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Aim To investigate the effect of microinjection of EX527, a selective SIRT1 antagonist, into the ventrolateral orbital cortex (VLO) on morphine-induced conditioned place preference (CPP), and to explore the role of CREB/BDNF in it. Methods The cannulas were implanted bilaterally in the VLO of rats by brain stereotaxis surgery, and the model of morphine-induced CPP was established. The behavioral experiment consisted of four stages:habituation (d 1), pre-test (d 2-4), conditioning training (d 5-14) and test (d 15). At the stage of conditioning training, EX527 (1 μL, 5 g·L
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Objective:To identify 24 <italic>Rana</italic> species such as <italic>Rana dybowskii</italic> by mitochondrial cytochrome C oxidase subunit I （<italic>CO</italic>Ⅰ） gene-based DNA barcoding and build the neighbour-joining （NJ） tree for hierarchical cluster analysis， so as to provide a basis for the identification and classification of <italic>Rana</italic> species as well as the discovery of new species. Method:<italic>R. dybowskii</italic>， <italic>R. chensinensis</italic>， <italic>R. amurensis</italic>， <italic>R. culaiensi</italic>s， and <italic>R. huanrenesis</italic>， ten for each species， were collected for DNA extraction and polymerase chain reaction （PCR） amplification<italic> </italic>and sequencing. A total of 50 <italic>CO</italic>Ⅰ gene sequences were obtained. Then 163 <italic>CO</italic>Ⅰ gene sequences for 24 species of <italic>Rana</italic> and one <italic>CO</italic>Ⅰ gene sequence for <italic>Pelophylax</italic>，<italic> Odorrana</italic>， <italic>Nidirana</italic>， <italic>Hylarana</italic>， and <italic>Amolops</italic> were harvested from GenBank. After sequence alignment by MEGA X， the parsimony-informative sites of <italic>CO</italic>Ⅰ gene sequences were analyzed and the intraspecific and interspecific genetic distances were calculated， followed by the built of NJ tree and hierarchical cluster analysis. Result:The <italic>CO</italic>Ⅰ gene sequences of 24<italic> Rana</italic> species including <italic>R. dybowskii</italic> were 554 bp in length and there were 210 parsimony-informative sites in total. The intraspecific genetic distance of each species was smaller than 2%. Except that the interspecific genetic distance between <italic>R. sangzhiensis</italic> and <italic>R. zhengi</italic> was 0.004， the genetic distances between the other species ranged from 0.024 to 0.228. <italic>R. sangzhiensis</italic> and <italic>R. zhengi</italic> were clustered into one branch and some <italic>R. dybowskii</italic> and <italic>R. uenoi</italic> into one branch. There were two separate branches for <italic>R. chensinensis</italic> and the other species were all clustered independently. Conclusion:<italic>CO</italic>Ⅰ-based DNA barcoding enabled the identification of 24 species of <italic>Rana</italic> including <italic>R.dybowskii</italic>. The findings supported that <italic>R. sangzhiensis</italic>， <italic>R. zhengi</italic>， <italic>R. coreana</italic>， and <italic>R. kunyuensis</italic> were the same species. One branch of <italic>R. chensinensis </italic>might be one of the four undownloaded species in Ranidae or a new species. The results have demonstrated that <italic>CO</italic>Ⅰ-based DNA barcoding allows not only the identification of 24 species of Rana including <italic>R. dybowskii </italic>but also the classification of ranidae species and the discovery of new species or subspecies.
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Objective: To analyze family-based haplotype frequencies of HLA-A, -B, -C, -DRB1 and -DQB1 genes and their clinical significance. Methods: The data of HLA genotyping in 3568 families undergoing related haploidentical transplantation between 2012 and 2017 at the First Affiliated Hospital of Soochow University were retrospectively evaluated. The HLA genotyping was performed by PCR amplification with sequence-based typing (PCR-SBT) and sequence-specific oligonucleotide probe (PCR-SSOP) methods. The family genetic analysis and haplotype frequencies were also investigated. Results: All the families were divided into 3 groups, including group1 of 1 422 entire families; group2 of 1 310 patients and either of their parents or one of their children; group3 of 836 patients and their HLA≥5/10 matched sibling donors. In the haplotypes with frequencies greater than 0.1% in group1+ group2, the frequency of A*11∶01-B*40∶01-C*03∶04-DRB1*11∶01-DQB1*03∶01, A*02∶07-B*51∶01-C*14∶02-DRB1*09:01-DQB1*03∶03 were significantly different between group1 and group2 (P=0.029, 0.033) . The frequency of A*11∶01-B*46∶01-C*01∶02∶01G-DRB1*09∶01-DQB1*03∶03 was significantly different between group1 and group3 (P=0.035) . The frequency of A*02∶01-B*40∶01-C*07∶02-DRB1*09∶01-DQB1*03∶03 was significantly different between group1 and group2 (P=0.034) , or group1 and group3 (P=0.034) . The frequency of A*24∶02-B*13∶01-C*03∶04-DRB1*12∶02-DQB1*03:01 was significantly different between group2 and group3 (P=0.046) . Conclusion: In this study, we summarize the prevalence of haplotype frequencies in terms of HLA-A, -B, -C, -DRB1 and-DQB1. Based on the database of family haplotype analysis, patients and donor candidates are sorted with matched HLA genotype while unmatched HLA haplotype. Even in patients without entire family information, HLA haplotype analysis assists in choosing the optimal related or unrelated donors.