Autoantibody microarrays for biomarker discovery

Identification of autoantigens and the detection of autoantibody reactivity are useful in biomarker discovery and for explaining the role of important biochemical pathways in disease. Despite all of their potential advantages, the main challenge to working with autoantibodies is their sensitivity. Nevertheless, proteomics may hold the key to overcoming this limitation by providing the means to multiplex. Clearly, the ability to detect multiple autoantigens using a platform such as a high-density antigen microarray would improve sensitivity and specificity of detection for autoantibody profiling. The aims of this review are to: briefly describe the current status of antigen–autoantibody microarrays; provide examples of their use in biomarker discoveries; address current limitations; and provide examples and strategies to facilitate their implementation in the clinical setting.     

Depth-related changes to density,diversity and structure of benthic megafaunal assemblages in the Fimbul ice shelf region,Weddell Sea,Antarctica

The depth-related patterns in the benthic megafauna of the NE Weddell Sea shelf at the edge of the Fimbul Ice Shelf were investigated at seven sites using towed camera platform photographs. Megafaunal density decreased with depth from 77,939 ha⁻¹ at 245 m to 8,895 ha⁻¹ at 510 m. While diversity was variable, with H′ ranging between 1.34 and 2.28, there were no depth related patterns. Multivariate analyses revealed two distinct assemblages; a shallow assemblage with dense patches of suspension feeders in undisturbed areas and a deep assemblage where these were not present. Disturbance from icebergs explained many observed patterns in faunal distribution. In shallow waters probable effects of disturbance were observed as changes in successional stages; in deeper waters changes in habitat as a result of past disturbance explained faunal distributions. In deeper areas ice ploughing created a mosaic landscape of fine and coarse sediments. Total megafaunal density was highest in areas of coarse sediment (up to 2.9 higher than in finer sediment areas) but diversity was highest in intermediate areas (H′ = 2.35).     

Mesozoic tectono-sedimentary evolution of Rocca Busambra in western Sicily

The Rocca Busambra ridge in western Sicily is a shallow to pelagic Meso-Cenozoic carbonate structural unit of the Sicilian Chain with a variety of tectono-sedimentary features. Palaeofaults, unconformities (buttress unconformity, onlap, downlap), a network of neptunian dykes with several infilling generations, several large hiatuses, different facies and lateral facies changes, and erosional submarine and subaerial surfaces are observed. Detailed fieldwork and structural analyses have indicated the occurrence of fault planes with different orientations. These data, combined with facies studies and physical-stratigraphy analyses, allow for the distinction of different depositional regions. A lateral change from an open-marine carbonate platform with a stepped fault margin (located in the westernmost sector) to a deeper basinal depositional setting in the east, in the context of an upper slope scalloped margin and base-of-slope systems with talus breccias, is envisaged here. Extensional to transtensional tectonic pulses punctuated the sedimentary evolution during Early Toarcian, Late Jurassic, Early Cretaceous, Late Cretaceous, and Early Miocene times. The collected data show that most fault planes have preserved their original orientations throughout the reactivation processes. The reconstructed Meso-Cenozoic tectono-sedimentary evolution is closely related to the late syn-rift and post-rift tectonic evolution of the Tethyan continental margin.     

Systematic analysis of multigene predictors in gastric cancer exploiting gene expression signature

Gastric cancer (GC) is the second most common cause of cancer death worldwide but could be more curable if diagnosed at an earlier stage. At present, the capability to predict the efficaciousness of molecular diagnosis for GC for each patient remains elusive. The purpose of this study was to identify tumor biomarkers through systems analysis of multigene predictors exploiting the available data resource. In this study, we investigated the top 10% overexpressed genes in GC from five data sets of the Oncomine platform, with 265 GC samples versus 174 normal gastric mucosa samples. Sixteen candidate genes were identified as predictors of GC, of which 14 genes were verified through the comparison of expression levels in specimens from normal (chronic gastritis, 21 samples) and GC groups (38 samples). In addition, unique molecular portraits of diffuse adenocarcinoma (DA), intestinal adenocarcinoma (IA), and mixed adenocarcinoma (MA) were studied through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, where DA showed higher extracellular matrix alteration while IA and MA showed higher cell-cycle alteration than other types. We also found that the elevated expressions of genes during GC progression were independent of gene mutations, and high core-binding factor subunit β expression is correlated with a high overall survival rate in GC patients. Our research may provide an efficient clinical diagnosis of GC at an early stage with high accuracy and thus help improve the overall survival rate through early therapeutic interventions.     

Integration of heterologous genes in several yeast species using vectors containing a Hansenula polymorpha-derived rDNA-targeting element

A method that has been successfully used to generate recombinant Hansenula polymorpha strains by transformation with rDNA-targeting vectors was applied in the present study to a range of alternative yeast hosts, using vectors with an H. polymorpha-derived integration sequence. The dimorphic yeast Arxula adeninivorans, which is currently being assessed for heterologous gene expression, was the main focus of the study. As in H. polymorpha, it was possible to co-integrate more than a single plasmid carrying an expressible gene. Additionally, the vectors were examined in two further species, Pichia stipitis and Saccharomyces cerevisiae. Based on these results the design of a 'universal' fungal vector appears to be feasible.     

Nanobiohybrid Material‐Based Bioelectronic Devices

Biomolecules, especially proteins and nucleic acids, have been widely studied to develop biochips for various applications in scientific fields ranging from bioelectronics to stem cell research. However, restrictions exist due to the inherent characteristics of biomolecules, such as instability and the constraint of granting the functionality to the biochip. Introduction of functional nanomaterials, recently being researched and developed, to biomolecules have been widely researched to develop the nanobiohybrid materials because such materials have the potential to enhance and extend the function of biomolecules on a biochip. The potential for applying nanobiohybrid materials is especially high in the field of bioelectronics. Research in bioelectronics is aimed at realizing electronic functions using the inherent properties of biomolecules. To achieve this, various biomolecules possessing unique properties have been combined with novel nanomaterials to develop bioelectronic devices such as highly sensitive electrochemical‐based bioelectronic sensing platforms, logic gates, and biocomputing systems. In this review, recently reported bioelectronic devices based on nanobiohybrid materials are discussed. The authors believe that this review will suggest innovative and creative directions to develop the next generation of multifunctional bioelectronic devices.     

利用分子量阵列平台进行特定序列甲基化分析的方法探讨

目的：探讨利用分子量阵列平台进行特定序列甲基化分析的方法。方法：通过对不同扩增条件和扩增效率及不同条件处理的质谱分析比较了MassArray平台进行甲基化分析的特点。结果：本研究通过与重亚硫酸盐测序结果比较证实,MassArray分子量阵列技术平台能够反映甲基化修饰的真实水平;通过不同条件下PCR扩增效率与甲基化分析的结果,发现扩增效率是制约MassArray分子量阵列技术平台甲基化分析的关键因素,而产物的放置时间和不同的处理没有明显影响甲基化分析。结论：Mas-sArray甲基化分析平台是高效快速检测甲基化修饰的平台,在使用过程中应该根据实际的实验条件,进行合理的质控。     

Nanotechnology-based intelligent drug design for cancer metastasis treatment

Traditional chemotherapy used today at clinics is mainly inherited from the thinking and designs made four decades ago when the Cancer War was declared. The potency of those chemotherapy drugs on in-vitro cancer cells is clearly demonstrated at even nanomolar levels. However, due to their non-specific effects in the body on normal tissues, these drugs cause toxicity, deteriorate patient's life quality, weaken the host immunosurveillance system, and result in an irreversible damage to human's own recovery power. Owing to their unique physical and biological properties, nanotechnology-based chemotherapies seem to have an ability to specifically and safely reach tumor foci with enhanced efficacy and low toxicity. Herein, we comprehensively examine the current nanotechnology-based pharmaceutical platforms and strategies for intelligent design of new nanomedicines based on targeted drug delivery system (TDDS) for cancer metastasis treatment, analyze the pros and cons of nanomedicines versus traditional chemotherapy, and evaluate the importance that nanomaterials can bring in to significantly improve cancer metastasis treatment.