Monounsaturated fatty acid, carbohydrate intake, and diabetes status are associated with arterial pulse pressure

Background Diabetes is a global epidemic. Cardiovascular disease (CVD) is one of the most prevalent consequences of diabetes. Nutrition is considered a modifiable risk factor for CVD, particularly for individuals with diabetes; albeit, there is little consensus on the role of carbohydrates, proteins and fats for arterial health for persons with or without diabetes. In this study, we examined the association of macronutrients with arterial pulse pressure (APP), a surrogate measure of arterial health by diabetes status and race. Methods Participants were 892 Mexican Americans (MA), 1059 Black, non-Hispanics (BNH) and 2473 White, non-Hispanics (WNH) with and without diabetes of a weighted sample from the National Nutrition and Health Examination Survey (NHANES) 2007-2008. The cross-sectional analysis was performed with IBM-SPSS version 18 with the complex sample analysis module. The two-year sample weight for the sub-sample with laboratory values was applied to reduce bias and approximate a nationally, representative sample. Arterial stiffness was assessed by arterial pulse pressure (APP). Results APP was higher for MA [B = 0.063 (95% CI 0.015 to 0.111), p = 0.013] and BNH [B = 0.044 (95% CI 0.006 to 0.082), p = 0.018] than WNH, controlling for diabetes, age, gender, body mass index (BMI), fiber intake, energy intake (Kcal) and smoking. A two-way interaction of diabetes by carbohydrate intake (grams) was inversely associated with APP [B = -1.18 (95% CI -0.178 to -0.058), p = 0.001], controlling for race, age, gender, BMI, Kcal and smoking. BNH with diabetes who consumed more mono-unsaturated fatty acids (MUFA) than WNH with diabetes had lower APP [B = -0.112 (95%CI-0.179 to -0.045), p = 0.003] adjusting for saturated fatty acids, Kcal, age, gender, BMI and smoking. Conclusion Higher MUFA and carbohydrate intake for persons with diabetes reflecting lower APP may be due to replacement of saturated fats with CHO and MUFA. The associations of APP with diabetes, race and dietary intake need to be confirmed with intervention and prospective studies. Confirmation of these results would suggest that dietary interventions for minorities with diabetes may improve arterial health.

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

Developing an Enhanced Model for Combined Heat and Air Infiltration Energy Simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building’s energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.

Environmental analysis of polar herbicides in complex organic-rich matrices by high performance liquid chromatography atmospheric pressure ionization mass spectrometry (HPLC-API-MS)

A comprehensive forensic investigation of sensitive ecosystems in the Everglades Area is presented. Assessing the background levels of contamination in these ecosystems represents a vital resource to build up forensic evidence required to enforce future environmental crimes within the studied areas. This investigation presents the development and validation of a fractionation and isolation method for two families of herbicides commonly applied in the vicinity of the study area, including phenoxy acids like 2,4-D, MCPA, and silvex; as well as the most common triazine-based herbicides like atrazine, prometyne, simazine and related metabolites like DIA and DEA. Accelerated solvent extraction (ASE) and solid phase extraction (SPE) were used to isolate the analytes from abiotic matrices containing large amounts of organic material. Atmospheric-pressure ionization (API) with electrospray ionization in negative mode (ESP-), and Chemical Ionization in the positive mode (APCI+) were used to perform the characterization of the herbicides of interest.