Journal of Theoretical Biology最新文献_第3页

Kinetics, thresholds, and a comparison of mechanisms underlying systemic infection by Listeria monocytogenes 单核细胞增生李斯特菌全身性感染的动力学、阈值和机制比较。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-12-04 DOI: 10.1016/j.jtbi.2024.112009

Tristen M. Jackson

Studies on the system-scale pathogenesis of Listeria monocytogenes infection have classically focused on its ability to colonize in the intestines following an exposure event. However, despite this, many of the most dangerous complications arising from L. monocytogenes infection are observed days, weeks, or months after exposure, resulting indirectly from bacteria escaping this intestinal colonization hub and invading other organs. Over time, findings of various individual phenomena observed during systemic infection have accumulated, including a shift away from the principal route of intestinal dissemination, delays in bacterial colonization of the central nervous system, differing bacterial flux rates across organs, and multi-stability of bacterial population levels. To further our quantitative understanding of foodborne bacterial infection dynamics, a compartmental model of systemic infection that synthesizes these findings is proposed. Under parameterization to infection in BALB/c mice, the model is used to show a substantial decrease in bacterial populations resulting from dissemination through the mesenteric lymph nodes, as compared to the portal vein, when controlling for the number of bacteria passing through each route. Due to the compartmental nature of this model, we anticipate that this result may be paralleled in other microbes which make use of these pathways to escape the intestinal environment. Additionally, we predict thresholds for intestinal dissemination along each of these routes, which must be surpassed to induce systemic infection, and describe how these thresholds change over time. Supplementarily, logistic curves are fitted to synthetic data as a means of robustly quantifying the dose–response relationship beyond the intestinal barrier.

关于单核细胞增生李斯特菌感染的系统规模发病机制的研究一直集中在暴露事件后其在肠道内定植的能力上。然而，尽管如此，许多由单核增生乳杆菌感染引起的最危险的并发症是在暴露后数天、数周或数月后观察到的，这是由于细菌逃离肠道定植中心并入侵其他器官间接造成的。随着时间的推移，在全系统感染期间观察到的各种个体现象的发现已经积累起来，包括肠道传播主要途径的转移，中枢神经系统细菌定植的延迟，跨器官细菌通量的不同以及细菌种群水平的多重稳定性。为了进一步定量了解食源性细菌感染动力学，提出了综合这些发现的全身性感染的室室模型。在BALB/c小鼠感染的参数化下，该模型显示，当控制通过每种途径的细菌数量时，与门静脉相比，通过肠系膜淋巴结传播的细菌数量大幅减少。由于该模型的区隔性，我们预计这一结果可能与其他利用这些途径逃离肠道环境的微生物相似。此外，我们还预测了肠道传播的阈值，这些阈值必须超过才能诱发全身性感染，并描述了这些阈值如何随时间变化。此外，logistic曲线被拟合到合成数据中，作为一种稳健量化肠屏障之外的剂量-反应关系的手段。

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引用次数: 0

HIV transactivation: Stochastic modeling for studying the effects of BET inhibitors on the modulation of P-TEFb levels HIV交易激活：研究BET抑制剂对P-TEFb水平调节作用的随机模型。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-12-04 DOI: 10.1016/j.jtbi.2024.112011

Miranda Harkess , Sudha Kumari , Trilochan Bagarti , Niraj Kumar

Latency is the major obstacle in eradicating HIV from infected patients. Recent studies have shown that BET protein inhibitors can successfully reverse this latency by inhibiting the binding of BET proteins with positive cellular cofactor P-TEFb. Thus, availability of P-TEFbs plays an important role in HIV transactivation. However, in cells of our immune system which are primarily infected by the virus, number of P-TEFb is very low and is considered as one of the factors in inducing viral latency. At such small numbers of P-TEFb, the internal fluctuations can have a decisive role in the cell fate decision and fluctuations in the P-TEFb levels can switch the HIV to either a state of active replication or to a state of latency. Aimed at quantitative understanding of how BET inhibitors affect the statistics of P-TEFb level, we develop a coarse-grained stochastic model. However, the interaction between P-TEFb and BET proteins makes the problem analytically challenging. To address the nonlinearity arising due to such interactions, we use Langevin equation based approach to study the statistics of steady-state P-TEFb levels and explore the variations of some of the important quantities such as noise and fano factor associated with P-TEFb as well as correlations between BET and P-TEFb levels with model parameters. The analytic results derived exhibit that these quantities, in general, show non-monotonic response with respect to the parameters of the model. The results derived will be helpful in estimating the model parameters as well in identifying the pathways that can be intervened for effective HIV transactivation.

潜伏期是从感染患者身上根除艾滋病毒的主要障碍。最近的研究表明，BET蛋白抑制剂可以通过抑制BET蛋白与阳性细胞辅因子P-TEFb的结合成功逆转这种潜伏期。因此，P-TEFbs的可用性在艾滋病毒的反应中起着重要作用。然而，在我们主要被病毒感染的免疫系统细胞中，P-TEFb的数量非常低，被认为是诱导病毒潜伏期的因素之一。在P-TEFb数量如此之少的情况下，内部波动可能在细胞命运决定中起决定性作用，P-TEFb水平的波动可以将HIV切换到主动复制状态或延迟状态。为了定量了解BET抑制剂如何影响P-TEFb水平的统计，我们开发了一个粗粒度随机模型。然而，P-TEFb和BET蛋白之间的相互作用使得这个问题在分析上具有挑战性。为了解决由于这种相互作用而产生的非线性，我们使用基于朗格万方程的方法研究稳态P-TEFb水平的统计数据，并探索与P-TEFb相关的一些重要量（如噪声和fano因子）的变化，以及BET和P-TEFb水平与模型参数之间的相关性。解析结果表明，这些量对模型参数一般表现出非单调响应。所得的结果将有助于估计模型参数，以及确定可以干预有效的HIV交互激活的途径。

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引用次数: 0

A hybrid approach to study and forecast climate-sensitive norovirus infections in the USA 研究和预测美国气候敏感诺如病毒感染的混合方法

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-26 DOI: 10.1016/j.jtbi.2024.112007

Juping Ji , Shohel Ahmed , Hao Wang

Norovirus, responsible for acute gastroenteritis and foodborne diseases in the United States, is influenced significantly by environmental factors. This study employs a hybrid approach to develop a foodborne disease model that incorporates indirect incidence to examine the correlation between norovirus outbreaks and environmental conditions, specifically focusing on the impact of temperature and humidity on virus transmission. By analyzing weekly average climate data and confirmed case data from four United States regions (Southern, Northeastern, Midwestern, and Western), we assess the mortality rates and estimate transmission rates using the inverse method. Our numerical results confirm that norovirus outbreaks predominantly occur in colder months. However, higher temperatures or increased humidity during warmer months appear to mitigate the spread of the virus. Utilizing climate data, this study also forecasts transmission rates and infection cases up to eight weeks in advance using a generalized boosting machine learning model.

诺如病毒在美国引起急性肠胃炎和食源性疾病，受到环境因素的显著影响。本研究采用混合方法开发了一种食源性疾病模型，该模型纳入了间接发病率，以检查诺如病毒爆发与环境条件之间的相关性，特别关注温度和湿度对病毒传播的影响。通过分析来自美国四个地区（南部、东北部、中西部和西部）的每周平均气候数据和确诊病例数据，我们评估了死亡率，并使用逆方法估计了传播率。我们的数值结果证实，诺如病毒爆发主要发生在寒冷的月份。然而，在温暖的月份，较高的温度或增加的湿度似乎可以减轻病毒的传播。利用气候数据，这项研究还使用广义增强机器学习模型提前八周预测传播率和感染病例。

引用次数: 0

Optimal control of vaccination for an epidemic model with standard incidence rate 具有标准发病率的流行病模型的疫苗接种最优控制。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-26 DOI: 10.1016/j.jtbi.2024.111993

Li Li , Na Zheng , Chen Liu , Zhen Wang , Zhen Jin

A critical challenge for diseases spread is the development of effective prevention and control measures while minimizing costs, representing the foremost priority. Unfortunately, research in this crucial area remains inadequately explored. Consequently, this paper addresses the issue by leveraging an SI reaction–diffusion epidemic model incorporating a logistic birth rate and standard incidence rate. Employing vaccination as a control variable and integrating sparse optimal control theory, the study elucidates the achievement of epidemic prevention and control through the optimization of resource allocation, emphasizing a perspective rooted in pattern structure transformation. On the one hand, we theoretically prove the existence of the optimal solutions, first-order necessary optimality conditions, and the sparsity properties. On the other hand, we use numerical simulations to verify the rationality of the control method and the effectiveness of the control strategy from three aspects of control effect, control error and control cost. In addition, tailored targeting options are proposed based on the economic status of each region, specifying the required inoculum amount for each moment. Ultimately, the study demonstrates the effectiveness of input vaccination in controlling epidemics in a majority of areas. In summary, this work offers crucial insights into the prevention and control of a non-quasimonotonic reaction–diffusion epidemic model.

疾病传播面临的一个严峻挑战是制定有效的预防和控制措施，同时最大限度地降低成本，这也是重中之重。遗憾的是，对这一关键领域的研究仍然不够深入。因此，本文利用包含逻辑出生率和标准发病率的 SI 反应扩散流行病模型来解决这一问题。研究以疫苗接种为控制变量，结合稀疏最优控制理论，通过优化资源配置来实现疫情防控，强调从模式结构转换的角度出发。一方面，我们从理论上证明了最优解的存在性、一阶必要最优条件和稀疏性。另一方面，我们利用数值模拟从控制效果、控制误差和控制成本三个方面验证了控制方法的合理性和控制策略的有效性。此外，还根据各地区的经济状况提出了有针对性的目标选择方案，规定了每个时刻所需的接种量。最终，该研究证明了投入式疫苗接种在大多数地区控制流行病的有效性。总之，这项工作为预防和控制非类比反应-扩散流行病模型提供了重要见解。

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引用次数: 0

Optimisation of gene expression noise for cellular persistence against lethal events 优化基因表达噪音，使细胞持续对抗致死事件。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-25 DOI: 10.1016/j.jtbi.2024.111996

Pavol Bokes , Abhyudai Singh

Bacterial cell persistence, crucial for survival under adverse conditions like antibiotic exposure, is intrinsically linked to stochastic fluctuations in gene expression. Certain genes, while inhibiting growth under normal circumstances, confer tolerance to antibiotics at elevated expression levels. The occurrence of antibiotic events lead to instantaneous cellular responses with varied survival probabilities correlated with gene expression levels. Notably, cells with lower protein concentrations face higher mortality rates. This study aims to elucidate an optimal strategy for protein expression conducive to cellular survival. Through comprehensive mathematical analysis, we determine the optimal burst size and frequency that maximise cell proliferation. Furthermore, we explore how the optimal expression distribution changes as the cost of protein expression to growth escalates. Our model reveals a hysteresis phenomenon, characterised by discontinuous transitions between deterministic and stochastic optima. Intriguingly, stochastic optima possess a noise floor, representing the minimal level of fluctuations essential for optimal cellular resilience.

细菌细胞的持久性对于在抗生素暴露等不利条件下的生存至关重要，它与基因表达的随机波动有着内在联系。某些基因虽然在正常情况下会抑制生长，但在表达水平升高时会产生对抗生素的耐受性。抗生素事件的发生会导致细胞瞬时反应，其存活概率与基因表达水平相关。值得注意的是，蛋白质浓度较低的细胞死亡率较高。本研究旨在阐明有利于细胞存活的最佳蛋白质表达策略。通过综合数学分析，我们确定了使细胞增殖最大化的最佳猝发大小和频率。此外，我们还探讨了最佳表达分布如何随着蛋白质表达对生长的成本增加而发生变化。我们的模型揭示了一种滞后现象，其特点是确定性最优和随机最优之间的不连续转换。耐人寻味的是，随机最佳值具有噪音底限，代表了细胞最佳恢复能力所必需的最低波动水平。

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引用次数: 0

An analytical, numerical and experimental study of in-vitro SARS-CoV-2 evolution in Vero B4 cells 体外 SARS-CoV-2 在 Vero B4 细胞中演变的分析、数值和实验研究。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-23 DOI: 10.1016/j.jtbi.2024.112000

Matthew Nicol , Julian D.J. Sng , Yanshan Zhu , Sissy Therese Sonnleitner , Kirsty R. Short , Meagan Carney

We derive a numerical model representing the emergence and evolution of SARS-CoV-2 variants, informed by data from in-vitro passaging experiments in Vero B4 cells. We compare our numerical simulation results against probabilistic derivations of the expected probability of and time until the fittest variant becomes fixed in the population. Contrary to literature surrounding DNA viruses and eukaryotes where probabilities of fitness extremes are often modelled by exponential decaying tail, we show that above wildtype fitness differences for SARS-CoV-2 are actually best modelled by a heavy-tailed Fréchet distribution. Furthermore, we find that SARS-CoV-2 variants evolve through an essentially deterministic process rather than a diffusional one, with the dynamics driven by the fitness difference between the top variants rather than by the sampling/dilution process. An interesting consequence of this setting is that the number of variant virions, rather than their proportion, is a better predictor of the probability of fixation for a given variant.

我们根据 Vero B4 细胞体外传代实验的数据，推导出一个代表 SARS-CoV-2 变异体出现和进化的数值模型。我们将数值模拟结果与最合适变种在群体中固定下来的预期概率和时间的概率推导结果进行了比较。与有关 DNA 病毒和真核生物的文献（这些文献通常用指数衰减尾数来模拟适合度极值的概率）相反，我们发现，SARS-CoV-2 高于野生型的适合度差异实际上最好用重尾弗雷谢特分布来模拟。此外，我们还发现，SARS-CoV-2 变体的演化过程基本上是确定性的，而不是扩散性的，其动态是由顶级变体之间的适应度差异而不是采样/稀释过程驱动的。这种设定的一个有趣结果是，变异病毒的数量而不是其比例更能预测变异体固定的概率。

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引用次数: 0

Noise-induced entrainment of the circadian clock by thermoperiods in tomato: A computational approach 番茄昼夜节律时钟在噪声诱导下受恒温周期影响：计算方法

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-22 DOI: 10.1016/j.jtbi.2024.111999

Ting Huang , Hengmin Lv , Yiting Shu , Jian Luo , Linxuan Yu , Bing Chen , Xin Sun , Xilin Hou , Xiong You , Tonghua Zhang

The endogenous circadian rhythm (approximately 24 h) allows plants to adapt to daily light and temperature variations. Although the mechanism of photoperiod entrainment has been studied extensively, entrainment to diurnal temperature rhythms remains poorly understood. Here we investigate the stochastic entrainment of the circadian clock in the model crop tomato, subject to different thermoperiods. We first proposed the deterministic model of the thermoresponsive circadian clock. The expressions of the circadian clock genes under constant warm temperature (29 ℃) were quantified by RT-qPCR for basal parameters estimation through minimizing the cost function. Model simulations by the stochastic simulation algorithm showed warm temperatures resulting in an advanced phase for approximately 3–4 h. A few hundred molecules for the system size of the stochastic model were sufficient to engage the robust oscillations. Multiple temperature inputs and abnormal temperature cycles similarly showed the invariant robustness of the oscillations. In addition, phases of the core circadian elements were remarkably correlated linearly with periods under temperature cycles. Whereas, the phases were correlated with the duration of daily warm temperature stimuli in a polynomial mode.

内源昼夜节律（约 24 小时）使植物能够适应每天的光照和温度变化。尽管对光周期诱导机制进行了广泛的研究，但对昼夜温度节律的诱导仍然知之甚少。在此，我们研究了模式作物番茄在不同温度周期下昼夜节律时钟的随机诱导。我们首先提出了恒温昼夜节律钟的确定性模型。通过RT-qPCR定量分析恒温（29 ℃）条件下昼夜节律时钟基因的表达量，并通过最小化成本函数估算基础参数。通过随机模拟算法进行的模型模拟显示，暖温会导致大约 3-4 小时的高级阶段。在随机模型的系统规模中，几百个分子就足以产生稳健的振荡。多重温度输入和异常温度循环同样显示了振荡的不变稳健性。此外，在温度周期下，核心昼夜节律元素的相位与周期呈显著的线性相关。而相位与每日温暖温度刺激持续时间之间的关系是多项式而非线性的。

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引用次数: 0

Phase synchronization analysis of EEG functional connectivity in Parkinson’s disease 帕金森病脑电图功能连接的相位同步分析。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-20 DOI: 10.1016/j.jtbi.2024.111997

Karthikeyan Rajagopal , Nafise Naseri , Fatemeh Parastesh , Farnaz Ghassemi , Sajad Jafari

There is a growing need for research on Parkinson’s disease (PD), a neurological condition that often affects the elderly. By examining brain network connectivity, researchers are able to discover how different brain regions interact during various cognitive and behavioral tasks. They can also understand how changes in nonlinear connections may be linked to neurological and mental illnesses. In this paper, the synchrony levels of 59 EEG channels from 26 Parkinson’s patients and 13 healthy subjects is examined by utilizing Phase-Lag Index (PLI) during a motor task and resting-state conditions. Examining different EEG frequency bands shows that whole-brain synchronization in the delta band is significantly lower in PD patients compared to healthy subjects during the task. PD patients also exhibit a lower clustering coefficient and a higher shortest path length in this band during the task, which shows the higher small-worldness in Parkinson’s patients compared to healthy individuals. Moreover, the global efficiency in the delta band is significantly reduced in PD patients during the task. An analysis of local efficiency shows that PD and control groups differ in 57 channels. These results reveal that Parkinson’s patients appear to have considerable pathological abnormalities in their delta band connectivity and its characteristic features.

帕金森病（Parkinson's disease，简称PD）是一种经常影响老年人的神经系统疾病，对该病的研究需求与日俱增。通过研究大脑网络的连通性，研究人员能够发现不同的大脑区域在完成各种认知和行为任务时是如何相互作用的。他们还能了解非线性连接的变化如何与神经和精神疾病相关联。本文利用相位滞后指数（PLI）研究了 26 名帕金森病患者和 13 名健康受试者在运动任务和静息状态条件下 59 个脑电图通道的同步水平。对不同脑电图频段的研究表明，与健康受试者相比，帕金森病患者在完成任务时，δ频段的全脑同步性明显较低。帕金森病患者在完成任务时，该频段的聚类系数较低，最短路径长度较高，这表明帕金森病患者的小世界性高于健康人。此外，帕金森病患者在完成任务时，δ波段的全局效率明显降低。对局部效率的分析表明，帕金森病组和对照组在 57 个通道上存在差异。这些结果表明，帕金森病患者的δ波段连通性及其特征似乎存在相当大的病理异常。

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引用次数: 0

A stochastic population model for the impact of cancer cell dormancy on therapy success 癌细胞休眠对治疗成功率影响的随机群体模型。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-19 DOI: 10.1016/j.jtbi.2024.111995

Jochen Blath , Anna Kraut , Tobias Paul , András Tóbiás

Therapy evasion – and subsequent disease progression – is a major challenge in current oncology. An important role in this context seems to be played by various forms of cancer cell dormancy. For example, therapy-induced dormancy, over short timescales, can create serious obstacles to aggressive treatment approaches such as chemotherapy, and long-term dormancy may lead to relapses and metastases even many years after an initially successful treatment.

In this paper, we focus on individual cancer cells switching into and out of a dormant state both spontaneously as well as in response to treatment. We introduce an idealized mathematical model, based on stochastic agent-based interactions, for the dynamics of cancer cell populations involving individual short-term dormancy, and allow for a range of (multi-drug) therapy protocols. Our analysis – based on simulations of the many-particle limit – shows that in our model, depending on the specific underlying dormancy mechanism, even a small initial population (of explicitly quantifiable size) of dormant cells can lead to therapy failure under classical single-drug treatments that would successfully eradicate the tumour in the absence of dormancy. We further investigate and quantify the effectiveness of several multi-drug regimes (manipulating dormant cancer cells in specific ways, including increasing or decreasing resuscitation rates or targeting dormant cells directly). Relying on quantitative results for concrete simulation parameters, we provide some general basic rules for the design of (multi-)drug treatment protocols depending on the types and processes of dormancy mechanisms present in the population.

逃避治疗--以及随后的疾病进展--是当前肿瘤学面临的一大挑战。在这种情况下，各种形式的癌细胞休眠似乎发挥了重要作用。例如，治疗诱导的短时间休眠会严重阻碍化疗等积极治疗方法，而长期休眠则可能导致复发和转移，甚至在最初的成功治疗多年后仍是如此。在本文中，我们将重点研究单个癌细胞自发地以及在治疗过程中进出休眠状态的情况。我们引入了一个理想化的数学模型，该模型以随机代理互动为基础，适用于涉及个体短期休眠的癌细胞群动态，并允许一系列（多种药物）治疗方案。我们的分析--基于多粒子极限的模拟--表明，在我们的模型中，根据特定的潜在休眠机制，即使是很小的（可明确量化的）初始休眠细胞群也会导致经典单药治疗的失败，而在没有休眠的情况下，这些单药治疗会成功根除肿瘤。我们进一步研究并量化了几种多药治疗方案的有效性（以特定方式操纵休眠癌细胞，包括提高或降低复苏率或直接针对休眠细胞）。根据具体模拟参数的量化结果，我们提供了设计（多种）药物治疗方案的一些一般基本规则，这些规则取决于群体中存在的休眠机制的类型和过程。

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引用次数: 0

Cooperative SIR dynamics as a model for spontaneous blood clot initiation 作为自发血凝块形成模型的合作 SIR 动力学。

IF 1.9 4区数学 Q2 BIOLOGY

Journal of Theoretical Biology

Pub Date : 2024-11-17 DOI: 10.1016/j.jtbi.2024.111991

Philip Greulich

Blood clotting is an important physiological process to suppress bleeding upon injury, but when it occurs inadvertently, it can cause thrombosis, which can lead to life threatening conditions. Hence, understanding the microscopic mechanistic factors for inadvertent, spontaneous blood clotting, in absence of a vessel breach, can help in predicting and averting such conditions. Here, we present a minimal model – reminiscent of the SIR model – for the initiating stage of spontaneous blood clotting, the collective activation of blood platelets. This model predicts that in the presence of very small initial activation signals, collective activation of the platelet population is possible, but requires a sufficient degree of heterogeneity of platelet sensitivity. To propagate the activation signal and achieve collective activation of the bulk platelet population, it requires the presence of, possibly only few, hyper-sensitive platelets, but also a sufficient proportion of platelets with intermediate, yet higher-than-average sensitivity. A comparison with experimental results demonstrates a qualitative agreement for high platelet signalling activity.

血液凝结是受伤后抑制出血的重要生理过程，但如果不慎发生，则可能导致血栓形成，从而危及生命。因此，在没有血管破裂的情况下，了解不经意间自发凝血的微观机理因素有助于预测和预防此类情况的发生。在此，我们提出了一个自发性血液凝结初始阶段--血小板集体活化--的最小模型（类似于 SIR 模型）。该模型预测，在初始激活信号很小的情况下，血小板群的宏观激活是可能的，但需要血小板敏感性有足够的异质性。要传播活化信号并实现大量血小板的集体活化，可能需要存在少数超敏感血小板，但也需要足够比例的血小板具有中等但高于平均水平的敏感性。与实验结果的比较表明，两者在高血小板信号活性方面的定性一致。

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引用次数: 0