to establish both groups and the raw RNA-seq data were analysed. Weighted gene co-expression network analysis (WGCNA) was used to screen the key micro-RNA modules. The centrality of key genes were determined by module membership (mm) and gene significance (GS). The key pathways were identified by enrichment analysis with Kyoto Protocol Gene and Genome Encyclopedia (KEGG), and the key genes were validated by protein-protein interactions network. Result: Upon investigation, 1185 up- and down-regulated genes were gathered and distributed into three modules in response to their degree of correlation to clinical traits of IS, among which the turquoise module show a trait-correlation of 0.77. The top 140 genes were further identified by GS and MM. KEGG analysis showed two pathways may evolve in the progress of IS. Discussion: CXCL12 and EIF2a may be important biomarkers for the accurate diagnosis and treatment in IS.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 3","pages":"93-100"},"PeriodicalIF":2.3,"publicationDate":"2021-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38827692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fuzzy logic and Lyapunov-based non-linear controllers for HCV infection.","authors":"Ali Hamza,&nbsp;Iftikhar Ahmad,&nbsp;Muhammad Uneeb","doi":"10.1049/syb2.12014","DOIUrl":"https://doi.org/10.1049/syb2.12014","url":null,"abstract":"<p><p>Hepatitis C is the liver disease caused by the Hepatitis C virus (HCV) which can lead to serious health problems such as liver cancer. In this research work, the non-linear model of HCV having three state variables (uninfected hepatocytes, infected hepatocytes and virions) and two control inputs has been taken into account, and four non-linear controllers namely non-linear PID controller, Lyapunov Redesign controller, Synergetic controller and Fuzzy Logic-Based controller have been proposed to control HCV infection inside the human body. The controllers have been designed for the anti-viral therapy in order to control the amount of uninfected hepatocytes to the desired safe limit and to track the amount of infected hepatocytes and virions to their reference value which is zero. One control input is the Pegylated interferon (peg-IFN-α) which acts in reducing the infected hepatocytes and the other input is ribavirin which blocks the production of virions. By doing so, the uninfected hepatocytes increase and achieve the required safe limit. Lyapunov stability analysis has been used to prove the stability of the whole system. The comparative analysis of the proposed nonlinear controllers using MATLAB/Simulink have been done with each other and with linear PID. These results depict that the infected hepatocytes and virions are reduced to the desired level, enhancing the rate of sustained virologic response (SVR) and reducing the treatment period as compared with previous strategies introduced in the literature.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"15 2","pages":"53-71"},"PeriodicalIF":2.3,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25528516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}