综合多组学数据的肝细胞癌分层策略及进展

肝细胞癌（hepatocellular carcinoma,HCC）是最常见和致命的肝脏恶性肿瘤。这种疾病的治疗一直受到其异质性的阻碍,极大限制了其个性化治疗的进展。因此,将高度异质的HCC分成具有相似特征的分子亚类对其临床治疗有着重要意义。随着高通量技术的不断发展,多种组学数据的关联研究可以加深了解HCC发生背后的生物学机制,也为HCC分层研究打开了新的思路。本文对当前HCC多组学分层策略及其相关研究进行了综述,并总结了当前HCC亚型的多组学特征。     

国家公园类型划分与空间识别——以云南省为例

国家公园是我国推进生态文明建设的重大制度创新,如何科学地对国家公园进行类型划分及空间识别,是国家公园布局和建设中的基础性工作,既有必要性也有紧迫性。本研究以中国国情为基础,参考国际经验,将国家公园划分为荒野导向型、生态优先型、游憩导向型与遗产导向型,构建了一个比较完整的国家公园分类体系。并以自然和人文多样化程度较高的云南为案例,以“双评价”为基础建立了一套指标体系和区划规则,利用人工神经网络建立土地利用演化学习算法,利用融入自适应惯性机制的元胞自动机展开时空模拟,对云南全域进行高分辨率不同类型国家公园的空间辨识,并通过收缩-膨胀原理对识别区域进行比较、修正和优化,进而提出未来云南国家公园布局的综合方案。结果表明: 云南省国家公园主要集中在三江地区与横断山区、滇西以及西南部地区,这3类地区可作为未来国家公园区划与分类保护的重点。本研究所建立的国家公园类型划分和空间识别的一般性可推广的研究范式和工作流程可作为全国应用的参考。     

中药羌活的研究

本文对中药羌活进行了本草考证,概括了羌活的化学成分、药理等方面的研究成果,并对羌活原植物的根进行了显微观察、薄层层析分析等,为正确鉴定药用羌活提供了资料。     

茶树品种‘金牡丹’自然杂交后代遗传鉴定

为了对‘金牡丹’茶树自然杂交后代进行遗传鉴定,利用EST-SSR毛细管电泳荧光标记技术对65个金牡丹自然杂交后代进行研究。结果表明,28对SSR标记共扩增出192个等位片段,平均等位基因数(Na)、平均观测杂合度(Ho)及遗传多态信息量(PIC)分别为6.86、0.540、0.532。单亲基因型已知时的累积排除概率为0.999,说明选择的28对SSR标记位点具有高度的多态性和较高的排除概率,适用于遗传分析和个体的亲子鉴定。15个‘金牡丹’自然杂交后代的遗传鉴定结果表明,MD44、JMD45、JMD47、JMD32为早生绿茶类型;JMD51、JMD53为闽北肉桂乌龙茶类型;MD2、JMD56为闽南‘铁观音’乌龙茶类型;JMD24、JMD26、JMD29、JMD55、JMD59、JMD27、JMD61为‘黄棪’乌龙茶类型。     

越南槐根的抗HIV活性成分研究

为研究越南槐(Sophora tonkinensis)根的抗HIV蛋白酶活性成分及其分子对接机制,采用硅胶、MCI、Sephadex LH-20等多种色谱分离方法,对越南槐根的化学成分进行分离,采用HIV蛋白酶对化合物进行体外抗HIV活性筛选,运用分子对接手段初步探究活性化合物与HIV-1蛋白酶的结合机制。结果表明,从越南槐中共分离得到8个化合物,根据波谱数据分别鉴定为三叶豆紫檀苷(1)、苦参碱(2)、N-acetylnicotinamide (3)、2′-O-甲基腺苷(4)、毛蕊异黄酮苷(5)、玫瑰花苷(6)、环广豆根素(7)、芒柄花苷(8),此外还分离得到塑化剂衍生物邻苯二甲酸二(2-乙基)己酯(9)和邻苯二甲酸二异丁酯(10)。抗HIV蛋白酶活性测试显示化合物1和2的IC50分别为13.2和38.6μg/m L,分子对接表明其与HIV蛋白酶有一定的结合作用。化合物3～5为首次从该植物中分离得到,化合物1和2显示中等的抗HIV蛋白酶活性。     

Chemical Composition and Insecticidal Activity against Tribolium Castaneum of Thapsia garganica L. Seed Essential Oil

Due to the several side effects of synthetic pesticides, including environmental pollution, threats to human health, and the development of pest resistance to insecticides, the use of alternative healthy, available and efficient agents in pest management strategies is necessary. Recently, the use of essential oil obtained from aromatic plants has shown significant potential for insect pest management. For this reason, the essential oil isolated from seeds of Thapsia garganica L. was investigated for the first time for its chemical profile, and its toxicity and repellency effects against Tribolium castaneum adults. Qualitative and quantitative analyses of the chemical composition by gas chromatography coupled to mass spectrometry (GC/MS) revealed the presence of 18 organic volatiles representing 96.8 % of the total constituents. The main compounds were 1,4-dimethylazulene (51.3 %) followed by methyl palmitate (8.2 %), methyl linoleate (6.2 %) and costol (5.1 %). Concerning the repellent effect, results revealed that SEO (Seed Essential Oil) was very repellent towards T. castaneum adults, with 100 % repellency after 2 h of exposure. Furthermore, the essential oil exhibited remarkable contact toxicity against T. castaneum (93.3 % of mortality) at the concentration of 10 % (v/v). The median lethal dose (LD₅₀) of the topical application of the seed essential oil was 4.4 %. These encouraging outcomes suggested that the essential oil from T. garganica seeds could be considered a potent natural alternative to residual persistent and toxic insecticides.     

Quantitative Detection of 15 Serum Bile Acid Metabolic Products by LC/MS/MS in the Diagnosis of Primary Biliary Cholangitis

To determine 15 bile acid metabolic products in human serum by liquid chromatography-tandem mass spectrometry (LC/MS/MS) and value their diagnostic outcome in primary biliary cholangitis (PBC). Serum from 20 healthy controls and 26 patients with PBC were collected and went LC/MS/MS analysis of 15 bile acid metabolic products. The test results were analyzed by bile acid metabolomics, and the potential biomarkers were screened and their diagnostic performance was judged by statistical methods such as principal component and partial least squares discriminant analysis and area under curve (AUC). 8 differential metabolites can be screened out: Deoxycholic acid (DCA), Glycine deoxycholic acid (GDCA), Lithocholic acid (LCA), Glycine ursodeoxycholic acid (GUDCA), Taurolithocholic acid (TLCA), Tauroursodeoxycholic acid (TUDCA), Taurodeoxycholic acid (TDCA), Glycine chenodeoxycholic acid (GCDCA). The performance of the biomarkers was evaluated by the AUC, specificity and sensitivity. In conclusion, DCA, GDCA, LCA, GUDCA, TLCA, TUDCA, TDCA and GCDCA were identified as eight potential biomarkers to distinguish between healthy people and PBC patients by multivariate statistical analysis, which provided reliable experimental basis for clinical practice.     

Antioxidant and Antidiabetic Properties of Extracts from Three Underutilized Food Plants of North East India

Three underutilized leafy vegetables Sarcochlamys pulcherrima (Roxb.) Gaudich (SP), Ipomoea aquatica Forssk. (IA) and Zanthoxylum rhetsa (Roxb.) DC (ZR) were extracted with different solvents viz. 95 % ethyl alcohol, methanol and hot water. The extracts were evaluated for their antioxidant potential via DPPH, ABTS and FRAP assay along with electroanalytical studies using cyclic voltammetry. The antidiabetic potential was determined by recording their α-amylase and α-glucosidase inhibitory assay. The total phenolic content (TPC), total flavonoid content (TFC) and the liquid chromatography-mass spectrometry (LC/MS) based phytochemical profiles of the extracts were also determined. All three extracts of SP exhibited significant antioxidant capacity. The antidiabetic potential of the IA and ZR extracts was found to be higher than or at par with that of standard acarbose. LC/MS studies reveal the presence of hitherto reported antioxidant and antidiabetic compounds like gamma-aminobutyric acid, cinnamic acid, caffeic acid, α-viniferin, piperlonguminine, niacin, kaempferol, etc., in the extracts.     

DNA barcoding of Cymbidium by genome skimming: Call for next-generation nuclear barcodes

Cymbidium is an orchid genus that has undergone rapid radiation and has high ornamental, economic, ecological and cultural importance, but its classification based on morphology is controversial. The plastid genome (plastome), as an extension of plant standard DNA barcodes, has been widely used as a potential molecular marker for identifying recently diverged species or complicated plant groups. In this study, we newly generated 237 plastomes of 50 species (at least two individuals per species) by genome skimming, covering 71.4% of members of the genus Cymbidium. Sequence-based analyses (barcoding gaps and automatic barcode gap discovery) and tree-based analyses (maximum likelihood, Bayesian inference and multirate Poisson tree processes model) were conducted for species identification of Cymbidium. Our work provides a comprehensive DNA barcode reference library for Cymbidium species identification. The results show that compared with standard DNA barcodes (rbcL + matK) as well as the plastid trnH-psbA, the species identification rate of the plastome increased moderately from 58% to 68%. At the same time, we propose an optimized identification strategy for Cymbidium species. The plastome cannot completely resolve the species identification of Cymbidium, the main reasons being incomplete lineage sorting, artificial cultivation, natural hybridization and chloroplast capture. To further explore the potential use of nuclear data in identifying species, the Skmer method was adopted and the identification rate increased to 72%. It appears that nuclear genome data have a vital role in species identification and are expected to be used as next-generation nuclear barcodes.     

Comparison of mechanistic and hybrid modeling approaches for characterization of a CHO cultivation process: Requirements,pitfalls and solution paths

Despite the advantages of mathematical bioprocess modeling, successful model implementation already starts with experimental planning and accordingly can fail at this early stage. For this study, two different modeling approaches (mechanistic and hybrid) based on a four-dimensional antibody-producing CHO fed-batch process are compared. Overall, 33 experiments are performed in the fractional factorial four-dimensional design space and separated into four different complex data partitions subsequently used for model comparison and evaluation. The mechanistic model demonstrates the advantage of prior knowledge (i.e., known equations) to get informative value relatively independently of the utilized data partition. The hybrid approach displayes a higher data dependency but simultaneously yielded a higher accuracy on all data partitions. Furthermore, our results demonstrate that independent of the chosen modeling framework, a smart selection of only four initial experiments can already yield a very good representation of a full design space independent of the chosen modeling structure. Academic and industry researchers are recommended to pay more attention to experimental planning to maximize the process understanding obtained from mathematical modeling.