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To analyze the biological effects of radiation, it is important that the conditions of in vitro experiments match closely with those of in vivo experiments. In this study, we constructed an irradiation system to conduct irradiation experiments under conditions similar to those of in vivo experiments. The Dongnam Institute of Radiological and Medial Sciences has a gamma irradiator including 60Co radioisotope for research purposes and accreditation for standard calibration of the ion chamber. The temperature of the water phantom was maintained the same as that of the normal human body, and the physical dosimetry was carried out accurately using the ion chamber with traceability. We report the measurement of lateral profiles, depth profiles, and absorbed dose rate in water, Dw, at the irradiation location of the blood samples using a farmer-type ion chamber. We simulated the source, collimator, irradiator, phantom, and extra structure of the gamma irradiation system using the Monte Carlo code and compared the simulated and the experimental results. The experimentally and theoretically evaluated dose rates were 0.2975 ± 0.0055 Gymin–1 (at coverage factor k = 2) and 0.2978 ± 0.0052 Gymin–1 (at coverage factor k = 2) at source-to-surface distance of 100 cm and 5 gcm–2 depth in the water phantom, respectively. Blood irradiation will be conducted in vitro, under conditions similar to in vivo conditions, to provide the dose-response curve based on dosimetry with traceability.

Background Cardiometabolic risk (CMR) is associated with cognitive health, but the association can be affected by broader social, economic, and medical contexts. The United States and China have very different developmental and epidemiological histories, and thus CMR among older people could be linked to cognitive function differently in the 2 countries. Methods Cross-sectional and longitudinal ordinary least squares regression models were estimated for each country using nationally representative samples of populations over age 50: 7 430/4 474 Americans and 6 108/3 655 Chinese in the cross-sectional/longitudinal samples. Results In the United States, higher CMR is associated with worse cognitive function (b  = −0.08, p  < .016). Longitudinally, CMR increase is associated with worse cognitive function at a marginally significant level (b  = −0.10, p  = .055). No relationship between CMR level or change and cognitive function is observed in China. Higher education levels are linked to better cognitive function and slower cognitive decline in both countries. Unlike older Americans, relative to those with very low education levels, among older Chinese with the highest education level, a higher CMR links to better cognitive function (b  = 0.63, p  = .013) and slower cognitive decline (b  = 0.35, p  = .062); Nevertheless, a rapid increase in CMR is additionally harmful (b  = −0.54, p  = .050) for cognitive function and may lead to faster cognitive decline (b  = −0.35, p  = .079). Conclusions The significant relationship between CMR and cognitive function in the United States suggests the importance of monitoring and controlling CMR factors at older ages. The insignificant relationship in China may be explained by the high CMR among those with high education levels, highlighting the need for improving cardiometabolic health through education and promoting healthy lifestyles. [ABSTRACT FROM AUTHOR]

Introduction: A growing number of international population surveys have included measurement of biomarkers, but differ in the type of specimens collected, sample processing procedures, shipment protocols, and laboratory assay platforms. The purpose of this study is to harmonize biomarker data from nine nationally representative studies of people 50 years of age and over by adjusting for assay platforms and type of specimens for total cholesterol (total‐C), high‐density lipoprotein cholesterol (HDL‐C), glycosylated hemoglobin (HbA1c), and C‐reactive protein (CRP). Methods: Sets of 24 identical serum, plasma, whole blood, and dried blood spot harmonization samples with known analyte levels were generated at a reference laboratory, shipped at −80°C to the respective study laboratories, and subsequently assayed following the study laboratory's protocol. Both original and harmonized study data were used to calculate mean values and at‐risk prevalence. Results: The correlation coefficients between the biomarker values of the harmonization samples obtained by the study laboratories and the reference laboratory were 0.99 or above for all analytes and laboratories, indicating the high quality of assays at all laboratories. However, using the harmonized data from each study, there were significant differences in the mean values and country ranking of the prevalence of at‐risk levels of these four biomarkers. Conclusions: While the biomarker data from the different study laboratories were highly correlated, indicating very high correlation of rank order of specimens, absolute values did vary significantly. This can have a major impact on assessment of international differences in estimates of risks for chronic morbidity and mortality. [ABSTRACT FROM AUTHOR]

Introduction: The Health and Retirement Study (HRS) has collected biomarker data over multiple waves. Such data can help improve our understanding of health changes in individuals and the causal pathways related to health. There are, however, technical challenges to using the HRS dried blood spots (DBS) biomarker data due to changes over time in assay protocols, platforms, and laboratories. We provide technical and summary information on biological indicators collected as part of the HRS from 2006 to 2016 that should be helpful to users of the data. Methods: We describe the opportunities and challenges provided by the HRS DBS data as well as insights provided by the data. The HRS collected DBS from its nationally representative sample of respondents 51 years of age or older from 2006 to 2016. DBS‐based biomarkers were collected from half the sample in 2006, 2010, and 2014, and from the other half of the sample in 2008, 2012, and 2016. These DBS specimens were used to assay total and HDL cholesterol, glycosylated hemoglobin, C‐reactive protein, and cystatin C from 2006 to 2016, and Interleukin 6 was added in 2014/2016. Samples included approximately 6000 individuals at each wave, and completion rates ranged from 81% to 90%. HRS transformed DBS values into venous blood equivalents to make them more comparable to those of the whole blood‐based assays collected in most other studies and to facilitate longitudinal analysis. Results: Distribution of changes over time by age shows that total cholesterol levels decreased for each age, while HbA1c levels increased. Cystatin C shows a clear age gradient, but a number of other markers do not. Non‐Hispanic Black persons and Hispanic respondents have a higher incidence of risk levels of each biomarker except for CRP among non‐Hispanic Black older persons. Conclusion: These public‐use DBS data provide analysis opportunities that can be used to improve our understanding of health change with age in both populations and among individuals. [ABSTRACT FROM AUTHOR]

Objectives: This study examined differences in accelerated biological aging among non-Hispanic Blacks, Hispanics, and non-Hispanic Whites in the United States and assessed whether including life course socioeconomic conditions attenuated observed racial/ethnic differences. Methods: Data came from the Venous Blood Collection Subsample of the Health and Retirement Study. We used a comprehensive summary measure of biological age (BA-22). We determined whether key lifetime socioeconomic conditions contributed to racial/ethnic differences in biological aging. Results: Findings indicated that non-Hispanic Blacks and Hispanics have accelerated aging, and non-Hispanic Whites have decelerated aging. Racial/ethnic differences were strongly tied to educational attainment. We also observed a significant difference by birthplace for Hispanics. US-born Hispanics had accelerated biological aging, whereas foreign-born Hispanics did not. In age-stratified analyses, these racial/ethnic differences were found for adults aged 56–74, but not for adults aged 75+. Conclusions: These findings provide insight into biological differences underlying racial/ethnic disparities in health. [ABSTRACT FROM AUTHOR]