整合组织学图像信息增强空间转录组细胞聚类的分辨率

【目的】增加空间转录组基因表达的空间分辨率以提升遗传发育与疾病研究中的细胞谱系和类型变化的精度,提供更精细的分子表型信息。【方法】通过图像分割实现空间转录组点阵的细胞空间分布模拟,使用线性插值方法重构超分辨率基因空间表达,并利用图聚类方法揭示组织中细胞分布的空间偏好性。【结果】将新方法SpaGMM在小鼠后脑10X Visium数据集上进行检验,可以精确识别小鼠脑神经空间结构域。通过与几种空间转录组聚类的常用方法进行比较,结果显示SpaGMM的聚类结果更加符合组织学区域的注释,这些区域具有大量标记基因的空间表达支持。SpaGMM还可以从小鼠小脑区域中区分出浦肯野细胞(Purkinje cell)和伯格曼胶质细胞(Bergmann glial cell)所对应的组织区域,发现不同细胞层中存在互补的基因表达模式。【结论】SpaGMM可以通过提高点阵的空间分辨率揭示组织结构域的精细结构。

双自编码结合变分贝叶斯的单细胞RNA-Seq聚类

近年来单细胞RNA测序(scRNA-seq)技术的快速发展使得在单个细胞水平上研究组织器官的异质性成为可能。针对单细胞RNA测序数据中准确鉴定细胞类型问题,提出一种新的基于双自编码结合变分贝叶斯高斯混合模型的聚类方法,称之为sc-VBDAE。首先通过对抗自编码网络的编码和解码过程重构数据,然后使用经典自编码对数据进行降维,获得低维且有效的数据。最后使用变分贝叶斯高斯混合模型对细胞进行聚类,并可视化聚类结果。在10个scRNA-seq数据上的实验结果表明,该方法在6个数据集上ARI指标均优于其它方法,在数据集Biase和Klein上ARI指标值达到0.90及以上。

基于DAE的单细胞RNA测序数据聚类研究

传统数据降维方法处理单细胞RNA测序数据存在特征提取能力较差、聚类精度较低等问题,有必要引入深度学习方法以提高对复杂数据特征的提取能力。在对数据不进行任何人工筛选的条件下,利用DAE提取表达能力更强的数据特征,分别以K⁃means和DBSCAN聚类作为DAE的顶层设置形成DAE+K⁃means和DAE+DBSCAN组合模型,将这两种深度学习组合模型在Deng数据集上与传统聚类模型SC3进行对比。与SC3的0.73聚类精度相比,DAE+K⁃means和DAE+DBSCAN的聚类精度分别达到0.93和0.97,分别提高了0.2和0.24。实验结果表明,DAE在单细胞聚类领域具有广阔的应用前景。

高原低氧环境下红细胞增多和血液粘度间关系的研究

目的 :观察高原低氧环境下人体红细胞增多和血液粘度间的关系。方法 :对进入高原不同时间人群进行血液流变学 (红细胞压积、血液粘度、红细胞变形性和聚集性以及供氧指数等 )检测和分析。结果 :①红细胞压积和红细胞变形性随进住高原时间的延长而显著升高 ;②血液粘度在进住高原的早期明显升高 ,后期恢复正常 ;③红细胞的聚集性在进住高原的早期显著升高 ,后期则下降 ;④组织供氧指数在进住高原的早期明显降低 ,而后期恢复正常。结论 :在高原低氧环境下 ,人体血液粘度不随红细胞压积增高按比例升高 ,红细胞变形性增强和红细胞聚集性下降可能抑制了红细胞压积增高所引起的血液粘度的过度升高 。

Legalon-SIL downregulates HCV core and NS5A in human hepatocytes expressing full-length HCV

AIM: To determine the effect of Legalon-SIL (LS) on hepatitis C virus (HCV) core and NS5A expression and on heme oxygenase-1 (HMOX-1) and its transcriptional regulators in human hepatoma cells expressing full length HCV genotype 1b. METHODS: CON1 cells were treated with 50 μmol/L or 200 μmol/L LS. Cells were harvested after 2, 6 and 24 h. HCV RNA and protein levels were determined by quantitative real-time polymerase chain reaction and Western blotting, respectively. RESULTS: HCV RNA (core and NS5A regions) wasdecreased after 6 h with LS 200 μmol/L (P < 0.05). Both 50 and 200 μmol/L LS decreased HCV RNA levels [core region (by 55% and 88%, respectively) and NS5A region (by 62% and 87%, respectively) after 24 h compared with vehicle (dimethyl sulphoxide) control (P < 0.01). Similarly HCV core and NS5A protein were decreased (by 85%, P < 0.01 and by 65%, P < 0.05, respectively) by LS 200 μmol/L. Bach1 and HMOX-1 RNA were also downregulated by LS treatment (P < 0.01), while Nrf2 protein was increased (P < 0.05).CONCLUSION: Our results demonstrate that treatment with LS downregulates HCV core and NS5A expression in CON1 cells which express full length HCV genotype 1b, and suggests that LS may prove to be a valuable alternative or adjunctive therapy for the treatment of HCV infection.

Toxicity and Accumulation of Selenite in Four Microalgae

The toxicity and bioaccumulation of selenite in four microalgae, Spirulina platensis, Dunaliella salina, Dunaliella bardawill and Phaeodactylum tricornutum cultured in the presence of selenite were investigated. Lower concentrations of selenite were generally nontoxic and frequently stimulated algal growth, while higher concentrations of selenite inhibited algal growth. Selenite was more toxic to D. salina and D. bardawill than to S. platensis and P. tricornutum . All algae cultured in selenite were able to incorporate Se to different degrees, which depended on algal species. The distributions of selenite among intracellular macromolecular compounds were different among algal species: most of the selenite was associated with proteins in S. platensis, D. salina and D. bardawill , while most of the selenite was associated with lipids in P. tricornutum , which reflected the physiological differences among the algae. These observations suggest that algae are able to accumulate selenite and bind it with intracellular macromolecular compounds when exposed to high concentration of selenite. This may represent a form of storage or detoxification of selenite by the algae.

CYTOTOXICITY AND GENOTOXICITY OF POLYETHYLENIMINE AND NICKEL CHLORIDE IN RED SEA BREAM (Pagrosomus major) FIN CELL LINE RSBF

A continuous marine fish cell line RSBF (i.e. Red Sea Bream Fin) was utilized to screen the cytotoxicity and genotoxicity of polyethylenimine (PEI) and nickel chloride (NiCl 2) in this study on the deleterious effects of aquatic genotoxins on fish. At the 0.01 to 1 μg/ml concentration tested, PEI had acute toxicity to the treated RSBF cells (IC 50 =1.12, 0.92, 0.88 and 0.64 μg/ml PEI for time 0 h, 24 h, 48 h and 72 h after treatment, respectively) and markedly inhibited their proliferation in a dose dependent manner. At the 0.001 to 5 μmol/L concentration tested, NiCl 2 posed no acute toxicity but significantly stimulated their growth (107%-214% of control). Random amplified polymorphic DNA (RAPD) technique was used to detect the genotoxic effects of PEI and NiCl 2 by comparing the RAPD banding patterns of the control and treated cells. RAPD analysis indicated that at the concentrations tested, PEI was more genotoxic than NiCl 2 to RSBF cells; that there was a slight dose dependent response in the genotoxic effect of PEI but not NiCl 2; and that RAPD technique might provide a sensitive, non specific genotoxic endpoint. And the potent cytotoxicity and genotoxicity of PEI on fish cells showed that we should be cautious in utilizing it as gene vector in fish gene transfer and human gene therapy.

SQoE KQIs Anomaly Detection in Cellular Networks: Fast Online Detection Framework with Hourglass Clustering

The explosive growth of data volume in mobile networks makes fast online diagnose a pressing search problem. In this paper, an object-oriented detection framework with a two-step clustering, named as Hourglass Clustering, is given. Where three object parameters are chosen as Synthetical Quality of Experience（SQo E） Key Quality Indicators（KQIs） to reflect accessibility, integrality, and maintainability of networks. Then, we choose represented Key Performance Indicators（r KPIs） as cause parameters with correlation analysis. For these two kinds of parameters, a hybrid algorithm combining the self-organizing map（SOM） and

Influences of sea ice on eastern Bering Sea phytoplankton

The influence of sea ice on the species composition and cell density of phytoplankton was investigated in the eastern Bering Sea in spring 2008. Diatoms, particularly pennate diatoms, dominated the phytoplankton community. The dominant species were Grammonema islandica （Grunow in Van Heurck） Hasle, Fragilariopsis cylindrus （Grunow） Krieger, F. oceanica （Cleve） Hasle, Navicula vanhoeffenii Gran, Thalassiosira antarctica Comber, T. gravida Cleve, T. nordenskioeldii Cleve, and T. rotula Meunier. Phytoplankton cell densities varied from 0.08× 10^4 to 428.8× 10^4 cells/L, with an average of 30.3× 10^4 cells/L. Using cluster analysis, phytoplankton were grouped into three assemblages defined by ice-forming conditions： open wate.r, ice edge, and sea ice assemblages. In spring, when the sea ice melts, the phytoplankton dispersed from the sea ice to the ice edge and even into open waters. Thus, these phytoplankton in the sea ice may serve as a “seed bank” for phytoplankton population succession in the subarctic ecosystem. Moreover, historical studies combined with these results suggest that the sizes of diatom species have become smaller, shifting from microplankton to nannoplankton-dominated communities.