This study examined the post-thaw recovery of Jurkat cells cryopreserved in single osmolyte solutions containing sucrose, glycerol or isoleucine, as well as in a combination of the three osmolytes. Cell response was determined using low temperature Raman Spectroscopy and variation in post-thaw recovery with composition was analyzed using statistical modeling. Post-thaw recovery of Jurkat cells in single osmolyte was low. A combination of the osmolytes displayed a non-linear relationship between composition and post-thaw recovery, suggesting that interactions exist between the different solutes. The post-thaw recovery for an optimized multicomponent solution was comparable to that observed using 10% dimethyl sulfoxide and a cooling rate of 1 °C/min. Statistical modeling was used to characterize the importance of each osmolyte in the combination and test for interactions between osmolytes. Higher concentrations of glycerol increase post-thaw recovery and interactions between sucrose and glycerol, as well as sucrose and isoleucine improve post-thaw recovery. Raman images clearly demonstrated that damaging intracellular ice formation was observed more often in the presence of single osmolytes as well as non-optimized multi-component solution compositions.

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This study examined the post‐thaw recovery of Jurkat cells cryopreserved in three combinations of five osmolytes including trehalose, sucrose, glycerol, mannitol, and creatine. Cellular response was characterized using low‐temperature Raman spectroscopy, and variation of post‐thaw recovery was analyzed using statistical modeling. Combinations of osmolytes displayed distinct trends of post‐thaw recovery, and a nonlinear relationship between compositions and post‐thaw recovery was observed, suggesting interactions not only between different solutes but also between solutes and cells. The post‐thaw recovery for optimized cryoprotectants in different combinations of osmolytes at a cooling rate of 1°C/min was comparable to that measured with 10% dimethyl sulfoxide. Statistical modeling was used to understand the importance of individual osmolytes as well as interactions between osmolytes on post‐thaw recovery. Both higher concentrations of glycerol and certain interactions between sugars and glycerol were found to typically increase the post‐thaw recovery. Raman images showed the influence of osmolytes and combinations of osmolytes on ice crystal shape, which reflected the interactions between osmolytes and water. Differences in the composition also influenced the presence or absence of intracellular ice formation, which could also be detected by Raman. These studies help us understand the modes of action for cryoprotective agents in these osmolyte solutions.

This study presents the influence of control parameters including population (NP) size, mutation factor (F), crossover (Cr), and four types of differential evolution (DE) algorithms including random, best, local-to-best, and local-to-best with self-adaptive (SA) modification for the purpose of optimizing the compositions of dimethylsufloxide (DMSO)-free cryoprotectants. Post-thaw recovery of Jurkat cells cryopreserved with two DMSO-free cryoprotectants at a cooling rate of 1 °C/min displayed a nonlinear, four-dimensional structure with multiple saddle nodes, which was a suitable training model to tune the control parameters and select the most appropriate type of differential evolution algorithm. Self-adaptive modification presented better performance in terms of optimization accuracy and sensitivity of mutation factor and crossover among the four different types of algorithms tested. Specifically, the classical type of differential evolution algorithm exhibited a wide acceptance to mutation factor and crossover. The optimization performance is more sensitive to mutation than crossover and the optimization accuracy is proportional to the population size. Increasing population size also reduces the sensitivity of the algorithm to the value of the mutation factor and crossover. The analysis of optimization accuracy and convergence speed suggests larger population size with F > 0.7 and Cr > 0.3 are well suited for use with cryopreservation optimization purposes. The tuned differential evolution algorithm is validated through finding global maximums of other two DMSO-free cryoprotectant formulation datasets. The results of these studies can be used to help more efficiently determine the optimal composition of multicomponent DMSO-free cryoprotectants in the future.