Browsing by Author "Parker, Daniel"
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Item Open Access Age-Related Adverse Inflammatory and Metabolic Changes Begin Early in Adulthood.(The journals of gerontology. Series A, Biological sciences and medical sciences, 2018-05-22) Parker, Daniel; Sloane, Richard; Pieper, Carl F; Hall, Katherine S; Kraus, Virginia B; Kraus, William E; Huebner, Janet L; Ilkayeva, Olga R; Bain, James R; Newby, L Kristin; Cohen, Harvey Jay; Morey, Miriam CAging is characterized by deleterious immune and metabolic changes, but the onset of these changes is unknown. We measured immune and metabolic biomarkers in adults beginning at age 30. To our knowledge, this is the first study to evaluate these biomarkers in adults aged 30 to over 80. Biomarkers were quantified in 961 adults. Tumor necrosis factor alpha (TNF-α), tumor necrosis factor receptor I (TNFR-I), tumor necrosis factor receptor II (TNFR-II), interleukin (IL)-2, IL-6, VCAM-I, D-Dimer, G-CSF, regulated on activation, normal T cell expressed and secreted (RANTES), matrix metalloproteinase-3 (MMP-3), adiponectin, and paraoxonase activity were measured by ELISA. Acylcarnitines and amino acids (AAs) were measured by mass spectrometry and reduced to a single factor using principal components analysis (PCA). Glycine was analyzed separately. The relationship between age and biomarkers was analyzed by linear regression with sex, race, and body mass index (BMI) as covariates. Age was positively correlated with TNF-α, TNFR-I, TNFR-II, IL-6, IL-2, VCAM-1, D-Dimer, MMP-3, adiponectin, acylcarnitines, and AAs. Age was negative correlated with G-CSF, RANTES, and paraoxonase activity. BMI was significant for all biomarkers except IL-2, VCAM-1, RANTES, paraoxonase activity, and the AA factor. Excluding MMP-3, greater BMI was associated with potentially adverse changes in biomarker concentrations. Age-related changes in immune and metabolic biomarkers, known to be associated with poor outcomes in older adults, begin as early as the thirties.Item Open Access Field-Based Assessments of Behavioral Patterns During Shiftwork in Police Academy Trainees Using Wearable Technology.(Journal of biological rhythms, 2022-06) Erickson, Melissa L; Wang, Will; Counts, Julie; Redman, Leanne M; Parker, Daniel; Huebner, Janet L; Dunn, Jessilyn; Kraus, William ECircadian misalignment, as occurs in shiftwork, is associated with numerous negative health outcomes. Here, we sought to improve data labeling accuracy from wearable technology using a novel data pre-processing algorithm in 27 police trainees during shiftwork. Secondarily, we explored changes in four metabolic salivary biomarkers of circadian rhythm during shiftwork. Using a two-group observational study design, participants completed in-class training during dayshift for 6 weeks followed by either dayshift or nightshift field-training for 6 weeks. Using our novel algorithm, we imputed labels of circadian misaligned sleep episodes that occurred during daytime, which were previously were mislabeled as non-sleep by Garmin, supported by algorithm performance analysis. We next assessed changes to resting heart rate and sleep regularity index during dayshift versus nightshift field-training. We also examined changes in field-based assessments of salivary cortisol, uric acid, testosterone, and melatonin during dayshift versus nightshift. Compared to dayshift, nightshift workers experienced larger changes to resting heart rate, sleep regularity index (indicating reduced sleep regularity), and alterations in sleep/wake activity patterns accompanied by blunted salivary cortisol. Salivary uric acid and testosterone did not change. These findings show wearable technology combined with specialized data pre-processing can be used to monitor changes in behavioral patterns during shiftwork.