A Comparative Study of Different Methodologies for Fault Diagnosis in Multivariate Quality Control

Different methodologies for fault diagnosis in multivariate quality control have been proposed in recent years. These methods work in the space of the original measured variables and have performed reasonably well when there is a reduced number of mildly correlated quality and/or process variables with a well-conditioned covariance matrix. These approaches have been introduced by emphasizing their positive or negative virtues, generally on an individual basis, so it is not clear for the practitioner the best method to be used. This paper provides a comprehensive study of the performance of diverse methodological approaches when tested on a large number of distinct simulated scenarios. Our primary aim is to highlight key weaknesses and strengths in these methods as well as clarifying their relationships and the requirements for their implementation in practice.Vidal Puig, S.; Ferrer, A. (2014). A Comparative Study of Different Methodologies for Fault Diagnosis in Multivariate Quality Control. Communications in Statistics - Simulation and Computation. 43(5):986-1005. doi:10.1080/03610918.2012.720745S9861005435Arteaga, F., & Ferrer, A. (2010). How to simulate normal data sets with the desired correlation structure. Chemometrics and Intelligent Laboratory Systems, 101(1), 38-42. doi:10.1016/j.chemolab.2009.12.003Doganaksoy, N., Faltin, F. W., & Tucker, W. T. (1991). Identification of out of control quality characteristics in a multivariate manufacturing environment. Communications in Statistics - Theory and Methods, 20(9), 2775-2790. doi:10.1080/03610929108830667Fuchs, C., & Benjamini, Y. (1994). Multivariate Profile Charts for Statistical Process Control. Technometrics, 36(2), 182-195. doi:10.1080/00401706.1994.10485765Hawkins, D. M. (1991). Multivariate Quality Control Based on Regression-Adiusted Variables. Technometrics, 33(1), 61-75. doi:10.1080/00401706.1991.10484770Editorial Board. (2007). Computational Statistics & Data Analysis, 51(8), iii-v. doi:10.1016/s0167-9473(07)00125-9Hayter, A. J., & Tsui, K.-L. (1994). Identification and Quantification in Multivariate Quality Control Problems. Journal of Quality Technology, 26(3), 197-208. doi:10.1080/00224065.1994.11979526HOCHBERG, Y. (1988). A sharper Bonferroni procedure for multiple tests of significance. Biometrika, 75(4), 800-802. doi:10.1093/biomet/75.4.800HOMMEL, G. (1988). A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika, 75(2), 383-386. doi:10.1093/biomet/75.2.383Kourti, T., & MacGregor, J. F. (1996). Multivariate SPC Methods for Process and Product Monitoring. Journal of Quality Technology, 28(4), 409-428. doi:10.1080/00224065.1996.11979699Li, J., Jin, J., & Shi, J. (2008). Causation-BasedT2Decomposition for Multivariate Process Monitoring and Diagnosis. Journal of Quality Technology, 40(1), 46-58. doi:10.1080/00224065.2008.11917712Mason, R. L., Tracy, N. D., & Young, J. C. (1995). Decomposition ofT2 for Multivariate Control Chart Interpretation. Journal of Quality Technology, 27(2), 99-108. doi:10.1080/00224065.1995.11979573Mason, R. L., Tracy, N. D., & Young, J. C. (1997). A Practical Approach for Interpreting Multivariate T2 Control Chart Signals. Journal of Quality Technology, 29(4), 396-406. doi:10.1080/00224065.1997.11979791Murphy, B. J. (1987). Selecting Out of Control Variables With the T 2 Multivariate Quality Control Procedure. The Statistician, 36(5), 571. doi:10.2307/2348668Rencher, A. C. (1993). The Contribution of Individual Variables to Hotelling’s T 2 , Wilks’ Λ, and R 2. Biometrics, 49(2), 479. doi:10.2307/2532560Roy, J. (1958). Step-Down Procedure in Multivariate Analysis. The Annals of Mathematical Statistics, 29(4), 1177-1187. doi:10.1214/aoms/1177706449Runger, G. C., Alt, F. B., & Montgomery, D. C. (1996). Contributors to a multivariate statistical process control chart signal. Communications in Statistics - Theory and Methods, 25(10), 2203-2213. doi:10.1080/03610929608831832Sankoh, A. J., Huque, M. F., & Dubey, S. D. (1997). Some comments on frequently used multiple endpoint adjustment methods in clinical trials. Statistics in Medicine, 16(22), 2529-2542. doi:10.1002/(sici)1097-0258(19971130)16:223.0.co;2-jTukey, J. W., Ciminera, J. L., & Heyse, J. F. (1985). Testing the Statistical Certainty of a Response to Increasing Doses of a Drug. Biometrics, 41(1), 295. doi:10.2307/253066

Photoswitchable diacylglycerols enable optical control of protein kinase C.

Increased levels of the second messenger lipid diacylglycerol (DAG) induce downstream signaling events including the translocation of C1-domain-containing proteins toward the plasma membrane. Here, we introduce three light-sensitive DAGs, termed PhoDAGs, which feature a photoswitchable acyl chain. The PhoDAGs are inactive in the dark and promote the translocation of proteins that feature C1 domains toward the plasma membrane upon a flash of UV-A light. This effect is quickly reversed after the termination of photostimulation or by irradiation with blue light, permitting the generation of oscillation patterns. Both protein kinase C and Munc13 can thus be put under optical control. PhoDAGs control vesicle release in excitable cells, such as mouse pancreatic islets and hippocampal neurons, and modulate synaptic transmission in Caenorhabditis elegans. As such, the PhoDAGs afford an unprecedented degree of spatiotemporal control and are broadly applicable tools to study DAG signaling

Rituximab in B-Cell Hematologic Malignancies: A Review of 20 Years of Clinical Experience

Rituximab is a human/murine, chimeric anti-CD20 monoclonal antibody with established efficacy, and a favorable and well-defined safety profile in patients with various CD20-expressing lymphoid malignancies, including indolent and aggressive forms of B-cell non-Hodgkin lymphoma. Since its first approval 20 years ago, intravenously administered rituximab has revolutionized the treatment of B-cell malignancies and has become a standard component of care for follicular lymphoma, diffuse large B-cell lymphoma, chronic lymphocytic leukemia, and mantle cell lymphoma. For all of these diseases, clinical trials have demonstrated that rituximab not only prolongs the time to disease progression but also extends overall survival. Efficacy benefits have also been shown in patients with marginal zone lymphoma and in more aggressive diseases such as Burkitt lymphoma. Although the proven clinical efficacy and success of rituximab has led to the development of other anti-CD20 monoclonal antibodies in recent years (e.g., obinutuzumab, ofatumumab, veltuzumab, and ocrelizumab), rituximab is likely to maintain a position within the therapeutic armamentarium because it is well established with a long history of successful clinical use. Furthermore, a subcutaneous formulation of the drug has been approved both in the EU and in the USA for the treatment of B-cell malignancies. Using the wealth of data published on rituximab during the last two decades, we review the preclinical development of rituximab and the clinical experience gained in the treatment of hematologic B-cell malignancies, with a focus on the well-established intravenous route of administration. This article is a companion paper to A. Davies, et al., which is also published in this issue

AAV-mediated delivery of an anti-BACE1 VHH alleviates pathology in an Alzheimer's disease model

Single domain antibodies (VHHs) are potentially disruptive therapeutics, with important biological value for treatment of several diseases, including neurological disorders. However, VHHs have not been widely used in the central nervous system (CNS), largely because of their restricted blood–brain barrier (BBB) penetration. Here, we propose a gene transfer strategy based on BBB-crossing adeno-associated virus (AAV)-based vectors to deliver VHH directly into the CNS. As a proof-of-concept, we explored the potential of AAV-delivered VHH to inhibit BACE1, a well-characterized target in Alzheimer’s disease. First, we generated a panel of VHHs targeting BACE1, one of which, VHH-B9, shows high selectivity for BACE1 and efficacy in lowering BACE1 activity in vitro. We further demonstrate that a single systemic dose of AAV-VHH-B9 produces positive long-term (12 months plus) effects on amyloid load, neuroinflammation, synaptic function, and cognitive performance, in the AppNL-G-F Alzheimer’s mouse model. These results constitute a novel therapeutic approach for neurodegenerative diseases, which is applicable to a range of CNS disease targets