Use of Wearable Activity-Monitoring Technologies to Promote Physical Activity in Cancer Survivors: Challenges and Opportunities for Improved Cancer Care

The aim of this review was to explore the acceptability, opportunities, and challenges associated with wearable activity-monitoring technology to increase physical activity (PA) behavior in cancer survivors. A search of Medline, Embase, CINAHL, and SportDiscus was conducted from 1 January 2011 through 3 October 2022. The search was limited to English language, and peer-reviewed original research. Studies were included if they reported the use of an activity monitor in adults (+18 years) with a history of cancer with the intent to motivate PA behavior. Our search identified 1832 published articles, of which 28 met inclusion/exclusion criteria. Eighteen of these studies included post-treatment cancer survivors, eight were on active cancer treatment, and two were long-term cancer survivor studies. ActiGraph accelerometers were the primary technology used to monitor PA behaviors, with Fitbit as the most commonly utilized self-monitoring wearable technology. Overall, wearable activity monitors were found to be an acceptable and useful tool in improving self-awareness, motivating behavioral change, and increasing PA levels. Self-monitoring wearable activity devices have a positive impact on short-term PA behaviors in cancer survivors, but the increase in PA gradually attenuated through the maintenance phase. Further study is needed to evaluate and increase the sustainability of the use of wearable technologies to support PA in cancer survivors

Bayesian Analysis of Haplotypes for Linkage Disequilibrium Mapping

Haplotype analysis of disease chromosomes can help identify probable historical recombination events and localize disease mutations. Most available analyses use only marginal and pairwise allele frequency information. We have developed a Bayesian framework that utilizes full haplotype information to overcome various complications such as multiple founders, unphased chromosomes, data contamination, and incomplete marker data. A stochastic model is used to describe the dependence structure among several variables characterizing the observed haplotypes, for example, the ancestral haplotypes and their ages, mutation rate, recombination events, and the location of the disease mutation. An efficient Markov chain Monte Carlo algorithm was developed for computing the estimates of the quantities of interest. The method is shown to perform well in both real data sets (cystic fibrosis data and Friedreich ataxia data) and simulated data sets. The program that implements the proposed method, BLADE, as well as the two real datasets, can be obtained from http://www.fas.harvard.edu/∼junliu/TechRept/01folder/diseq_prog.tar.gz

Fruit and vegetable intake and body adiposity among populations in Eastern Canada: The Atlantic Partnership for Tomorrow's Health Study

Objectives The prevalence of obesity among populations in the Atlantic provinces is the highest in Canada. Some studies suggest that adequate fruit and vegetable consumption may help body weight management. We assessed the associations between fruit and vegetable intake with body adiposity among individuals who participated in the baseline survey of the Atlantic Partnership for Tomorrow’s Health (Atlantic PATH) cohort study.Methods We carried out a cross-sectional analysis among 26 340 individuals (7979 men and 18 361 women) aged 35–69 years who were recruited in the baseline survey of the Atlantic PATH study. Data on fruit and vegetable intake, sociodemographic and behavioural factors, chronic disease, anthropometric measurements and body composition were included in the analysis.Results In the multivariable regression analyses, 1 SD increment of total fruit and vegetable intake was inversely associated with body mass index (−0.12 kg/m2; 95% CI −0.19 to –0.05), waist circumference (−0.40 cm; 95% CI −0.58 to –0.23), percentage fat mass (−0.30%; 95% CI −0.44 to –0.17) and fat mass index (−0.14 kg/m2; 95% CI −0.19 to –0.08). Fruit intake, but not vegetable intake, was consistently inversely associated with anthropometric indices, fat mass, obesity and abdominal obesity.Conclusions Fruit and vegetable consumption was inversely associated with body adiposity among the participant population in Atlantic Canada. This association was primarily attributable to fruit intake. Longitudinal studies and randomised trials are warranted to confirm these observations and investigate the underlying mechanisms

Adiposity Measures and Plasma Adipokines in Females with Rheumatoid and Osteoarthritis

The objective of this study was to examine the relationship between adipokines and adiposity in individuals with rheumatoid and osteoarthritis in the Atlantic PATH cohort. Using a nested case-control analysis, participants in the Atlantic PATH cohort with rheumatoid or osteoarthritis were matched for measures of adiposity with participants without a history of arthritis. Both measured and self-reported data were used to examine disease status, adiposity, and lifestyle factors. Immunoassays were used to measure plasma markers. BMI was positively correlated with percentage body fat, fat mass index (FMI), and a change in BMI from 18 years of age in all 3 groups. There were no statistical differences between levels of plasma adipokines; adiponectin levels were 6.6, 7.9, and 8.2 μg/ml, leptin levels were 10.3, 13.7, and 11.5 ng/ml, and resistin levels were 10.0, 12.1, and 10.8 ng/ml in participants without arthritis, with rheumatoid arthritis, and with osteoarthritis, respectively. Those with higher levels of adiponectin were more likely to have osteoarthritis (but not rheumatoid arthritis). No association was found between arthritis types and leptin or resistin. This study demonstrates differences in measures of adiposity and adipokines in specific types of arthritis and highlights the need for more research targeting specific adipokines during arthritic disease progression

The mouse deafness locus (dn) is associated with an inversion on chromosome 19

Recombination data for the mouse deafness locus (dn) on chromosome 19 are consistent with the presence of an inversion for which one of the breakpoints is between D19Mit14 and D19Mit96, a distance of less than 226 kb. Fluorescence in situ hybridization studies using a bacterial artificial chromosome on interphase (G1) nuclei provide additional support for the presence of an inversion. The dn gene is probably the orthologue of the human DFNB7/DFNB11 gene on chromosome 9. Copyright (C) 1998 Elsevier Science B.V

Assembly of a high-resolution map of the Acadian Usher syndrome region and localization of the nuclear EF-hand acidic gene

Usher syndrome type 1C (USH1C) occurs in a small population of Acadian descendants from southwestern Louisiana. Linkage and linkage disequilibrium analyses localize USH1C to chromosome 11p between markers D11S1397 and D11S1888, an interval of less than 680 kb. Here, we refine the USH1C linkage to a region less than 400 kb, between genetic markers D11S1397 and D11S1890. Using 17 genetic markers from this interval, we have isolated a contiguous set of 60 bacterial artificial chromosomes (BACs) that span the USH1C critical region. Exon trapping of BAC clones from this region resulted in the recovery of an exon of the nuclear EF-hand acidic (NEFA) gene. However, DNA sequence analysis of the NEFA cDNA from lymphocytes of affected individuals provided no evidence of mutation, making structural mutations in the NEFA protein unlikely as the cellular cause of Acadian Usher syndrome. Copyright (C) 1998 Elsevier Science B.V

Monitoring and classification of dimensional faults for automotive body assembly

Sudden process changes occurring during automobile body assembly processes will influence the downstream assembly process and the functionality and final appearance of the vehicle. Furthermore, these faults could result in a decreased production rate and an increase in the cost if sudden process changes are so serious that the production line has to be stopped for investigation. Thus, sudden process changes should be detected and eliminated as soon as possible to prevent defective products from being produced and to reduce the cost of repairs/reworks. A monitoring algorithm is developed to detect, classify, and group process changes by analyzing the dimensional data of car bodies. The results of this monitoring algorithm can help diagnose the root causes of variation according to the locations of measurement points, body structure, assembly sequence, and tooling layout. Measurement data obtained from an optical coordinate measuring machine (OCMM) are used to demonstrate the monitoring technique.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45577/1/10696_2005_Article_BF01358905.pd

Bayesian Analysis of Haplotypes for Linkage Disequilibrium Mapping

Haplotype analysis of disease chromosomes can help identify probable historical recombination events and localize disease mutations. Most available analyses use only marginal and pairwise allele frequency information. We have developed a Bayesian framework that utilizes full haplotype information to overcome various complications such as multiple founders, unphased chromosomes, data contamination, and incomplete marker data. A stochastic model is used to describe the dependence structure among several variables characterizing the observed haplotypes, for example, the ancestral haplotypes and their ages, mutation rate, recombination events, and the location of the disease mutation. An efficient Markov chain Monte Carlo algorithm was developed for computing the estimates of the quantities of interest. The method is shown to perform well in both real data sets (cystic fibrosis data and Friedreich ataxia data) and simulated data sets. The program that implements the proposed method, BLADE, as well as the two real datasets, can be obtained from http://www.fas.harvard.edu/∼junliu/TechRept/01folder/diseq_prog.tar.gz