A Study of Hα Line Profile Variations in β Lyr

We examine over 160 archival Hα spectra from the Ritter Observatory for the interacting binary β Lyr obtained between 1996 and 2000. The emission is characteristically double-peaked, but asymmetric, and with an absorption feature that is persistently blueshifted. Using a set of simplifying assumptions, phase varying emission line profiles are calculated for Hα formed entirely in a Keplerian disk, and separately for the line formed entirely from an off-center bipolar flow. However, a dynamic spectrum of the data indicates that the blueshifted feature is not always present, and the data are even suggestive of a drift of the feature in velocity shift. We explore whether a circumbinary envelope, hot spot on the accretion disk, or accretion stream could explain the observations. While none are satisfactory, an accretion stream explanation is somewhat promising

Improving the predictions of computational models of convection-enhanced drug delivery by accounting for diffusion non-gaussianity

Convection-enhanced delivery (CED) is an innovative method of drug delivery to the human brain, that bypasses the blood-brain barrier by injecting the drug directly into the brain. CED aims to target pathological tissue for central nervous system conditions such as Parkinson's and Huntington's disease, epilepsy, brain tumors, and ischemic stroke. Computational fluid dynamics models have been constructed to predict the drug distribution in CED, allowing clinicians advance planning of the procedure. These models require patient-specific information about the microstructure of the brain tissue, which can be collected non-invasively using magnetic resonance imaging (MRI) pre-infusion. Existing models employ the diffusion tensor, which represents Gaussian diffusion in brain tissue, to provide predictions for the drug concentration. However, those predictions are not always in agreement with experimental observations. In this work we present a novel computational fluid dynamics model for CED that does not use the diffusion tensor, but rather the diffusion probability that is experimentally measured through diffusion MRI, at an individual-participant level. Our model takes into account effects of the brain microstructure on the motion of drug molecules not taken into account in previous approaches, namely the restriction and hindrance that those molecules experience when moving in the brain tissue, and can improve the drug concentration predictions. The duration of the associated MRI protocol is 19 min, and therefore feasible for clinical populations. We first prove theoretically that the two models predict different drug distributions. Then, using in vivo high-resolution diffusion MRI data from a healthy participant, we derive and compare predictions using both models, in order to identify the impact of including the effects of restriction and hindrance. Including those effects results in different drug distributions, and the observed differences exhibit statistically significant correlations with measures of diffusion non-Gaussianity in brain tissue. The differences are more pronounced for infusion in white-matter areas of the brain. Using experimental results from the literature along with our simulation results, we show that the inclusion of the effects of diffusion non-Gaussianity in models of CED is necessary, if reliable predictions that can be used in the clinic are to be generated by CED models

Improving the Predictions of Computational Models of Convection-Enhanced Drug Delivery by Accounting for Diffusion Non-gaussianity

Convection-enhanced delivery (CED) is an innovative method of drug delivery to the human brain, that bypasses the blood-brain barrier by injecting the drug directly into the brain. CED aims to target pathological tissue for central nervous system conditions such as Parkinson's and Huntington's disease, epilepsy, brain tumors, and ischemic stroke. Computational fluid dynamics models have been constructed to predict the drug distribution in CED, allowing clinicians advance planning of the procedure. These models require patient-specific information about the microstructure of the brain tissue, which can be collected non-invasively using magnetic resonance imaging (MRI) pre-infusion. Existing models employ the diffusion tensor, which represents Gaussian diffusion in brain tissue, to provide predictions for the drug concentration. However, those predictions are not always in agreement with experimental observations. In this work we present a novel computational fluid dynamics model for CED that does not use the diffusion tensor, but rather the diffusion probability that is experimentally measured through diffusion MRI, at an individual-participant level. Our model takes into account effects of the brain microstructure on the motion of drug molecules not taken into account in previous approaches, namely the restriction and hindrance that those molecules experience when moving in the brain tissue, and can improve the drug concentration predictions. The duration of the associated MRI protocol is 19 min, and therefore feasible for clinical populations. We first prove theoretically that the two models predict different drug distributions. Then, using in vivo high-resolution diffusion MRI data from a healthy participant, we derive and compare predictions using both models, in order to identify the impact of including the effects of restriction and hindrance. Including those effects results in different drug distributions, and the observed differences exhibit statistically significant correlations with measures of diffusion non-Gaussianity in brain tissue. The differences are more pronounced for infusion in white-matter areas of the brain. Using experimental results from the literature along with our simulation results, we show that the inclusion of the effects of diffusion non-Gaussianity in models of CED is necessary, if reliable predictions that can be used in the clinic are to be generated by CED models

A global database of lake surface temperatures collected by in situ and satellite methods from 1985–2009

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues

Rapid and highly variable warming of lake surface waters around the globe

In this first worldwide synthesis of in situ and satellite‐derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice‐covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice‐free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes

Lake-wide physical and biological trends associated with warming in Lake Baikal

Eutrophication and warming of lakes are occurring globally. Lake Baikal, a large ancient lake composed of three basins, has recently experienced benthic eutrophication at local sites and lake warming in the south basin. Here, we look for signals of warming and pelagic eutrophication across the entire lake using physical and biological data collected at a subset of 79 stations sampled ca. annually (1977–2003) during the period of summer stratification. Lake-wide, surface waters warmed 2.0 °C; and, consistent with this warming, the abundance of two warm-water, cosmopolitan zooplankton taxa increased between two (pelagic cladocerans) and 12-fold (Cyclops kolensis). C. kolensis increased throughout the lake, whereas cladocerans increased significantly only in the north basin. In contrast, abundance of the cold-water endemic copepod, Epischura baikalensis, that dominates the crustacean zooplankton community, did not change. With the exception of one coastal station in the north basin, there is no evidence of pelagic eutrophication. Although chlorophyll concentrations increased 46% lake-wide (0.82 to 1.20 μg/L), the increasing trend was significant only in the south basin. Surprisingly, mean Secchi transparency increased by 1.4 m lake-wide across the 26-year time series with significant deepening of water transparency occurring in the central and north basins. This suggests a decline in productivity in the north and middle basins, but an increase in the south basin. Taken together, these findings suggest that physical and biological changes associatedwithwarming have occurred in Lake Baikal, butwide-spread pelagic eutrophication in the lake\u27s three basins has not

"I feel so stupid because I can't give a proper answer ..." How older adults describe chronic pain: a qualitative study

Background - Over 50% of older adults experience chronic pain. Poorly managed pain threatens independent functioning, limits social activities and detrimentally affects emotional wellbeing. Yet, chronic pain is not fully understood from older adults’ perspectives; subsequently, pain management in later life is not necessarily based on their priorities or needs. This paper reports a qualitative exploration of older adults’ accounts of living with chronic pain, focusing on how they describe pain, with a view to informing approaches to its assessment. Methods - Cognitively intact men and women aged over sixty-five who lived in the community opted into the study through responding to advertisements in the media and via contacts with groups and organisations in North-East Scotland. Interviews were transcribed and thematically analysed using a framework approach. Results - Qualitative individual interviews and one group interview were undertaken with 23 older adults. Following analysis, the following main themes emerged: diversity in conceptualising pain using a simple numerical score; personalising the meaning of pain by way of stories, similes and metaphors; and, contextualising pain in relation to its impact on activities. Conclusions - The importance of attending to individuals’ stories as a meaningful way of describing pain for older adults is highlighted, suggesting that a narrative approach, as recommended and researched in other areas of medicine, may usefully be applied in pain assessment for older adults. Along with the judicious use of numerical tools, this requires innovative methods to elicit verbal accounts, such as using similes and metaphors to help older adults describe and discuss their experience, and contextualising the effects of pain on activities that are important to them

Surface-based tracking for short association fibre tractography

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed

Three Novel Pigmentation Mutants Generated by Genome-Wide Random ENU Mutagenesis in the Mouse

Three mutant mice with pigmentation phenotypes were recovered from a genomewide random mouse chemical mutagenesis study. White toes (Whto; MGI:1861986), Belly spot and white toes (Bswt; MGI:2152776) and Dark footpads 2 (Dfp2; MGI:1861991) were identified following visual inspection of progeny from a male exposed to the point mutagen ethylnitrosourea (ENU). In order to rapidly localize the causative mutations, genome-wide linkage scans were performed on pooled DNA samples from backcross animals for each mutant line. Whto was mapped to proximal mouse chromosome (Mmu) 7 between Cen (the centromere) and D7Mit112 (8.0 cM from the centromere), Bswt was mapped to centric Mmul between D1Mit214 (32.1 cM) and D1Mit480 (32.8 cM) and Dfp2 was mapped to proximalMmu4 between Cen and D4Mit18 (5.2 cM). Whto, Bswt and Dfp2 may provide novel starting points in furthering the elucidation of genetic and biochemical pathways relevant to pigmentation and associated biological processes