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The morphology of Spirulina during cultivation is susceptible to external interferences, but the morphogenesis mechanism is still unclear. Here the proteomic changes of linear Spirulina and spiral Spirulina were comparatively investigated via isobaric tag for relative and absolute quantitation (iTRAQ). Totally 165 and 167 differences in proteins expression were screened out from the TJSD2/TJSD3 and TJBC4-1/TJBC4-2 groups, respectively. Gene ontology and metabolic pathway analysis of differences in proteins expression uncovered the metabolic pathways (photosynthesis, carbon fixation, sugar metabolism) that were significantly enriched with the proteins correlated with Spirulina morphogenesis. The results of differences in proteins expression in metabolic pathway were verified by quantitative real-time PCR. We also built a putative model of Spirulina morphogenesis mechanism and thought multiple metabolic pathways interact and take part in Spirulina morphogenesis.

Introduction: Published data regarding the association between solute carrier family 30, member 8 (SLC30A8) rs13266634 polymorphism and type 2 diabetes mellitus (T2DM) and impaired glucose regulation (IGR) risks in Chinese population are in-consistent. The purpose of this meta-analysis was to evaluate the association between SLC30A8 rs13266634 and T2DM/IGR in a Chinese population. Material and Methods: Three English (PubMed, Embase, and Web of Science) and three Chinese databases (Wanfang, CNKI, and CBMD database) were used for searching articles from January 2005 to January 2018. Odds ratio (OR) and 95% confidence interval (95%CI) were calculated with the random-effect model. Trial sequential analysis was also utilized. Results: Twenty-eight case-control studies with 25,912 cases and 26,975 controls were included for SLC30A8 and T2DM. Pooled risk allele C frequency for rs13266634 was 60.6% (95%CI: 59.2-62.0%) in the T2DM group and 54.8% (95%CI: 53.2-56.4%) in the control group which had estimated OR of 1.23 (95%CI: 1.17-1.28). Individuals who carried major homozygous CC and heterozygous CT genotype were at 1.51 and 1.23 times higher risk of T2DM, respectively, than those carrying minor homozygous TT. The most appropriate genetic analysis model was the co-dominant model based on comparison of OR1, OR2 and OR3. Five articles that involved 4,627 cases and 6,166 controls were included for SLC30A8 and IGR. However, no association was found between SLC30A8 rs13266634 and IGR (C vs. T, OR = 1.13, 95%CI: 0.98-1.30, p = 0.082). TSA revealed that the pooled sample sizes of T2DM exceeded the estimated required information size but not the IGR. Conclusion: The present meta-analysis demonstrated that SLC30A8 rs13266634 was a potential risk factor for T2DM, and more studies should be performed to confirm the association between rs13266634 polymorphism and IGR.