The experiences of women with polycystic ovary syndrome on a very low-calorie diet

The research was funded by an educational grant from LighterLife. Broom was the Medical Director for LighterLife at the time of the research. Johnson is the Head of Nutrition and Research at LighterLife. The authors report no other conflicts of interest in this work.Peer reviewedPublisher PD

Subtidal seagrass detector: development of a deep learning seagrass detection and classification model for seagrass presence and density in diverse habitats from underwater photoquadrats

This paper presents the development and evaluation of a Subtidal Seagrass Detector (the Detector). Deep learning models were used to detect most forms of seagrass occurring in a diversity of habitats across the northeast Australian seascape from underwater images and classify them based on how much the cover of seagrass was present. Images were collected by scientists and trained contributors undertaking routine monitoring using drop-cameras mounted over a 50 x 50 cm quadrat. The Detector is composed of three separate models able to perform the specific tasks of: detecting the presence of seagrass (Model #1); classify the seagrass present into three broad cover classes (low, medium, high) (Model #2); and classify the substrate or image complexity (simple of complex) (Model #3). We were able to successfully train the three models to achieve high level accuracies with 97%, 80.7% and 97.9%, respectively. With the ability to further refine and train these models with newly acquired images from different locations and from different sources (e.g. Automated Underwater Vehicles), we are confident that our ability to detect seagrass will improve over time. With this Detector we will be able rapidly assess a large number of images collected by a diversity of contributors, and the data will provide invaluable insights about the extent and condition of subtidal seagrass, particularly in data-poor areas

Quetiapine in refractory hyperactive and mixed intensive care delirium: a case series

IntroductionDelirium affects up to 80% of patients admitted to intensive care units (ICUs) and contributes to increased morbidity and mortality. Haloperidol is the gold standard for treatment, although quetiapine has been successfully used in the management of delirium.MethodsWe conducted a retrospective study of patients admitted to the ICU between February 2008 and May 2010 who were prescribed quetiapine by the attending clinician. Data collected included demographics, history of drug and/or alcohol dependence, ICU and hospital length of stay, length of mechanical ventilation and the duration of treatment with sedatives and medications for delirium. The daily dose of quetiapine was recorded. Hyperactive or mixed delirium was identified by a validated chart review and a Richmond Agitation Sedation Scale (RASS) score persistently greater than 1 for 48 hours despite therapy.ResultsSeventeen patients were included. Delirium onset occurred after a median of five days. Patients were being given at least four agents for delirium prior to the introduction of quetiapine, and they had a median RASS score of 3. Quetiapine was initiated at a 25 mg daily dose and titrated to a median daily dose of 50 mg. The median duration of delirium prior to quetiapine therapy was 15 days. Quetiapine commencement was associated with a reduction in the need for other medications (within 0 to 6 days) and resolution of delirium within a median of four days. Adverse events included somnolence and transient hypotension.ConclusionsThis case series provides an initial effort to explore a possible role for quetiapine in the management of refractory hyperactive and mixed ICU delirium

Synthesizing 35 years of seagrass spatial data from the Great Barrier Reef World Heritage Area, Queensland, Australia

The Great Barrier Reef World Heritage Area in Queensland, Australia contains globally significant seagrasses supporting key ecosystem services, including habitat and food for threatened populations of dugong and turtle. We compiled 35 years of data in a spatial database, including 81,387 data points with georeferenced seagrass and species presence/absence, depth, dominant sediment type, and collection date. We include data collected under commercial contract that have not been publicly available. Twelve seagrass species were recorded. The deepest seagrass was found at 76 m. Seagrass meadows are at risk from anthropogenic, climate and weather processes. Our database is a valuable resource that provides coastal managers and the global marine community with a long-term spatial resource describing seagrass populations from the mid-1980s against which to benchmark change. We address the data issues involved in hindcasting over 30 years to ensure confidence in the accuracy and reliability of data included

Quantification of hepatic steatosis with 3-T MR imaging: Validation in ob/ob mice

Purpose: To validate quantitative imaging techniques used to detect and measure steatosis with magnetic resonance (MR) imaging in an ob/ob mouse model of hepatic steatosis. Materials and Methods: The internal research animal and resource center approved this study. Twenty-eight male ob/ob mice in progressively increasing age groups underwent imaging and were subsequently sacrificed. Six ob /+ mice served as control animals. Fat fraction imaging was performed with a chemical shift-based water-fat separation method. The following three methods of conventional fat quantification were compared with imaging: lipid extraction and qualitative and quantitative histologic analysis. Fat fraction images were reconstructed with single- and multiple-peak spectral models of fat and with and without correction for T2* effects. Fat fraction measurements obtained with the different reconstruction methods were compared with the three methods of fat quantification, and linear regression analysis and two-sided and two-sample t tests were performed. Results:Lipid extraction and qualitative and quantitative histologic analysis were highly correlated with the results of fat fraction imaging (r2 = 0.92, 0.87, 0.82, respectively). No significant differences were found between imaging measurements and lipid extraction (P = .06) or quantitative histologic (P = .07) measurements when multiple peaks of fat and T2* correction were included in image reconstruction. Reconstructions in which T2* correction, accurate spectral modeling, or both were excluded yielded lower agreement when compared with the results yielded by other techniques. Imaging measurements correlated particularly well with histologic grades in mice with low fat fractions (intercept, -1.0% ± 1.2 [standard deviation ]). Conclusion: MR imaging can be used to accurately quantify fat in vivo in an animal model of hepatic steatosis and may serve as a quantitative biomarker of hepatic steatosis. © RSNA, 2010

Pollen season trends as markers of climate change impact:Betula, Quercus and Poaceae

The incidences of respiratory allergies are at an all-time high. Pollen aeroallergens can reflect changing climate, with recent studies in Europe showing some, but not all, pollen types are increasing in severity, season duration and experiencing an earlier onset. This study aimed to identify pollen trends in the UK over the last twenty-six years for a range of pollen sites, with a focus on the key pollen types of Poaceae (grass), Betula (birch) and Quercus (oak) and to examine the relationship of these trends with meteorological factors. Betula pollen seasons show no significant trends for onset, first high day or duration but increasing pollen production in the Midlands region of the UK is being driven by warmer temperatures in the previous June and July. Quercus pollen seasons are starting earlier, due to increasing temperature and sunshine totals in April, but are not becoming more severe. The seasons are lasting longer, although no significant climate drivers for this were identified. The first high day of the Poaceae pollen season is occurring earlier in central UK regions due to an increasing trend for all temperature variables in the previous December, January, April, May and June. Severity and duration of the season show no significant trends and are spatially and temporally variable. Important changes are occurring in the UK pollen seasons that will impact on the health of respiratory allergy sufferers, with more severe Betula pollen seasons and longer Quercus pollen seasons. Most of the changes identified were caused by climate drivers of increasing temperature and sunshine total. However, Poaceae pollen seasons are neither becoming more severe nor longer. The reasons for this included a lack of change in some monthly meteorological variables, or land-use change, such as grassland being replaced by urban areas or woodland

Combination of complex-based and magnitude-based multiecho water-fat separation for accurate quantification of fat-fraction

Multipoint water-fat separation techniques rely on different water-fat phase shifts generated at multiple echo times to decompose water and fat. Therefore, these methods require complex source images and allow unambiguous separation of water and fat signals. However, complex-based water-fat separation methods are sensitive to phase errors in the source images, which may lead to clinically important errors. An alternative approach to quantify fat is through magnitude-based methods that acquire multiecho magnitude images. Magnitude-based methods are insensitive to phase errors, but cannot estimate fat-fraction greater than 50%. In this work, we introduce a water-fat separation approach that combines the strengths of both complex and magnitude reconstruction algorithms. A magnitude-based reconstruction is applied after complex-based water-fat separation to removes the effect of phase errors. The results from the two reconstructions are then combined. We demonstrate that using this hybrid method, 0-100% fat-fraction can be estimated with improved accuracy at low fat-fractions. Magn Reson Med, 2011. © 2011 Wiley-Liss, Inc. Copyright © 2011 Wiley-Liss, Inc

The First National Study of Neighborhood Parks

An extensive infrastructure of neighborhood parks supports leisure time physical activity in most U.S. cities; yet, most Americans do not meet national guidelines for physical activity. Neighborhood parks have never been assessed nationally to identify their role in physical activity

T1 independent, T2* corrected chemical shift based fat-water separation with multi-peak fat spectral modeling is an accurate and precise measure of hepatic steatosis

Purpose: To determine the precision and accuracy of hepatic fat-fraction measured with a chemical shift-based MRI fat-water separation method, using single-voxel MR spectroscopy (MRS) as a reference standard. Materials and Methods: In 42 patients, two repeated measurements were made using a T 1-independent, T2 *-corrected chemical shift-based fat-water separation method with multi-peak spectral modeling of fat, and T 2-corrected single voxel MR spectroscopy. Precision was assessed through calculation of Bland-Altman plots and concordance correlation intervals. Accuracy was assessed through linear regression between MRI and MRS. Sensitivity and specificity of MRI fat-fractions for diagnosis of steatosis using MRS as a reference standard were also calculated. Results: Statistical analysis demonstrated excellent precision of MRI and MRS fat-fractions, indicated by 95% confidence intervals (units of absolute percent) of [-2.66%,2.64%] for single MRI ROI measurements, [-0.81%,0.80%] for averaged MRI ROI, and [-2.70%,2.87%] for single-voxel MRS. Linear regression between MRI and MRS indicated that the MRI method is highly accurate. Sensitivity and specificity for detection of steatosis using averaged MRI ROI were 100% and 94%, respectively. The relationship between hepatic fat-fraction and body mass index was examined. Conclusion: Fat-fraction measured with T1-independent T 2*-corrected MRI and multi-peak spectral modeling of fat is a highly precise and accurate method of quantifying hepatic steatosis. © 2011 Wiley-Liss, Inc