Ventilation behavior during upper-body incremental exercise

Pires, FO, Hammond, J, Lima-Silva, AE, Bertuzzi, RCM, and Kiss, MAPDM. Ventilation behavior during upper-body incremental exercise. J Strength Cond Res 25(1): 225-230, 2011-This study tested the ventilation (V(E)) behavior during upper-body incremental exercise by mathematical models that calculate 1 or 2 thresholds and compared the thresholds identified by mathematical models with V-slope, ventilatory equivalent for oxygen uptake (V(E)/(V) over dotO(2)), and ventilatory equivalent for carbon dioxide uptake (V(E)/(V) over dotCO(2)). Fourteen rock climbers underwent an upper-body incremental test on a cycle ergometer with increases of approximately 20 W.min(-1) until exhaustion at a cranking frequency of approximately 90 rpm. The V(E) data were smoothed to 10-second averages for V(E) time plotting. The bisegmental and the 3-segmental linear regression models were calculated from 1 or 2 intercepts that best shared the V(E) curve in 2 or 3 linear segments. The ventilatory threshold(s) was determined mathematically by the intercept(s) obtained by bisegmental and 3-segmental models, by V-slope model, or visually by V(E)/(V) over dotO(2) and V(E)/(V) over dotCO(2). There was no difference between bisegmental (mean square error [MSE] = 35.3 +/- 32.7 l.min(-1)) and 3-segmental (MSE = 44.9 +/- 47.8 l.min(-1)) models in fitted data. There was no difference between ventilatory threshold identified by the bisegmental (28.2 +/- 6.8 ml.kg(-1).min(-1)) and second ventilatory threshold identified by the 3-segmental (30.0 +/- 5.1 ml.kg(-1).min(-1)), V(E)/(V) over dotO(2) (28.8 +/- 5.5 ml.kg(-1).min(-1)), or V-slope (28.5 +/- 5.6 ml.kg(-1).min(-1)). However, the first ventilatory threshold identified by 3-segmental (23.1 +/- 4.9 ml.kg(-1).min(-1)) or by VE/(V) over dotO(2) (24.9 +/- 4.4 ml.kg(-1).min(-1)) was different from these 4. The V(E) behavior during upper-body exercise tends to show only 1 ventilatory threshold. These findings have practical implications because this point is frequently used for aerobic training prescription in healthy subjects, athletes, and in elderly or diseased populations. The ventilatory threshold identified by V(E) curve should be used for aerobic training prescription in healthy subjects and athletes.

Wood CO(2) efflux and foliar respiration for Eucalyptus in Hawaii and Brazil

We measured CO(2) efflux from wood for Eucalyptus in Hawaii for 7 years and compared these measurements with those on three-and four-and-a-half-year-old Eucalyptus in Brazil. In Hawaii, CO(2) efflux from wood per unit biomass declined similar to 10x from age two to age five, twice as much as the decline in tree growth. The CO(2) efflux from wood in Brazil was 8-10x lower than that for comparable Hawaii trees with similar growth rates. Growth and maintenance respiration coefficients calculated from Hawaii wood CO(2) efflux declined with tree age and size (the growth coefficient declined from 0.4 mol C efflux mol C(-1) wood growth at age one to 0.1 mol C efflux mol C(-1) wood growth at age six; the maintenance coefficient from 0.006 to 0.001 mu mol C (mol C biomass)(-1) s(-1) at 20 degrees C over the same time period). These results suggest interference with CO(2) efflux through bark that decouples CO(2) efflux from respiration. We also compared the biomass fractions and wood CO(2) efflux for the aboveground woody parts for 3- and 7-year-old trees in Hawaii to estimate how focusing measurements near the ground might bias the stand-level estimates of wood CO(2) efflux. Three-year-old Eucalyptus in Hawaii had a higher proportion of branches < 0.5 cm in diameter and a lower proportion of stem biomass than did 7-year-old trees. Biomass-specific CO(2) efflux measured at 1.4 m extrapolated to the tree could bias tree level estimates by similar to 50%, assuming no refixation from bark photosynthesis. However, the bias did not differ for the two tree sizes. Foliar respiration was identical per unit nitrogen for comparable treatments in Brazil and Hawaii (4.2 mu mol C mol N(-1) s(-1) at 20 degrees C).

Improved Prediction of Hydrocarbon Flash Points from Boiling Point Data

Flash points (T(FP)) of hydrocarbons are calculated from their flash point numbers, N(FP), with the relationship T(FP) (K) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901 In turn, the N(FP) values can be predicted from experimental boiling point numbers (Y(BP)) and molecular structure with the equation N(FP) = 0.987 Y(BP) + 0.176D + 0.687T + 0.712B - 0.176 where D is the number of olefinic double bonds in the structure, T is the number of triple bonds, and B is the number of aromatic rings. For a data set consisting of 300 diverse hydrocarbons, the average absolute deviation between the literature and predicted flash points was 2.9 K.

Calculating Flash Point Numbers from Molecular Structure: An Improved Method for Predicting the Flash Points of Acyclic Alkanes

We report a novel method for calculating flash points of acyclic alkanes from flash point numbers, N(FP), which can be calculated from experimental or calculated boiling point numbers (Y(BP)) with the equation N(FP) = 1.020Y(BP) - 1.083 Flash points (FP) are then determined from the relationship FP(K) = 23.369N(FP)(2/3) + 20.010N(FP)(1/3) + 31.901 For it data set of 102 linear and branched alkanes, the correlation of literature and predicted flash points has R(2) = 0.985 and an average absolute deviation of 3.38 K. N(FP) values can also be estimated directly from molecular structure to produce an even closer correspondence of literature and predicted FP values. Furthermore, N(FP) values provide a new method to evaluate the reliability of literature flash point data.

Electroanalytical Method for the Analysis of Methyldopa In Pharmaceutical Tablets Using a Crude Extract of Laccase from Pycnoporus sanguineus as Oxidizing Agent

Several colorimetric and chromatographic methods have been used for the identification and quantification of methyldopa (MA) in pharmaceutical formulations and clinical samples. However, these methods are time- and reagent-consuming, which stimulated our efforts to develop a simple, fast, and low-cost alternative method. We carried out an electroanalytical method for the determination of MA in pharmaceutical formulations using the crude enzymatic extract of laccase from Pycnoporus sanguineus as oxidizing agent. This method is based on the biochemical oxidation of MA by laccase (LAC), both in solution, followed by electrochemical reduction on glassy carbon electrode surface. This method was employed for the determination of MA in pure and pharmaceutical formulations and compared with the results obtained using the official method. A wide linear curve from 23 x 10(-5) to 1 x 10(-4) mol L(-1) was found with a detection limit calculated from 43 x 10(-6) mol L(-1).