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The stealthy hano-machine behind mast cell granule size distribution

机译:桅杆细胞颗粒尺寸分布后面的隐身漫步机

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摘要

The classical model of mast cell secretory granule formation suggests that newly synthesized secretory mediators, transported from the rough endoplasmic reticulum to the Golgi complex, undergo post-transitional modification and are packaged for secretion by condensation within membrane-bound granules of unit size. These unit granules may fuse with other granules to form larger granules that reside in the cytoplasm until secreted. A novel stochastic model for mast cell granule growth and elimination (G&E) as well as inventory management is presented. Resorting to a statistical mechanics approach in which SNAP (Soluble NSF Attachment Protein) REceptor (SNARE) components are viewed as interacting particles, the G&E model provides a simple 'nano-machine' of SNARE self-aggregation that can perform granule growth and secretion. Granule stock is maintained as a buffer to meet uncertainty in demand by the extracellular environment and to serve as source of supply during the lead time to produce granules of adaptive content. Experimental work, mathematical calculations, statistical modeling and a rationale for the emergence of nearly last-in, first out inventory management, are discussed.
机译:肥大细胞分泌颗粒形成的经典模型表明,新合成的分泌介质,从粗糙的内质网传送到戈尔基复合物,经历过渡后改性,并通过单位尺寸的膜结合颗粒内的缩合包装以分泌。这些单元颗粒可以融合与其他颗粒,以形成较大的颗粒,其在细胞质中直至分泌。提出了一种肥大细胞颗粒生长和消除(G&E)的新型随机模型及库存管理。借助统计力学方法,其中捕获(可溶性NSF附着蛋白)受体(SNARE)组分被视为相互作用颗粒,G&E模型提供了一种简单的“纳米机”,其可以进行颗粒生长和分泌。将颗粒股作为缓冲液,以满足细胞外环境需求的不确定性,并且在提前期间用作供应源以产生适应性含量的颗粒。讨论了实验工作,数学计算,统计建模和近上次出现的初始库存管理的理由。

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