The influence of substrate roughness, patterning, curvature, and compliance in peeling problems

NMP is supported by the European Commission under the Graphene FET Flagship (WP14 'Polymer composites' No. 604391) and FET Proactive 'Neurofibres' grant No. 732344. FB is supported by 'Neurofibres' grant No. 732344

Adjusting bone mass for differences in projected bone area and other confounding variables: an allometric perspective.

The traditional method of assessing bone mineral density (BMD; given by bone mineral content [BMC] divided by projected bone area [Ap], BMD = BMC/Ap) has come under strong criticism by various authors. Their criticism being that the projected bone "area" (Ap) will systematically underestimate the skeletal bone "volume" of taller subjects. To reduce the confounding effects of bone size, an alternative ratio has been proposed called bone mineral apparent density [BMAD = BMC/(Ap)3/2]. However, bone size is not the only confounding variable associated with BMC. Others include age, sex, body size, and maturation. To assess the dimensional relationship between BMC and projected bone area, independent of other confounding variables, we proposed and fitted a proportional allometric model to the BMC data of the L2-L4 vertebrae from a previously published study. The projected bone area exponents were greater than unity for both boys (1.43) and girls (1.02), but only the boy's fitted exponent was not different from that predicted by geometric similarity (1.5). Based on these exponents, it is not clear whether bone mass acquisition increases in proportion to the projected bone area (Ap) or an estimate of projected bone volume (Ap)3/2. However, by adopting the proposed methods, the analysis will automatically adjust BMC for differences in projected bone size and other confounding variables for the particular population being studied. Hence, the necessity to speculate as to the theoretical value of the exponent of Ap, although interesting, becomes redundant

Birth weight is associated with brain tissue volumes seven decades later but not with MRI markers of brain ageing

Birth weight, an indicator of fetal growth, is associated with cognitive outcomes in early life (which are predictive of cognitive ability in later life) and risk of metabolic and cardiovascular disease across the life course. Brain health in older age, indexed by MRI features, is associated with cognitive performance, but little is known about how variation in normal birth weight impacts on brain structure in later life. In a community dwelling cohort of participants in their early seventies we tested the hypothesis that birth weight is associated with the following MRI features: total brain (TB), grey matter (GM) and normal appearing white matter (NAWM) volumes; whiter matter hyperintensity (WMH) volume; a general factor of fractional anisotropy (gFA) and peak width skeletonised mean diffusivity (PSMD) across the white matter skeleton. We also investigated the associations of birth weight with cortical surface area, volume and thickness. Birth weight was positively associated with TB, GM and NAWM volumes in later life (β ≥ 0.194), and with regional cortical surface area but not gFA, PSMD, WMH volume, or cortical volume or thickness. These positive relationships appear to be explained by larger intracranial volume, rather than by age-related tissue atrophy, and are independent of body height and weight in adulthood. This suggests that larger birth weight is linked to more brain tissue reserve in older life, rather than age-related brain structural features, such as tissue atrophy or WMH volume

FIRE (facilitating implementation of research evidence) : a study protocol

Research evidence underpins best practice, but is not always used in healthcare. The Promoting Action on Research Implementation in Health Services (PARIHS) framework suggests that the nature of evidence, the context in which it is used, and whether those trying to use evidence are helped (or facilitated) affect the use of evidence. Urinary incontinence has a major effect on quality of life of older people, has a high prevalence, and is a key priority within European health and social care policy. Improving continence care has the potential to improve the quality of life for older people and reduce the costs associated with providing incontinence aids

Reduction of fibrillar strain-rate sensitivity in steroid-induced osteoporosis linked to changes in mineralized fibrillar nanostructure

As bone is used in a dynamic mechanical environment, understanding the structural origins of its time-dependent mechanical behaviour – and the alterations in metabolic bone disease – is of interest. However, at the scale of the mineralized fibrillar matrix (nanometre-level), the nature of the strain-rate dependent mechanics is incompletely understood. Here, we investigate the fibrillar- and mineral-deformation behaviour in a murine model of Cushing’s syndrome, used to understand steroid induced osteoporosis, using synchrotron small- and wide-angle scattering/diffraction combined with in situ tensile testing at three strain rates ranging from 10-4 to 10-1 s-1. We find that the effective fibril- and mineral-modulus and fibrillar-reorientation show no significant increase with strain-rate in osteoporotic bone, but increase significantly in normal (wild-type) bone. By applying a fibril-lamellar two-level structural model of bone matrix deformation to fit the results, we obtain indications that altered collagen-mineral interactions at the nanoscale – along with altered fibrillar orientation distributions – may be the underlying reason for this altered strain-rate sensitivity. Our results suggest that an altered strain-rate sensitivity of the bone matrix in osteoporosis may be one of the contributing factors to reduced mechanical competence in such metabolic bone disorders, and that increasing this sensitivity may improve biomechanical performance

Alterations in dorsal and ventral posterior cingulate connectivity in APOE ε4 carriers at risk of Alzheimer's disease

Background Recent evidence suggests that exercise plays a role in cognition and that the posterior cingulate cortex (PCC) can be divided into dorsal and ventral subregions based on distinct connectivity patterns. Aims To examine the effect of physical activity and division of the PCC on brain functional connectivity measures in subjective memory complainers (SMC) carrying the epsilon 4 allele of apolipoprotein E (APOE 4) allele. Method Participants were 22 SMC carrying the APOE ɛ4 allele (ɛ4+; mean age 72.18 years) and 58 SMC non-carriers (ɛ4–; mean age 72.79 years). Connectivity of four dorsal and ventral seeds was examined. Relationships between PCC connectivity and physical activity measures were explored. Results ɛ4+ individuals showed increased connectivity between the dorsal PCC and dorsolateral prefrontal cortex, and the ventral PCC and supplementary motor area (SMA). Greater levels of physical activity correlated with the magnitude of ventral PCC–SMA connectivity. Conclusions The results provide the first evidence that ɛ4+ individuals at increased risk of cognitive decline show distinct alterations in dorsal and ventral PCC functional connectivity

Stress detection using wearable physiological and sociometric sensors

Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that capture physiological and social responses. We compare the performance using different classifiers including support vector machine, AdaBoost, and k-nearest neighbour. Our experimental results show that by combining the measurements from both sensor systems, we could accurately discriminate between stressful and neutral situations during a controlled Trier social stress test (TSST). Moreover, this paper assesses the discriminative ability of each sensor modality individually and considers their suitability for real time stress detection. Finally, we present an study of the most discriminative features for stress detection

Refining epigenetic prediction of chronological and biological age

Background Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. Methods First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women’s Health Initiative study). Results Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10−52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10−60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. Conclusions The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age