Recycling controls membrane domains

We study the coarsening of strongly microphase separated membrane domains in the presence of recycling of material. We study the dynamics of the domain size distribution under both scale-free and size-dependent recycling. Closed form solutions to the steady state distributions and its associated central moments are obtained in both cases. Moreover, for the size-independent case, the~time evolution of the moments is analytically calculated, which provide us with exact results for their corresponding relaxation times. Since these moments and relaxation times are measurable quantities, the biophysically significant free parameters in our model may be determined by comparison with experimental data.Comment: 5 pages, 4 figure

Composition variation and underdamped mechanics near membrane proteins and coats

We study the effect of membrane proteins on the shape, composition and thermodynamic stability of the surrounding membrane. When the coupling between membrane composition and curvature is strong enough the nearby composition and shape both undergo a transition from over-damped to under-damped spatial variation, well before the membrane becomes unstable in the bulk. This transition is associated with a change in the sign of the thermodynamic energy and hence has the unusual features that it can favour the early stages of coat assembly necessary for vesiculation (budding), while suppressing the activity of mechanosensitive membrane channels and transporters. Our results also suggest an approach to obtain physical parameters that are otherwise difficult to measure

Wrist-worn Accelerometry for Runners: Objective Quantification of Training Load.

PURPOSE: This study aimed to apply open-source analysis code to raw habitual physical activity data from wrist-worn monitors to: 1) objectively, unobtrusively, and accurately discriminate between "running" and "nonrunning" days; and 2) develop and compare simple accelerometer-derived metrics of external training load with existing self-report measures. METHODS: Seven-day wrist-worn accelerometer (GENEActiv; Activinsights Ltd, Kimbolton, UK) data obtained from 35 experienced runners (age, 41.9 ± 11.4 yr; height, 1.72 ± 0.08 m; mass, 68.5 ± 9.7 kg; body mass index, 23.2 ± 2.2 kg·m; 19 [54%] women) every other week over 9 to 18 wk were date-matched with self-reported training log data. Receiver operating characteristic analyses were applied to accelerometer metrics ("Average Acceleration," "Most Active-30mins," "Mins≥400 mg") to discriminate between "running" and "nonrunning" days and cross-validated (leave one out cross-validation). Variance explained in training log criterion metrics (miles, duration, training load) by accelerometer metrics (Mins≥400 mg, "workload (WL) 400-4000 mg") was examined using linear regression with leave one out cross-validation. RESULTS: Most Active-30mins and Mins≥400 mg had >94% accuracy for correctly classifying "running" and "nonrunning" days, with validation indicating robustness. Variance explained in miles, duration, and training load by Mins≥400 mg (67%-76%) and WL400-4000 mg (55%-69%) was high, with validation indicating robustness. CONCLUSIONS: Wrist-worn accelerometer metrics can be used to objectively, unobtrusively, and accurately identify running training days in runners, reducing the need for training logs or user input in future prospective research or commercial activity tracking. The high percentage of variance explained in existing self-reported measures of training load by simple, accelerometer-derived metrics of external training load supports the future use of accelerometry for prospective, preventative, and prescriptive monitoring purposes in runners

A comparison of analytical approaches to investigate associations for accelerometry-derived physical activity spectra with health and developmental outcomes in children

Under embargo until: 2021-09-20The use of high-resolution physical activity intensity spectra obtained from accelerometry can improve knowledge of associations with health and development beyond the use of traditional summary measures of intensity. The aim of the present study was to compare three different approaches for determining associations for spectrum descriptors of physical activity (the intensity gradient, principal component analysis, and multivariate pattern analysis) with relevant outcomes in children. We used two datasets including physical activity spectrum data (ActiGraph GT3X+) and 1) a cardiometabolic health outcome in 841 schoolchildren and 2) a motor skill outcome in 1081 preschool children. We compared variance explained (R2) and associations with the outcomes for the intensity gradient (slope) across the physical activity spectra, a two-component principal component model describing the physical activity variables, and multivariate pattern analysis using the intensity spectra as the explanatory data matrices. Results were broadly similar for all analytical approaches. Multivariate pattern analysis explained the most variance in both datasets, likely resulting from use of more of the information available from the intensity spectra. Yet, volume and intensity dimensions of physical activity are not easily disentangled and their relative importance may be interpreted differently using different methodology.acceptedVersio

Using accelerometry to classify physical activity intensity in older adults:What is the optimal wear-site?

This study aimed to determine the optimal accelerometer wear-site specific cut-points for discrimination of the sedentary time, light physical activity and moderate-to-vigorous physical activity (MVPA) in older adults. Twenty-three adults (14 females) aged 55-77 years wore a GENEActiv accelerometer on their non-dominant wrist, dominant wrist, waist and dominant ankle whilst undertaking eight, five-minute bouts of activity: lay supine, seated reading, slow walking, medium walking, fast walking, folding laundry, sweeping and stationary cycling. VO2 was assessed concurrently using indirect calorimetry. Receiver-operating-characteristic (ROC) analyses were used to derive wear-site specific cut-points for classifying intensity. Indirect calorimetry indicated that being lay supine and seated reading were classified as sedentary (3 METs). Areas under ROC curves indicated that the classification of sedentary activity was good for the non-dominant wrist and excellent for all other wear sites. Classification of MVPA was excellent for the waist and ankle, good for the waist and poor for the dominant and non-dominant wrists. Overall, the ankle location performed better than in other locations. Ankle-worn accelerometry appears to provide the most suitable wear-site to discriminate between sedentary time and MVPA in older adults

A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person’s most active minutes are accumulated, can a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were carried out on five datasets using wrist-worn accelerometers: children (N=145), adolescent girls (N=1669), office workers (N=114), pre- (N=1218) and post- (N=1316) menopausal women, and adults with type 2 diabetes (N=475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person’s most active 60, 30 and 2 minutes are accumulated: M60ACC; M30ACC and M2ACC, respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17-68% in children and 15%-81% in adults, tending to decline with age. The proportion of pre-and postmenopausal women with M2ACC values meeting thresholds for bone health ranged from 6-13%. Conclusions: These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie

Wear Compliance and Activity in Children Wearing Wrist and Hip-Mounted Accelerometers.

PURPOSE: This study aimed to (i) explore children's compliance to wearing wrist and hip-mounted accelerometers, (ii) compare children's physical activity (PA) derived from wrist and hip raw accelerations, and (iii) examine differences in raw and counts PA measured by hip-worn accelerometry. METHODS: One hundred and twenty nine 9-10 y old children wore a wrist-mounted GENEActiv accelerometer (GAwrist) and a hip-mounted ActiGraph GT3X+ accelerometer (AGhip) for 7 d. Both devices measured raw accelerations and the AGhip also provided counts-based data. RESULTS: More children wore the GAwrist than the AGhip regardless of wear time criteria applied (p<.001 - .035). Raw data signal vector magnitude (SVM; r = .68), moderate PA (MPA; r = .81), vigorous PA (VPA; r = .85), and moderate-to-vigorous PA (MVPA; r = .83) were strongly associated between devices (p<.001). GAwrist SVM (p = .001), MPA (p = .037), VPA (p = .002), and MVPA (p = .016) were significantly greater than AGhip. According to GAwrist raw data, 86.9% of children engaged in at least 60 min MVPA[BULLET OPERATOR]d, compared to 19% for AGhip. ActiGraph MPA (raw) was 42.00 ± 1.61 min[BULLET OPERATOR]d compared to 35.05 ± 0.99 min[BULLET OPERATOR]d (counts) (p=.02). Actigraph VPA was 7.59 ± 0.46 min[BULLET OPERATOR]d (raw) and 37.06 ± 1.85 min[BULLET OPERATOR]d (counts; p=.19). CONCLUSION: In children accelerometer wrist placement promotes superior compliance than the hip. Raw accelerations were significantly higher for GAwrist compared to AGhip, possibly due to placement location and technical differences between devices. AGhip PA calculated from raw accelerations and counts differed substantially, demonstrating that PA outcomes derived from cutpoints for raw output and counts cannot be directly compared