Mathematical Biosciences最新文献

{"title":"A mechanistic modeling and estimation framework for environmental pathogen surveillance","authors":"Matthew Wascher ,&nbsp;Colin J. Klaus ,&nbsp;Chance Alvarado ,&nbsp;Jenny Panescu ,&nbsp;Mikkel Quam ,&nbsp;Karen C. Dannemiller ,&nbsp;Joseph H. Tien","doi":"10.1016/j.mbs.2024.109257","DOIUrl":"10.1016/j.mbs.2024.109257","url":null,"abstract":"<div><div>Environmental pathogen surveillance is a promising disease surveillance modality that has been widely adopted for SARS-CoV-2 monitoring. The highly variable nature of environmental pathogen data is a challenge for integrating these data into public health response. One source of this variability is heterogeneous infection both within an individual over the course of infection as well as between individuals in their pathogen shedding over time. We present a mechanistic modeling and estimation framework for connecting environmental pathogen data to the number of infected individuals. Infected individuals are modeled as shedding pathogen into the environment via a Poisson process whose rate parameter <span><math><msub><mrow><mi>λ</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span> varies over the course of their infection. These shedding curves <span><math><msub><mrow><mi>λ</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span> are themselves random, allowing for variation between individuals. We show that this results in a Poisson process for environmental pathogen levels with rate parameter a function of the number of infected individuals, total shedding over the course of infection, and pathogen removal from the environment. Theoretical results include determination of identifiable parameters for the model from environmental pathogen data and simple, explicit formulas for the likelihood for particular choices of individual shedding curves. We give a two step Bayesian inference framework, where the first step corresponds to calibration from data where the number of infected individuals is known, followed by an estimation step from environmental surveillance data when the number of infected individuals is unknown. We apply this modeling and estimation framework to synthetic data, as well as to an empirical case study of SARS-CoV-2 in environmental dust collected from isolation rooms housing university students. Both the synthetic data and empirical case study indicate high inter-individual variation in shedding, leading to wide credible intervals for the number of infected individuals. We examine how uncertainty in estimates of the number of infected individuals from environmental pathogen levels scales with the true number of infected individuals and model misspecification. While credible intervals for the number of infected individuals are wide, our results suggest that distinguishing between no infection and small-to-moderate levels of infection (<span><math><mrow><mo>≈</mo><mn>10</mn></mrow></math></span> infected individuals) may be possible, and that it is broadly possible to differentiate between moderate (<span><math><mrow><mo>≈</mo><mn>40</mn></mrow></math></span>) and high (<span><math><mrow><mo>≈</mo><mn>200</mn></mrow></math></span>) numbers of infected individuals.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"377 ","pages":"Article 109257"},"PeriodicalIF":1.9,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142038129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stoichiometric theory in aquatic carbon sequestration under elevated carbon dioxide","authors":"Zhenyao Sun ,&nbsp;Hao Wang ,&nbsp;Meng Fan","doi":"10.1016/j.mbs.2024.109285","DOIUrl":"10.1016/j.mbs.2024.109285","url":null,"abstract":"<div><p>Global climate change projections indicate that the atmospheric concentration of carbon dioxide will increase twofold by the end of this century. However, how the elevated carbon dioxide affects aquatic carbon sequestration and species composition within aquatic microbial communities remains inconclusive. To address this knowledge gap, we formulate a bacteria-algae interaction model to characterize the effects of elevated carbon dioxide on aquatic ecosystems and rigorously derive the thresholds determining the persistence and extinction of algae or bacteria. We explore the impacts of abiotic factors, such as light intensity, nutrient concentration, inorganic carbon concentration and water depth, on algae and bacteria dynamics. The main findings indicate that the elevated atmospheric carbon dioxide will increase algae biomass and thus facilitate carbon sequestration. On the other hand, the elevated atmospheric carbon dioxide will reduce bacterial biomass, and excessive carbon dioxide concentrations can even destroy bacterial communities. Numerical simulations indicate that eutrophication and intensified light intensity can reduce aquatic carbon sequestration, while elevated atmospheric carbon dioxide levels can mitigate eutrophication. Furthermore, higher algae respiration and death rates are detrimental to carbon sequestration, whereas the increased bacterial respiration rates promote carbon sequestration.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109285"},"PeriodicalIF":1.9,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WENDY: Covariance dynamics based gene regulatory network inference","authors":"Yue Wang ,&nbsp;Peng Zheng ,&nbsp;Yu-Chen Cheng ,&nbsp;Zikun Wang ,&nbsp;Aleksandr Aravkin","doi":"10.1016/j.mbs.2024.109284","DOIUrl":"10.1016/j.mbs.2024.109284","url":null,"abstract":"<div><div>Determining gene regulatory network (GRN) structure is a central problem in biology, with a variety of inference methods available for different types of data. For a widely prevalent and challenging use case, namely single-cell gene expression data measured after intervention at multiple time points with unknown joint distributions, there is only one known specifically developed method, which does not fully utilize the rich information contained in this data type. We develop an inference method for the GRN in this case, netWork infErence by covariaNce DYnamics, dubbed WENDY. The core idea of WENDY is to model the dynamics of the covariance matrix, and solve this dynamics as an optimization problem to determine the regulatory relationships. To evaluate its effectiveness, we compare WENDY with other inference methods using synthetic data and experimental data. Our results demonstrate that WENDY performs well across different data sets.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"377 ","pages":"Article 109284"},"PeriodicalIF":1.9,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142019937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights of infected Schwann cells extinction and inherited randomness in a stochastic model of leprosy","authors":"Salil Ghosh ,&nbsp;Sourav Rana ,&nbsp;Satyajit Mukherjee ,&nbsp;Priti Kumar Roy","doi":"10.1016/j.mbs.2024.109281","DOIUrl":"10.1016/j.mbs.2024.109281","url":null,"abstract":"<div><p>Investigating disease progression, transmission of infection and impacts of Multidrug Therapy (MDT) to inhibit demyelination in leprosy involves a certain amount of difficulty in terms of the in-built uncertain complicated and complex intracellular cell dynamical interactions. To tackle this scenario and to elucidate a more realistic, rationalistic approach of examining the infection mechanism and associated drug therapeutic interventions, we propose a four-dimensional ordinary differential equation-based model. Stochastic processes has been employed on this deterministic system by formulating the Kolmogorov forward equation introducing a transition state and the quasi-stationary distribution, exact distribution analysis have been investigated which allow us to estimate an expected time to extinction of the infected Schwann cells into the human body more prominently. Additionally, to explore the impact of uncertainty in the key intracellular factors, the stochastic system is investigated incorporating random perturbations and environmental noises in the disease dissemination, proliferation and reinfection rates. Rigorous numerical simulations validating the analytical outcomes provide us significant novel insights on the progression of leprosy and unravelling the existing major treatment complexities. Analytical experiments along with the simulations utilizing Monte-Carlo method and Euler–Maruyama scheme involving stochasticity predicts that the bacterial density is underestimated due to the recurrence of infection and suggests that maintaining a drug-efficacy rate in the range <span><math><mrow><mn>0</mn><mo>.</mo><mn>6</mn><mo>−</mo><mn>0</mn><mo>.</mo><mn>8</mn></mrow></math></span> would be substantially efficacious in eradicating leprosy.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109281"},"PeriodicalIF":1.9,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142006206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Presence and infestation waves of hematophagous arthropod species","authors":"M. Adrian Acuña-Zegarra,&nbsp;Mayra R. Tocto-Erazo,&nbsp;Claudio C. García-Mendoza,&nbsp;Daniel Olmos-Liceaga","doi":"10.1016/j.mbs.2024.109282","DOIUrl":"10.1016/j.mbs.2024.109282","url":null,"abstract":"<div><p>The invasion of hematophagous arthropod species in human settlements represents a threat, not only to the economy but also to the health system in general. Recent examples of this phenomenon were seen in Paris and Mexico City, evidencing the importance of understanding these dynamics. In this work, we present a reaction–diffusion model to describe the invasion dynamics of hematophagous arthropod species. The proposed model considers a denso-dependent growth rate and parameters related to the control of the invasive species. Our results illustrate the existence of two invasion levels (presence and infestation) within a region, depending on control parameter values. We also prove analytically the existence of the presence and infestation waves and show different theoretical types of invasion waves that result from varying control parameters. In addition, we present a condition threshold that determines whether or not an infestation occurs. Finally, we illustrate some results when considering the case of bedbugs and brown dog ticks as invasion species.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109282"},"PeriodicalIF":1.9,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142006207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Derivation and dynamics of discrete population models with distributed delay in reproduction","authors":"Sabrina H. Streipert ,&nbsp;Gail S.K. Wolkowicz","doi":"10.1016/j.mbs.2024.109279","DOIUrl":"10.1016/j.mbs.2024.109279","url":null,"abstract":"<div><p>We introduce a class of discrete single species models with distributed delay in the reproductive process and a cohort dependent survival function that accounts for survival pressure during that delay period. These delay recurrences track the mature population for species in which individuals reach maturity after at least <span><math><mi>τ</mi></math></span> and at most <span><math><mrow><mi>τ</mi><mo>+</mo><msub><mrow><mi>τ</mi></mrow><mrow><mi>M</mi></mrow></msub></mrow></math></span> breeding cycles. Under realistic model assumptions, we prove the existence of a critical delay threshold, <span><math><msub><mrow><mover><mrow><mi>τ</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>c</mi></mrow></msub></math></span>. For given delay kernel length <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mi>M</mi></mrow></msub></math></span>, if each individual takes at least <span><math><msub><mrow><mover><mrow><mi>τ</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>c</mi></mrow></msub></math></span> time units to reach maturity, then the population is predicted to go extinct. We show that the positive equilibrium is decreasing in both <span><math><mi>τ</mi></math></span> and <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mi>M</mi></mrow></msub></math></span>. In the case of a constant reproductive rate, we provide an equation to determine <span><math><msub><mrow><mover><mrow><mi>τ</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>c</mi></mrow></msub></math></span> for fixed <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mi>M</mi></mrow></msub></math></span>, and similarly, provide a lower bound on the kernel length, <span><math><msub><mrow><mover><mrow><mi>τ</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>M</mi></mrow></msub></math></span> for fixed <span><math><mi>τ</mi></math></span> such that the population goes extinct if <span><math><mrow><msub><mrow><mi>τ</mi></mrow><mrow><mi>M</mi></mrow></msub><mo>≥</mo><msub><mrow><mover><mrow><mi>τ</mi></mrow><mrow><mo>˜</mo></mrow></mover></mrow><mrow><mi>M</mi></mrow></msub></mrow></math></span>. We compare these critical thresholds for different maturation distributions and show that if all else is the same, to avoid extinction it is best if all individuals in the population have the shortest delay possible. We apply the model derivation to a Beverton–Holt model and discuss its global dynamics. For this model with kernels that share the same mean delay, we show that populations with the largest variance in the time required to reach maturity have higher population levels and lower chances of extinction.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109279"},"PeriodicalIF":1.9,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finding Hopf bifurcation islands and identifying thresholds for success or failure in oncolytic viral therapy","authors":"Sana Jahedi ,&nbsp;Lin Wang ,&nbsp;James A. Yorke ,&nbsp;James Watmough","doi":"10.1016/j.mbs.2024.109275","DOIUrl":"10.1016/j.mbs.2024.109275","url":null,"abstract":"<div><p>We model interactions between cancer cells and viruses during oncolytic viral therapy. One of our primary goals is to identify parameter regions that yield treatment failure or success. We show that the tumor size under therapy at a particular time is less than the size without therapy. Our analysis demonstrates two thresholds for the horizontal transmission rate: a “failure threshold” below which treatment fails, and a “success threshold” above which infection prevalence reaches 100% and the tumor shrinks to its smallest size. Moreover, we explain how changes in the virulence of the virus alter the success threshold and the minimum tumor size. Our study suggests that the optimal virulence of an oncolytic virus depends on the timescale of virus dynamics. We identify a threshold for the virulence of the virus and show how this threshold depends on the timescale of virus dynamics. Our results suggest that when the timescale of virus dynamics is fast, administering a more virulent virus leads to a greater reduction in the tumor size. Conversely, when the viral timescale is slow, higher virulence can induce oscillations with high amplitude in the tumor size. Furthermore, we introduce the concept of a “Hopf bifurcation Island” in the parameter space, an idea that has applications far beyond the results of this paper and is applicable to many mathematical models. We elucidate what a Hopf bifurcation Island is, and we prove that small Islands can imply very slowly growing oscillatory solutions.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109275"},"PeriodicalIF":1.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141914967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breakdown of Boltzmann-type models for the alignment of self-propelled rods","authors":"Patrick Murphy ,&nbsp;Misha Perepelitsa ,&nbsp;Ilya Timofeyev ,&nbsp;Matan Lieber-Kotz ,&nbsp;Brandon Islas ,&nbsp;Oleg A. Igoshin","doi":"10.1016/j.mbs.2024.109266","DOIUrl":"10.1016/j.mbs.2024.109266","url":null,"abstract":"<div><p>Studies in the collective motility of organisms use a range of analytical approaches to formulate continuous kinetic models of collective dynamics from rules or equations describing agent interactions. However, the derivation of these kinetic models often relies on Boltzmann’s “molecular chaos” hypothesis, which assumes that correlations between individuals are short-lived. While this assumption is often the simplest way to derive tractable models, it is often not valid in practice due to the high levels of cooperation and self-organization present in biological systems. In this work, we illustrated this point by considering a general Boltzmann-type kinetic model for the alignment of self-propelled rods where rod reorientation occurs upon binary collisions. We examine the accuracy of the kinetic model by comparing numerical solutions of the continuous equations to an agent-based model that implements the underlying rules governing microscopic alignment. Even for the simplest case considered, our comparison demonstrates that the kinetic model fails to replicate the discrete dynamics due to the formation of rod clusters that violate statistical independence. Additionally, we show that introducing noise to limit cluster formation helps improve the agreement between the analytical model and agent simulations but does not restore the agreement completely. These results highlight the need to both develop and disseminate improved moment-closure methods for modeling biological and active matter systems.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109266"},"PeriodicalIF":1.9,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0025556424001263/pdfft?md5=d3610de789d955115816de8934e2ce02&pid=1-s2.0-S0025556424001263-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141914966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of homophily on coupled behavior-disease dynamics near a tipping point","authors":"Zitao He,&nbsp;Chris T. Bauch","doi":"10.1016/j.mbs.2024.109264","DOIUrl":"10.1016/j.mbs.2024.109264","url":null,"abstract":"<div><p>Understanding the interplay between social activities and disease dynamics is crucial for effective public health interventions. Recent studies using coupled behavior-disease models assumed homogeneous populations. However, heterogeneity in population, such as different social groups, cannot be ignored. In this study, we divided the population into social media users and non-users, and investigated the impact of homophily (the tendency for individuals to associate with others similar to themselves) and online events on disease dynamics. Our results reveal that homophily hinders the adoption of vaccinating strategies, hastening the approach to a tipping point after which the population converges to an endemic equilibrium with no vaccine uptake. Furthermore, we find that online events can significantly influence disease dynamics, with early discussions on social media platforms serving as an early warning signal of potential disease outbreaks. Our model provides insights into the mechanisms underlying these phenomena and underscores the importance of considering homophily in disease modeling and public health strategies.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109264"},"PeriodicalIF":1.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S002555642400124X/pdfft?md5=74385800e80062ca5184deb43245a2fe&pid=1-s2.0-S002555642400124X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141891445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Control of schistosomiasis by the selective competitive and predatory intervention of intermediate hosts: A mathematical modeling approach","authors":"Zadoki Tabo ,&nbsp;Livingstone Luboobi ,&nbsp;Philipp Kraft ,&nbsp;Lutz Breuer ,&nbsp;Christian Albrecht","doi":"10.1016/j.mbs.2024.109263","DOIUrl":"10.1016/j.mbs.2024.109263","url":null,"abstract":"<div><p>Schistosomiasis, a freshwater-borne neglected tropical disease, disproportionately affects impoverished communities mainly in the tropical regions. Transmission involves humans and intermediate host (IH) snails. This manuscript introduces a mathematical model to probe schistosomiasis dynamics and the role of non-host snail competitors and predators as biological control agents for IH snails. The numerical analyses include investigations into steady-state conditions and reproduction numbers associated with uncontrolled scenarios, as well as scenarios involving non-host snail competitors and/or predators. Sensitivity analysis reveals that increasing snail mortality rates is a key to reducing the IH snail population and control of the transmission. Results show that specific snail competitors and/or predators with strong competition/predation abilities reduce IH snails and the subsequent infectious cercaria populations, reduce the transmission, and possibly eradicate the disease, while those with weaker abilities allow disease persistence. Hence our findings advocate for the effectiveness of snail competitors with suitable competitive pressures and/or predators with appropriate predatory abilities as nature-based solutions for combating schistosomiasis, all while preserving IH snail biodiversity. However, if these strategies are implemented at insignificant levels, IH snails can dominate, and disease persistence may pose challenges. Thus, experimental screening of potential (native) snail competitors and/or predators is crucial to assess the likely behavior of biological agents and determine the optimal biological control measures for IH snails.</p></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"376 ","pages":"Article 109263"},"PeriodicalIF":1.9,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0025556424001238/pdfft?md5=06a7af3d9e784d286965fd9ae24cddf4&pid=1-s2.0-S0025556424001238-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141877034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}