Health Care Providers' Advice on Lifestyle Modification in the US Population: Results from the NHANES 2011-2016

OBJECTIVE: Healthcare providers are encouraged to prescribe lifestyle modifications for preventing and managing obesity and associated chronic conditions. However, the pattern of lifestyle advice provision is unknown. We investigate the prevalence of advised lifestyle modification according to weight status and chronic conditions in a US nationally representative sample. METHODS: Adults 20-64 years (n=11,467) from National Health and Nutrition Examination Study between 2011 and 2016 were analyzed, with weight status, and chronic conditions (high blood pressure, high blood cholesterol, osteoarthritis, coronary heart disease and type 2 diabetes mellitus). Lifestyle modification advice by healthcare providers included increase physical activity/exercise, reduce dietary fat/calories, control/lose weight, and all of above. RESULTS: High blood pressure (32.7%) and cholesterol (29.3%) were highly prevalent compared to osteoarthritis (7.4%), type 2 diabetes (5.7%) and coronary heart disease (3.7%). Those with type 2 diabetes received considerably frequent advice (56.5%; 95%CI: 52.4%-60.6%) than those with high blood pressure (31.4%; 95%CI:29.3%-33.6%) and cholesterol (27.0%; 95%CI:24.9%-29.3%). Prevalence of lifestyle advice exhibited substantial increases with graded BMI and comorbidity (all P<0.001). After adjusting for comorbid conditions, advice were more commonly reported among women, those overweight/obese, non-white, or insured. Remarkably low proportion of overweight (21.4: 95%CI: 18.7-24.3%) and obese (44.2%;95%CI:41.0%-47.4%) adults free of chronic conditions reported receiving any lifestyle advice. CONCLUSION: Prevalence of lifestyle modification advised by healthcare providers is generally low among US adults with chronic conditions, and worryingly low among those without chronic conditions however overweight or obese. Prescribed lifestyle modification is a missing opportunity in implementing sustainably strategies reducing chronic condition burden

Detection and Localization of Myocardial Infarction Based on Multi-Scale ResNet and Attention Mechanism

PURPOSE: Myocardial infarction (MI) is one of the most common cardiovascular diseases, frequently resulting in death. Early and accurate diagnosis is therefore important, and the electrocardiogram (ECG) is a simple and effective method for achieving this. However, it requires assessment by a specialist; so many recent works have focused on the automatic assessment of ECG signals. METHODS: For the detection and localization of MI, deep learning models have been proposed, but the diagnostic accuracy of this approaches still need to be improved. Moreover, with deep learning methods the way in which a given result was achieved lacks interpretability. In this study, ECG data was obtained from the PhysioBank open access database, and was analyzed as follows. Firstly, the 12-lead ECG signal was preprocessed to identify each beat and obtain each heart interval. Secondly, a multi-scale deep learning model combined with a residual network and attention mechanism was proposed, where the input was the 12-lead ECG recording. Through the SENet model and the Grad-CAM algorithm, the weighting of each lead was calculated and visualized. Using existing knowledge of the way in which different types of MI gave characteristic patterns in specific ECG leads, the model was used to provisionally diagnose the type of MI according to the characteristics of each of the 12 ECG leads. RESULTS: Ten types of MI anterior, anterior lateral, anterior septal, inferior, inferior lateral, inferior posterior, inferior posterior lateral, lateral, posterior, and posterior lateral were diagnosed. The average accuracy, sensitivity, and specificity for MI detection of all lesion types was 99.98, 99.94, and 99.98%, respectively; and the average accuracy, sensitivity, and specificity for MI localization was 99.79, 99.88, and 99.98%, respectively. CONCLUSION: When compared to existing models based on traditional machine learning methods, convolutional neural networks and recurrent neural networks, the results showed that the proposed model had better diagnostic performance, being superior in accuracy, sensitivity, and specificity

Allele Size Miscalling due to the Pull-Up Effect Influencing Size Standard Calibration in Capillary Electrophoresis: A Case Study Using HEX Fluorescent Dye in Microsatellites

Microsatellites are important genetic markers and have been broadly employed in many genetic studies. Currently, polymorphisms in microsatellites are often detected by an automated system of capillary electrophoresis with fluorescent dyes. In this situation, different dye combinations may cause pull-up/bleed-through problems, which introduce noise signals from one dye channel into another, causing genotyping errors. Here, we report the detection of such a problem at two microsatellite loci that used the HEX dye. Using three datasets, we tested for noise effects in four allele-scoring programmes: Genemapper, Genemarker, Gelquest and Fragman. We found that, because some allele sizes were identical or close to the size of one of the internal size standards, all four programmes gave allele size calling errors due to wrongly identifying pull-up signals as the internal size standard. In addition, because allele miscalling in this study was caused by the fluorescent dye that the microsatellites used introducing noise of the same colour as the internal size standard used, the pull-up correction function in Genemapper, Genemarker and Fragman failed to deal with this. Considering that pull-up peak scoring errors can occur with any dye colour, the phenomenon is not limited to the current HEX dye. Using different software and visual scoring of each result will allow accurate sizing of microsatellite alleles

Supernovae from rotating stars

The present paper discusses the main physical effects produced by stellar rotation on presupernovae, as well as observations which confirm these effects and their consequences for presupernova models. Rotation critically influences the mass of the exploding cores, the mass and chemical composition of the envelopes and the types of supernovae, as well as the properties of the remnants and the chemical yields. In the formation of gamma-ray bursts, rotation and the properties of rotating stars appear as the key factor. In binaries, the interaction between axial rotation and tidal effects often leads to interesting and unexpected results. Rotation plays a key role in shaping the evolution and nucleosynthesis in massive stars with very low metallicities (metallicity below about the Small Magellanic Cloud metallicity down to Population III stars). At solar and higher metallicities, the effects of rotation compete with those of stellar winds. In close binaries, the synchronisation process can lock the star at a high rotation rate despite strong mass loss and thus both effects, rotation and stellar winds, have a strong impact. In conclusion, rotation is a key physical ingredient of the stellar models and of presupernova stages, and the evolution both of single stars and close binaries. Moreover, important effects are expected along the whole cosmic history.Comment: 36 pages, 15 figures, published in Handbook of Supernovae, A.W. Alsabti and P. Murdin (eds), Springe

Development of IR-based short-range communication techniques for swarm robot applications

This paper proposes several designs for a reliable infra-red based communication techniques for swarm robotic applications. The communication system was deployed on an autonomous miniature mobile robot (AMiR), a swarm robotic platform developed earlier. In swarm applications, all participating robots must be able to communicate and share data. Hence a suitable communication medium and a reliable technique are required. This work uses infrared radiation for transmission of swarm robots messages. Infrared transmission methods such as amplitude and frequency modulations will be presented along with experimental results. Finally the effects of the modulation techniques and other parameters on collective behavior of swarm robots will be analyzed

Protein–like fully reversible tetramerisation and super-association of an aminocellulose

Unusual protein-like, partially reversible associative behaviour has recently been observed in solutions of the water soluble carbohydrates known as 6-deoxy-6-(v-aminoalkyl)aminocelluloses, which produce controllable self-assembling films for enzyme immobilisation and other biotechnological applications. Now, for the first time, we have found a fully reversible self-association (tetramerisation) within this family of polysaccharides. Remarkably these carbohydrate tetramers are then seen to associate further in a regular way into supra-molecular complexes. Fully reversible oligomerisation has been hitherto completely unknown for carbohydrates and instead resembles in some respects the assembly of polypeptides and proteins like haemoglobin and its sickle cell mutation. Our traditional perceptions as to what might be considered ‘‘protein-like’’ and what might be considered as ‘‘carbohydrate-like’’ behaviour may need to be rendered more flexible, at least as far as interaction phenomena are concerned

A close examination of double filtering with fold change and t test in microarray analysis

<p>Abstract</p> <p>Background</p> <p>Many researchers use the double filtering procedure with fold change and <it>t </it>test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods.</p> <p>Results</p> <p>This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while <it>t </it>statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure.</p> <p>Conclusion</p> <p>We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure.</p

The global cardiovascular magnetic resonance registry (GCMR) of the society for cardiovascular magnetic resonance (SCMR): its goals, rationale, data infrastructure, and current developments

GCMR received seed funding from SCMR (SCMR_GRANT_001) for the development and maintenance of GCMR websites and database infrastructure

Synthesis and Application of Carbon–Iron Oxide Microspheres’ Black Pigments in Electrophoretic Displays

Carbon–iron oxide microspheres’ black pigments (CIOMBs) had been prepared via ultrasonic spray pyrolysis of aqueous solutions containing ferrous chloride and glucose. Due to the presence of carbon, CIOMBs not only exhibited remarkably acid resistance, but also could be well dispersed in both polar solvents and nonpolar solvent. Finally, dispersions of hollow CIOMBs in tetrachloroethylene had successfully been applied in electrophoretic displays