Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska

Remotely sensed snow cover observations provide an opportunity to improve operational snowmelt and streamflow forecasting in remote regions. This is particularly true in Alaska, where remote basins and a spatially and temporally sparse gaging network plague efforts to understand and forecast the hydrology of subarctic boreal basins and where climate change is leading to rapid shifts in basin function. In this study, the operational framework employed by the United States (US) National Weather Service, including the Alaska Pacific River Forecast Center, is adapted to integrate Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed observations of fractional snow cover area (fSCA) to determine if these data improve streamflow forecasts in interior Alaska river basins. Two versions of MODIS fSCA are tested against a base case extent of snow cover derived by aerial depletion curves: the MODIS 10A1 (MOD10A1) and the MODIS Snow Cover Area and Grain size (MODSCAG) product over the period 2000–2010. Observed runoff is compared to simulated runoff to calibrate both iterations of the model. MODIS-forced simulations have improved snow depletion timing compared with snow telemetry sites in the basins, with discernable increases in skill for the streamflow simulations. The MODSCAG fSCA version provides moderate increases in skill but is similar to the MOD10A1 results. The basins with the largest improvement in streamflow simulations have the sparsest streamflow observations. Considering the numerous low-quality gages (discontinuous, short, or unreliable) and ungauged systems throughout the high-latitude regions of the globe, this result is valuable and indicates the utility of the MODIS fSCA data in these regions. Additionally, while improvements in predicted discharge values are subtle, the snow model better represents the physical conditions of the snowpack and therefore provides more robust simulations, which are consistent with the US National Weather Service's move toward a physically based National Water Model. Physically based models may also be more capable of adapting to changing climates than statistical models corrected to past regimes. This work provides direction for both the Alaska Pacific River Forecast Center and other forecast centers across the US to implement remote-sensing observations within their operational framework, to refine the representation of snow, and to improve streamflow forecasting skill in basins with few or poor-quality observations.</p

Predicting forefoot-orthosis interactions in rheumatoid arthritis using computational modelling

Foot orthoses are prescribed to reduce forefoot plantar pressures and pain in people with rheumatoid arthritis. Computational modelling can assess how the orthoses affect internal tissue stresses, but previous studies have focused on a single healthy individual. This study aimed to ascertain whether simplified forefoot models would produce differing biomechanical predictions at the orthotic interface between people with rheumatoid arthritis of varying severity, and in comparison to a healthy control. The forefoot models were developed from magnetic resonance data of 13 participants with rheumatoid arthritis and one healthy individual. Measurements of bony morphology and soft tissue thickness were taken to assess deformity. These were compared to model predictions (99th% shear strain and plantar pressure, max. pressure gradient, volume of soft tissue over 10% shear strain), alongside clinical data including body mass index and Leeds Foot Impact Scale–Impairment/Footwear score (LFIS-IF). The predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models’ range. Medial first metatarsal head curvature moderately correlated to all model predicted outcomes (0.529 < r < 0.574, 0.040 < p < 0.063). BMI strongly correlated to all model predictions except pressure gradients (0.600 < r < 0.652, p < 0.05). There were no apparent relationships between model predictions and instances of bursae, erosion and synovial hypertrophy or LFIS-IF score. The forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. Models capable of predicting subject specific biomechanical orthotic interactions could be used in the future to inform more personalised devices to protect skin and soft tissue health. While the model results did not clearly correlate with all clinical measures, there was a wide range in model predictions and morphological measures across the participants. Thus, the need for assessment of foot orthoses across a population, rather than for one individual, is clear

Longitudinal assessment of cognitive and psychosocial functioning after Hurricanes Katrina and Rita: Exploring disaster impact on middle-aged, older, and oldest-old adults

The authors examined the effects of Hurricanes Katrina and Rita on cognitive and psychosocial functioning in a lifespan sample of adults 6-14 months after the storms. Participants were recruited from the Louisiana Healthy Aging Study. Most were assessed during the immediate impact period and retested for this study. Analyses of pre- and post-disaster cognitive data confirmed that storm-related decrements in working memory for middle-aged and older adults observed in the immediate impact period had returned to pre-hurricane levels in the post-disaster recovery period. Middle-aged adults reported more storm-related stressors and greater levels of stress than the two older groups at both waves of testing. These results are consistent with a burden perspective on post-disaster psychological reactions. © 2012 Wiley Periodicals, Inc

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

The prevalence of foot pain and association with baseline characteristics in people participating in education and supervised exercise for knee or hip osteoarthritis: a cross-sectional study of 26,003 participants from the GLA:D® registry

Background: osteoarthritis (OA) affecting the knee or hip is highly prevalent in the general population and has associated high disease burden. Early identification of modifiable risk factors that prevent, limit, or resolve disease symptoms is critical. Foot pain may represent a potentially modifiable factor however little is known about the prevalence of foot pain in people with knee or hip OA nor whether foot pain is associated with clinical characteristics. The main aim of this study was therefore to determine the prevalence of foot pain in people with knee or hip OA attending an education and supervised exercise-based intervention in Denmark (GLA:D®) and determine if baseline demographic or clinical characteristics are associated with foot pain. Methods: analysis was conducted on baseline data of 26,003 people with symptomatic knee or hip OA completing a pain mannequin as part of the Good Life with osteoArthritis in Denmark (GLA:D®) primary care programme. Odds Ratios (OR) and 95% confidence intervals (CI) were calculated to estimate the strength of association between baseline clinical characteristics (including pain severity in worst knee/hip joint, number of painful knee/hip joints, pain medication use and physical activity level) and the presence of baseline foot pain. Results: twelve percent of participants (n=3,049) reported foot pain. In those people with index knee OA (n= 19,391), knee pain severity (OR 1.01 CI 1.00, 1.01), number of painful knee/hip joints (OR 1.67 CI 1.58, 1.79), and use of pain medication (OR 1.23 CI 1.12, 1.36) were statistically associated with foot pain. Excluding use of pain medication, similar associations were seen in those with index hip OA.Conclusion: twelve percent of people with knee or hip OA participating in GLA:D® had foot pain. Those with worse knee/hip pain, and greater number of painful joints were more likely to report foot pain. This study is the first to demonstrate a significant relationship between clinical characteristics and foot pain in people with knee or hip OA participating in education and supervised exercise. Future investigation should consider the role that foot pain may play on knee and hip related outcomes following therapeutic intervention.<br/

Increased Zinc Availability Enhances Initial Aggregation and Biofilm Formation of Streptococcus pneumoniae

Bacteria growing within biofilms are protected from antibiotics and the immune system. Within these structures, horizontal transfer of genes encoding virulence factors, and promoting antibiotic resistance occurs, making biofilms an extremely important aspect of pneumococcal colonization and persistence. Identifying environmental cues that contribute to the formation of biofilms is critical to understanding pneumococcal colonization and infection. Iron has been shown to be essential for the formation of pneumococcal biofilms; however, the role of other physiologically important metals such as copper, zinc, and manganese has been largely neglected. In this study, we investigated the effect of metals on pneumococcal aggregation and early biofilm formation. Our results show that biofilms increase as zinc concentrations increase. The effect was found to be zinc-specific, as altering copper and manganese concentrations did not affect biofilm formation. Scanning electron microscopy analysis revealed structural differences between biofilms grown in varying concentrations of zinc. Analysis of biofilm formation in a mutant strain lacking the peroxide-generating enzyme pyruvate oxidase, SpxB, revealed that zinc does not protect against pneumococcal H2O2. Further, analysis of a mutant strain lacking the major autolysin, LytA, indicated the role of zinc as a negative regulator of LytA-dependent autolysis, which could affect biofilm formation. Additionally, analysis of cell-cell aggregation via plating and microscopy revealed that high concentrations of zinc contribute to intercellular interaction of pneumococci. The findings from this study demonstrate that metal availability contributes to the ability of pneumococci to form aggregates and subsequently, biofilms