216 research outputs found

    Speckle Space-Time Covariance in High-Contrast Imaging

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    We introduce a new framework for point-spread function (PSF) subtraction based on the spatio-temporal variation of speckle noise in high-contrast imaging data where the sampling timescale is faster than the speckle evolution timescale. One way that space-time covariance arises in the pupil is as atmospheric layers translate across the telescope aperture and create small, time-varying perturbations in the phase of the incoming wavefront. The propagation of this field to the focal plane preserves some of that space-time covariance. To utilize this covariance, our new approach uses a Karhunen-Lo\'eve transform on an image sequence, as opposed to a set of single reference images as in previous applications of Karhunen-Lo\'eve Image Processing (KLIP) for high-contrast imaging. With the recent development of photon-counting detectors, such as microwave kinetic inductance detectors (MKIDs), this technique now has the potential to improve contrast when used as a post-processing step. Preliminary testing on simulated data shows this technique can improve contrast by at least 10-20% from the original image, with significant potential for further improvement. For certain choices of parameters, this algorithm may provide larger contrast gains than spatial-only KLIP.Comment: Accepted to A

    Effectiveness of a Total Meal Replacement Program (OPTIFAST Program) on Weight Loss: Results from the OPTIWIN Study

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    Objective: The aim of this study was to test the effectiveness of the OPTIFAST program (OP), a total meal replacement dietary intervention, compared with a food-based (FB) dietary plan for weight loss. Methods: Participants with BMI 30 to 55 kg/m2, age 18 to 70 years old, were randomized to OP or FB dietary and lifestyle interventions for 26 weeks, followed by a weight-maintenance phase. Outcomes were percent change in body weight (%WL) from baseline to weeks 26 and 52, associated changes in body composition (using dual energy x-ray absorptiometry), and adverse events. Primary analysis used repeated-measures multivariable linear mixed models to compare outcomes between groups in a modified intention-to-treat fashion (mITT). Results: A total of 273 participants (83% of randomized; 135 OP, 138 FB) made up the mITT population. Mean age was 47.1 ± 11.2 years; 82% were female and 71% non-Hispanic white. Baseline BMI was 38.8 ± 5.9 kg/m2. At 26 weeks, OP %WL was 12.4%±0.6% versus 6.0%±0.6% in FB (P <0.001). At 52 weeks, OP %WL was 10.5% ± 0.6% versus 5.5% ± 0.6% in FB (P < 0.001). Fat mass loss was greater for OP; lean mass loss was proportional to total weight loss. There was no difference in serious adverse event rates between groups. Conclusions: Compared with an FB approach, OP was more effective with greater sustained weight loss

    Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems

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    Most current methods for identifying coherent structures in spatially-extended systems rely on prior information about the form which those structures take. Here we present two new approaches to automatically filter the changing configurations of spatial dynamical systems and extract coherent structures. One, local sensitivity filtering, is a modification of the local Lyapunov exponent approach suitable to cellular automata and other discrete spatial systems. The other, local statistical complexity filtering, calculates the amount of information needed for optimal prediction of the system's behavior in the vicinity of a given point. By examining the changing spatiotemporal distributions of these quantities, we can find the coherent structures in a variety of pattern-forming cellular automata, without needing to guess or postulate the form of that structure. We apply both filters to elementary and cyclical cellular automata (ECA and CCA) and find that they readily identify particles, domains and other more complicated structures. We compare the results from ECA with earlier ones based upon the theory of formal languages, and the results from CCA with a more traditional approach based on an order parameter and free energy. While sensitivity and statistical complexity are equally adept at uncovering structure, they are based on different system properties (dynamical and probabilistic, respectively), and provide complementary information.Comment: 16 pages, 21 figures. Figures considerably compressed to fit arxiv requirements; write first author for higher-resolution version

    The Association of 1-Year Weight Loss From Bariatric Surgery and Self-Reported Sleep: A Prospective Cohort

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    OBJECTIVE: This study examined the association of weight loss following bariatric surgery with self-reported sleep quality after accounting for other sleep-related factors. METHODS: Participants were from the Bariatric Experience Long Term (BELONG) study. Participants completed a survey up to 6 months before surgery and approximately 1 year after surgery. The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality. One-year percentage total weight loss (%TWL) was determined from electronic medical records. Covariates included demographics, Charlson Comorbidity Index, geocoded variables to assess neighborhood quality, and physical activity. The authors assessed the association between %TWL at 1 year and PSQI component scores with separate cumulative logit models. RESULTS: There were 997 participants in the analytic cohort. Participants were 86.2% women, 37.0% Hispanic, and 13.7% Black adults. Mean one-year %TWL was 26.3 (SD 8.7). Each 1% increase in %TWL was associated with a 3% better daytime dysfunction score (odds ratio = 1.03; 95% CI: 1.02-1.05) and a 2% better sleep quality score (odds ratio = 1.02; 95% CI: 1.00-1.03). No significant differences were found for the other PSQI components. CONCLUSIONS: Weight loss from bariatric surgery was associated with better self-reported sleep at 1 year. For people undergoing bariatric surgery, there may be an added benefit of better sleep

    Neighborhood Deprivation and Residential Property Values Do Not Affect Weight Loss at 1 or 3 Years After Bariatric Surgery

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    OBJECTIVE: This study examined the association between individual- and neighborhood-level sociodemographic factors and surgical weight loss at 1 year (short term) and 3 years (long term). METHODS: Data were obtained from the baseline survey of the BELONG (Bariatric Experience Long Term) prospective longitudinal cohort study. Individual-level self-reported data on sex, race and ethnicity, education, and household income were obtained by survey. Data from the 2010 US Census were used to calculate area Neighborhood Deprivation Index score and median value of owner-occupied housing units at the census tract level. RESULTS: Patients (N = 1341) had a mean age of 43.4 (SD 11.3) years, were mostly female (86%), were mostly Black or Hispanic (52%), had some college education (83%), and had annual household incomes ≥$51,000 (55%). Percentage total weight loss was 25.8% (SD 9.0%) at year 1 and 22.2% (SD 10.5%) at year 3. Race and ethnicity and age were significant predictors of weight loss at 1 and 3 years with a small effect of self-reported household income at year 1. There were no significant associations between census tract-level Neighborhood Deprivation Index score or value of owner-occupied housing units and weight loss at either time point. CONCLUSIONS: Health systems could improve the chances of weight-loss maintenance after surgery by addressing factors related to racial and ethnic disparities and to income disparities

    Maternal inflammatory, lipid and metabolic markers and associations with birth and breastfeeding outcomes

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    BackgroundConditions in utero influence intrauterine and postnatal infant growth and a few studies indicate that maternal inflammation and insulin resistance might affect birth and breastfeeding outcomes. Furthermore, hormones in human milk (HM) may influence infant appetite-regulation and thereby milk intake, but the associations are less understood.Objective(1) To investigate associations between maternal inflammatory, lipid and metabolic markers and birth and breastfeeding outcomes, and (2) to assess predictors of maternal inflammatory, lipid and metabolic markers in pregnancy.MethodsSeventy-one mother-infant dyads participating in the Mothers, Infants and Lactation Quality (MILQ) study were included in the present study. Fasting blood samples were collected around 28th gestational week, and HM samples at three time points from 1.0 to 8.5 months, where milk intake was assessed using 24-h test weighing. Maternal plasma inflammatory, lipid and metabolic markers included high-sensitive C-reactive protein (hs-CRP), tumor-necrosis factor-α (TNFα), interferon-γ (IFNγ), Interleukin (IL)-6, IL-8, high-, low-, and very-low-density lipoprotein (HDL, LDL, VLDL), total-cholesterol, triglycerides, leptin, adiponectin, insulin, C-peptide, the homeostasis model assessment of insulin resistance (HOMA-IR) and glucose concentration at t = 120 min following an oral glucose tolerance test. Of these, TNFα, IFNγ, IL-6, IL-8, leptin, adiponectin and insulin were also measured in HM samples.ResultsHDL in pregnancy was inversely associated with gestational age (GA) at birth and GA-adjusted birthweight z-score, whereas triglycerides and glucose (t = 120) were positively associated with GA-adjusted birthweight z-score. Higher hs-CRP, VLDL and triglycerides were associated with a higher placental weight. Furthermore, higher HDL, insulin, leptin and HOMA-IR were associated with longer duration of exclusive breastfeeding (EBF). Higher pre-pregnancy BMI was the main predictor of higher levels of hs-CRP, log-TNFα, leptin, insulin, C-peptide, and HOMA-IR.ConclusionMaternal lipid and metabolic markers influenced birthweight z-score and placental weight as well as duration of EBF. Furthermore, pre-pregnancy BMI and maternal age predicted levels of several inflammatory and metabolic markers during pregnancy. Our findings indicate that maternal lipid and metabolic profiles in pregnancy may influence fetal growth and breastfeeding, possibly explained by overweight and/or higher placental weight.Clinical trial registrationhttps://clinicaltrials.gov/, identifier NCT03254329

    Baseline Psychosocial, Environmental, Health, and Behavioral Correlates of 1- and 3-Year Weight Loss After Bariatric Surgery

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    PURPOSE: Weight loss surgery is an effective, long-term treatment for severe obesity but individual response to surgery varies widely. The purpose of this study was to test a comprehensive theoretical model of factors that may be correlated with the greatest surgical weight loss at 1-3 years following surgery. Such a model would help determine what predictive factors to measure when patients are preparing for surgery that may ensure the best weight outcomes. MATERIALS AND METHODS: The Bariatric Experience Long Term (BELONG) study collected self-reported and medical record-based baseline information as correlates of 1- and 3-year % total weight loss (TWL) in n = 1341 patients. Multiple linear regression was used to determine the associations between 120 baseline variables and %TWL. RESULTS: Participants were 43.4 ± 11.3 years old, Hispanic or Black (52%; n = 699), women (86%; n = 1149), and partnered (72%; n = 965) and had annual incomes of ≥ $51,000 (60%; n = 803). A total of 1006 (75%) had 3-year follow-up weight. Regression models accounted for 10.1% of the variance in %TWL at 1-year and 13.6% at 3 years. Only bariatric operation accounted for a clinically meaningful difference (~ 5%) in %TWL at 1-year. At 3 years after surgery, only bariatric operation, Black race, and BMI ≥ 50 kg/m CONCLUSIONS: Our findings combined with many others support a move away from extensive screening and selection of patients at the time of surgery to a focus on improving access to this treatment

    Detecting RNA base methylations in single cells by in situ hybridization.

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    Methylated bases in tRNA, rRNA and mRNA control a variety of cellular processes, including protein synthesis, antimicrobial resistance and gene expression. Currently, bulk methods that report the average methylation state of ~104-107 cells are used to detect these modifications, obscuring potentially important biological information. Here, we use in situ hybridization of Molecular Beacons for single-cell detection of three methylations (m62A, m1G and m3U) that destabilize Watson-Crick base pairs. Our method-methylation-sensitive RNA fluorescence in situ hybridization-detects single methylations of rRNA, quantifies antibiotic-resistant bacteria in mixtures of cells and simultaneously detects multiple methylations using multicolor fluorescence imaging
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