Effects of Sensor-Augmented Pump Therapy on Glycemic Variability in Well-Controlled Type 1 Diabetes in the STAR 3 Study

Compared with multiple daily injections (MDI), sensor-augmented pump (SAP) insulin therapy may reduce glycemic variability and oxidative stress in type 1 diabetes in a glycosylated hemoglobin (A1C)-independent manner

The Prograde Orbit of Exoplanet TrES-2b

We monitored the Doppler shift of the G0V star TrES-2 throughout a transit of its giant planet. The anomalous Doppler shift due to stellar rotation (the Rossiter-McLaughlin effect) is discernible in the data, with a signal-to-noise ratio of 2.9, even though the star is a slow rotator. By modeling this effect we find that the planet's trajectory across the face of the star is tilted by -9 +/- 12 degrees relative to the projected stellar equator. With 98% confidence, the orbit is prograde.Comment: ApJ, in press [15 pages

Maximum Entropy Reconstruction of the Interstellar Medium: I. Theory

We have developed a technique to map the three-dimensional structure of the local interstellar medium using a maximum entropy reconstruction technique. A set of column densities N to stars of known distance can in principle be used to recover a three-dimensional density field n, since the two quantities are related by simple geometry through the equation N = C n, where C is a matrix characterizing the stellar spatial distribution. In practice, however, there is an infinte number of solutions to this equation. We use a maximum entropy reconstruction algorithm to find the density field containing the least information which is consistent with the observations. The solution obtained with this technique is, in some sense, the model containing the minimum structure. We apply the algorithm to several simulated data sets to demonstrate its feasibility and success at recovering ``real'' density contrasts. This technique can be applied to any set of column densities whose end points are specified. In a subsequent paper we shall describe the application of this method to a set of stellar color excesses to derive a map of the dust distribution, and to soft X-ray absorption columns to hot stars to derive a map of the total density of the interstellar medium.Comment: 23 pages, 7 fig.; accepted for publication in the Ap.

Voxel-based supervised machine learning of peripheral zone prostate cancer using noncontrast multiparametric MRI

Purpose: The aim of this study was to develop and assess the performance of supervised machine learning technique to classify magnetic resonance imaging (MRI) voxels as cancerous or noncancerous using noncontrast multiparametric MRI (mp-MRI), comprised of T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and advanced diffusion tensor imaging (DTI) parameters. Materials and methods: In this work, 191 radiomic features were extracted from mp-MRI from prostate cancer patients. A comprehensive set of support vector machine (SVM) models for T2WI and mp-MRI (T2WI + DWI, T2WI + DTI, and T2WI + DWI + DTI) were developed based on novel Bayesian parameters optimization method and validated using leave-one-patient-out approach to eliminate any possible overfitting. The diagnostic performance of each model was evaluated using the area under the receiver operating characteristic curve (AUROC). The average sensitivity, specificity, and accuracy of the models were evaluated using the test data set and the corresponding binary maps generated. Finally, the SVM plus sigmoid function of the models with the highest performance were used to produce cancer probability maps. Results: The T2WI + DWI + DTI models using the optimal feature subset achieved the best performance in prostate cancer detection, with the average AUROC, sensitivity, specificity, and accuracy of 0.93 ± 0.03, 0.85 ± 0.05, 0.82 ± 0.07, and 0.83 ± 0.04, respectively. The average diagnostic performance of T2WI + DTI models was slightly higher than T2WI + DWI models (+3.52%) using the optimal radiomic features. Conclusions: Combination of noncontrast mp-MRI (T2WI, DWI, and DTI) features with the framework of a supervised classification technique and Bayesian optimization method are able to differentiate cancer from noncancer voxels with high accuracy and without administration of contrast agent. The addition of cancer probability maps provides additional functionality for image interpretation, lesion heterogeneity evaluation, and treatment management.</p

Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease

Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk-prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine which was the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models and adjusting for atherosclerotic risk factors (per relevant risk scores), and the predictive utility was determined by the C-statistic and categorical net reclassification index. We show that eGFRcys is most strongly associated with CVD and mortality, and, along with albuminuria, adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment

Circulating amino acids and the risk of macrovascular, microvascular and mortality outcomes in individuals with type 2 diabetes : results from the ADVANCE trial

Aims/hypotheses We aimed to quantify the association of individual circulating amino acids with macrovascular disease, microvascular disease and all-cause mortality in individuals with type 2 diabetes. Methods We performed a case-cohort study (N = 3587), including 655 macrovascular events, 342 microvascular events (new or worsening nephropathy or retinopathy) and 632 all-cause mortality events during follow-up, in a secondary analysis of the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) study. For this study, phenylalanine, isoleucine, glutamine, leucine, alanine, tyrosine, histidine and valine were measured in stored plasma samples by proton NMR metabolomics. Hazard ratios were modelled per SD increase in each amino acid. Results In models investigating associations and potential mechanisms, after adjusting for age, sex and randomised treatment, phenylalanine was positively, and histidine inversely, associated with macrovascular disease risk. These associations were attenuated to the null on further adjustment for extended classical risk factors (including eGFR and urinary albumin/creatinine ratio). After adjustment for extended classical risk factors, higher tyrosine and alanine levels were associated with decreased risk of microvascular disease (HR 0.78; 95% CI 0.67, 0.91 and HR 0.86; 95% CI 0.76, 0.98, respectively). Higher leucine (HR 0.79; 95% CI 0.69, 0.90), histidine (HR 0.89; 95% CI 0.81, 0.99) and valine (HR 0.79; 95% CI 0.70, 0.88) levels were associated with lower risk of mortality. Investigating the predictive ability of amino acids, addition of all amino acids to a risk score modestly improved classification of participants for macrovascular (continuous net reclassification index [NRI] +35.5%, p <0.001) and microvascular events (continuous NRI +14.4%, p = 0.012). Conclusions/interpretation We report distinct associations between circulating amino acids and risk of different major complications of diabetes. Low tyrosine appears to be a marker of microvascular risk in individuals with type 2 diabetes independently of fundamental markers of kidney function.Peer reviewe

Circulating amino acids and the risk of macrovascular, microvascular and mortality outcomes in individuals with type 2 diabetes : results from the ADVANCE trial

Aims/hypotheses We aimed to quantify the association of individual circulating amino acids with macrovascular disease, microvascular disease and all-cause mortality in individuals with type 2 diabetes. Methods We performed a case-cohort study (N = 3587), including 655 macrovascular events, 342 microvascular events (new or worsening nephropathy or retinopathy) and 632 all-cause mortality events during follow-up, in a secondary analysis of the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) study. For this study, phenylalanine, isoleucine, glutamine, leucine, alanine, tyrosine, histidine and valine were measured in stored plasma samples by proton NMR metabolomics. Hazard ratios were modelled per SD increase in each amino acid. Results In models investigating associations and potential mechanisms, after adjusting for age, sex and randomised treatment, phenylalanine was positively, and histidine inversely, associated with macrovascular disease risk. These associations were attenuated to the null on further adjustment for extended classical risk factors (including eGFR and urinary albumin/creatinine ratio). After adjustment for extended classical risk factors, higher tyrosine and alanine levels were associated with decreased risk of microvascular disease (HR 0.78; 95% CI 0.67, 0.91 and HR 0.86; 95% CI 0.76, 0.98, respectively). Higher leucine (HR 0.79; 95% CI 0.69, 0.90), histidine (HR 0.89; 95% CI 0.81, 0.99) and valine (HR 0.79; 95% CI 0.70, 0.88) levels were associated with lower risk of mortality. Investigating the predictive ability of amino acids, addition of all amino acids to a risk score modestly improved classification of participants for macrovascular (continuous net reclassification index [NRI] +35.5%, p <0.001) and microvascular events (continuous NRI +14.4%, p = 0.012). Conclusions/interpretation We report distinct associations between circulating amino acids and risk of different major complications of diabetes. Low tyrosine appears to be a marker of microvascular risk in individuals with type 2 diabetes independently of fundamental markers of kidney function.Peer reviewe

Possible detection of two giant extrasolar planets orbiting the eclipsing polar UZ Fornacis

We present new high-speed, multi-observatory, multi-instrument photometry of the eclipsing polar UZ For in order to measure precise mid-eclipse times with the aim of detecting any orbital period variations. When combined with published eclipse times and archival data spanning ~27 years, we detect departures from a linear and quadratic trend of ~60 s. The departures are strongly suggestive of two cyclic variations of 16(3) and 5.25(25) years. The two favoured mechanisms to drive the periodicities are either two giant extrasolar planets as companions to the binary (with minimum masses of 6.3(1.5)M(Jupiter) and 7.7(1.2)M(Jupiter)) or a magnetic cycle mechanism (e.g. Applegate's mechanism) of the secondary star. Applegate's mechanism would require the entire radiant energy output of the secondary and would therefore seem to be the least likely of the two, barring any further refinements in the effect of magnetic fieilds (e.g. those of Lanza et al.). The two planet model can provide realistic solutions but it does not quite capture all of the eclipse times measurements. A highly eccentric orbit for the outer planet would fit the data nicely, but we find that such a solution would be unstable. It is also possible that the periodicities are driven by some combination of both mechanisms. Further observations of this system are encouraged.Comment: 10 pages, 4 figures, 2 table

Comparison of conventional lipoprotein tests and apolipoproteins in the prediction of cardiovascular disease: data from UK Biobank

Background: Total cholesterol and high-density lipoprotein cholesterol (HDL-C) measurements are central to cardiovascular disease (CVD) risk assessment, but there is continuing debate around the utility of other lipids for risk prediction. Methods: Participants from UK Biobank without baseline CVD and not taking statins, with relevant lipid measurements (n=346 686), were included in the primary analysis. An incident fatal or nonfatal CVD event occurred in 6216 participants (1656 fatal) over a median of 8.9 years. Associations of nonfasting lipid measurements (total cholesterol, HDL-C, non–HDL-C, direct and calculated low-density lipoprotein cholesterol [LDL-C], and apolipoproteins [Apo] A1 and B) with CVD were compared using Cox models adjusting for classical risk factors, and predictive utility was determined by the C-index and net reclassification index. Prediction was also tested in 68 649 participants taking a statin with or without baseline CVD (3515 CVD events). Results: ApoB, LDL-C, and non–HDL-C were highly correlated (r&gt;0.90), while HDL-C was strongly correlated with ApoA1 (r=0.92). After adjustment for classical risk factors, 1 SD increase in ApoB, direct LDL-C, and non–HDL-C had similar associations with composite fatal/nonfatal CVD events (hazard ratio, 1.23, 1.20, 1.21, respectively). Associations for 1 SD increase in HDL-C and ApoA1 were also similar (hazard ratios, 0.81 [both]). Adding either total cholesterol and HDL-C, or ApoB and ApoA, to a CVD risk prediction model (C-index, 0.7378) yielded similar improvement in discrimination (C-index change, 0.0084; 95% CI, 0.0065, 0.0104, and 0.0089; 95% CI, 0.0069, 0.0109, respectively). Once total and HDL-C were in the model, no further substantive improvement was achieved with the addition of ApoB (C-index change, 0.0004; 95% CI, 0.0000, 0.0008) or any measure of LDL-C. Results for predictive utility were similar for a fatal CVD outcome, and in a discordance analysis. In participants taking a statin, classical risk factors (C-index, 0.7118) were improved by non–HDL-C (C-index change, 0.0030; 95% CI, 0.0012, 0.0048) or ApoB (C-index change, 0.0030; 95% CI, 0.0011, 0.0048). However, adding ApoB or LDL-C to a model already containing non–HDL-C did not further improve discrimination. Conclusions: Measurement of total cholesterol and HDL-C in the nonfasted state is sufficient to capture the lipid-associated risk in CVD prediction, with no meaningful improvement from addition of apolipoproteins, direct or calculated LDL-C