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Tryptophan (TRP) metabolites along the kynurenine (KYN) pathway (KP) have been found to influence muscle. Pro-inflammatory cytokines are known to stimulate the degradation of TRP down the KP. Given that both inflammation and KP metabolites have been connected with loss of muscle, we assessed the potential mediating role of KP metabolites on inflammation and muscle mass in older men. 505 men (85.0±4.2yrs) from the Osteoporotic Fractures in Men cohort study with measured D3-creatine dilution (D3Cr) muscle mass, KP metabolites, and inflammation markers (C-reactive protein (CRP), alpha-1-acid glycoprotein (AGP) and a subsample (n=305) with interleukin (IL-6, IL-1β, IL-17A) and tumor necrosis factor-α (TNF-α)) were included in the analysis. KP metabolites and inflammatory markers were measured using liquid chromatography-tandem mass spectrometry and immunoassays, respectively. 23-92% of the inverse relationship between inflammatory markers and D3Cr muscle mass was mediated by KP metabolites (indirect effect p0.05). KP metabolites, particularly higher ratios of KYN/TRP, 3-HK/XA, 3-HK/3-HAA, QA/3-HAA and a lower ratio of NAM/QA, mediated the relationship between inflammation and low muscle mass. Our preliminary cross-sectional data suggest that interventions to alter D3Cr muscle mass may focus on KP metabolites rather than inflammation per se.

BackgroundFor breast cancer survivors, moderate to vigorous physical activity (MVPA) is associated with improved survival. Less is known about the interrelationships of daytime activities (sedentary behavior [SB], light-intensity physical activity, and MVPA) and associations with survivors' health outcomes. This study will use isotemporal substitution to explore reallocations of time spent in daytime activities and associations with cancer recurrence biomarkers.MethodsBreast cancer survivors (N = 333; mean age 63 y) wore accelerometers and provided fasting blood samples. Linear regression models estimated the associations between daytime activities and cancer recurrence biomarkers. Isotemporal substitution models estimated cross-sectional associations with biomarkers when time was reallocated from of one activity to another. Models were adjusted for wear time, demographics, lifestyle factors, and medical conditions.ResultsMVPA was significantly associated with lower insulin, C-reactive protein, homeostatic model assessment of insulin resistance, and glucose, and higher sex hormone-binding globulin (all P < .05). Light-intensity physical activity and SB were associated with insulin and homeostatic model assessment of insulin resistance (both P < .05). Reallocating 18 minutes of SB to MVPA resulted in significant beneficial associations with insulin (-9.3%), homeostatic model assessment of insulin resistance (-10.8%), glucose (-1.7%), and sex hormone-binding globulin (7.7%). There were no significant associations when 79 minutes of SB were shifted to light-intensity physical activity.ConclusionsResults illuminate the possible benefits for breast cancer survivors of replacing time spent in SB with MVPA.

BackgroundPhysical inactivity and unhealthy diet are modifiable behaviors that lead to several cancers. Biologically, these behaviors are linked to cancer through obesity-related insulin resistance, inflammation, and oxidative stress. Individual strategies to change physical activity and diet are often short lived with limited effects. Interventions are expected to be more successful when guided by multi-level frameworks that include environmental components for supporting lifestyle changes. Understanding the role of environment in the pathways between behavior and cancer can help identify what environmental conditions are needed for individual behavioral change approaches to be successful, and better recognize how environments may be fueling underlying racial and ethnic cancer disparities.MethodsThis cross-sectional study was designed to select participants (n = 602 adults, 40% Hispanic, in San Diego County) from a range of neighborhoods ensuring environmental variability in walkability and food access. Biomarkers measuring cancer risk were measured with fasting blood draw including insulin resistance (fasting plasma insulin and glucose levels), systemic inflammation (levels of CRP), and oxidative stress measured from urine samples. Objective physical activity, sedentary behavior, and sleep were measured by participants wearing a GT3X+ ActiGraph on the hip and wrist. Objective measures of locations were obtained through participants wearing a Qstarz Global Positioning System (GPS) device on the waist. Dietary measures were based on a 24-h food recall collected on two days (weekday and weekend). Environmental exposure will be calculated using static measures around the home and work, and dynamic measures of mobility derived from GPS traces. Associations of environment with physical activity, obesity, diet, and biomarkers will be measured using generalized estimating equation models.DiscussionOur study is the largest study of objectively measured physical activity, dietary behaviors, environmental context/exposure, and cancer-related biomarkers in a Hispanic population. It is the first to perform high quality measures of physical activity, sedentary behavior, sleep, diet and locations in which these behaviors occur in relation to cancer-associated biomarkers including insulin resistance, inflammation, impaired lipid metabolism, and oxidative stress. Results will add to the evidence-base of how behaviors and the built environment interact to influence biomarkers that increase cancer risk.Trial registrationClinicalTrials.gov NCT02094170 , 03/21/2014.

Objectives: We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention setting. Methods: Data were from a randomized weight loss trial that encouraged increased PA among 333 postmenopausal breast cancer survivors. PA was estimated using accelerometry and a validated questionnaire at baseline and 6-months. Accelerometer data were processed using standard cut-points and a validated machine learning algorithm. Agreement of PA at each time-point and change was assessed using mixed effects regression models and concordance correlation. Results: At baseline, self-report and machine learning provided similar PA estimates (mean dif- ference = 11.5 min/day) unlike self-report and standard cut-points (mean difference = 36.3 min/ day). Cut-point and machine learning methods assessed PA change over time more similarly than other comparisons. Specifically, the mean difference of PA change for the cut-point versus machine learning methods was 5.1 min/day for intervention group and 2.9 in controls, whereas it was ≥ 24.7 min/day for other comparisons. Conclusions: Intervention researchers are facing the issue of self-report measures introducing bias and accelerometer cut-points being insensi- tive. Machine learning approaches may bridge this gap.

Engineering professors are well positioned to support their undergraduate students, who often experience diminished mental health. This paper examines engineering professors' perceptions of their undergraduate engineering students' experiences of stress. The described perceptions include when they notice student stress, which stressors they perceive, and supports that these students use. In this qualitative study, we interviewed 24 engineering professors and four career advisors at 18 institutions in the United States about these topics. Results show that these professors often had consistent access to notice indicators of student distress. They described key sources of student stress: balancing responsibilities, significant academic stress, and a culture of competition. They were less likely to notice student stressors associated with interpersonal relationships and identity-related stressors, which are less related to their role as professors. Supports that professors described included interpersonal relationships and health and wellness activities. This lays a foundation for encouraging engineering professors to support their students' mental health and wellness even more. [ABSTRACT FROM AUTHOR]

BackgroundAs the US population ages, there is an increasing need for evidence based, peer-led physical activity programs, particularly in ethnically diverse, low income senior centers where access is limited.Methods/designThe Peer Empowerment Program 4 Physical Activity' (PEP4PA) is a hybrid Type II implementation-effectiveness trial that is a peer-led physical activity (PA) intervention based on the ecological model of behavior change. The initial phase is a cluster randomized control trial randomized to either a peer-led PA intervention or usual center programming. After 18 months, the intervention sites are further randomized to continued support or no support for another 6 months. This study will be conducted at twelve senior centers in San Diego County in low income, diverse communities. In the intervention sites, 24 peer health coaches and 408 adults, aged 50 years and older, are invited to participate. Peer health coaches receive training and support and utilize a tablet computer for delivery and tracking. There are several levels of intervention. Individual components include pedometers, step goals, counseling, and feedback charts. Interpersonal components include group walks, group sharing and health tips, and monthly celebrations. Community components include review of PA resources, walkability audit, sustainability plan, and streetscape improvements. The primary outcome of interest is intensity and location of PA minutes per day, measured every 6 months by wrist and hip accelerometers and GPS devices. Secondary outcomes include blood pressure, physical, cognitive, and emotional functioning. Implementation measures include appropriateness & acceptability (perceived and actual fit), adoption & penetration (reach), fidelity (quantity & quality of intervention delivered), acceptability (satisfaction), costs, and sustainability.DiscussionUsing a peer led implementation strategy to deliver a multi-level community based PA program can enhance program adoption, implementation, and sustainment.Trial registrationClinicalTrials.gov, USA ( NCT02405325 ). Date of registration, March 20, 2015. This website also contains all items from the World Health Organization Trial Registration Data Set.

BackgroundAs the US population ages, there is an increasing need for evidence based, peer-led physical activity programs, particularly in ethnically diverse, low income senior centers where access is limited.Methods/designThe Peer Empowerment Program 4 Physical Activity' (PEP4PA) is a hybrid Type II implementation-effectiveness trial that is a peer-led physical activity (PA) intervention based on the ecological model of behavior change. The initial phase is a cluster randomized control trial randomized to either a peer-led PA intervention or usual center programming. After 18 months, the intervention sites are further randomized to continued support or no support for another 6 months. This study will be conducted at twelve senior centers in San Diego County in low income, diverse communities. In the intervention sites, 24 peer health coaches and 408 adults, aged 50 years and older, are invited to participate. Peer health coaches receive training and support and utilize a tablet computer for delivery and tracking. There are several levels of intervention. Individual components include pedometers, step goals, counseling, and feedback charts. Interpersonal components include group walks, group sharing and health tips, and monthly celebrations. Community components include review of PA resources, walkability audit, sustainability plan, and streetscape improvements. The primary outcome of interest is intensity and location of PA minutes per day, measured every 6 months by wrist and hip accelerometers and GPS devices. Secondary outcomes include blood pressure, physical, cognitive, and emotional functioning. Implementation measures include appropriateness & acceptability (perceived and actual fit), adoption & penetration (reach), fidelity (quantity & quality of intervention delivered), acceptability (satisfaction), costs, and sustainability.DiscussionUsing a peer led implementation strategy to deliver a multi-level community based PA program can enhance program adoption, implementation, and sustainment.Trial registrationClinicalTrials.gov, USA ( NCT02405325 ). Date of registration, March 20, 2015. This website also contains all items from the World Health Organization Trial Registration Data Set.

Photogrammetry is a significant tool museums utilize to produce high-quality 3D models for research and exhibit content. As advancements in computer hardware and software continue, it is crucial to assess the effectiveness of photogrammetry software in producing research-quality 3D models. This study evaluates the efficacy of Apple's Object Capture photogrammetry API to create high-quality 3D models. The results indicate that Object Capture is a viable option to create research-quality models efficiently for a variety of natural and cultural heritage objects. Object Capture is notable for its minimal need for masking backgrounds within images and its ability to create models with fewer than 100 images and process 3D models in under 10 minutes. [ABSTRACT FROM AUTHOR]

Extensive evidence leads us to expect that health disparities by race and socioeconomic status found in one generation might be reproduced in the next. To the extent that this occurs it is important to assess life course processes responsible for the reproduction. Prospective evidence concerning such life course processes is hard to come by as it requires long-term follow-up of individuals from childhood through adult life. We present data from the Child Health and Development Disparities study that provides evidence relevant to this issue with respect to self-rated health. Mothers and offspring recruited in California's Bay Area between 1959 and 1967 were assessed during pregnancy with follow-up exams of offspring along with in-person interviews with mothers (at offspring ages 5, 9-11, 15-17) and offspring (at ages 15-17, ∼50). Available data allow us to assess the importance of three potential life course pathways in the reproduction of inequalities in self-rated health - socioeconomic pathways, cognitive pathways and pathways involving emerging health itself. As expected we found that race and SES disparities in SRH are reproduced across generations. They are evident in mothers, not strong or significant in offspring at 15-17, but present once again in offspring at age ∼50. Concerning potential pathways, we found that indicators of child health were related to adult SRH and played some role in accounting for race but not SES disparities in adult SRH. Cognitive abilities were unrelated to adult SRH with childhood SES controlled. Childhood SES was associated with adult SRH independent of other childhood factors and is reduced to non-significance only when offspring college attainment is controlled. Race and SES disparities in self-reported health in one generation are re-expressed in the next with strongest support for SES pathways in this transmission.

The No Child Left Behind Act is comprised of four pillars, one of which is "proven education methods." This paper attempts to provide a historical context for the development of evidence-based education by examining its foundation in medical practice. Next, the rationale for evidence of educational effectiveness based on a scientific "gold standard," the randomized controlled trial (RCT), is explored and the relative limitations of this approach are outlined. Finally, important distinctions between medicine and education are explained.