Comparison between bottom-up and top-down approaches in the estimation of measurement uncertainty.

BACKGROUND: Measurement uncertainty is a metrological concept to quantify the variability of measurement results. There are two approaches to estimate measurement uncertainty. In this study, we sought to provide practical and detailed examples of the two approaches and compare the bottom-up and top-down approaches to estimating measurement uncertainty. METHODS: We estimated measurement uncertainty of the concentration of glucose according to CLSI EP29-A guideline. Two different approaches were used. First, we performed a bottom-up approach. We identified the sources of uncertainty and made an uncertainty budget and assessed the measurement functions. We determined the uncertainties of each element and combined them. Second, we performed a top-down approach using internal quality control (IQC) data for 6 months. Then, we estimated and corrected systematic bias using certified reference material of glucose (NIST SRM 965b). RESULTS: The expanded uncertainties at the low glucose concentration (5.57 mmol/L) by the bottom-up approach and top-down approaches were ±0.18 mmol/L and ±0.17 mmol/L, respectively (all k=2). Those at the high glucose concentration (12.77 mmol/L) by the bottom-up and top-down approaches were ±0.34 mmol/L and ±0.36 mmol/L, respectively (all k=2). CONCLUSIONS: We presented practical and detailed examples for estimating measurement uncertainty by the two approaches. The uncertainties by the bottom-up approach were quite similar to those by the top-down approach. Thus, we demonstrated that the two approaches were approximately equivalent and interchangeable and concluded that clinical laboratories could determine measurement uncertainty by the simpler top-down approach.

Rodent-specific hypoxia response elements enhance PAI-1 expression through HIF-1 or HIF-2 in mouse hepatoma cells.

Plasminogen activator inhibitor-1 (PAI-1) is an important regulator of numerous pathophysiological processes such as inflammation, thrombosis, angiogenesis and tumor metastasis. Its expression is induced by hypoxia at the transcriptional level, via the hypoxia inducible factor-1 (HIF-1) or -2 (HIF-2). In this study, we elucidated the mechanism of transcriptional regulation of mouse PAI-1 gene by hypoxia in mouse hepatoma cells. We searched for hypoxia response elements (HREs) of murine PAI-1 promoter using several molecular biological assays. DNAse I hypersensitivity assay first suggested that PAI-1 gene expression is up-regulated by protein-DNA interactions at the -3.6- and -3-kb upstream regions of the PAI-1 gene transcription start site. An approximately 6.4-kb region of DNA containing the 5'-flanking promoter region of the PAI-1 gene was isolated, mapped, and cloned into reporter gene assay vectors and sequenced. Luciferase reporter gene assay subsequently identified two functional HREs, located around -3.6 kb of the 5'-flanking promoter region of PAI-1 gene that were responsible for the enhancement of luciferase reporter gene activity. Mutation of the HREs in this fragment abolished luciferase reporter gene activity. Finally, in vitro and in vivo protein-DNA interaction assays confirmed binding of the two HREs to HIF-1 or HIF-2 protein. Our results show that two HREs located around -3.6 kb of the 5'-flanking promoter region of the mouse PAI-1 gene function as hypoxia enhancers, which, alongside other regulatory regions, control PAI-1 gene transcription by HIF-1 or HIF-2 under hypoxic environments in mouse hepatoma cells.