Type 2 diabetes prevention focused on normalization of glycemia: A two-year pilot study

The purpose of this study is to assess the effects of an alternative approach to type 2 diabetes prevention. Ninety-six patients with prediabetes (age 52 (10) years; 80% female; BMI 39.2 (7.1) kg/

Air-sea gas transfer velocity estimates from the Jason-1 and TOPEX altimeters : prospects for a long-term global time series

Author Posting. © Elsevier B.V., 2006. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 66 (2007): 173-181, doi:10.1016/j.jmarsys.2006.03.020.Estimation of global and regional air–sea fluxes of climatically important gases is a key goal of current climate research programs. Gas transfer velocities needed to compute these fluxes can be estimated by combining altimeter-derived mean square slope with an empirical relation between transfer velocity and mean square slope derived from field measurements of gas fluxes and small-scale wave spectra [Frew, N.M., Bock, E.J., Schimpf, U., Hara, T., Hauβecker, H., Edson, J.B., McGillis, W.R., Nelson, R.K., McKenna, S.P., Uz, B.M., Jähne, B., 2004. Air–sea gas transfer: Its dependence on wind stress, small-scale roughness and surface films, J. Geophys. Res., 109, C08S17, doi: 10.1029/2003JC002131.]. We previously reported initial results from a dual-frequency (Ku- and C-band) altimeter algorithm [Glover, D.M., Frew, N.M., McCue, S.J., Bock, E.J., 2002. A Multi-year Time Series of Global Gas Transfer Velocity from the TOPEX Dual Frequency, Normalized Radar Backscatter Algorithm, In: Gas Transfer at Water Surfaces, editors: Donelan, M., Drennan, W., Saltzman, E., and Wanninkhof, R., Geophysical Monograph 127, American Geophysical Union, Washington, DC, 325–331.] for estimating the air–sea gas transfer velocity (k) from the mean square slope of short wind waves (40–100 rad/m) and derived a 6-year time series of global transfer velocities based on TOPEX observations. Since the launch of the follow-on altimeter Jason-1 in December 2001 and commencement of the TOPEX/Jason-1 Tandem Mission, we have extended this time series to 12 years, with improvements to the model parameters used in our algorithm and using the latest corrected data releases. The prospect of deriving multi-year and interdecadal time series of gas transfer velocity from TOPEX, Jason-1 and follow-on altimeter missions depends on precise intercalibration of the normalized backscatter. During the Tandem Mission collinear phase, both satellites followed identical orbits with a mere 73-s time separation. The resulting collocated, near-coincident normalized radar backscatter (σ°) data from both altimeters present a unique opportunity to intercalibrate the two instruments, compare derived fields of transfer velocity and estimate the precision of the algorithm. Initial results suggest that the monthly gas transfer velocity fields generated from the two altimeters are very similar. Comparison of along-track Ku-band and C-band σ° during the collinear phase indicates that observed discrepancies are due primarily to small offsets between TOPEX and Jason-1 σ°. The Jason-1 k values have an apparent bias of + 4% relative to TOPEX, while the precision estimated from the two observation sets is 5–7% and scales with k. The resultant long-term, global, mean k is 16 cm/h.We gratefully acknowledge funding support from NASA under grant NAGW–2431 and JPL contract 961425

Defining care products to finance health care in the Netherlands

A case-mix project started in the Netherlands with the primary goal to define a complete set of health care products for hospitals. The definition of the product structure was completed 4 years later. The results are currently being used for billing purposes. This paper focuses on the methodology and techniques that were developed and applied in order to define the casemix product structure. The central research question was how to develop a manageable product structure, i.e., a limited set of hospital products, with acceptable cost homogeneity. For this purpose, a data warehouse with approximately 1.5 million patient records from 27 hospitals was build up over a period of 3 years. The data associated with each patient consist of a large number of a priori independent parameters describing the resource utilization in different stages of the treatment process, e.g., activities in the operating theatre, the lab and the radiology department. Because of the complexity of the database, it was necessary to apply advanced data analysis techniques. The full analyses process that starts from the database and ends up with a product definition consists of four basic analyses steps. Each of these steps has revealed interesting insights. This paper describes each step in some detail and presents the major results of each step. The result consists of 687 product groups for 24 medical specialties used for billing purposes

A new approach to estimation of global air-sea gas transfer velocity fields using dual-frequency altimeter backscatter

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C11003, doi:10.1029/2006JC003819.A new approach to estimating air-sea gas transfer velocities based on normalized backscatter from the dual-frequency TOPEX and Jason-1 altimeters is described. The differential scattering of Ku-band (13.6 GHz) and C-band (5.3 GHz) microwave pulses is used to isolate the contribution of small-scale waves to mean square slope and gas transfer. Mean square slope is derived for the nominal wave number range 40–100 rad m−1 by differencing mean square slope estimates computed from the normalized backscatter in each band, using a simple geometric optics model. Model parameters for calculating the differenced mean square slope over this wave number range are optimized using in situ optical slope measurements. An empirical relation between gas transfer velocity and mean square slope, also based on field measurements, is then used to derive gas transfer velocities. Initial results demonstrate that the calculated transfer velocities exhibit magnitudes and a dynamic range which are generally consistent with existing field measurements. The new algorithm is used to construct monthly global maps of gas transfer velocity and to illustrate seasonal transfer velocity variations over a 1-year period. The measurement precision estimated from >106 duplicate observations of the sea surface by TOPEX and Jason-1 altimeters orbiting in tandem is better than 10%. The estimated overall uncertainty of the method is ±30%. The long-term global, area-weighted, Schmidt number corrected, mean gas transfer velocity is 13.7 ± 4.1 cm h−1. The new approach, based on surface roughness, represents a potential alternative to commonly used parameterizations based on wind speed.Financial support for this research from the National Aeronautics and Space Administration through Jet Propulsion Laboratory contract 961425 and the NOAA Global Carbon Cycle Program under grant NA16GP2918, Office of Global Programs is gratefully acknowledged

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Using stable isotope analysis to answer fundamental questions in invasion ecology : progress and prospects

CITATION: McCue, M. D. et al. 2020. Using stable isotope analysis to answer fundamental questions in invasion ecology: progress and prospects. Methods in Ecology and Evolution, 11(2):196-214. doi:10.1111/2041-210X.13327The original publication is available at https://besjournals.onlinelibrary.wiley.com/journal/2041210xWhat makes some species successful invaders while others fail, and why some invaders have major impacts in invaded ecosystems are pivotal questions that are attracting major research effort. The increasing availability of high resolution, georeferenced stable isotope landscapes (‘isoscapes'), coupled with the commercialization of stable isotope‐enriched tracer molecules and the development of new analytical approaches, is facilitating novel applications of stable isotope techniques in ecology. We can now address ecological questions that were previously intractable. We review and discuss how stable isotope analysis (SIA) can complement fundamental research themes in the study of biological invasions, especially in answering questions relating to the physiological and ecological mechanisms underlying invasion processes and invader impacts. SIA was first used for simply describing the diet of invaders but, more recently, SIA‐informed metrics of population and community trophic structure have been advanced. These approaches now permit the comparison of diets across space and time and provide quantitative tools to compare food webs across different stages of invasion. SIA has also been pivotal in quantifying competition for resources between native and non‐native species (e.g., competition for food, water, or nutrient use). Specific questions related to modes of dispersal (e.g., origin and distance/direction traveled) and mechanisms of establishment can also be addressed using SIA in diverse taxa. An overarching goal is to highlight examples of recent studies that have used SIA in key areas of invasion ecology and use these to synthesize testable predictions where SIA could be applied to future studies. We conclude by highlighting several paths forward and describing how unresolved challenges in quantifying the rates, impacts, and mechanisms underlying invasions could potentially benefit from the use of SIA.Publisher’s versio

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges