153 research outputs found

    Beta cell function in type 1 diabetes determined from clinical and fasting biochemical variables

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    AIMS/HYPOTHESIS: Beta cell function in type 1 diabetes is commonly assessed as the average plasma C-peptide concentration over 2 h following a mixed-meal test (CPAVE). Monitoring of disease progression and response to disease-modifying therapy would benefit from a simpler, more convenient and less costly measure. Therefore, we determined whether CPAVE could be reliably estimated from routine clinical variables. METHODS: Clinical and fasting biochemical data from eight randomised therapy trials involving participants with recently diagnosed type 1 diabetes were used to develop and validate linear models to estimate CPAVE and to test their accuracy in estimating loss of beta cell function and response to immune therapy. RESULTS: A model based on disease duration, BMI, insulin dose, HbA1c, fasting plasma C-peptide and fasting plasma glucose most accurately estimated loss of beta cell function (area under the receiver operating characteristic curve [AUROC] 0.89 [95% CI 0.87, 0.92]) and was superior to the commonly used insulin-dose-adjusted HbA1c (IDAA1c) measure (AUROC 0.72 [95% CI 0.68, 0.76]). Model-estimated CPAVE (CPEST) reliably identified treatment effects in randomised trials. CPEST, compared with CPAVE, required only a modest (up to 17%) increase in sample size for equivalent statistical power. CONCLUSIONS/INTERPRETATION: CPEST, approximated from six variables at a single time point, accurately identifies loss of beta cell function in type 1 diabetes and is comparable to CPAVE for identifying treatment effects. CPEST could serve as a convenient and economical measure of beta cell function in the clinic and as a primary outcome measure in trials of disease-modifying therapy in type 1 diabetes

    Comparing airborne algorithms for greenhouse gas flux measurements over the Alberta oil sands

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    To combat global warming, Canada has committed to reducing greenhouse gases to be (GHGs) 40 %–45 % below 2005 emission levels by 2025. Monitoring emissions and deriving accurate inventories are essential to reaching these goals. Airborne methods can provide regional and area source measurements with small error if ideal conditions for sampling are met. In this study, two airborne mass-balance box-flight algorithms were compared to assess the extent of their agreement and their performance under various conditions. The Scientific Aviation’s (SciAv) Gaussian algorithm and the Environment and Climate Change Canada’s top-down emission rate retrieval algorithm (TERRA) were applied to data from five samples. Estimates were compared using standard procedures, by systematically testing other method fits, and by investigating the effects on the estimates when method assumptions were not met. Results indicate that in standard scenarios the SciAv and TERRA mass-balance box-flight methods produce similar estimates that agree (3%–25%) within algorithm uncertainties (4%– 34%). Implementing a sample-specific surface extrapolation procedure for the SciAv algorithm may improve emission estimation. Algorithms disagreed when non-ideal conditions occurred (i.e., under non-stationary atmospheric conditions). Overall, the results provide confidence in the box-flight methods and indicate that emissions estimates are not overly sensitive to the choice of algorithm but demonstrate that fundamental algorithm assumptions should be assessed for each flight. Using a different method, the Airborne Visible InfraRed Imaging Spectrometer – Next Generation (AVIRIS-NG) independently mapped individual plumes with emissions 5 times larger than the source SciAv sampled three days later. The range in estimates highlights the utility of increased sampling to get a more complete understanding of the temporal variability of emissions and to identify emission sources within facilities. In addition, hourly on-site activity data would provide insight to the observed temporal variability in emissions and make a comparison to reported emissions more straightforward

    The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening

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    Aims/hypothesis: Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. Methods: Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. Results: Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. Conclusions/interpretation: Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress

    Lunar Regolith Characterization for Simulant Design and Evaluation

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    NASA's Marshall Space Flight Center (MSFC), in conjunction with the United States Geological Survey (USGS), is implementing a new data acquisition strategy to support the development and evaluation of lunar regolith simulants. The objective is to characterize the variance in particle composition, size, shape, and bulk density of the lunar regolith. Apollo drive and drill cores are the preferred samples as they allow for investigation of variation with depth, and many proposed operations on the moon will involve excavation of lunar regolith to depths of at least tens of centimeters. Multiple Apollo cores will be sampled multiple times along their vertical axes and analyzed. This will permit statistical statements about variation both within a core, between closely spaced cores, and between distant areas

    Dysglycemia and Index60 as Prediagnostic End Points for Type 1 Diabetes Prevention Trials

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    OBJECTIVE: We assessed dysglycemia and a T1D Diagnostic Index60 (Index60) ≥1.00 (on the basis of fasting C-peptide, 60-min glucose, and 60-min C-peptide levels) as prediagnostic end points for type 1 diabetes among Type 1 Diabetes TrialNet Pathway to Prevention Study participants. RESEARCH DESIGN AND METHODS: Two cohorts were analyzed: 1) baseline normoglycemic oral glucose tolerance tests (OGTTs) with an incident dysglycemic OGTT and 2) baseline Index60 <1.00 OGTTs with an incident Index60 ≥1.00 OGTT. Incident dysglycemic OGTTs were divided into those with (DYS/IND+) and without (DYS/IND-) concomitant Index60 ≥1.00. Incident Index60 ≥1.00 OGTTs were divided into those with (IND/DYS+) and without (IND/DYS-) concomitant dysglycemia. RESULTS: The cumulative incidence for type 1 diabetes was greater after IND/DYS- than after DYS/IND- (P < 0.01). Within the normoglycemic cohort, the cumulative incidence of type 1 diabetes was higher after DYS/IND+ than after DYS/IND- (P < 0.001), whereas within the Index60 <1.00 cohort, the cumulative incidence after IND/DYS+ and after IND/DYS- did not differ significantly. Among nonprogressors, type 1 diabetes risk at the last OGTT was greater for IND/DYS- than for DYS/IND- (P < 0.001). Hazard ratios (HRs) of DYS/IND- with age and 30- to 0-min C-peptide were positive (P < 0.001 for both), whereas HRs of type 1 diabetes with these variables were inverse (P < 0.001 for both). In contrast, HRs of IND/DYS- and type 1 diabetes with age and 30- to 0-min C-peptide were consistent (all inverse [P < 0.01 for all]). CONCLUSIONS: The findings suggest that incident dysglycemia without Index60 ≥1.00 is a suboptimal prediagnostic end point for type 1 diabetes. Measures that include both glucose and C-peptide levels, such as Index60 ≥1.00, appear better suited as prediagnostic end points

    Real-world study of patients with locally advanced HNSCC in the community oncology setting

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    IntroductionThere is a need to understand the current treatment landscape for LA HNSCC in the real-world setting.MethodsThis retrospective study assessed real-world outcomes and treatment patterns of 1,158 adult patients diagnosed with locally advanced (stage III-IVB) HNSCC initiating chemoradiotherapy (CRT) within the period January 2015 to December 2017 in a large network of US community oncology practices. Structured data were abstracted from electronic health records. Demographic, clinical and treatment characteristics were analyzed descriptively overall and stratified by index treatment (cisplatin + radiotherapy [RT], cisplatin + other chemotherapy + RT, or cetuximab + RT). Time to next treatment (TTNT) and overall survival (OS) were measured using the Kaplan-Meier method, and median duration of treatment was assessed. OS was compared across treatment cohorts using multinomial logistic regression with inverse probability treatment weighting. To identify covariates associated with OS, a multivariable adjusted Cox proportional hazard model was used.ResultsThis study examined 22,782 records, of which 2124 had stage III to stage IVB and no other cancers, and 1158 met all eligibility criteria. Among the treatment cohorts analyzed (cisplatin + RT, cisplatin + other chemotherapy + RT, or cetuximab + RT), cisplatin + RT was the most common concurrent chemotherapy (65.8%). Among 1158 patients, 838 (72.4%) did not initiate subsequent treatment and 139 (12.0%) died. The median TTNT and median OS were only reached by the cetuximab + RT cohort. Among patients with oropharynx primary tumor location, patients with human papilloma virus (HPV) positive status had the longest time on treatment and highest survival at 60 months. Covariates associated with improved survival were never/former tobacco use, HPV positive status, and overweight or obese body mass index. Covariates associated with poorer survival were age of 60+ years, primary tumor location of hypopharynx or oral cavity and Eastern Cooperative Oncology Group performance status score of 2+.ConclusionThese data describe real-world treatment patterns in locally advanced head and neck squamous cell cancer and sets the baseline to assess outcomes for future studies on the community oncology population

    Selection of antigenically advanced variants of seasonal influenza viruses

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    Influenza viruses mutate frequently, necessitating constant updates of vaccine viruses. To establish experimental approaches that may complement the current vaccine strain selection process, we selected antigenic variants from human H1N1 and H3N2 influenza virus libraries possessing random mutations in the globular head of the haemagglutinin protein (which includes the antigenic sites) by incubating them with human and/or ferret convalescent se
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