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Correcting for enzyme immunoassay changes in long term monitoring studies.

ABSTRACT: Enzyme immunoassays (EIAs) are a common tool for measuring steroid hormones in wildlife due to their low cost, commercial availability, and rapid results. Testing technologies improve continuously, sometimes requiring changes in protocols or crucial assay components. Antibody replacement between EIA kits can cause differences in EIA sensitivity, which can hinder monitoring hormone concentration over time. The antibody in a common cortisol EIA kit used for long-term monitoring of stress in wildlife was replaced in 2014, causing differences in cross reactivity and standard curve concentrations. Therefore, the objective of this study was to develop a method to standardize results following changes in EIA sensitivity. We validated this method using cortisol concentrations measured in the hair of brown bears (Ursus arctos).•We used a simple linear regression to model the relationship between cortisol concentrations using kit 1 and kit 2.•We found a linear relationship between the two kits (R² = 0.85) and used the regression equation (kit2 = (0.98 × kit1) + 1.65) to predict cortisol concentrations in re-measured samples.•Mean predicted percent error was 16% and 72% of samples had a predicted percent error <20%, suggesting that this method is well-suited for correcting changes in EIA sensitivity.

SUBMITTER: Wilson AE

PROVIDER: S-EPMC8374155 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Correcting for enzyme immunoassay changes in long term monitoring studies.

Wilson Abbey E AE Sergiel Agnieszka A Selva Nuria N Swenson Jon E JE Zedrosser Andreas A Stenhouse Gordon G Janz David M DM

MethodsX 20210106

Enzyme immunoassays (EIAs) are a common tool for measuring steroid hormones in wildlife due to their low cost, commercial availability, and rapid results. Testing technologies improve continuously, sometimes requiring changes in protocols or crucial assay components. Antibody replacement between EIA kits can cause differences in EIA sensitivity, which can hinder monitoring hormone concentration over time. The antibody in a common cortisol EIA kit used for long-term monitoring of stress in wildli ...[more]

PMID: 34434735

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Project description:Aquatic pesticide pollution from both agricultural and urban pest control is a concern in many parts of the world. Making an accurate assessment of pesticide exposure is the starting point to protecting aquatic ecosystems. This in turn requires the design of an effective monitoring program. Monitoring is also essential to evaluate the efficacy of mitigation measures aimed to curb pesticide pollution. However, empirical evidence for their efficacy can be confounded by additional influencing factors, most prominently variable weather conditions. This review summarizes the experiences gained from long-term (>5 years) pesticide monitoring studies for detecting trends and provides recommendations for their improvement. We reviewed articles published in the scientific literature, with a few complements from selected grey literature, for a total of 20 studies which fulfill our search criteria. Overall, temporal trends of pesticide use and hydrological conditions were the two most common factors influencing aquatic pesticide pollution. Eighteen studies demonstrated observable effects to surface water concentrations from changes in pesticide application rates (e.g., use restriction) and sixteen studies from interannual variability in hydrological conditions during the application period. Accounting for seasonal- and streamflow-related variability in trend analysis is important because the two factors can obscure trends caused by changes in pesticide use or management practices. Other mitigation measures (e.g., buffer strips) were only detectable in four studies where concentrations or loads were reduced by > 45%. Collecting additional agricultural (e.g., pesticide use, mitigation measures) and environmental (e.g., precipitation, stream flow) data, as well as establishing a baseline before the implementation of mitigation measures have been consistently reported as prerequisites to interpret water quality trends from long-term monitoring studies, but have rarely been implemented in the past.

Project description:To examine the long-term relationship between changes in water and beverage intake and weight change.Prospective cohort studies of 50013 women aged 40-64 years in the Nurses' Health Study (NHS, 1986-2006), 52987 women aged 27-44 years in the NHS II (1991-2007) and 21988 men aged 40-64 years in the Health Professionals Follow-up Study (1986-2006) without obesity and chronic diseases at baseline.We assessed the association of weight change within each 4-year interval, with changes in beverage intakes and other lifestyle behaviors during the same period. Multivariate linear regression with robust variance and accounting for within-person repeated measures were used to evaluate the association. Results across the three cohorts were pooled by an inverse-variance-weighted meta-analysis.Participants gained an average of 1.45 kg (5th to 95th percentile: -1.87 to 5.46) within each 4-year period. After controlling for age, baseline body mass index and changes in other lifestyle behaviors (diet, smoking habits, exercise, alcohol, sleep duration, TV watching), each 1 cup per day increment of water intake was inversely associated with weight gain within each 4-year period (-0.13 kg; 95% confidence interval (CI): -0.17 to -0.08). The associations for other beverages were: sugar-sweetened beverages (SSBs) (0.36 kg; 95% CI: 0.24-0.48), fruit juice (0.22 kg; 95% CI: 0.15-0.28), coffee (-0.14 kg; 95% CI: -0.19 to -0.09), tea (-0.03 kg; 95% CI: -0.05 to -0.01), diet beverages (-0.10 kg; 95% CI: -0.14 to -0.06), low-fat milk (0.02 kg; 95% CI: -0.04 to 0.09) and whole milk (0.02 kg; 95% CI: -0.06 to 0.10). We estimated that replacement of 1 serving per day of SSBs by 1 cup per day of water was associated with 0.49 kg (95% CI: 0.32-0.65) less weight gain over each 4-year period, and the replacement estimate of fruit juices by water was 0.35 kg (95% CI: 0.23-0.46). Substitution of SSBs or fruit juices by other beverages (coffee, tea, diet beverages, low-fat and whole milk) were all significantly and inversely associated with weight gain.Our results suggest that increasing water intake in place of SSBs or fruit juices is associated with lower long-term weight gain.

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Correcting for enzyme immunoassay changes in long term monitoring studies.

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Correcting for enzyme immunoassay changes in long term monitoring studies.

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