Mass spectrometry imaging as a tool for surgical decision‐making

Despite significant advances in image‐guided therapy, surgeons are still too often left with uncertainty when deciding to remove tissue. This binary decision between removing and leaving tissue during surgery implies that the surgeon should be able to distinguish tumor from healthy tissue. In neurosurgery, current image‐guidance approaches such as magnetic resonance imaging (MRI) combined with neuronavigation offer a map as to where the tumor should be, but the only definitive method to characterize the tissue at stake is histopathology. Although extremely valuable information is derived from this gold standard approach, it is limited to very few samples during surgery and is not practically used for the delineation of tumor margins. The development and implementation of faster, comprehensive, and complementary approaches for tissue characterization are required to support surgical decision‐making – an incremental and iterative process with tumor removed in multiple and often minute biopsies. The development of atmospheric pressure ionization sources makes it possible to analyze tissue specimens with little to no sample preparation. Here, we highlight the value of desorption electrospray ionization as one of many available approaches for the analysis of surgical tissue. Twelve surgical samples resected from a patient during surgery were analyzed and diagnosed as glioblastoma tumor or necrotic tissue by standard histopathology, and mass spectrometry results were further correlated to histopathology for critical validation of the approach. The use of a robust statistical approach reiterated results from the qualitative detection of potential biomarkers of these tissue types. The correlation of the mass spectrometry and histopathology results to MRI brings significant insight into tumor presentation that could not only serve to guide tumor resection, but that is also worthy of more detailed studies on our understanding of tumor presentation on MRI. Copyright © 2013 John Wiley & Sons, Ltd.     

Scanning Probe Microscopy beyond Imaging: A General Tool for Quantitative Analysis

A simple, fast and general approach for quantitative analysis of scanning probe microscopy (SPM) images is reported. As a proof of concept it is used to determine with a high degree of precision the value of observables such as 1) the height, 2) the flowing current and 3) the corresponding surface potential (SP) of flat nanostructures such as gold electrodes, organic semiconductor architectures and graphenic sheets. Despite histogram analysis, or frequency count (Fc), being the most common mathematical tool used to analyse SPM images, the analytical approach is still lacking. By using the mathematical relationship between Fc and the collected data, the proposed method allows quantitative information on observable values close to the noise level to be gained. For instance, the thickness of nanostructures deposited on very rough substrates can be quantified, and this makes it possible to distinguish the contribution of an adsorbed nanostructure from that of the underlying substrate. Being non‐numerical, this versatile analytical approach is a useful and general tool for quantitative analysis of the Fc that enables all signals acquired and recorded by an SPM data array to be studied with high precision.     

TargetATPsite: A template‐free method for ATP‐binding sites prediction with residue evolution image sparse representation and classifier ensemble

Understanding the interactions between proteins and ligands is critical for protein function annotations and drug discovery. We report a new sequence‐based template‐free predictor (TargetATPsite) to identify the Adenosine‐5′‐triphosphate (ATP) binding sites with machine‐learning approaches. Two steps are implemented in TargetATPsite: binding residues and pockets predictions, respectively. To predict the binding residues, a novel image sparse representation technique is proposed to encode residue evolution information treated as the input features. An ensemble classifier constructed based on support vector machines (SVM) from multiple random under‐samplings is used as the prediction model, which is effective for dealing with imbalance phenomenon between the positive and negative training samples. Compared with the existing ATP‐specific sequence‐based predictors, TargetATPsite is featured by the second step of possessing the capability of further identifying the binding pockets from the predicted binding residues through a spatial clustering algorithm. Experimental results on three benchmark datasets demonstrate the efficacy of TargetATPsite. © 2013 Wiley Periodicals, Inc.     

Liquid crystal parameters through image analysis

A technique which combines image analysis and polarising optical microscope (POM) is a useful tool for the physical investigation of discotic liquid crystals, such as hexabutoxytriphenylene and hexahexyloxytriphenylene. This investigation includes the phase transitions, optical properties and order parameter as a function of temperature. Textures of discotic liquid crystals are captured as a function of temperature using POM. These microscopic textures are analysed using MATLAB software to compute statistical parameters, Legendre moments, optical parameters and order parameters of discotic liquid crystal samples. Compared with other techniques in the literature, the proposed methodology is a reliable and very simple technique for the physical investigation of liquid crystals.     

Optical properties of a mesogen by image analysis

An image analysis technique in conjunction with polarising optical microscopy (POM) is proposed for assessment of the thermo-optical properties of homogeneously aligned chiral ester liquid crystals of the type ((S)-(-)-2-methylbutyl 4′-(4″-n-alkanoyloxybenzoyloxy) biphenyl-4-carboxylates, where n?=?16 or 18. Chiral ester textures are recorded as a function of temperature using POM provided with a hot-stage and a high-resolution colour camera. Temperature-dependent optical parameters, or thermo-optical properties such as optical transmission, degree of polarisation, absorption coefficient and birefringence are computed for chiral esters by analysing the texture of samples using MATLAB software. This is a simple experimental technique for observing how the optical parameters of liquid crystals change with temperature.     

基于Gabor小波变换的ICA火灾图像纹理识别算法

针对火灾图像纹理识别问题,提出了基于Gabor小波变换的ICA火灾图像纹理识别算法,并根据火灾图像纹理识别特点进行了优化。首先用不同尺度和方向的Gabor滤波器对待识别图像滤波,得到其特征图像,然后将特征图像转化成特征向量作为ICA的输入,得到基矢量子空间,再将测试图像经过Gabor滤波器的特征向量投影到ICA子空间中得到系数向量作为目标识别特征,最后用支持向量机进行识别。通过与Gabor滤波器法和ICA方法的对比实验,表明该算法可以在火灾纹理图像的识别率上比传统方法提高5%以上,为火灾图像识别提供了一种新思路。     

Tween-80–n-Butanol–Diesel–Water Microemulsion System—A Class of Alternative Diesel Fuel

Tween-80–n–butanol–diesel–water microemulsion systems with various surfactant:cosurfactant (S:C) ratio have been reported as a class of alternative diesel fuel from their phase behavior, clouding phenomena, conductivity, turbidity, and inflammation studies. Temperature induced clouding of microemulsion containing 2% brine at an S:C ratio of 1:1 from a suitable turbid zone has been examined to see the stability of the diesel–water microemulsion systems. Regression models have been proposed to understand the impact of various components of the microemulsion on their cloud point (CP) values. Conductivity of the microemulsions at various S:C ratio increases with the volume of brine having two cut points depicting the presence of three microheterogenous phases within the system, whereas turbidity shows a linear increase. Dye-probed investigation of water-rich and oil-rich zones of the microemulsions indicates the involvement of a dynamic mass transfer process within the various zones. The intensities of flames produced during burning of the microemulsions with various O:E:W weight percentages selected from the isotropic regions of the phase diagrams have been estimated using MATLAB image processing method and the impacts of various components on the fuel use of the microemulsions have been analyzed.     

Dynamic Visualization of Free Radicals at Single Oxygen Bubbles using Chemiluminescence

The generation of free radicals is a key process in the formation and the collapse of the bubbles in water, however, the direct and dynamic observation of the radicals in this process at single bubbles has never been achieved. Here, the hydroxyl (OH^.) and oxygen (O₂^.−) radicals at single oxygen bubbles are continuously traced using chemiluminescence (CL), in which these radicals at the bubble react with the surrounding luminol in the solution emitting the light. Varied increase trends of luminescence are observed in the generation of a bubble, floating, short parking at the water/air interface and the final explosion, revealing the complexity in the distribution of radicals at the bubble unprecedentedly. Despite more radicals are observed at the bubble generated at a deep position under the water for the stabilization, almost the same amount of radicals are included in the bubbles that is independent on the water pressure during the production of the bubble. This rich information collected from the dynamic study of bubbles illustrates the complicated generation and distribution process of radicals at the bubbles, and will facilitate the understanding of the function about the bubbles.     

利用智能手机测定补铁药物中的铁含量*

为进一步提升图像比色法测定补铁药物中铁含量的准确性及普适性,考察了拍摄环境对结果的影响,确定了适用于图像比色分析的定量参数,比较使用不同容器来盛装溶液所获得的比色结果,在最优条件下测定了实际样品中铁的含量及加标回收率。结果显示,获得可靠数据的关键是将标准溶液、待测液以及空白溶液拍摄在同一张图片上;由溶液图像R值换算的吸光度值与浓度具有最佳的线性关系;分析以比色皿、试管、点滴板为容器获得的溶液图片,都能得到适合于定量比色分析的数据;测定的加标回收率大于95%。该方法操作简便,测定结果准确,可在各种条件下的高中化学实验室中开展。     

An evaluation method based on absolute difference to validate the performance of SBNUC algorithms

Scene-based non-uniformity correction (SBNUC) algorithms are an important part of infrared image processing; however, SBNUC algorithms usually cause two defects: (1) ghosting artifacts and (2) over-correction. In this paper, we use the absolute difference based on guided image filter (AD-GF) method to validate the performance of SBNUC algorithms. We obtain a self-separation source using the improved guided image filter to process the input image, and use the self-separation source to obtain the space-high-frequency parts of the input image and the corrected image. Finally, we use the absolute difference between the two space-high-frequency parts as the evaluation result. Based on experimental results, the AD-GF method has better robustness and can validate the performance of SBNUC algorithms even if ghosting artifacts or over-correction occur. Also the AD-GF method can measure how SBNUC algorithms perform in the time domain, it’s an effective evaluation method for SBNUC algorithm.