The use of ionisation constants of amino acids for protein signal analysis within the resonant recognition model--application to proteases

Biological functions of proteins and their active 3D structures are determined by the linear sequences of amino acids. The resonant recognition model (RRM) is a physico-mathematical model developed for structure/function analysis of protein and DNA sequences. Here, we are comparing results of the RRM analysis [1,2] of protease proteins using the electron-ion interaction potential (EIIP) and ionisation constant (IC) of amino acids. The results obtained reveal that the IC parameter can be successfully used to determine the characteristic patterns of different functional protease subgroups.     

Visualizing the internal structure of polyethylene glycol-impregnated wood by digital breast tomosynthesis

This study proposes digital breast tomosynthesis (DBT) as a low-tube-voltage method for imaging wood artifacts treated with polyethylene glycol (PEG). In case of general clinical X-ray Computed Tomography (X-CT), PEG-impregnated wood images typically suffer from low contrast between the PEG and the tree-ring. Because X-CT uses high-tube-voltage X-rays that have high energy, they are transmitted regardless of the X-ray absorption difference of the substance, and therefore, it is not suitable for imaging PEG-impregnated wood. Mammography uses low-tube-voltage X-rays, and therefore, it is suitable for delineating substances with small X-ray absorption differences. However, although mammography can produce high-contrast images of wood, it cannot distinguish three-dimensional (3D) structures such as tree rings, because those are projection images. DBT is a type of mammography used to enhance contrast using low-tube voltage, and it enables imaging 3D structures by exposure X-rays to objects several times changing the exposure angle, and it can obtain quasi-computed tomography. Therefore, we believe that by applying DBT to dendroarchaeology, it would be possible to obtain high-contrast, high-resolution images in the visualization of the internal structure of wood.In this study, we used clinical X-CT, mammography, and DBT to obtain images of wood after PEG impregnation, and we evaluated the internal structure of the wood and the visibility of annual rings. We obtained DBT images as a tomogram with a thickness of 1 mm, which eliminated the distortion of tree rings in the sagittal direction and duplication of the PEG and the tree-ring. Further, tree-rings were easily visualized without a noticeable blur, and the DBT contrast was improved compared to clinical X-CT contrast because DBT was performed at low voltage. Important wooden artifacts excavated from ruins were preserved by PEG. Therefore, this method can be expected to become a very useful tool for dendroarchaeology when used as a complementary tool for microfocus X-CT.     

数字化骨科理念辅助椎弓根置钉在寰枢椎不稳中的临床应用

目的:探讨3D打印辅助置钉技术用于寰枢椎不稳椎弓根置钉的安全性及准确性。方法:收集2013年1月到2015年1月西安交通大学第一附属医院收治的寰枢椎不稳病例,术前采用3D打印技术构建个体化3D打印模型,在模型上模拟置钉,获取最佳置钉点、置钉角度等个体化置钉数据,并于术中辅助椎弓根螺钉置入。通过CT扫描评价置钉准确性,测量术前、术后患者寰齿间隙判断寰枢椎复位情况,测量颈延角评价脊髓压迫改善情况,并采用日本骨科学会(JOA)评分判断患者脊髓功能改善情况。术后定期随访观察固定效果、稳定性、神经损伤等手术并发症的发生情况。结果:13例患者均采用3D打印辅助置钉技术进行内固定治疗,手术顺利,术中及术后无血管、神经损伤等并发症,复位及内固定效果满意。共置入椎弓根螺钉31枚,其中29枚完全在椎弓根内,置钉准确率为93.5%。寰枢椎较术前明显复位,术后寰齿间隙、颈延角和JOA评分较术前明显改善,差异具有统计学意义(P0.05)。结论:3D打印技术辅助上颈椎椎弓根置钉的准确性及安全性均较高。     

Changes in sexual signals are greater than changes in ecological traits in a dichromatic group of fishes

Understanding the mechanisms by which phenotypic divergence occurs is central to speciation research. These mechanisms can be revealed by measuring differences in traits that are subject to different selection pressures; greater influence of different types of selection can be inferred from greater divergence in associated traits. Here, we address the potential roles of natural and sexual selection in promoting phenotypic divergence between species of snubnose darters by comparing differences in body shape, an ecologically relevant trait, and male color, a sexual signal. Body shape was measured using geometric morphometrics, and male color was measured using digital photography and visual system‐dependent color values. Differences in male color are larger than differences in body shape across eight allopatric, phylogenetically independent species pairs. While this does not exclude the action of divergent natural selection, our results suggest a relatively more important role for sexual selection in promoting recent divergence in darters. Variation in the relative differences between male color and body shape across species pairs reflects the continuous nature of speciation mechanisms, ranging from ecological speciation to speciation by sexual selection alone.     

Conventional digital cameras as a tool for assessing leaf area index and biomass for cereal breeding

Affordable and easy-to-use methods for assessing biomass and leaf area index （LAI） would be of interest in most breeding programs. Here, we describe the evaluation of a protocol for photographic sampling and image analysis aimed at providing low-labor yet robust indicators of biomass and LAI. In this trial, two genotypes of triticale, two of bread wheat, and four of tritordeum were studied. At six dates during the growing cycle, biomass and LAI were measured destructively, and digital photography was taken on the same dates. Several vegetation indices were calculated from each image. The results showed that repeatable and consistent values of the indices were obtained in consecutive photographic samplings on the same plots. The photographic indices were highly correlated with the destructive measure-ments, though the magnitude of the correlation was lower after anthesis. This work shows that photographic assess-ment of biomass and LAI can be fast, affordable, have good repeatability, and can be used under bright and overcast skies. A practical vegetation index derived from pictures is the fraction of green pixels over the total pixels of the image, and as it shows good correlations with all biomass variables, is the most robust to lighting conditions and has easy interpretation.     

Content-based histopathology image retrieval using CometCloud

Background

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance.

Results

The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers.

Conclusions

In this paper, we present a set of newly developed CBIR algorithms and validate them using two different pathology applications, which are regularly evaluated in the practice of pathology. Comparative experimental results demonstrate excellent performance throughout the course of a set of systematic studies. Additionally, we present and evaluate a framework to enable the execution of these algorithms across distributed resources. We show how parallel searching of content-wise similar images in the dataset significantly reduces the overall computational time to ensure the practical utility of the proposed CBIR algorithms.     

Impact of variance components on reliability of absolute quantification using digital PCR

Background

Digital polymerase chain reaction (dPCR) is an increasingly popular technology for detecting and quantifying target nucleic acids. Its advertised strength is high precision absolute quantification without needing reference curves. The standard data analytic approach follows a seemingly straightforward theoretical framework but ignores sources of variation in the data generating process. These stem from both technical and biological factors, where we distinguish features that are 1) hard-wired in the equipment, 2) user-dependent and 3) provided by manufacturers but may be adapted by the user. The impact of the corresponding variance components on the accuracy and precision of target concentration estimators presented in the literature is studied through simulation.

Results

We reveal how system-specific technical factors influence accuracy as well as precision of concentration estimates. We find that a well-chosen sample dilution level and modifiable settings such as the fluorescence cut-off for target copy detection have a substantial impact on reliability and can be adapted to the sample analysed in ways that matter. User-dependent technical variation, including pipette inaccuracy and specific sources of sample heterogeneity, leads to a steep increase in uncertainty of estimated concentrations. Users can discover this through replicate experiments and derived variance estimation. Finally, the detection performance can be improved by optimizing the fluorescence intensity cut point as suboptimal thresholds reduce the accuracy of concentration estimates considerably.

Conclusions

Like any other technology, dPCR is subject to variation induced by natural perturbations, systematic settings as well as user-dependent protocols. Corresponding uncertainty may be controlled with an adapted experimental design. Our findings point to modifiable key sources of uncertainty that form an important starting point for the development of guidelines on dPCR design and data analysis with correct precision bounds. Besides clever choices of sample dilution levels, experiment-specific tuning of machine settings can greatly improve results. Well-chosen data-driven fluorescence intensity thresholds in particular result in major improvements in target presence detection. We call on manufacturers to provide sufficiently detailed output data that allows users to maximize the potential of the method in their setting and obtain high precision and accuracy for their experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-283) contains supplementary material, which is available to authorized users.     

Quantification of epigenetic biomarkers: an evaluation of established and emerging methods for DNA methylation analysis

Background

DNA methylation is an important epigenetic mechanism in several human diseases, most notably cancer. The quantitative analysis of DNA methylation patterns has the potential to serve as diagnostic and prognostic biomarkers, however, there is currently a lack of consensus regarding the optimal methodologies to quantify methylation status. To address this issue we compared five analytical methods: (i) MethyLight qPCR, (ii) MethyLight digital PCR (dPCR), methylation-sensitive and -dependent restriction enzyme (MSRE/MDRE) digestion followed by (iii) qPCR or (iv) dPCR, and (v) bisulfite amplicon next generation sequencing (NGS). The techniques were evaluated for linearity, accuracy and precision.

Results

MethyLight qPCR displayed the best linearity across the range of tested samples. Observed methylation measured by MethyLight- and MSRE/MDRE-qPCR and -dPCR were not significantly different to expected values whilst bisulfite amplicon NGS analysis over-estimated methylation content. Bisulfite amplicon NGS showed good precision, whilst the lower precision of qPCR and dPCR analysis precluded discrimination of differences of < 25% in methylation status. A novel dPCR MethyLight assay is also described as a potential method for absolute quantification that simultaneously measures both sense and antisense DNA strands following bisulfite treatment.

Conclusions

Our findings comprise a comprehensive benchmark for the quantitative accuracy of key methods for methylation analysis and demonstrate their applicability to the quantification of circulating tumour DNA biomarkers by using sample concentrations that are representative of typical clinical isolates.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1174) contains supplementary material, which is available to authorized users.