A 2-D/3-D model-based method to quantify the complexity of microvasculature imaged by in vivo multiphoton microscopy

This paper presents model-based information-theoretic methods to quantify the complexity of tumor microvasculature, taking into account shape, textural, and structural irregularities. The proposed techniques are completely automated, and are applicable to optical slices (3-D) or projection images (2-D). Improvements upon the prior literature include: (i) measuring local (vessel segment) as well as global (entire image) vascular complexity without requiring explicit segmentation or tracing; (ii) focusing on the vessel boundaries in the complexity estimate; and (iii) added robustness to image artifacts common to tumor microvasculature images. Vessels are modeled using a family of super-Gaussian functions that are based on the superquadric modeling primitive common in computer vision. The superquadric generalizes a simple ellipsoid by including shape parameters that allow it to approximate a cylinder with elliptical cross-sections (generalized cylinder). The super-Gaussian is obtained by composing a superquadric with an exponential function giving a form that is similar to a standard Gaussian function but with the ability to produce level sets that approximate generalized cylinders. Importantly, the super-Gaussian is continuous and differentiable so it can be fit to image data using robust non-linear regression. This fitting enables quantification of the intrinsic complexity of vessel data vis-a-vis the super-Gaussian model within a minimum message length (MML) framework. The resulting measures are expressed in units of information (bits). Synthetic and real-data examples are provided to illustrate the proposed measures.     

First clinical evaluation of the CELL-DYN® 3200 haematology analyser

A prototype of the CELL-DYN 3200® haematology analyser was evaluated in a tertiary care hospital laboratory. Precision, effects of sample ageing, linearity, carry-over, and com-parability of cellular blood counts and five-part leucocyte differentiation were determined in accordance with the ICSH guidelines for the evaluation of blood cell analysers; the results were satisfactory for all parameters tested: haemoglobin concentration, RBC, MCV, WBC, platelet count, and counts of neutrophils, lymphocytes, monocytes, and eosinophils. Two-hundred and forty-seven routine blood samples were used for the comparability studies. The cellular blood count results from the CELL-DYN 3200® and the Bayer Diagnostic H-1 systems corresponded closely (correlation coefficient r > 0.96 for all parameters). For 201 samples without an instrument-generated suspect flag the same was true with regard to the dif-ferential parameters, although somewhat lower correlation was observed for monocyte counts (r = 0.88). Comparisons to 400-cell microscopic differentials gave similar results (r > 0.93 for neutrophil, lymphocyte and eosinophil counts). Our results suggest that the CELL-DYN 3200® analyser will serve the needs for automated blood cell counting and differential leucocyte counting in a tertiary care hospital laboratory.     

An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms

Breast cancer is becoming a leading death of women all over the world; clinical experiments demonstrate that early detection and accurate diagnosis can increase the potential of treatment. In order to improve the breast cancer diagnosis precision, this paper presents a novel automated segmentation and classification method for mammograms. We conduct the experiment on both DDSM database and MIAS database, firstly extract the region of interests (ROIs) with chain codes and using the rough set (RS) method to enhance the ROIs, secondly segment the mass region from the location ROIs with an improved vector field convolution (VFC) snake and following extract features from the mass region and its surroundings, and then establish features database with 32 dimensions; finally, these features are used as input to several classification techniques. In our work, the random forest is used and compared with support vector machine (SVM), genetic algorithm support vector machine (GA-SVM), particle swarm optimization support vector machine (PSO-SVM), and decision tree. The effectiveness of our method is evaluated by a comprehensive and objective evaluation system; also, Matthew’s correlation coefficient (MCC) indicator is used. Among the state-of-the-art classifiers, our method achieves the best performance with best accuracy of 97.73 %, and the MCC value reaches 0.8668 and 0.8652 in unique DDSM database and both two databases, respectively. Experimental results prove that the proposed method outperforms the other methods; it could consider applying in CAD systems to assist the physicians for breast cancer diagnosis.     

ECLIA法与ELISA法检测HBV-M大批量标本的实验研究

目的 探讨应用ELISA与ECLIA两种方法检测大批量HBV-M标本的优缺点,了解健康体检人群中HBV携带的模式分布状况.方法 ELISA法用ELISA-STAR采用条形码技术和网络系统,进行HBV-M自动化检测,同时使用ECLIA法对ELISA法检测的阳性结果及灰区标本进行复查、验证,并进行统计学分析.结果 68328例健康体检者检出12种乙肝五项模式,其中HBsAg阳性率3.07％,HBsAb阳性率56.09％.以ECLIA法为标准,ELISA法检测HBsAg存在假阳性,检测HBsAb、HBeAb、HBcAb三抗体有假阴性.两种方法检测HBeAg的结果差别无意义.结论 ELISA法使用ELISA-STAR功能强大、结果稳定、敏感度低,适合大批量标本筛查;而ECLIA法可作为金标准,灵敏度高,更加智能,可对低浓度标本审核验证.两种检测方法互补,确保了检验质量,适合大批量标本操作,值得推广.     

Automated clinical trial eligibility prescreening: increasing the efficiency of patient identification for clinical trials in the emergency department

Objectives (1) To develop an automated eligibility screening (ES) approach for clinical trials in an urban tertiary care pediatric emergency department (ED); (2) to assess the effectiveness of natural language processing (NLP), information extraction (IE), and machine learning (ML) techniques on real-world clinical data and trials.Data and methods We collected eligibility criteria for 13 randomly selected, disease-specific clinical trials actively enrolling patients between January 1, 2010 and August 31, 2012. In parallel, we retrospectively selected data fields including demographics, laboratory data, and clinical notes from the electronic health record (EHR) to represent profiles of all 202795 patients visiting the ED during the same period. Leveraging NLP, IE, and ML technologies, the automated ES algorithms identified patients whose profiles matched the trial criteria to reduce the pool of candidates for staff screening. The performance was validated on both a physician-generated gold standard of trial–patient matches and a reference standard of historical trial–patient enrollment decisions, where workload, mean average precision (MAP), and recall were assessed.Results Compared with the case without automation, the workload with automated ES was reduced by 92% on the gold standard set, with a MAP of 62.9%. The automated ES achieved a 450% increase in trial screening efficiency. The findings on the gold standard set were confirmed by large-scale evaluation on the reference set of trial–patient matches.Discussion and conclusion By exploiting the text of trial criteria and the content of EHRs, we demonstrated that NLP-, IE-, and ML-based automated ES could successfully identify patients for clinical trials.     

Coding for spatial goals in the prelimbic/infralimbic area of the rat frontal cortex

Finding one's way in space requires a distributed neural network to support accurate spatial navigation. In the rat, this network likely includes the hippocampus and its place cells. Although such cells allow the organism to locate itself in the environment, an additional mechanism is required to specify the animal's goal. Here, we show that firing activity of neurons in medial prefrontal cortex (mPFC) reflects the motivational salience of places. We recorded mPFC neurons from rats performing a place navigation task, and found that a substantial proportion of cells in the prelimbic/infralimbic area had place fields. A much smaller proportion of cells with such properties was found in the dorsal anterior cingulate area. Furthermore, the distribution of place fields in prelimbic/infralimbic cells was not homogeneous: goal locations were overrepresented. Because such locations were spatially dissociated from rewards, we suggest that mPFC neurons might be responsible for encoding the rat's goals, a process necessary for path planning.     

Genetic variants within ANRIL (antisense non coding RNA in the INK4 locus) are associated with risk of psoriasis

BackgroundPsoriasis is a systemic inflammatory disease which mostly affects skin. Evidences support the role of autoimmune responses in this disorder. The long non-coding RNA (lncRNA) antisense non coding RNA in the INK4 locus (ANRIL) has been shown to participate in modulation of immune response and in the pathogenesis of immune-related disorders.MethodsWe genotyped four single nucleotide polymorphisms (SNPs) with this lncRNA (rs1333045, rs1333048, rs4977574 and rs10757278) in 286 patients with psoriasis and 300 age-/sex-matched controls to identify the role of ANRIL as a risk locus for psoriasis.ResultsThe C allele of rs1333048 SNP was significantly more prevalent among cases compared with controls (OR (95% CI) = 1.56 (1.23–1.97), adjusted P value = 8.31E−4). The A allele of the rs4977574 had a protective effect against psoriasis (OR (95% CI) = 0.63 (0.49–0.81), adjusted P value = 0.001). The G allele of the rs10757278 conferred risk of psoriasis in the assessed population (OR (95% CI) = 1.9 (1.51–2.4), adjusted P value = 2.18 E−7). The C A G A haplotype (rs1333045, rs1333048, rs4977574 and rs10757278, respectively) was reported to be a protective haplotype against psoriasis (OR (95% CI) = 0.5 (0.35–0.71), adjusted P value = 0.001). The C A G G and T C G G haplotypes conferred risk of psoriasis in the assessed population (OR (95% CI) = 2.37 (1.59–3.54), adjusted P value = 2.4E−4; OR (95% CI) = 5.42 (2.88–10.22), adjusted P value = 1.1E−7, respectively).ConclusionConsequently, ANRIL can be regarded as a risk locus of psoriasis in the assessed population. Future studies are needed to verify whether this contribution is exerted through modulation of immune responses.     

自动体外除颤仪的配置现状及实施研究进展

自动体外除颤仪(automated external defibrillator,AED)是一种便携式的医疗设备,用于院外心脏骤停(out-of-hospital cardiac arrest,OHCA)患者的早期除颤。欧美等发达国家自上世纪90年代实施推广AED以来取得一定成效,但国内居民对其认知水平和普及程度较低。本文通过综述国内外AED的研究现状及存在问题,为我国今后的研究及相关政策制定提供参考。