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The global ageing population and the long prodromal period for the development of cognitive decline and dementia brings a need to understand the antecedents of both successful and impaired cognitive ageing. It is increasingly apparent that the trajectory of risk-factor change, as well as the level of the risk factor, may be associated with an increased or decreased risk of cognitive decline or dementia.
Our aim was to summarise the published evidence and to generate hypotheses related to risk-factor trajectories and risk of incident cognitive decline or dementia.
We collated data from longitudinal observational studies relating to trajectory of blood pressure, obesity and cholesterol and later cognitive decline or dementia using standard systematic review methodology. The databases MEDLINE, Embase and PsycINFO were searched from inception to 26 April 2018.
Thirteen articles were retained for inclusion. Analytical methods varied. Our summary of the current evidence base suggests that first body mass index and then blood pressure rises and then falls more steeply in those who go on to develop dementia. The evidence for cholesterol was less consistent.
Based on our review we present the hypothesis that weight falls around 10 years and blood pressure around 5 years before diagnosis. Confirmatory work is required. However, characterisation of risk according to combinations and patterns of risk factors may ultimately be integrated into the assessments used to identify those at risk of receiving a diagnosis of cognitive decline or dementia in late life.
This study is aimed at developing a Rural Primary Health Care (PHC) Model for delivering comprehensive PHC for dementia in rural settings and addressing the gap in knowledge about disseminating and implementing evidence-based dementia care in a rural PHC context.
Limited access to specialists and services in rural areas leads to increased responsibility for dementia diagnosis and management in PHC, yet a gap exists in evidence-based best practices for rural dementia care.
Elements of the Rural PHC Model for Dementia were based on seven principles of effective PHC for dementia identified from published research and organized into three domains: team-based care, decision support, and specialist-to-provider support. Since 2013 the researchers have collaborated with a rural PHC team in a community of 1000 people in the Canadian province of Saskatchewan to operationalize these elements in ways that were feasible in the local context. The five-step approach included: building relationships; conducting a problem analysis/needs assessment; identifying core and adaptable elements of a decision support tool embedded in the model and resolving applicability issues; implementing and adapting the intervention with local stakeholders; and sustaining the model while incrementally scaling up.
Developing and sustaining relationships at regional and PHC team levels was critical. A comprehensive needs assessment identified challenges related to all domains of the Rural PHC Model. An existing decision support tool for dementia diagnosis and management was adapted and embedded in the team’s electronic medical record. Strategies for operationalizing other model elements included integrating team-based care co-ordination into the decision support tool and family-centered case conferences. Research team specialists provided educational sessions on topics identified by the PHC team. This paper provides an example of a community-based process for adapting evidence-based practice principles to a real-world setting.
To profile discretionary food and beverage (DF) consumption among Australian adults.
Cross-sectional analysis. Dietary and sociodemographic data were used to profile DF intake. Prevalence of DF consumption, DF servings (1 serving=600 kJ), nutrient contribution from DF and top DF food groups by self-reported eating occasions were determined. DF consumers (>0 g) were classified according to quartile of DF intake and general linear models adjusted for age and sex were used to determine associations.
2011–12 National Nutrition and Physical Activity Survey (NNPAS).
Adults aged ≥19 years (n 9341) who participated in the NNPAS 2011–12.
Most adults consumed DF (98 %) and over 60 % exceeded 3 DF servings/d, with a mean of 5·0 (se 0·0) DF servings/d. Cakes, muffins, scones, cake-type desserts contributed the most DF energy (8·4 %) of all food groups, followed by wines (8·1 %), pastries (8·0 %) and beers (6·1 %), with all these food groups consumed in large portions (2·3–3·0 DF servings). Lunch and dinner together contributed 45 % of total DF energy intake. High DF consumers had an average of 10 DF servings, and this group contained more younger adults, males, low socio-economic status, lower usual fruit intake and higher mean waist circumference, but not higher BMI.
A focus on DF consumed in large portions at lunch and dinner may help improve interventions aimed at reducing DF intake and addressing negative adiposity-related measures found in high DF consumers.
The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition methods have been applied recently to predict many psychiatric disorders, these techniques have not been utilized to predict subtypes of posttraumatic stress disorder (PTSD), including the dissociative subtype of PTSD (PTSD + DS).
Using Multiclass Gaussian Process Classification within PRoNTo, we examined the classification accuracy of: (i) the mean amplitude of low-frequency fluctuations (mALFF; reflecting spontaneous neural activity during rest); and (ii) seed-based amygdala complex functional connectivity within 181 participants [PTSD (n = 81); PTSD + DS (n = 49); and age-matched healthy trauma-unexposed controls (n = 51)]. We also computed mass-univariate analyses in order to observe regional group differences [false-discovery-rate (FDR)-cluster corrected p < 0.05, k = 20].
We found that extracted features could predict accurately the classification of PTSD, PTSD + DS, and healthy controls, using both resting-state mALFF (91.63% balanced accuracy, p < 0.001) and amygdala complex connectivity maps (85.00% balanced accuracy, p < 0.001). These results were replicated using independent machine learning algorithms/cross-validation procedures. Moreover, areas weighted as being most important for group classification also displayed significant group differences at the univariate level. Here, whereas the PTSD + DS group displayed increased activation within emotion regulation regions, the PTSD group showed increased activation within the amygdala, globus pallidus, and motor/somatosensory regions.
The current study has significant implications for advancing machine learning applications within the field of psychiatry, as well as for developing objective biomarkers indicative of diagnostic heterogeneity.
Transient storage and erosion of valley fills, or sediment buffering, is a fundamental but poorly quantified process that may significantly bias fluvial sediment budgets and marine archives used for paleoclimatic and tectonic reconstructions. Prolific sediment buffering is now recognized to occur within the mountainous upper Indus River headwaters and is quantified here for the first time using optically stimulated luminescence dating, petrography, detrital zircon U-Pb geochronology, and morphometric analysis to define the timing, provenance, and volumes of prominent valley fills. This study finds that climatically modulated sediment buffering occurs over 103–104 yr time scales and results in biases in sediment compositions and volumes. Increased sediment storage coincides with strong phases of summer monsoon and winter westerlies precipitation over the late Pleistocene (32–25 ka) and mid-Holocene (~8–6 ka), followed by incision and erosion with monsoon weakening. Glacial erosion and periglacial frost-cracking drive sediment production, and monsoonal precipitation mediates sediment evacuation, in contrast to the arid Transhimalaya and monsoonal frontal Himalaya. Plateau interior basins, although volumetrically large, lack transport capacity and are consequently isolated from the modern Indus River drainage. Marginal plateau catchments that both efficiently produce and evacuate sediment may regulate the overall compositions and volumes of exported sediment from the Himalayan rain shadow.
Wind tunnel measurements of snowdrift in a turbulent, logarithmic velocity boundary layer have been made in Davos, Switzerland, using natural snow. Regression analysis gives the drift threshold friction velocity (u*t), assuming an exponential drift profile and a simple drift to friction velocity relationship. Measurements over 15 snow covers show that u*t is influenced more by snow density and particle size than by ambient temperature and humidity, and varies from 0.27 to 0.69 ms–1. Schmidt’s threshold algorithm and a modified version used in SNOWPACK (a snow-cover model) agree well with observations if small bond sizes are assumed. Using particle hydraulic diameters, obtained from image processing, Bagnold’s threshold parameter is 0.18. Roughness lengths (z0) vary between snow covers but are constant until the start of drift. Threshold roughness lengths are proportional to . The influence of macroscopic objects on the roughness length is shown by the lower values measured over the smooth and flat snow surface of the wind tunnel (0.04 ≤ z0 ≤ 0.13 mm), compared to field measurements. Mean drifting-snow grain sizes for mainly new and partly decomposed snow are 100–175 μm, and independent of surface particle size.
Vitamin D deficiency (plasma 25-hydroxycholecalciferol (25(OH)D)<50 nmol/l) is highly prevalent, increases risk of non-communicable diseases (NCD) and associates with increased oxidative stress in obese subjects, the elderly and patients suffering from NCD. If confirmed as an independent driver of oxidative stress, nutritional and other public health strategies to improve vitamin D status would be strongly supported. We investigated vitamin D/oxidative stress links without the confounding effects of advanced age, obesity, smoking or pre-existing disease. Plasma 25(OH)D and biomarkers of oxidative stress and antioxidant status (plasma allantoin, oxidised LDL, ferric reducing antioxidant power (FRAP), ascorbic acid, urine 8-oxo-7,8-dihydro-2'-deoxyguanosine) were measured in fasting samples from 196 consenting, healthy adults aged 18–26 years. Correlation between 25(OH)D and each biomarker as well as biomarker differences across 25(OH)D quartiles and groups (<25/25–49/≥50 nmol/l) were investigated. Median 25(OH)D was 40 nmol/l; >70 % of participants were vitamin D deficient. No significant correlations and no biomarker differences across 25(OH)D quartiles or groups were seen except for total antioxidant status. A weak direct association (r 0·252, P<0·05) was observed between 25(OH)D and FRAP, and those in the lowest 25(OH)D quartile and group had significantly lower FRAP values. Results did not reveal a clear link between vitamin D status and oxidative stress biomarkers in the absence of advanced age, obesity and disease, though some evidence of depleted antioxidant status in those with vitamin D deficiency was seen. Poor antioxidant status may pre-date increased oxidative stress. Study of effects of correction of deficiency on antioxidant status and oxidative stress in vitamin D-deficient but otherwise healthy subjects is needed.
The CMP challenges for advanced technology nodes are discussed. Global and local uniformity challenges and their cumulative effects are presented. Uniformity improvements for advanced node integration were achieved through slurry, pad and platen optimization, innovative integration schemes, the reduction of incoming variation and the reduction of cumulative effects. We discuss reduction of typical CMP defect types. Defects resulting from simple mechanisms (foreign material, polish residues) and those resulting from chemical and physical interactions (corrosion, chemical attack, scratches, physical migration) and strategies for control are studied. Defectivity reduction measures include new post-CMP clean chemicals, new slurries and pads and reduction of incoming defectivity. Finally we discuss an observed tradeoff between good defectivity and good uniformity.
The success of scaling out depends on a clear understanding of the factors that affect adoption of grain legumes and account for the dynamism of those factors across heterogeneous contexts of sub-Saharan Africa. We reviewed literature on adoption of grain legumes and other technologies in sub-Saharan Africa and other developing countries. Our review enabled us to define broad factors affecting different components of the scaling out programme of N2Africa and the scales at which those factors were important. We identified three strategies for managing those factors in the N2Africa scaling out programme: (i) testing different technologies and practices; (ii) evaluating the performance of different technologies in different contexts; and (iii) monitoring factors that are difficult to predict. We incorporated the review lessons in a design to appropriately target and evaluate technologies in multiple contexts across scales from that of the farm to whole countries. Our implementation of this design has only been partially successful because of competing reasons for selecting activity sites. Nevertheless, we observe that grain legume species have been successfully targeted for multiple biophysical environments across sub-Saharan Africa, and to social and economic contexts within countries. Rhizobium inoculant and legume specific fertiliser blends have also been targeted to specific contexts, although not in all countries. Relatively fewer input and output marketing models have been tested due to public–private partnerships, which are a key mechanism for dissemination in the N2Africa project.
To identify risk factors for surgical site infections (SSIs) after spine operations.
Case-control study of SSIs among patients undergoing spine operations.
An academic health center.
We studied patients undergoing spinal fusions or laminectomies at the University of Iowa Hospitals and Clinics from January 1, 2007, through June 30, 2009. We included patients who acquired SSIs meeting the National Healthcare Safety Network definition. We randomly selected controls among patients who had spine operations during the study period and did not meet the SSI definition.
In total, 54 patients acquired SSIs after 2,309 spine operations (2.3 per 100 procedures). SSIs were identified a median of 20 days after spinal fusions and 17 days after laminectomies; 90.7% were identified after discharge and 72.2% were deep incisional or organ-space infections. Staphylococcus aureus caused 53.7% of SSIs. Of patients with SSIs, 64.9% (fusion) and 70.6% (laminectomy) were readmitted and 59.5% (fusion) and 64.7% (laminectomy) underwent reoperation. By multivariable analysis, increased body mass index, Surgical Department A, fusion of 4–8 vertebrae, and operation at a thoracic or lumbar/sacral level were significant risk factors for SSIs after spinal fusions. Lack of private insurance and hypertension were significant risk factors for SSIs after laminectomies. Surgeons from Department A were more likely to use nafcillin or vancomycin for perioperative prophylaxis and to do more multilevel fusions than surgeons from Department B.
SSIs after spine operations significantly increase utilization of healthcare resources. Possible remediable risk factors include obesity, hypertension, and perioperative antimicrobial prophylaxis.
We probe the relationship between surface magnetic fields and the X-ray emitting corona in the rapidly rotating star, AB Dor. Circularly polarised spectra have been inverted to produce a surface (photospheric) magnetic field map. This surface map has been extrapolated to model AB Dor's coronal field topology and X-ray light curve. Chandra/LETG light curves of AB Dor from the same epoch show intrinsic variability at the 30% level. Period analysis indicates a fraction of this is due to rotational modulation. We measure velocity shifts in emission line centroids as a function of Prot and find evidence of rotational modulation (max. vel. ∼ 40 ± 13km s—1). This modulation may indicate the presence of a localised X-ray emitting region at mid-to-high latitudes.
The subsurface exploration of other planetary bodies can be used to unravel their geological history and assess their habitability. On Mars in particular, present-day habitable conditions may be restricted to the subsurface. Using a deep subsurface mine, we carried out a program of extraterrestrial analog research – MINe Analog Research (MINAR). MINAR aims to carry out the scientific study of the deep subsurface and test instrumentation designed for planetary surface exploration by investigating deep subsurface geology, whilst establishing the potential this technology has to be transferred into the mining industry. An integrated multi-instrument suite was used to investigate samples of representative evaporite minerals from a subsurface Permian evaporite sequence, in particular to assess mineral and elemental variations which provide small-scale regions of enhanced habitability. The instruments used were the Panoramic Camera emulator, Close-Up Imager, Raman spectrometer, Small Planetary Linear Impulse Tool, Ultrasonic drill and handheld X-ray diffraction (XRD). We present science results from the analog research and show that these instruments can be used to investigate in situ the geological context and mineralogical variations of a deep subsurface environment, and thus habitability, from millimetre to metre scales. We also show that these instruments are complementary. For example, the identification of primary evaporite minerals such as NaCl and KCl, which are difficult to detect by portable Raman spectrometers, can be accomplished with XRD. By contrast, Raman is highly effective at locating and detecting mineral inclusions in primary evaporite minerals. MINAR demonstrates the effective use of a deep subsurface environment for planetary instrument development, understanding the habitability of extreme deep subsurface environments on Earth and other planetary bodies, and advancing the use of space technology in economic mining.
Depressive symptomology is now widely recognized as a key risk factor for falls. The evidence regarding the impact of major depressive disorder (MDD) on falls is unclear. A systematic review and exploratory meta-analysis was undertaken to explore the relationship between MDD and falls.
Major electronic database were searched from inception till April 2015. Studies that defined MDD and measured falls prospectively in older adults (≥60 years) were included. Studies relying on depressive symptomology alone were excluded. The methodological quality of included articles was assessed and study findings were synthesized using an exploratory meta-analysis.
From a potential of 415 articles, only three studies met the inclusion criteria. This included 976 unique older adults with a range of mean age from ≥65 to 83 years. The methodological quality of included studies was satisfactory. None of the included studies’ primary aim was to investigate the relationship between MDD and falls. The exploratory meta-analysis demonstrated older adults with MDD are at increased risk of falling compared to non-depressed older adults (odds ratio (OR) 4.0, 95% CI 2.0–8.1, I2 = 60%, n = 976).
There is a paucity of research considering falls in older adults with MDD. Our results demonstrate that the odds of falling appear to be greater among people with MDD (OR 4.0) than in previous meta-analyses that have only considered subthreshold depressive symptoms. Given the distinct nature and challenges with MDD, more research is required to better understand the falls risk in this group.