Social network size, loneliness, physical functioning and depressive symptoms among older adults: Examining reciprocal associations in four waves of the Longitudinal Aging Study Amsterdam (LASA)

Previous research indicates that social isolation, loneliness, physical dysfunction and depressive symptoms are interrelated factors, little is known about the potential pathways among them. The aim of the study is to analyse simultaneously reciprocal relationships that could exist between the four factors to clarify potential mediation effects. METHODS Within a large representative sample of older people in the Longitudinal Aging Study Amsterdam (LASA), participants aged 75 and over were followed up over a period of 11 years (four waves). We tested cross-lagged and autoregressive longitudinal associations of social network size, loneliness, physical functioning and depressive symptoms using structural equation modelling (SEM). RESULTS Several statistically significant cross-lagged associations were found: decreasing physical functioning (Coef.=-0.03; p<0.05), as well as social network size (Coef.=-0.02; p<0.05), predicted higher levels of loneliness, which predicted an increase in depressive symptoms (Coef.=0.17; p<0.05) and further reduction of social network (Coef.=-0.20; p<0.05). Decreasing physical functioning also predicted an increase in depressive symptoms (Coef.=-0.08; p<0.05). All autoregressive associations were statistically significant. CONCLUSION Interventions focused on promoting social activities among older adults after negative life events, such as loss of social contacts or declining physical function, may alleviate feelings of loneliness and act as mental health protector

How are falls and fear of falling associated with objectively measured physical activity in a cohort of community-dwelling older men?

BACKGROUND: Falls affect approximately one third of community-dwelling older adults each year and have serious health and social consequences. Fear of falling (FOF) (lack of confidence in maintaining balance during normal activities) affects many older adults, irrespective of whether they have actually experienced falls. Both falls and fear of falls may result in restrictions of physical activity, which in turn have health consequences. To date the relation between (i) falls and (ii) fear of falling with physical activity have not been investigated using objectively measured activity data which permits examination of different intensities of activity and sedentary behaviour. METHODS: Cross-sectional study of 1680 men aged 71-92 years recruited from primary care practices who were part of an on-going population-based cohort. Men reported falls history in previous 12 months, FOF, health status and demographic characteristics. Men wore a GT3x accelerometer over the hip for 7 days. RESULTS: Among the 12% of men who had recurrent falls, daily activity levels were lower than among non-fallers; 942 (95% CI 503, 1381) fewer steps/day, 12(95% CI 2, 22) minutes less in light activity, 10(95% CI 5, 15) minutes less in moderate to vigorous PA [MVPA] and 22(95% CI 9, 35) minutes more in sedentary behaviour. 16% (n = 254) of men reported FOF, of whom 52% (n = 133) had fallen in the past year. Physical activity deficits were even greater in the men who reported that they were fearful of falling than in men who had fallen. Men who were fearful of falling took 1766(95% CI 1391, 2142) fewer steps/day than men who were not fearful, and spent 27(95% CI 18, 36) minutes less in light PA, 18(95% CI 13, 22) minutes less in MVPA, and 45(95% CI 34, 56) minutes more in sedentary behaviour. The significant differences in activity levels between (i) fallers and non-fallers and (ii) men who were fearful of falling or not fearful, were mediated by similar variables; lower exercise self-efficacy, fewer excursions from home and more mobility difficulties. CONCLUSIONS: Falls and in particular fear of falling are important barriers to older people gaining health benefits of walking and MVPA. Future studies should assess the longitudinal associations between falls and physical activity

Quantitative cross-species extrapolation between humans and fish: The case of the anti-depressant fluoxetine

This article has been made available through the Brunel Open Access Publishing Fund.Fish are an important model for the pharmacological and toxicological characterization of human pharmaceuticals in drug discovery, drug safety assessment and environmental toxicology. However, do fish respond to pharmaceuticals as humans do? To address this question, we provide a novel quantitative cross-species extrapolation approach (qCSE) based on the hypothesis that similar plasma concentrations of pharmaceuticals cause comparable target-mediated effects in both humans and fish at similar level of biological organization (Read-Across Hypothesis). To validate this hypothesis, the behavioural effects of the anti-depressant drug fluoxetine on the fish model fathead minnow (Pimephales promelas) were used as test case. Fish were exposed for 28 days to a range of measured water concentrations of fluoxetine (0.1, 1.0, 8.0, 16, 32, 64 μg/L) to produce plasma concentrations below, equal and above the range of Human Therapeutic Plasma Concentrations (HTPCs). Fluoxetine and its metabolite, norfluoxetine, were quantified in the plasma of individual fish and linked to behavioural anxiety-related endpoints. The minimum drug plasma concentrations that elicited anxiolytic responses in fish were above the upper value of the HTPC range, whereas no effects were observed at plasma concentrations below the HTPCs. In vivo metabolism of fluoxetine in humans and fish was similar, and displayed bi-phasic concentration-dependent kinetics driven by the auto-inhibitory dynamics and saturation of the enzymes that convert fluoxetine into norfluoxetine. The sensitivity of fish to fluoxetine was not so dissimilar from that of patients affected by general anxiety disorders. These results represent the first direct evidence of measured internal dose response effect of a pharmaceutical in fish, hence validating the Read-Across hypothesis applied to fluoxetine. Overall, this study demonstrates that the qCSE approach, anchored to internal drug concentrations, is a powerful tool to guide the assessment of the sensitivity of fish to pharmaceuticals, and strengthens the translational power of the cross-species extrapolation

Harmonising data collection from osteoarthritis studies to enable stratification: recommendations on core data collection from an Arthritis Research UK clinical studies group

Objective. Treatment of OA by stratifying for commonly used and novel therapies will likely improve the range of effective therapy options and their rational deployment in this undertreated, chronic disease. In order to develop appropriate datasets for conducting post hoc analyses to inform approaches to stratification for OA, our aim was to develop recommendations on the minimum data that should be recorded at baseline in all future OA interventional and observational studies.Methods. An Arthritis Research UK study group comprised of 32 experts used a Delphi-style approach supported by a literature review of systematic reviews to come to a consensus on core data collection for OA studies.Results. Thirty-five systematic reviews were used as the basis for the consensus group discussion. For studies with a primary structural endpoint, core domains for collection were defined as BMI, age, gender, racial origin, comorbidities, baseline OA pain, pain in other joints and occupation. In addition to the items generalizable to all anatomical sites, joint-specific domains included radiographic measures, surgical history and anatomical factors, including alignment. To demonstrate clinical relevance for symptom studies, the collection of mental health score, self-efficacy and depression scales were advised in addition to the above.Conclusions. Currently it is not possible to stratify patients with OA into therapeutic groups. A list of core and optional data to be collected in all OA interventional and observational studies was developed, providing a basis for future analyses to identify predictors of progression or response to treatment

Planet Populations as a Function of Stellar Properties

Exoplanets around different types of stars provide a window into the diverse environments in which planets form. This chapter describes the observed relations between exoplanet populations and stellar properties and how they connect to planet formation in protoplanetary disks. Giant planets occur more frequently around more metal-rich and more massive stars. These findings support the core accretion theory of planet formation, in which the cores of giant planets form more rapidly in more metal-rich and more massive protoplanetary disks. Smaller planets, those with sizes roughly between Earth and Neptune, exhibit different scaling relations with stellar properties. These planets are found around stars with a wide range of metallicities and occur more frequently around lower mass stars. This indicates that planet formation takes place in a wide range of environments, yet it is not clear why planets form more efficiently around low mass stars. Going forward, exoplanet surveys targeting M dwarfs will characterize the exoplanet population around the lowest mass stars. In combination with ongoing stellar characterization, this will help us understand the formation of planets in a large range of environments.Comment: Accepted for Publication in the Handbook of Exoplanet

No association between the aluminium content of trabecular bone and bone density, mass or size of the proximal femur in elderly men and women

BACKGROUND: Aluminium is considered a bone toxic metal since poisoning can lead to aluminium-induced bone disease in patients with chronic renal failure. Healthy subjects with normal renal function retain 4% of the aluminium consumed. They might thus also accumulate aluminium and eventually be at risk of long-term low-grade aluminium intoxication that can affect bone health. METHODS: We therefore examined 62 patients with femoral neck fractures or osteoarthritis of the hip (age range 38–93), with the aim of examining whether aluminium in bone is associated with bone-mineral density (BMD), content (BMC) or width of the femoral neck measured by dual-energy X-ray absorptiometry (DXA). During operations bone biopsies were taken from the trabecular bone of the proximal femur. The samples were measured for their content of aluminium using a mass spectrometer. RESULTS: No significant association between the aluminium content in bone and femoral neck BMD, BMC or width could be found after multivariate adjustment. CONCLUSION: Our results indicate that the accumulated aluminium content in bone during life does not substantially influence the extent of osteoporosis

Bone mineral density enhances use of clinical risk factors in predicting ten-year risk of osteoporotic fractures in Chinese men: the Hong Kong Osteoporosis Study

This prospective study aimed to determine the risk factors and the 10-year probability of osteoporotic fracture in Southern Chinese men. The findings show substantial population differences in fracture incidence and risk prediction compared to the FRAX TM model, and the addition of BMD information to clinical risk factor assessment improved fracture risk prediction in Chinese men. Introduction: Clinical risk factors with or without bone mineral density (BMD) measurements are increasingly recognized as reliable predictors of fracture risk. Prospective data on fracture incidence in Asian men remain sparse. This prospective study aimed to determine the risk factors and the 10-year absolute fracture risk in Southern Chinese men. Methods: This is a part of the Hong Kong Osteoporosis Study. One thousand eight hundred ten (1,810) community-dwelling, treatment-naive men aged 50 years or above were evaluated. Baseline demographic characteristics, clinical risk factors and BMD were recorded. Ten-year risk of osteoporotic fracture was calculated using Cox proportional hazards models. Results: The mean age of subjects was 68.0 ± 10.3 years. After a mean follow-up period of 3.5±2.9 years (range 1 to 14 years), 37 incident low-trauma fractures were recorded. The incidence for all osteoporotic fractures and hip fractures was 635/100,000 and 123/100,000 person-years, respectively. The most significant predictors of osteoporotic fracture were history of fall (RR 14.5), femoral neck BMD T-score < -2.5 (RR 13.8) and history of fracture (RR 4.4). Each SD reduction in BMD was associated with a 1.8 to 2.6-fold increase in fracture risk. Subjects with seven clinical risk factors and BMD T-score of -1 had an absolute 10-year risk of osteoporotic fracture of 8.9%, but this increased to 22.7% if they also had a femoral neck BMD T-score of -2.5. Conclusions: These findings show substantial population differences in fracture incidence and risk prediction. The addition of BMD information to clinical risk factor assessment improved fracture risk prediction in Chinese men. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

Artificial Intelligence in Education

Artificial Intelligence (AI) technologies have been researched in educational contexts for more than 30 years (Woolf 1988; Cumming and McDougall 2000; du Boulay 2016). More recently, commercial AI products have also entered the classroom. However, while many assume that Artificial Intelligence in Education (AIED) means students taught by robot teachers, the reality is more prosaic yet still has the potential to be transformative (Holmes et al. 2019). This chapter introduces AIED, an approach that has so far received little mainstream attention, both as a set of technologies and as a field of inquiry. It discusses AIED’s AI foundations, its use of models, its possible future, and the human context. It begins with some brief examples of AIED technologies