A Handheld Metabolic Device (Lumen) to Measure Fuel Utilization in Healthy Young Adults: Device Validation Study

Background Metabolic carts measure the carbon dioxide (CO2) produced and oxygen consumed by an individual when breathing to assess metabolic fuel usage (carbohydrates versus fats). However, these systems are expensive, time-consuming, and only available in health care laboratory settings. A small handheld device capable of determining metabolic fuel usage via CO2 from exhaled air has been developed. Objective The aim of this study is to evaluate the validity of a novel handheld device (Lumen) for measuring metabolic fuel utilization in healthy young adults. Methods Metabolic fuel usage was assessed in healthy participants (n=33; mean age 23.1 years, SD 3.9 years) via respiratory exchange ratio (RER) values obtained from a metabolic cart as well as % CO2 from the Lumen device. Measurements were performed at rest in two conditions: fasting, and after consuming 150 grams of glucose, in order to determine changes in metabolic fuel usage. Reduced major axis regression and simple linear regression were performed to test for agreement between RER and Lumen % CO2. Results Both RER and Lumen % CO2 significantly increased after glucose intake (P<.001 for both) compared with fasting conditions, by 0.089 and 0.28, respectively. Regression analyses revealed an agreement between the two measurements (F1,63=18.54; P<.001). Conclusions This study shows the validity of Lumen for detecting changes in metabolic fuel utilization in a comparable manner with a laboratory standard metabolic cart, providing the ability for real-time metabolic information for users under any circumstances.

COMPARING DIRECT CARBONATE AND STANDARD GRAPHITE 14C DETERMINATIONS OF BIOGENIC CARBONATES

ABSTRACT The direct carbonate procedure for accelerator mass spectrometry radiocarbon (AMS 14C) dating of submilligram samples of biogenic carbonate without graphitization is becoming widely used in a variety of studies. We compare the results of 153 paired direct carbonate and standard graphite 14C determinations on single specimens of an assortment of biogenic carbonates. A reduced major axis regression shows a strong relationship between direct carbonate and graphite percent Modern Carbon (pMC) values (m = 0.996; 95% CI [0.991–1.001]). An analysis of differences and a 95% confidence interval on pMC values reveals that there is no significant difference between direct carbonate and graphite pMC values for 76% of analyzed specimens, although variation in direct carbonate pMC is underestimated. The difference between the two methods is typically within 2 pMC, with 61% of direct carbonate pMC measurements being higher than their paired graphite counterpart. Of the 36 specimens that did yield significant differences, all but three missed the 95% significance threshold by 1.2 pMC or less. These results show that direct carbonate 14C dating of biogenic carbonates is a cost-effective and efficient complement to standard graphite 14C dating.

A Handheld Metabolic Device (Lumen) to Measure Fuel Utilization in Healthy Young Adults: Device Validation Study (Preprint)

BACKGROUND Metabolic carts measure the carbon dioxide (CO₂) produced and oxygen consumed by an individual when breathing to assess metabolic fuel usage (carbohydrates versus fats). However, these systems are expensive, time-consuming, and only available in health care laboratory settings. A small handheld device capable of determining metabolic fuel usage via CO₂ from exhaled air has been developed. OBJECTIVE The aim of this study is to evaluate the validity of a novel handheld device (Lumen) for measuring metabolic fuel utilization in healthy young adults. METHODS Metabolic fuel usage was assessed in healthy participants (n=33; mean age 23.1 years, SD 3.9 years) via respiratory exchange ratio (RER) values obtained from a metabolic cart as well as % CO₂ from the Lumen device. Measurements were performed at rest in two conditions: fasting, and after consuming 150 grams of glucose, in order to determine changes in metabolic fuel usage. Reduced major axis regression and simple linear regression were performed to test for agreement between RER and Lumen % CO₂. RESULTS Both RER and Lumen % CO₂ significantly increased after glucose intake (<i>P</i>&lt;.001 for both) compared with fasting conditions, by 0.089 and 0.28, respectively. Regression analyses revealed an agreement between the two measurements (<i>F_1,63</i>=18.54; <i>P</i>&lt;.001). CONCLUSIONS This study shows the validity of Lumen for detecting changes in metabolic fuel utilization in a comparable manner with a laboratory standard metabolic cart, providing the ability for real-time metabolic information for users under any circumstances.

Global Calibration and Error Estimation of Altimeter, Scatterometer, and Radiometer Wind Speed Using Triple Collocation

The accuracy of wind speed measurements is important in many applications. In the present work, error standard deviations of wind speed measured by satellites and National Data Buoy Center (NDBC) buoys were estimated using triple collocation. The satellites included six altimeters, three scatterometers, and four radiometers. The six altimeters were TOPEX, ERS-2, JASON-1, ENVISAT, JASON-2, and CRYOSAT-2, whilst the three scatterometers were QUIKSCAT, METOP-A, and METOP-B and the four radiometers included SSMI-F15, AMSR-2, WINDSAT, and GMI. Hence, a total of 14 platform measurements, including NDBC buoy data, were used and the error standard deviations of each estimated. It was found that altimeters have the smallest error standard deviations for wind speed measurements followed by scatterometers and then radiometers. NDBC buoys have the largest error standard deviation. Since triple collocation can simultaneously perform error estimation as well as calibration for a given reference, this method enables us to perform intercalibration between platform measurements including NDBC buoy. In addition, the calibration relations obtained from triple collocation were compared with the calibrations obtained from the widely used reduced major axis (RMA) regression approach. This method, to some extent, can accommodate measurements in which both platforms contain errors. The results showed that calibration relations obtained from RMA and triple collocation are very similar, as indicated by statistical parameters such as RMSE, correlation coefficient, scatter index, and bias.

Validity of the Lumen® hand-held metabolic device to measure fuel utilization in healthy young adults

BackgroundMetabolic carts measure the carbon dioxide produced and oxygen consumed from the breath in order to assess metabolic fuel usage (carbohydrates vs. fats). However, these systems are expensive, time-consuming, and only available in the clinic. A small hand-held device capable of measuring metabolic fuel via CO2 from exhaled air has been developedObjectiveTo evaluate the validity of a novel hand-held device (Lumen®) for measuring metabolic fuel utilization in healthy young adultsMethodsMetabolic fuel usage was assessed in healthy participants (n = 33; age: 23.1 ± 3.9 y) via respiratory exchange ratio (RER) values from the “gold-standard” metabolic cart as well as %CO2 from the Lumen device. Measurements were performed at rest in two conditions, fasting, and after consuming 150 grams of glucose in order to determine changes in metabolic fuel. Reduced major axis regression was performed as well as Bland-Altman plots and linear regressions to test for agreement between RER and Lumen %CO2.ResultsBoth RER and Lumen %CO2 significantly increased after glucose intake compared with fasting conditions (P < .0001). Regression analyses and Bland-Altman plots revealed an agreement between the two measurements with a systematic bias resulting from the nature of the different units.ConclusionsThis study shows the validity of Lumen® to estimate metabolic fuel utilization in a comparable manner with the “gold-standard” metabolic cart, providing the ability for real-time metabolic information for users under any circumstances.

Abstract WP30: Delay and Dispersion Correction Leads to More Accurate Core Estimation for Endovascular Thrombectomy Patients

Objective: Endovascular thrombectomy (EVT) significantly improves clinical outcomes in acute ischemic stroke with large vessel occlusion. Clinical benefits are inversely proportional to size of the pre-treatment ischemic core. Therefore, accurate measurement of the size of core is critical in selecting patients for EVT. Different post-processing perfusion algorithms for automated core calculation on perfusion CT (CTP) are based on variations of deconvolution of the tissue concentration time curve with the arterial input function (single value decomposition, or SVD). In this study, we compared ischemic core estimated by two different CTP automated algorithms to the final infarct volume as demonstrated by follow up diffusion weighted imaging (DWI). Methods: We performed a retrospective analysis of patients who underwent EVT. Inclusion criteria were CT perfusion scan prior to EVT, successful EVT with mTICI 2b-3 reperfusion, and DWI scan 24-48 hours post-EVT. CTP data were processed by two different post-processing algorithms: ‘delay-insensitive’ single value decomposition (DISVD) and delay and dispersion corrected single value decomposition (ddSVD) using the respective commercially available automated CTP software. CTP core volumes from both methods were compared with DWI final infarct volumes using an independent software (MRIcron) for concordance. The agreement between a given algorithm and MRI was estimated using Lin’s concordance coefficient and further investigated using reduced major axis regression. Results: One hundred and three patients who underwent EVT and achieved successful mTICI 2b-3 reperfusion were included. Both algorithms had excellent agreement with MRI (Lin’s concordance coefficients: DISVD 0.8 (95% CI: 0.73; 0.87), ddSVD 0.92 (95% CI: 0.89; 0.95). Compared to ddSVD (reduced major axis slope = 0.95), DISVD exhibited larger extent of proportional bias (slope = 1.12). Conclusion: Both algorithms showed excellent agreement with FIV calculated on MRI but DISVD post-processing overestimated the larger ischemic cores, which may lead to unnecessary exclusion of patients from EVT due to a 'large core'.

Allometric growth in meiofaunal invertebrates: do all kinorhynchs show homogeneous trends?

Allometry determines relevant modifications in metazoan morphology and biology and is affected by many different factors, such as ontogenetic constraints and natural selection. A linear mixed model approach and reduced major axis regression were used to explore evolutionary interspecific allometric trends between the total trunk length and the lengths of the segments and spines in the phylum Kinorhyncha at three taxonomic levels: the whole phylum, the class and the family. Statistically significant results were found in all the trunk segments, meaning that these body units grow proportionally correlated with the body, contrary to the results obtained for the spines. Developmental and morphophysiological constraints could lead to negative allometry in the first and last segments, because these body regions in kinorhynchs are essential to the implementation of some of the main biological functions, such as feeding and locomotion. The differential arrangement of cuticular appendages between the taxonomic groups considered seems to cause different evolutionary trends, because positive allometry may appear if a segment requires more space to accommodate a large number of organs and appendages, and vice versa. The presence of sexual dimorphism could also define positive allometry of a segment, owing to the need to harbour the sexually dimorphic appendages and their associated structures.

Soil grain size analysis by the dynamometer method – a comparison to the pipette and hydrometer method

The aim of the presented work was to compare the results of grain size distribution measurement by an innovative dynamometer method, developed by the authors, with results obtained by the pipette and hydrometer methods. Repeatability of results obtained in the dynamometer method was also determined. The content of three fractions with equivalent diameters <0.002 mm, 0.002–0.063 mm and 0.063–2.0 mm was measured. The results were compared using ordinary linear regression and additionally in the repeatability analysis by RMA (reduced major axis regression). It was found that the proposed dynamometer method is characterized by good result repeatability with no systematic errors when compared with the pipette method. The RMSE (root mean square error) value when referring to the pipette method calculated for the three fractions considered in total was 4.9096 and was lower than the analogous for the hydrometer method, which amounted to 5.4577. Values of determination coefficients in the comparison of dynamometer method and pipette method are within the range of 0.9681–0.9951 for the different fractions. It was found that slightly larger differences in relation to the pipette method occurred for the fractions <0.002 mm and 0.002–0.063 mm, and smaller for the fraction 0.063–2.0 mm. Similarly, greater differences between repetitions in the dynamometer method were observed for the fraction <0.002 mm, and smaller for the 0.063–2.0 mm fraction. Possible sources of errors in the dynamometer method were discussed, as were proposals for their reduction.

Comparison of VOC measurements made by PTR-MS, Adsorbent Tube/GC-FID-MS and DNPH-derivatization/HPLC during the Sydney Particle Study, 2012: a contribution to the assessment of uncertainty in current atmospheric VOC measurements

Understanding uncertainty is essential for utilizing atmospheric VOC measurements in robust ways to develop atmospheric science. This study describes an inter-comparison of the VOC data, and the derived uncertainty estimates, measured with three independent techniques (PTR-MS, AT-GC-FID and DNPH-HPLC) during the Sydney Particle Study campaigns in 2012. The compounds and compound classes compared, based on objective selection criteria from the available data, were: benzene, toluene, C8 aromatics, isoprene, formaldehyde, acetaldehyde and acetone. Bottom-up uncertainty analyses were undertaken for each compound and each measurement system. Top-down uncertainties were quantified via the inter-comparisons. Four metrics were used for the inter-comparisons: the slope and intercept as determined by reduced major axis regression, the correlation, and the root mean standard deviation of the observation from the regression line. In all seven comparisons the correlations between independent measurement techniques were high with R2 values of median 0.93 (range: 0.72–0.98) and small root mean standard deviations of the observations from the regression line with a median of 0.13 (range: 0.04–0.23 ppb). These results give a high degree of confidence that for each comparison the response of the two independent techniques are dominated by the same constituents. The slope and intercept as determined by reduced major axis regression gives a different story. The slopes varied considerably with a median of 1.23 and range 1.08 to 2.03. The intercepts varied with a median of 0.02 and range −0.07 to 0.31 ppb. An ideal comparison would give a slope of 1.00 and an intercept of zero. This analysis identified some poorly understood and poorly quantified sources of uncertainty in the measurement techniques including: the contributions of non-target compounds to the measurement of the target compound for benzene, toluene and isoprene by PTR-MS; and, the under-reporting of formaldehyde, acetaldehyde and acetone by the DNPH technique. As well as these, this study has identified a specific interference of liquid water with acetone measurements by the DNPH technique. These relationships reported for Sydney 2012 were incorporated into a larger analysis with 61 other published inter-comparison studies for the same compounds. Overall for the light aromatics, isoprene and the C1–C3 carbonyls the uncertainty in a set of measurements varies by a factor of between 1.5 and two. These uncertainties (~50 %) are significantly higher than uncertainties estimated using standard propagation of error methods, which in this case were ~22 % or less, and are the result of the presence of poorly understood or neglected processes that affect the measurement and its uncertainty. The uncertainties in VOC measurements identified here should be considered when: assessing the reliability of VOC measurements from individual instruments; when utilising VOC data to constrain and inform air quality and climate models; when using VOC observations for human exposure studies; and, when comparing ambient VOC data with satellite retrievals.