Integrating Industry and National Economic Accounts: First Steps and Future Improvements

The integration of the annual I-O accounts with the GDP-by-industry accounts is the most recent in a series of improvements to the industry accounts provided by the BEA in recent years. BEA prepares two sets of national industry accounts: The I-O accounts, which consist of the benchmark I-O accounts and the annual I-O accounts, and the GDPby- industry accounts. Both the I-O accounts and the GDP-by-industry accounts present measures of gross output, intermediate inputs, and value added by industry. However, in the past, they were inconsistent because of the use of different methodologies, classification frameworks, and source data. The integration of these accounts eliminated these inconsistencies and improved the accuracy of both sets of accounts. The integration of the annual industry accounts represents a major advance in the timeliness, accuracy, and consistency of these accounts, and is a result of significant improvements in BEA's estimating methods. The paper describes the new methodology, and the future steps required to integrate the industry accounts with the NIPAs. The new methodology combines source data between the two industry accounts to improve accuracy; it prepares the newly integrated accounts within an I-O framework that balances and reconciles industry production with commodity usage. Moreover, the new methodology allows the acceleration of the release of the annual I-O accounts by 2 years and for the first time, provides a consistent time series of annual I-O accounts. Three appendices are provided: A description of the probability-based method to rank source data by quality; a description of the new balancing produced for producing the annual I-O accounts; and a description of the computation method used to estimate chaintype price and quantity indexes in the GDP-by-industry accounts.

Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics

Integrative genomics has the potential to uncover relevant loci, as clinical outcome and response to chemotherapies are most likely not due to a single gene (or data type) but rather a complex relationship involving genetic variation, mRNA, DNA methylation, and copy number variation. In addition to this complexity, many complex phenotypes are thought to be controlled by the interplay of multiple genes within the same molecular pathway or gene set (GS). To address these two challenges, we propose an integrative gene set analysis approach and apply this strategy to a cisplatin (CDDP) pharmacogenomics study involving lymphoblastoid cell lines for which genome-wide SNP and mRNA expression data was collected. Application of the integrative GS analysis implicated the role of the RNA binding and cytoskeletal part GSs. The genes LMNB1 and CENPF, within the cytoskeletal part GS, were functionally validated with siRNA knockdown experiments, where the knockdown of LMNB1 and CENPF resulted in CDDP resistance in multiple cancer cell lines. This study demonstrates the utility of an integrative GS analysis strategy for detecting novel genes associated with response to cancer therapies, moving closer to tailored therapy decisions for cancer patients.National Institutes of Health (U.S.) (NIH/NCI GM61388)National Institutes of Health (U.S.) (NIH/NCI CA140879)National Institutes of Health (U.S.) (NIH/NCI GM86689)National Institutes of Health (U.S.) (NIH/NCI CA130828)National Institutes of Health (U.S.) (NIH/NCI CA138461)National Institutes of Health (U.S.) (NIH/NCI CA102701)Mayo Foundation for Medical Education and Researc

Recommendations for Clinical CYP2C9 Genotyping Allele Selection: A Joint Recommendation of the Association for Molecular Pathology and College of American Pathologists

The goals of the Association for Molecular Pathology Pharmacogenomics (PGx) Working Group of the Association for Molecular Pathology Clinical Practice Committee are to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document provides recommendations for a minimum panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories when designing assays for CYP2C9 testing. The Working Group considered the functional impact of the variants, allele frequencies in different populations and ethnicities, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. Our goal is to promote standardization of testing PGx genes and alleles across clinical laboratories. These recommendations are not to be interpreted as restrictive but to provide a reference guide. The current document will focus on CYP2C9 testing that can be applied to all CYP2C9-related medications. A separate recommendation on warfarin PGx testing is being developed to include recommendations on CYP2C9 alleles and additional warfarin sensitivity–associated genes and alleles

2024 pest management guide for grapes in Washington

The Pest Management Guide for Grapes in Washington presents various chemicals and their uses against pest problems in Washington vineyards. While the recommendations are based on eastern Washington conditions, the information may often be applied to similar pest problems found throughout the state. Specific and more detailed information on pests and diseases can be found in the Field Guide for Integrated Pest Management in Pacific Northwest Vineyards (PNW644). Recommendations are suggested guidelines. They are not intended to represent pest control programs. The use of other materials and varying rates and treatments for control of particular pests depends on individual circumstances

Centerscope

Centerscope, formerly Scope, was published by the Boston University Medical Center "to communicate the concern of the Medical Center for the development and maintenance of improved health care in contemporary society.

The Cancer Genomics Resource List 2014

Context.— Genomic sequencing for cancer is offered by commercial for-profit laboratories, independent laboratory networks, and laboratories in academic medical centers and integrated health networks. The variability among the tests has created a complex, confusing environment. Objective.— To address the complexity, the Personalized Health Care (PHC) Committee of the College of American Pathologists proposed the development of a cancer genomics resource list (CGRL). The goal of this resource was to assist the laboratory pathology and clinical oncology communities. Design.— The PHC Committee established a working group in 2012 to address this goal. The group consisted of site-specific experts in cancer genetic sequencing. The group identified current next-generation sequencing (NGS)–based cancer tests and compiled them into a usable resource. The genes were annotated by the working group. The annotation process drew on published knowledge, including public databases and the medical literature. Results.— The compiled list includes NGS panels offered by 19 laboratories or vendors, accompanied by annotations. The list has 611 different genes for which NGS-based mutation testing is offered. Surprisingly, of these 611 genes, 0 genes were listed in every panel, 43 genes were listed in 4 panels, and 54 genes were listed in 3 panels. In addition, tests for 393 genes were offered by only 1 or 2 institutions. Table 1 provides an example of gene mutations offered for breast cancer genomic testing with the annotation as it appears in the CGRL 2014. Conclusions.— The final product, referred to as the Cancer Genomics Resource List 2014, is available as supplemental digital content

Use of the gamma method for self-contained gene-set analysis of SNP data

Gene-set analysis (GSA) evaluates the overall evidence of association between a phenotype and all genotyped single nucleotide polymorphisms (SNPs) in a set of genes, as opposed to testing for association between a phenotype and each SNP individually. We propose using the Gamma Method (GM) to combine gene-level P-values for assessing the significance of GS association. We performed simulations to compare the GM with several other self-contained GSA strategies, including both one-step and two-step GSA approaches, in a variety of scenarios. We denote a ‘one-step' GSA approach to be one in which all SNPs in a GS are used to derive a test of GS association without consideration of gene-level effects, and a ‘two-step' approach to be one in which all genotyped SNPs in a gene are first used to evaluate association of the phenotype with all measured variation in the gene and then the gene-level tests of association are aggregated to assess the GS association with the phenotype. The simulations suggest that, overall, two-step methods provide higher power than one-step approaches and that combining gene-level P-values using the GM with a soft truncation threshold between 0.05 and 0.20 is a powerful approach for conducting GSA, relative to the competing approaches assessed. We also applied all of the considered GSA methods to data from a pharmacogenomic study of cisplatin, and obtained evidence suggesting that the glutathione metabolism GS is associated with cisplatin drug response

Preclinical discovery of candidate genes to guide pharmacogenetics during phase I development: the example of the novel anticancer agent ABT-751

ABT-751, a novel orally available antitubulin agent, is mainly eliminated as inactive glucuronide (ABT-751G) and sulfate (ABT-751S) conjugates. We performed a pharmacogenetic investigation of ABT-751 pharmacokinetics using in-vitro data to guide the selection of genes for genotyping in a phase I trial of ABT-751