口腔粘膜中朗格罕氏细胞的研究

朗格罕细胞（ｌａｎｇｅｒｈａｎｓｃｅｌ,ＬＣ）是一种骨髓来源的免疫活性细胞,具有呈递抗原,诱导免疫反应的功能。口腔粘膜的复层鳞状上皮中亦有ＬＣ分布,它们是口腔粘膜防御体系的组成部分。本研究运用ＡＴＰ酶组织化学方法和电镜技术,对２５例人的口腔粘膜标本中的ＬＣ的形态、结构及数量分布进行观察,结果提示,在口腔粘膜的上皮中,ＬＣ主要分布于上皮的基底部,并且趋于环绕结缔组织乳头排列,ＬＣ的数量也因部位不同而有显著差异     

OLFACTORY RESPONSES OF COTTON BOLLWORM,HELICOVERPA ARMIGERA TO SEX PHEROMONE AND PLANT VOLATILE COMPONENTS*

Abstract Electroantennograms (EAGs) were recorded from unmated, laboratory-reared male and female Helicover pa armigera (Lepidoptera:Noctuidae) adults to two sex pheromone components and a range of plant volatile components, some of which are known volatiles from leaves and fruits. The female-produced sex pheromone was not detected by other female moths. The sex pheromone components to which male moths responded previously show to possess biological activity. As for plant volatile components, a large degree of EAG response uniformity between male and female moth was observed. The greatest EAG responses of all plant volatiles tested were elicited by monoenic C-6 alcohol and aldehyde. They are constituents of the “general green-leaf odor” that emanates from most plants. The potential adaptive benefit of selective perception to sex pheromone and green-leaf volatile components is discussed.     

生态旅游资源定量评价指标体系与评价方法——以江苏海滨为例

生态旅游是新世纪最重要的旅游发展方向之一,生态旅游资源的评价有其特殊性.在综合考虑旅游资源条件、生态环境条件、旅游条件与发展潜力的基础上,尝试建立了新的生态旅游资源评价的指标体系.综合运用准主成份、主观经验判断法等方法,基于专家调查的结果,确定了指标体系各因子权重.并以江苏沿海湿地生态旅游资源为例,应用模糊综合评判法对江苏海滨湿地9个生态旅游区的生态旅游资源进行了评价,结果表明,所构建的指标体系具有较好的区分度、较强的普适性和可推广性.     

涎腺腺样囊性癌细胞蛋白激酶C的活性阻抑对其侵袭能力的影响

用蛋白激酶Ｃ（ＰＫＣ） 抑制剂Ｈ７ 作用于人涎腺腺样囊性癌ＳＡＣＣ８３ 系, 利用扫描电镜观察对人羊膜基底膜侵袭能力的影响。癌细胞接种于羊膜基底膜表面４８－ ７２ 小时后, 在扫描电镜下可以观察到对照组癌细胞侵袭现象, 侵袭的细胞伸出丝状伪足且侵入基底膜内, 伪足周围的基底膜断裂和被溶解, 而实验组癌细胞侵袭现象很难发现。细胞附于基底膜表面, 细胞表面较光滑且无明显伪足伸出, 基底膜无明显受损改变。实验结果表明, 降低涎腺腺样囊性癌细胞的ＰＫＣ活性可明显降低其侵袭能力, ＰＫＣ与涎腺腺样囊性癌的侵袭能力有密切的关系     

The RNA-Binding Protein QKI Suppresses Cancer-Associated Aberrant Splicing

Lung cancer is the leading cause of cancer-related death worldwide. Aberrant splicing has been implicated in lung tumorigenesis. However, the functional links between splicing regulation and lung cancer are not well understood. Here we identify the RNA-binding protein QKI as a key regulator of alternative splicing in lung cancer. We show that QKI is frequently down-regulated in lung cancer, and its down-regulation is significantly associated with a poorer prognosis. QKI-5 inhibits the proliferation and transformation of lung cancer cells both in vitro and in vivo. Our results demonstrate that QKI-5 regulates the alternative splicing of NUMB via binding to two RNA elements in its pre-mRNA, which in turn suppresses cell proliferation and prevents the activation of the Notch signaling pathway. We further show that QKI-5 inhibits splicing by selectively competing with a core splicing factor SF1 for binding to the branchpoint sequence. Taken together, our data reveal QKI as a critical regulator of splicing in lung cancer and suggest a novel tumor suppression mechanism involving QKI-mediated regulation of the Notch signaling pathway.     

SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples

Conventionally, overall gene expressions from microarrays are used to infer gene networks, but it is challenging to account splicing isoforms. High-throughput RNA Sequencing has made splice variant profiling practical. However, its true merit in quantifying splicing isoforms and isoform-specific exon expressions is not well explored in inferring gene networks. This study demonstrates SpliceNet, a method to infer isoform-specific co-expression networks from exon-level RNA-Seq data, using large dimensional trace. It goes beyond differentially expressed genes and infers splicing isoform network changes between normal and diseased samples. It eases the sample size bottleneck; evaluations on simulated data and lung cancer-specific ERBB2 and MAPK signaling pathways, with varying number of samples, evince the merit in handling high exon to sample size ratio datasets. Inferred network rewiring of well established Bcl-x and EGFR centered networks from lung adenocarcinoma expression data is in good agreement with literature. Gene level evaluations demonstrate a substantial performance of SpliceNet over canonical correlation analysis, a method that is currently applied to exon level RNA-Seq data. SpliceNet can also be applied to exon array data. SpliceNet is distributed as an R package available at http://www.jjwanglab.org/SpliceNet.     

Food Choice of White-Headed Langurs in Fusui,China

We studied the feeding ecology of white-headed langurs (Trachypithecus leucocephalus) from September 1997 to September 1998 in Fusui Rare and Precious Animal Reserve, SW Guangxi, China. We collected data in the central part of a group of limestone hills where the main population pool of langurs was located. The langurs fed on 50 plant species (belonging to 42 genera from 28 families) out of 164 species in the habitat (belonging to 112 genera from 48 families). Most of the food plant species were not common in the habitat. There are 16 important food species, including 6 key species. White-headed langurs were extremely folivorous, feeding mainly on young leaves (75% of total feeding records) of a broad range of less common plant species, which were in less disturbed areas. Thus, langur groups in high quality habitat had greater access to preferred foods, and the future of langurs in the Reserve may depend on immediate cessation of tree felling.     

c-CSN: Single-cell RNA Sequencing Data Analysis by Conditional Cell-specific Network

The rapid advancement of single-cell technologies has shed new light on the complex mechanisms of cellular heterogeneity. However, compared to bulk RNA sequencing(RNA-seq),single-cell RNA-seq(sc RNA-seq) suffers from higher noise and lower coverage, which brings new computational difficulties. Based on statistical independence, cell-specific network(CSN) is able to quantify the overall associations between genes for each cell, yet suffering from a problem of overestimation related to indirect effects. To overcome this problem, we propose the c-CSN method, which can construct the conditional cell-specific network(CCSN) for each cell. c-CSN method can measure the direct associations between genes by eliminating the indirect associations.c-CSN can be used for cell clustering and dimension reduction on a network basis of single cells.Intuitively, each CCSN can be viewed as the transformation from less ‘‘reliable" gene expression to more ‘‘reliable" gene–gene associations in a cell. Based on CCSN, we further design network flow entropy(NFE) to estimate the differentiation potency of a single cell. A number of sc RNA-seq datasets were used to demonstrate the advantages of our approach. 1) One direct association network is generated for one cell. 2) Most existing sc RNA-seq methods designed for gene expression matrices are also applicable to c-CSN-transformed degree matrices. 3) CCSN-based NFE helps resolving the direction of differentiation trajectories by quantifying the potency of each cell. c-CSN is publicly available at https://github.com/Lin Li-0909/c-CSN.