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为探讨斑嘴环企鹅（Spheniscus demersus）雏鸟的生长发育特征，对上海动物园0~7月龄斑嘴环企鹅雏鸟的体质量、体长、喙峰长、脚长和翅长进行测定，并利用Logistic和Gompertz两种非线性数学模型对各项体尺指标进行拟合分析。结果表明：Logistic和Gompertz两种模型的拟合度均较高，拟合系数（r2）均达0.970以上。斑嘴环企鹅的体质量、体长、喙峰长和脚长的生长过程用Logistic模型的拟合效果更佳（r2>0.980），而翅长的生长过程用Gompertz模型效果更佳。斑嘴环企鹅各项体尺指标存在极显著相关性（p

【目的】初步探讨LncRNA HULC对胶质母细胞瘤U87细胞株体内体外生长的作用机制。【方法】实时荧光定量PCR（qRT-PCR）检测胶质母细胞瘤U87细胞HULC过表达组（HULC-over）及其对照组（VEC）和沉默表达组（HULC-siRNA）及其对照组（NC）中HULC表达水平。CCK8增殖实验和克隆形成实验检测U87细胞增殖能力。流式细胞学技术检测U87细胞凋亡能力。小鼠异种原位移植模型按照注射U87细胞对应分为HULC-over组（n=10）和VEC组（n=10）及HULC-siRNA组（n=10）和NC组（n=10），观察各组小鼠生存期。免疫组化检测Ki67的表达。【结果】HULC-over组较VEC组HULC表达量显著升高，HULC-siRNA组较NC组HULC表达量显著降低（均P＜0.01）。CCK8增殖实验显示HULC-over组较VEC组细胞增殖率显著升高；HULC-siRNA组较NC组细胞增殖率显著降低（第2、3、4天，均P＜0.01）。细胞克隆实验显示VEC组和HULC-over组克隆形成率分别为（34.47±1.56）％和（95.4±2.74）％；NC组和HULC-siRNA组克隆形成率分别为（23.83±0.92）％和（10.23±0.61）％，过表达HULC克隆形成率升高，沉默表达HULC克隆形成率降低（均P＜0.01）。细胞凋亡实验显示VEC组和HULC-over组早期凋亡率分别为（3.55±0.56）%和（0.09±0.01）%；NC组和HULC-siRNA组早期凋亡率分别为（2.89±0.67）%和（7.13±0.14）%，过表达HULC细胞早期凋亡率降低，沉默表达HULC细胞早期凋亡率升高（P＜0.01）。小鼠生存期数据表明HULC-over组比VEC组存活时间更短，而HULC-siRNA组比NC组存活时间更长（P＜0.05）。与VEC组相比，Ki67蛋白在HULC-over组中表达上调；与NC组相比，Ki67蛋白在HULC-siRNA组中表达下调（均P＜0.05）。【结论】LncRNA HULC对胶质母细胞瘤U87细胞体内体外生长具有促进作用。

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Copyright of West China Journal of Stomatology is the property of Sichuan University, West China College of Stomatology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

According to the influence of energy consumption of embedded systems to operation time of various embedded systems, this paper took the energy consumption of software from system instruction level to source program level as a consideration. First.it proposed a consumption model for the source program level of energy, by analyzing the related features and instruction consumptions of source statement. Then.it optimized different categories of statements energy consumption of five classical algorithms based on model analysis. Finally.it compared the energy consumption of five groups of classical algorithm before and after optimization. Experiments show that this model reduces energy consumption of the optimized source program by 9.46% ~50.29% .and achieves the purpose of reducing the energy consumption of embedded system software. [ABSTRACT FROM AUTHOR]