Search PubMed⌕ Search

PubMed · 9390912

Quality assurance.

Abstract

Every pulmonary function laboratory should develop and implement a quality assurance program to minimize various technical sources of variation. This article has discussed six major components. First, the education and training of the technologists in the pulmonary function laboratory is probably the most important factor in obtaining accurate and reproducible results. A college-level education with an emphasis on math and science is recommended. After an appropriate training program, continued evaluation and feedback are important. Second, instrument maintenance should be performed on a scheduled basis to reduce or prevent instrument malfunctions. Corrective maintenance, which is usually unscheduled, should be performed by knowledgeable individuals and any repairs should be documented. Third, a procedure manual is very important to any successful quality assurance program. It should contain a broad range of information including administrative issues, quality-control procedures, stepwise instructions on test performance, and infection-control policies and procedures. Fourth, the procedures should be performed using published guidelines to help minimize the effects of the many variables. Fifth, a method to quality control each test procedure should be developed. The specific method(s) will vary according to the type of instrumentation and the manufacturer. Finally, the well-run quality assurance program must properly analyze and store the data collected. Sound statistical methods should be applied and various logs and lists should be developed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J Wanger. 1997. Quality assurance.. https://pubmed.ncbi.nlm.nih.gov/9390912/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗