A high rate of polypharmacy is, in part, a consequence of the increasing proportion of multimorbidity in the ageing population worldwide. Our understanding of the potential harm of taking multiple medications in an older, multi-morbid population, who are likely to be on a polypharmacy regime, is limited. This is a narrative literature review that aims to appraise and summarise recent studies published about polypharmacy. We searched MEDLINE using the search terms polypharmacy (and its variations, e.g. multiple prescriptions, inappropriate drug use, etc.) in titles. Systematic reviews and original studies in English published between 2003 and 2018 were included. In this review, we provide current definitions of polypharmacy. We identify the determinants and prevalence of polypharmacy reported in different studies. Finally, we summarise some of the findings regarding the association between polypharmacy and health outcomes in older adults, with a focus on frailty, hospitalisation and mortality. Polypharmacy was most often defined in terms of the number of medications that are being taken by an individual at any given time. Our review showed that the prevalence of polypharmacy varied between 10% to as high as around 90% in different populations. Chronic conditions, demographics, socioeconomics and self-assessed health factors were independent predictors of polypharmacy. Polypharmacy was reported to be associated with various adverse outcomes after adjusting for health conditions. Optimising care for polypharmacy with valid, reliable measures, relevant to all patients, will improve the health outcomes of older adult population.

Mountain glaciers integrate climate processes to provide an unmatched signal of regional climate forcing. However, extracting the climate signal via intercomparison of regional glacier mass-balance records can be problematic when methods for extrapolating and calibrating direct glaciological measurements are mixed or inconsistent. To address this problem, we reanalyzed and compared long-term mass-balance records from the US Geological Survey Benchmark Glaciers. These five glaciers span maritime and continental climate regimes of the western United States and Alaska. Each glacier exhibits cumulative mass loss since the mid-20th century, with average rates ranging from −0.58 to −0.30 m w.e. a−1. We produced a set of solutions using different extrapolation and calibration methods to inform uncertainty estimates, which range from 0.22 to 0.44 m w.e. a−1. Mass losses are primarily driven by increasing summer warming. Continentality exerts a stronger control on mass loss than latitude. Similar to elevation, topographic shading, snow redistribution and glacier surface features often exert important mass-balance controls. The reanalysis underscores the value of geodetic calibration to resolve mass-balance magnitude, as well as the irreplaceable value of direct measurements in contributing to the process-based understanding of glacier mass balance.

A quantitative understanding of snow thickness and snow water equivalent (SWE) on glaciers is essential to a wide range of scientific and resource management topics. However, robust SWE estimates are observationally challenging, in part because SWE can vary abruptly over short distances in complex terrain due to interactions between topography and meteorological processes. In spring 2013, we measured snow accumulation on several glaciers around the Gulf of Alaska using both ground-and helicopter-based ground-penetrating radar surveys, complemented by extensive ground truth observations. We found that SWE can be highly variable (40% difference) over short spatial scales (tens to hundreds of meters), especially in the ablation zone where the underlying ice surfaces are typically rough. Elevation provides the dominant basin-scale influence on SWE, with gradients ranging from 115 to 400 mm/100 m. Regionally, total accumulation and the accumulation gradient are strongly controlled by a glacier's distance from the coastal moisture source. Multiple linear regressions, used to calculate distributed SWE fields, show that robust results require adequate sampling of the true distribution of multiple terrain parameters. Final SWE estimates (comparable to winter balances) show reasonable agreement with both the Parameter-elevation Relationships on Independent Slopes Model climate data set (9-36% difference) and the U.S. Geological Survey Alaska Benchmark Glaciers (6-36% difference). All the glaciers in our study exhibit substantial sensitivity to changing snow-rain fractions, regardless of their location in a coastal or continental climate. While process-based SWE projections remain elusive, the collection of ground-penetrating radar (GPR)-derived data sets provides a greatly enhanced perspective on the spatial distribution of SWE and will pave the way for future work that may eventually allow such projections.

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Major depressive disorder is a leading cause of disability and significant mortality, yet mechanistic understanding remains limited. Over the past decade evidence has accumulated from case-control studies that depressive illness is associated with blunted reward activation in the basal ganglia and other regions such as the medial prefrontal cortex. However it is unclear whether this finding can be replicated in a large number of subjects. The functional anatomy of the medial prefrontal cortex and basal ganglia has been extensively studied and the former has excitatory glutamatergic projections to the latter. Reduced effect of glutamatergic projections from the prefrontal cortex to the nucleus accumbens has been argued to underlie motivational disorders such as depression, and many prominent theories of major depressive disorder propose a role for abnormal cortico-limbic connectivity. However, it is unclear whether there is abnormal reward-linked effective connectivity between the medial prefrontal cortex and basal ganglia related to depression. While resting state connectivity abnormalities have been frequently reported in depression, it has not been possible to directly link these findings to reward-learning studies. Here, we tested two main hypotheses. First, mood symptoms are associated with blunted striatal reward prediction error signals in a large community-based sample of recovered and currently ill patients, similar to reports from a number of studies. Second, event-related directed medial prefrontal cortex to basal ganglia effective connectivity is abnormally increased or decreased related to the severity of mood symptoms. Using a Research Domain Criteria approach, data were acquired from a large community-based sample of subjects who participated in a probabilistic reward learning task during event-related functional MRI. Computational modelling of behaviour, model-free and model-based functional MRI, and effective connectivity dynamic causal modelling analyses were used to test hypotheses. Increased depressive symptom severity was related to decreased reward signals in areas which included the nucleus accumbens in 475 participants. Decreased reward-related effective connectivity from the medial prefrontal cortex to striatum was associated with increased depressive symptom severity in 165 participants. Decreased striatal activity may have been due to decreased cortical to striatal connectivity consistent with glutamatergic and cortical-limbic related theories of depression and resulted in reduced direct pathway basal ganglia output. Further study of basal ganglia pathophysiology is required to better understand these abnormalities in patients with depressive symptoms and syndromes.