The effect of mental countermeasures on a novel brain‐based feedback concealed information test

The feedback concealed information test (fCIT) is a novel form of the CIT, providing participants with feedback regarding their memory concealment performance. The fCIT utilizes event‐related potentials (recognition‐P300 and feedback‐related event‐related potentials) and has been shown to provide high efficiency in detecting information concealment. However, it is unclear how well the fCIT performs in the presence of mental countermeasures. To address this question, participants were trained to use countermeasures during fCIT. Results showed that the recognition‐P300 efficiency decreased when participants used countermeasures. However, the efficiencies of feedback‐related negativity and feedback‐P300 were unchanged, with feedback‐P300 still showing a high detection efficiency (AUC = 0.86) during countermeasures. These findings demonstrate the potential of fCIT for subverting countermeasures.     

Software-Automated Implant Detection for Intraoperative 3D Imaging—First Clinical Evaluation on 214 Data Sets

Previous studies have demonstrated a frequent occurrence of screw/K-wire malpositioning during surgical fracture treatment under 2D fluoroscopy and a correspondingly high revision rate as a result of using intraoperative 3D imaging. In order to facilitate and accelerate the diagnosis of implant malpositioning in 3D data sets, this study investigates two versions of an implant detection software for mobile 3D C-arms in terms of their detection performance based on comparison with manual evaluation. The 3D data sets of patients who had received surgical fracture treatment at five anatomical regions were extracted from the research database. First, manual evaluation of the data sets was performed, and the number of implanted implants was assessed. For 25 data sets, the time required by four investigators to adjust each implant was monitored. Subsequently, the evaluation was performed using both software versions based on the following detection parameters: true-positive-rate, false-negative-rate, false-detection-rate and positive predictive value. Furthermore, the causes of false positive and false negative detected implants depending on the anatomical region were investigated. Two hundred fourteen data sets with overall 1767 implants were included. The detection parameters were significantly improved (p<.001) from version 1 to version 2 of the implant detection software. Automatic evaluation required an average of 4.1±0.4 s while manual evaluation was completed in 136.15±72.9 s (p<.001), with a statistically significant difference between experienced and inexperienced users (p=.005). In summary, version 2 of the implant detection software achieved significantly better results. The time saved by using the software could contribute to optimizing the intraoperative workflow.     

人内质网分子伴侣BiP的克隆、表达及其在RA患者血清抗体检测中的作用

以类风湿关节炎(rheumatoid arthritis,RA)患者滑膜组织文库cDNA为模板,用PCR方法扩增得到1965 bp人内质网分子伴侣BiP的全长cDNA,将其克隆入OmicsLinkTM表达载体pReceiver-B01a,构建重组表达质粒pReceiver-B01a-BiP。重组表达质粒导入大肠杆菌BL-21(DE3)菌株中诱导表达目的蛋白,表达产物以Ni+-NTA agarose层析柱纯化。SDS-PAGE和免疫印迹法(Western blot)分析发现,表达产物以可溶性蛋白和包涵体形式共同存在,表达量约占菌体蛋白总量的20%~30%。相对分子质量约为80000,纯度达到电泳级。经免疫印迹法鉴定,获得的BiP重组蛋白可以与RA患者血清反应,检测的抗BiP抗体在RA患者血清中的阳性率为75.4%(49/65),明显高于系统性红斑狼疮(systemic lupus erythe-matosus,SLE)患者14.6%(7/48)、原发性干燥综合征(primary Sj gren’s syndrome,pSS)患者7.3%(4/55)及正常人0%(0/71)(P<0.01)。表明,经原核表达获得的BiP全长蛋白,RA患者血清抗体可以很好结合,有望应用于临床血清学诊断。     

Data mining for signals in spontaneous reporting databases: proceed with caution

PURPOSE: To provide commentary and points of caution to consider before incorporating data mining as a routine component of any Pharmacovigilance program, and to stimulate further research aimed at better defining the predictive value of these new tools as well as their incremental value as an adjunct to traditional methods of post-marketing surveillance. METHODS/RESULTS: Commentary includes review of current data mining methodologies employed and their limitations, caveats to consider in the use of spontaneous reporting databases and caution against over-confidence in the results of data mining. CONCLUSIONS: Future research should focus on more clearly delineating the limitations of the various quantitative approaches as well as the incremental value that they bring to traditional methods of pharmacovigilance.     

Metallic and Metal Oxides Nanoparticles for Sensing Food Pathogens—An Overview of Recent Findings and Future Prospects

Nowadays, special importance is given to quality control and food safety. Food quality currently creates significant problems for the industry and implicitly for consumers and society. The effects materialize in economic losses, alterations of the quality and organoleptic properties of the commercial products, and, last but not least, they constitute risk factors for the consumer’s health. In this context, the development of analytical systems for the rapid determination of the sanitary quality of food products by detecting possible pathogenic microorganisms (such as Escherichia coli or Salmonella due to the important digestive disorders that they can cause in many consumers) is of major importance. Using efficient and environmentally friendly detection systems for identification of various pathogens that modify food matrices and turn them into food waste faster will also improve agri-food quality throughout the food chain. This paper reviews the use of metal nanoparticles used to obtain bio nanosensors for the purpose mentioned above. Metallic nanoparticles (Au, Ag, etc.) and their oxides can be synthesized by several methods, such as chemical, physical, physico-chemical, and biological, each bringing advantages and disadvantages in their use for developing nanosensors. In the “green chemistry” approach, a particular importance is given to the metal nanoparticles obtained by phytosynthesis. This method can lead to the development of good quality nanoparticles, at the same time being able to use secondary metabolites from vegetal wastes, as such providing a circular economy character. Considering these aspects, the use of phytosynthesized nanoparticles in other biosensing applications is also presented as a glimpse of their potential, which should be further explored.