Adipocyte development and insulin resistance

脂肪垫在能量过剩和不足时动态调节能量储存能力。这种重塑过程尚未完全理解，关于脂肪库和脂肪细胞数量可塑性之间的差异存在争议。 我们先前研究了小鼠脂肪细胞大小分布的变化，在附睾，腹股沟，腹膜后，和肠系膜脂肪下的体重增加和损失。通过数学建模，我们具体分析了脂肪细胞的招募，生长/收缩和损失，包括这些过程的大小依赖性。我们在所有四个脂肪库中发现了一个定性的普遍脂肪组织重塑过程：（1）体重增加时不断招募新细胞;（2）较大细胞（直径> 50微米）的生长和收缩与细胞表面积成比例;（3）在长期体重增加时发生细胞损失，较大细胞更容易受到影响。该数学模型给出了脂肪组织重塑的预测性综合图，并可用于检查这些特定细胞过程在肥胖和糖尿病中的相对重要性的变化。在以前的出版物中，我们表明，似乎有一个周期性的细胞大小的概率分布的变化，通过分析纵向数据从两个Zucker脂肪大鼠。在那项工作中，我们提出了一个可能产生这种周期性的数学模型，该模型的预测是，相对于食物，高脂肪饮食可能会导致周期缩短。 我们采用两种截然不同的模型，霍尔的身体成分模型和 同事，和脂肪组织动力学模型，并整合它们。这不是一个 轻松的练习事实上，有人可能会怀疑，这是可能的，因为霍尔模型 预测脂肪量的减少或增加取决于饮食，但不依赖于胰岛素 阻力另一方面，从Arner和同事的工作中， McLaughlin和他的同事以及其他人认为，脂肪组织状态与 胰岛素抵抗 我们解决这个难题与动力学建模。我们发现脂肪组织动力学 这意味着需要脂肪组织状态和身体成分之间的一致性 通过在组织和生物体尺度上匹配两种模型中的脂肪量损失和增加， 预测胰岛素抵抗个体的脂解率较低， 脂肪生成这一结果是在没有任何胰岛素依赖性的情况下获得的， 身体组成模型或脂肪组织动态模型。

Fat pads dynamically regulate energy storage capacity under energy excess and deficit. This remodeling process is not completely understood, with controversies regarding differences between fat depots and plasticity of adipose cell number. We previously examined changes of mouse adipose cell-size distributions in epididymal, inguinal, retroperitoneal, and mesenteric fat under both weight gain and loss. With mathematical modeling, we specifically analyzed the recruitment, growth/shrinkage, and loss of adipose cells, including the size dependence of these processes. We found a qualitatively universal adipose tissue remodeling process in all four fat depots: (1) There is continuous recruitment of new cells under weight gain; (2) The growth and shrinkage of larger cells (diameter > 50 microns) is proportional to cell surface area; and (3) Cell loss occurs under prolonged weight gain, with larger cells more susceptible. The mathematical model gives a predictive integrative picture of adipose tissue remodeling, and can be used to examine changes in the relative importance of these specific cellular processes in obesity and diabetes. In previous publications, we demonstrated that there appeared to be a periodicity in changes in the cell-size probability distributions by analyzing longitudinal data from two Zucker fatty rats. In that work, we proposed a mathematical model that could give rise to such periodicity, and a prediction of that model was that a high-fat diet may lead to a decrease in the period, relative to chow. We take two very different models, the body composition model of Hall and colleagues, and a model of adipose tissue dynamics, and integrate them. This is not a facile exercise. Indeed, one might wonder that it is possible at all, for the Hall model predicts fat mass loss or gain depending on diet but with no dependence on insulin resistance. On the other hand, it is well-known from the work of Arner and colleagues, McLaughlin and colleagues, and others, that adipose tissue state is correlated with insulin resistance. We resolve this puzzle with dynamical modeling. We show that the adipose tissue dynamics that is implied by requiring consistency between adipose tissue state and body composition by matching fat mass loss and gain in the two models at tissue and organism scales predicts that insulin resistant individuals have lower rates of lipolysis and higher rates of lipogenesis. This result is obtained without any insulin dependence in either the body composition model or the adipose tissue dynamic model.