A comparison of three methods for detecting KRAS mutations in formalin-fixed colorectal cancer specimens.

BACKGROUND: KRAS mutation testing is required to select patients with metastatic colorectal cancer (CRC) to receive anti-epidermal growth factor receptor antibodies, but the optimal KRAS mutation test method is uncertain. METHODS: We conducted a two-site comparison of two commercial KRAS mutation kits - the cobas KRAS Mutation Test and the Qiagen therascreen KRAS Kit - and Sanger sequencing. A panel of 120 CRC specimens was tested with all three methods. The agreement between the cobas test and each of the other methods was assessed. Specimens with discordant results were subjected to quantitative massively parallel pyrosequencing (MPP). DNA blends were tested to determine detection rates at 5% mutant alleles. RESULTS: Reproducibility of the cobas test between sites was 98%. Six mutations were detected by cobas that were not detected by Sanger, and five were confirmed by MPP. The cobas test detected eight mutations which were not detected by the therascreen test, and seven were confirmed by MPP. Detection rates with 5% mutant DNA blends were 100% for the cobas and therascreen tests and 19% for Sanger. CONCLUSION: The cobas test was reproducible between sites, and detected several mutations that were not detected by the therascreen test or Sanger. Sanger sequencing had poor sensitivity for low levels of mutation.

UK consensus project on quality in palliative day services: developing a quality indicator set using the RAND/UCLA appropriateness method

Introduction
Evaluating quality of palliative day services is essential for assessing care across diverse settings, and for monitoring quality improvement approaches.

Aim
To develop a set of quality indicators for assessment of all aspects (structure, process and outcome) of care in palliative day services.

Methods
Using a modified version of the RAND/UCLA appropriateness method (Fitch et al., 2001), a multidisciplinary panel of 16 experts independently completed a survey rating the appropriateness of 182 potential quality indicators previously identified during a systematic evidence review. Panel members then attended a one day, face-to-face meeting where indicators were discussed and subsequently re-rated. Panel members were also asked to rate the feasibility and necessity of measuring each indicator.

Results
71 indicators classified as inappropriate during the survey were removed based on median appropriateness ratings and level of agreement. Following the panel discussions, a further 60 were removed based on appropriateness and feasibility ratings, level of agreement and assessment of necessity. Themes identified during the panel discussion and findings of the evidence review were used to translate the remaining 51 indicators into a final set of 27.

Conclusion
The final indicator set included information on rationale and supporting evidence, methods of assessment, risk adjustment, and recommended performance levels. Further implementation work will test the suitability of this ‘toolkit’ for measurement and benchmarking. The final indicator set provides the basis for standardised assessment of quality across services, including care delivered in community and primary care settings.

Reference

• Fitch K, Bernstein SJ, Aguilar MD, et al. The RAND/UCLA Appropriateness Method User’s Manual. Santa Monica, CA: RAND Corporation; 2001. http://www.rand.org/pubs/monograph_reports/MR1269

A low overhead error confinement method based on application statistical characteristics

Reliability has emerged as a critical design constraint especially in memories. Designers are going to great lengths to guarantee fault free operation of the underlying silicon by adopting redundancy-based techniques, which essentially try to detect and correct every single error. However, such techniques come at a cost of large area, power and performance overheads which making many researchers to doubt their efficiency especially for error resilient systems where 100% accuracy is not always required. In this paper, we present an alternative method focusing on the confinement of the resulting output error induced by any reliability issues. By focusing on memory faults, rather than correcting every single error the proposed method exploits the statistical characteristics of any target application and replaces any erroneous data with the best available estimate of that data. To realize the proposed method a RISC processor is augmented with custom instructions and special-purpose functional units. We apply the method on the proposed enhanced processor by studying the statistical characteristics of the various algorithms involved in a popular multimedia application. Our experimental results show that in contrast to state-of-the-art fault tolerance approaches, we are able to reduce runtime and area overhead by 71.3% and 83.3% respectively.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.