生物細胞內凍結現象之機率模式與分析

Stochastic Modeling and Analysis of Intracellular Ice Formation Phenomenon in Biological Cells

林達德(Ta-Te Lin)

《農業機械學刊》 1卷4期 (1992/12) Pp. 10-21

https://doi.org/10.30062/JAM.199212.0002

摘要

傳統二段式低溫保存生物細胞程序中，最主要之控制因子為冷凍與解凍速率，而相對於程序中之高冷凍速率或低冷凍速率，造成細胞死亡的兩個效應則分別為細胞內凍結與溶液效應。因此，於建立不同種類細胞冷凍保存程序過程中，除透過實驗觀察外，建立數學模式以電腦模擬之方式分析細胞內凍結現象，將有助於深入瞭解其原理，亦可縮短設計冷凍保存程序之實驗流程。本研究中主要探討單細胞滲透壓特性之變異性對於細胞內凍結機率之影響，並将其併入數學模式中，改善現有模式之凍結機率預測能力。生物細胞内凍結現象之機率數學模式主要由兩個基本模式構成，第一個基本模式是以特定細胞之滲透壓特性為模式參數，據以計算各種冷凍過程中細胞内之過冷程度，從而提供第二個基本模式依過冷程度與時間因子計算單一細胞之細胞内凍結機率。細胞族群之凍結機率則再以細胞滲透壓特性之變異性為基礎，利用隨機模擬方法予以預測。電腦模擬結果顯示，細胞滲透壓特性之變異性會影響冷凍過程中細胞内之過冷程度，亦影響其細胞內凍結機率。在高冷凍速率時滲透壓特性變異性對細胞内凍結機率之影響甚小；在低冷凍速率時，較高之水滲透係數Lp(下標 0)值與FVb值有較低之凍結機率；△E值與原始體積較高時會導致較高之凍結機率。將滲透壓特性之變異性併入數學模式，以隨機模擬方式計算細胞族群之細胞内凍結機率，與文獻中旣有之果蠅胚胎和黑麥原生質體實驗數據比較，顯示其較單一細胞之機率模式有較佳之預測值。

關鍵字

細胞凍結 ； 低溫保存 ； 機率模式

並列摘要

In setting up a conventional two-step protocol for the cryopreservation of biological cells, cooling and warming rates are the two control factors affecting the survival rate. At slow cooling rates, the cells become dehydrated and may be damaged by exposure to the high concentration of electrolytes. At fast cooling rates, cells become supercooled as temperature decreases and damage may result from intracellular ice formation (IIF). Mathematical modeling of IIF will not only provide better understanding of the IIF mechanisms but also reduce the extensive experimentation needed to design the cryopreservation protocol. In this study, probability of IIF was first analyzed as affected by the variability of osmometric characteristics between individual cells. Base on an earlier model (Pitt et al., 1992), a stochastic model was developed which incorporated the variability of osmometric parameters and the extent of supercooling during freezing. Monte Carlo simulations were performed to predict the probability of IIP of a population of cells frozen at various cooling rates. Simulation results revealed that variability of osmometric parameters has inconsequential effect on the probability of IIF at fast cooling rate. At slow cooling rates, higher Lp(subscript 0) and FVb value resulted in lower IIF probability whil ehigher △E and initial volume resulted in higher IIF probability. Comparing to experimental IIF data of Drosophila embryos and rye protoplasts, incorporation of the variability of osmometric parameters into the stochastic model yielded better model prediction than using the mean values of model parameters.

並列關鍵字

Intracellular ice formation ； Cryopreservation ； Stochastic modeling