Pull-Down of Metalloproteins in Their Native States by Using Desthiobiotin-Based Probes

One-third of all proteins are estimated to require metals for structural stability and/or catalytic activity. Desthiobiotin probes containing metal binding groups can be used to capture metalloproteins with exposed active-site metals under mild conditions so as to prevent changes in metallation state. The proof-of-concept was demonstrated with carbonic anhydrase (CA), an open active site, Zn²⁺-containing protein. CA was targeted by using sulfonamide derivatives. Linkers of various lengths and structures were screened to determine the optimal structure for capture of the native protein. The optimized probes could selectively pull down CA from red blood cell lysate and other protein mixtures. Pull-down of differently metallated CAs was also investigated.     

Statistical analysis of subthreshold leakage current for VLSI circuits

We develop a method to estimate the variation of leakage current due to both intra-die and inter-die gate length process variability. We derive an analytical expression to estimate the probability density function (PDF) of the leakage current for stacked devices found in CMOS gates. These distributions of individual gate leakage currents are then combined to obtain the mean and variance of the leakage current for an entire circuit. We also present an approach to account for both the inter- and intra-die gate length variations to ensure that the circuit leakage PDF correctly models both types of variation. The proposed methods were implemented and tested on a number of benchmark circuits. Comparison to Monte Carlo simulation validates the accuracy of the proposed method and demonstrates the efficiency of the proposed analysis method. Comparison with traditional deterministic leakage current analysis demonstrates the need for statistical methods for leakage current analysis.     

Neutrophil attractant protein-1 and monocyte chemoattractant protein-1 in human serum. Effects of intravenous lipopolysaccharide on free attractants, specific IgG autoantibodies and immune complexes

We recently found that normal human sera contain IgG antibodies against two chemoattractants, neutrophil attractant protein-1 (NAP-1/IL-8) and monocyte chemoattractant protein-1 (MCP-1), as well as immune complexes of these proteins. Intravenously administered LPS was reported to cause a sharp rise in serum NAP-1 concentration. Our study was designed to determine if LPS also caused an increase in MCP-1 and to measure associated changes in concentrations of antibody and immune complex. LPS caused a rise to peak within 2 to 3 h in serum concentrations of free NAP-1 and MCP-1, followed by an almost equally rapid fall toward base-line levels by about 5 h postinjection. MCP-1 concentration in sera from the 11 subjects rose to a peak of 330 +/- 52 pM. The peak value for NAP-1 was 80 +/- 11 pM. In 10 of the 11 subjects, free IgG autoantibody to MCP-1 decreased from a mean pre-LPS value of 1820 +/- 660 pM to a mean low of 53% of the respective initial values. Corresponding data for IgG anti-NAP-1 were a pre-LPS concentration of 216 +/- 7 pM, which decreased to a mean low of 44% of the respective initial values. The finding in some subjects of a rapid rise in free antibody after the nadir suggests the possibility of acute regulation of autoantibody secretion rates. Although the results suggested that LPS-induced chemoattractant combined with free antibody, serum concentrations of MCP-1-IgG or NAP-1-IgG did not increase, which points to an as yet unknown mechanism for trapping and elimination of the immune complexes.     

Can predicate-argument structures be used for contextual opinion retrieval from blogs?

We present the results of our investigation on the use of predicate-argument structures for contextual opinion retrieval. The use of predicate-argument structure for opinion retrieval is a novel approach that exploits the grammatical derivation of sentences to show contextual and subjective relevance. We do not use frequency of certain keywords as it is usually done in keyword-based opinion retrieval approaches. Rather, our novel solution is based on frequency of contextually relevant and subjective sentences. We use a linear relevance model that leverages semantic similarities among predicate-argument structures of sentences. Thus, this paper presents the evaluation results of the linear relevance model. The model does a linear combination of a popular relevance model, our proposed transformed terms similarity model, and the absolute value of a sentence subjectivity scoring scheme. The predicate-argument structures are derived from the grammatical derivations of natural language query topics and the well formed sentences from blog documents. The derived predicate-argument structures are then semantically compared to compute an opinion relevance score. Our scoring technique uses the highest frequency of semantically related predicate-argument structures enriched with the total subjectivity score from sentences. Evaluation and experimental results show that predicate-argument structures can indeed be used for contextual opinion retrieval as it improves performance of opinion retrieval task by 15% over the popular TREC baselines.     

Prediction of the crack condition of highway pavements using machine learning models

Departments of Transportation regularly evaluate the condition of pavements through visual inspections, nondestructive evaluations, image recognition models and learning algorithms. The above methodologies, though efficient, have drawn attention due to their subjective errors, uncertainties, noise effects and overfitting. To improve on the outcomes of the shallow learning models already used in pavement crack prediction, this paper reports on an investigation of the use of recursive partitioning and artificial neural networks (ANN; deep learning frameworks) in predicting the crack rating of pavements. Explanatory variables such as the average daily traffic and truck factor, roadway functional class, asphalt thickness, and pavement condition time series data are employed in the model formulation. Overall, it is observed that the recursive partitioning (regression tree – R² > 0.8 and classification tree – R² > 0.6) and ANN (continuous response – R² > 0.8 and categorical response – R² > 0.6) are compelling machine learning models for the prediction of the crack ratings based on their goodness-of-fit statistics, mean absolute deviation (MAD < 0.4) and the root mean square errors (RMSE between 0.30 and 0.65).     

A review of U.S. Army Corps of Engineers airborne coastal mapping in the Great Lakes

The U.S. Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) collected its first airborne coastal mapping data on the Great Lakes in 1995. Since then, the JALBTCX has collected nearly 5 billion elevation and depth measurements and created over 2000 geographic information system (GIS) products for the shorelines of the Great Lakes. With improvements in airborne coastal mapping technology and the introduction of regional management for the USACE, surveys expanded into the regional scale, multi-sensor National Coastal Mapping Program (NCMP). The NCMP was initiated in 2004 to produce recurrent, regional, high-resolution light detection and ranging (lidar) elevation data and hyperspectral and aerial imagery to support regional sediment management, regulatory functions, flood damage reduction, asset management, emergency operations, and environmental stewardship. The JALBTCX is a collaboration among the USACE, the U.S. Naval Oceanographic Office (NAVOCEANO), and the National Oceanic and Atmospheric Administration (NOAA). The partners have worked together on airborne coastal mapping and charting since the late 1980s with the goal of advancing airborne lidar bathymetry and associated technologies. The collaboration has fielded three generations of airborne sensors and has transferred this technology to the commercial sector, supporting an expanding market for bathymetric lidar. The purpose of this paper is to provide an overview of the history of USACE survey efforts in the Great Lakes (1995–2012), an in-depth review of the resulting imagery and lidar data products, and new information product developments and applications to support environmental and coastal engineering throughout the Great Lakes region.     

硬件组合技术在数据库查询优化中的应用

查询优化技术是关系数据库成功运作的关键技术之一。随着现代数据库规模不断扩大到以十亿字节(GB)计量,对能够处理如此巨大的数据信息的系统的需求也随之而来。找到一种高效的信息提取方法对于使研发过程更快、更容易地进行是十分必要的。文章介绍了一种将与或图和数字逻辑电路技术应用于SQL查询优化,得到数据库中有效信息的技术方法。该方法中把与或图作为一种中间数据结构,用来描述布尔值域上的查询集合的子集;数字逻辑电路则用来表示二进制数集合上的各项逻辑运算功能的一种实现方式。该文同时给出了相关实验结果,实验表明这是一个十分有效的方法。     

Applications of microcontinuum fluid mechanics

A comprehensive review of the existing theories of microcontinuum fluid mechanics has been presented by the authors in a previous paper. In this paper the published applications of these microfluid theories to real and ideal flow problems have been reviewed briefly and these short reviews are presented in tabular form for easy reference.     

Cancer conferences. Can they be improved?

In a previous study, we showed that overexpression of cyclin D, a G1 cyclin, is frequently associated with keratinocyte carcinogenesis as an early event. Another G1 cyclin, cyclin E, was recently suggested to be a prognostic marker for breast cancer. In order to evaluate the role of cyclin E in human keratinocyte carcinogenesis, we analysed the expression of cyclin E by immunohistochemistry in normal skin, seborrheic keratosis (SK), keratoacanthoma (KA), actinic keratosis (AK), Bowen's disease (BD), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). Positive cells were seen rarely in normal epidermis, in 9 of 20 cases of SK, in 5 of 6 cases of KA, in 9 of 13 cases of AK and in all 27 cases of BD. Some of the cases of AK and BD had positive cells in the superficial epidermis, where atypicality is less obvious. In contrast, positive cells were seen in 4 of 25 cases of SCC and none of 15 cases of BCC. These results suggest that expression of cyclin E plays a role in the formation of benign and premalignant keratinocytic tumors, whereas down-regulation of cyclin E expression may be involved in carcinogenesis in human keratinocytes.