The ability of the Millon Clinical Multiaxial Inventory--Third Edition to detect malingering.

This study investigated the ability of the Millon Clinical Multiaxial Inventory--Third Edition (MCMI-III) to discriminate students malingering psychopathology (n=106) from bona fide psychiatric inpatients (n=202). Students were randomly assigned to a fake-bad or an honest-responding condition. Analyses investigated the ability of the modifier indices to discriminate fake-bad group participants from the psychiatric inpatients. Scale X raw cutoff score >178 yielded a positive predictive power (PPP) of 0.0, a negative predictive power (NPP) of 63.1, and a hit rate of 63.1%. Optimal cutoff scores were developed. Scale X Base Rate (BR) >84 provided a PPP of 55.6, an NPP of 72.1, and a hit rate of 65.2%. Scale Y BR     

基于J2ME的移动网络泡泡堂游戏设计与仿真

介绍了基于J2ME技术开发的手机泡泡堂游戏框架与文件结构。采用状态机、对象池、多线程、地图绘制等技术,设计了游戏场景、道具与关键代码,重点阐述了手机游戏地图绘制技术和游戏角色的产生与回收,给出了通信消息接口设计与网络连接方法,并进行了服务器仿真运行测试。系统具有较高的可移植性,可在主流手机平台中运行。     

MALDI-TOF MS: an upcoming tool for rapid detection of antibiotic resistance in microorganisms

MALDI-TOF MS profiling for microorganism detection has already been demonstrated in the 1990s, but has evolved to the first-line identification method in many laboratories just during the past five years. While this application of MALDI-TOF MS has proven its broad applicability, accuracy, robustness, and cost-effectiveness it is of particular interest to expand the capabilities of the mass spectrometric platform. Resistance detection is the most desirable further application of MALDI-TOF MS in microbiology, but maybe also the most challenging. Different approaches have been published regarding diverse antibiotic drugs and distinct microorganism classes. The current review shall give an overview about the developments of the recent years and their potential to get transformed in clinical useful assays in the future.     

Proteomics in aortic aneurysm – What have we learnt so far?

Aortic aneurysm is a deceptively indolent disease that can cause severe complications such as aortic rupture and dissection. In the normal aorta, vascular smooth muscle cells within the medial layer produce and sustain the extracellular matrix (ECM) that provides structural support but also retains soluble growth factors and regulates their distribution. Although the ECM is an obvious target to identify molecular processes leading to structural failure within the vessel wall, an in-depth proteomics analysis of this important sub-proteome has not been performed. Most proteomics analyses of the vasculature to date used homogenized tissue devoid of spatial information. In such homogenates, quantitative proteomics comparisons are hampered by the heterogeneity of clinical samples (i.e. cellular composition) and the dynamic range limitations stemming from highly abundant cellular proteins. An unbiased proteomics discovery approach targeting the ECM instead of the cellular proteome may decipher the complex, multivalent signals that are presented to cells during aortic remodelling. A better understanding of the ECM in healthy and diseased vessels will provide important pathogenic insights and has potential to reveal novel biomarkers.     

AptaCDSS-E: A classifier ensemble-based clinical decision support system for cardiovascular disease level prediction

Conventional clinical decision support systems are generally based on a single classifier or a simple combination of these models, showing moderate performance. In this paper, we propose a classifier ensemble-based method for supporting the diagnosis of cardiovascular disease (CVD) based on aptamer chips. This AptaCDSS-E system overcomes conventional performance limitations by utilizing ensembles of different classifiers. Recent surveys show that CVD is one of the leading causes of death and that significant life savings can be achieved if precise diagnosis can be made. For CVD diagnosis, our system combines a set of four different classifiers with ensembles. Support vector machines and neural networks are adopted as base classifiers. Decision trees and Bayesian networks are also adopted to augment the system. Four aptamer-based biochip data sets including CVD data containing 66 samples were used to train and test the system. Three other supplementary data sets are used to alleviate data insufficiency. We investigated the effectiveness of the ensemble-based system with several different aggregation approaches by comparing the results with single classifier-based models. The prediction performance of the AptaCDSS-E system was assessed with a cross-validation test. The experimental results show that our system achieves high diagnosis accuracy (>94%) and comparably small prediction difference intervals (<6%), proving its usefulness in the clinical decision process of disease diagnosis. Additionally, 10 possible biomarkers are found for further investigation.     

Trends in psychotherapy process research: Samples, measures, researchers, and classic publications.

Psychotherapy studies published in the Journal of Counseling Psychology (JCP) and the Journal of Consulting and Clinical Psychology (JCCP) between 1978 and 1992 were examined. Differences were found between the 2 journals. JCP published mostly process, outcome, and analog research, whereas JCCP published mostly outcome research. Most process and process-outcome studies across journals were of individual, brief therapy. Across the years, more diversity was evident in samples used in process research in terms of student status, gender, and race of clients and therapists. Three content areas were prominent in the process measures and classic studies: therapist techniques, therapist influence, and facilitative conditions. Lists are provided of the frequently used measures, most productive authors, and classic studies in process research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

移动网络手机实时监控系统的设计与实现

通过分析动力环境实时监控系统的实际需求,结合移动网络、J2ME、Java媒体框架等技术,提出了一个基于移动网络的手机实时监控系统的设计方案.涵盖了图像监控和数字监控两条通道,实现了视频监控、监控数据实时查询、告警和控制命令等功能.针对图像监控通道中高实时性的要求,提出了双缓冲多线程图像捕捉、自缓冲输入流机制、双播放器播放模式等多个创新方法对系统进行优化.最后结合系统在动力环境监控系统中应用案例,表明了系统的可行性和可靠性,且系统具有较高的性能.     

多维力传感器设计的评价准则与优化设计研究

在建立多维力传感器精度与刚度的数学模型的基础上，分别导出对传感器的精度与刚度进行评价的准则；提出多维力传感器优化设计的基本方法，并应用到实际的传感器设计中求解传感器的最优结构参数。     

Collection of daily patient reported outcomes is feasible and demonstrates differential patient experience in chronic kidney disease

Introduction: Patient reported outcomes (PROs) are a critical metric documenting the impact of disease and treatment from the patient's perspective. A variety of generic and disease specific PRO measures (PROMs) are used in chronic kidney disease (CKD) but studies are primarily cross‐sectional. None of the available PROMs are designed for frequent iterative application. Methods: An online PROM for daily use in dialysis and CKD 4/5 patients was developed. The custom website utilised visual analogue scales to capture 6 PROs (general well being (GWB), pain, sleep, breathing, energy, and appetite). Outcomes of interest were uptake, response rates, intermodality variation, and change in PRO corresponding to predefined events. Findings: Forty‐three patients submitted at least once and 34 submitted beyond 30 days. Median follow‐up was 247 days, 64% male, age 62 ± 12 years. In individuals submitting for >30 days, dialysis patients had significantly worse median scores compared to CKD for sleep (47[32–80], 97[76–99], P = 0.003), appetite (66[50–96], 97[88–100], P = 0.008), energy (47[40–89], 84[67–96], P = 0.031), and GWB (63[49–94], 93[71–98], P = 0.026). Patients demonstrated a variety of stable bandwidths of response, deviations from this were associated with specific events e.g., acute admission, vascular procedures, disturbed fluid status, and dialysis start. Discussion: We successfully introduced an online, patient acceptable, iterative PROM that discriminates symptom burden, cross‐sectionally, and longitudinally. Further work will prospectively examine the predictive power of changes in PRO and more rigorously investigate the potential use of these methods to optimise patient care.