Fitness Metrics Research Articles

Baseball performance via the lens of anthropometric testing, fitness metrics, and statistics: a longitudinal cross-sectional study

Background: Anthropometric testing (AT) and fitness metrics (FM) are contributing factors for success in sports. Limited evidence exists regarding longitudinal baseball AT or FM roles on baseball performance statistics (PS). AT, FM, and PS associations were examined for 5 yr to create a performance model. Methods: Eighty collegiate Division I players participated in this study. Height, mass, and body fat percentage (BF%) were selected as AT variables of interest. Grip strength (GS), one repetition maximum squat (1RMSQ), and vertical-jump height were selected for FM. Batting average percentage (AVG), slugging percentage (SLG), on-base percentage (OBP) baseball statistics were selected as offensive PS. Earned run average (ERA), batting average against percentage (B/AVG), and strike-out per innings pitched for 9 innings (SO/IP)*9 were selected for defensive PS. Results: Offensive (r=−0.15, P<0.005; rs=−0.17, P<0.001) and defensive (r=−0.253, P<0.001; rs=−0.314, P<0.001) statistics correlated with BF%. Offensive (r=0.26, P<0.001; rs=0.43, P<0.001) and defensive (r=0.39, P<0.001) statistics correlated with GS. Offensive (r=0.26, P<0.001; rs=0.43, P<0.001) and defensive (r=0.27, P<0.001) statistics correlated with 1RMSQ. Offensive statistics AVG (R2=0.48) and SLG (R2=0.46) were explained by 1RMSQ. For defensive statistics, 1RMSQ was the best fit for (SO/IP)*9 (R2=0.43) and B/AVG (R2=0.52), and GS was the best fit for ERA (R2=0.39). Squat and time interaction for B/AVG was significant (P=0.04). Conclusions: Baseball PS are associated with 1RMSQ and GS. Time moderates the effect of squat training on B/AVG. Pitchers need to include squats to lower their B/AVG. Coaches may focus on improving such FM variables and consider the time effect on selected FM that may affect PS. Level of Evidence: Level IV

On the Performance of Isotropic Hyperelastic Constitutive Models for Rubber-Like Materials: A State of the Art Review

Abstract Besides the well-known landmark models for the hyperelastic response of rubberlike materials, many new hyperelastic constitutive models have emerged over the last decade. Despite many reviews on constitutive modeling or elastomers, it is still a challenging endeavor for engineers to decide for a constitutive model for the specific rubber compound and application. In this work, we have reviewed 44 hyperelastic constitutive models for elastomers and assessed their strength and weaknesses under uniaxial, pure shear, and (equi)biaxial deformations. To this end, we first present a novel parameter identification methodology based on various multi-objective optimization strategies for the selection of the best constitutive models from a given set of uniaxial tension, pure shear, and (equi)biaxial tension experiments. We utilize a hybrid multi-objective optimization procedure using a genetic algorithm to generate multiple initial points for gradient-based search algorithm, Fmincon utility in matlab. The novelty of the approach is (i) simultaneous fitting with variable weight factors for uniaxial, equibiaxial, and pure shear data, and (ii) the sorting of the models based on objective normalized quality of fit metric. For the models incapable of simultaneously fitting the three distinct deformation data, the validity range is assessed through a threshold value for the quality of fit measure. Accordingly, 44 hyperelastic models are sorted with respect to their simultaneous fitting performance to the experimental dataset of Treloar and Kawabata. Based on the number of material parameters, and their fitting performance to experimental data, a detailed discussion is carried out.

Effect of High-Intensity Interval Training, Moderate Continuous Training, or Guideline-Based Physical Activity Advice on Peak Oxygen Consumption in Patients With Heart Failure With Preserved Ejection Fraction

Endurance exercise is effective in improving peak oxygen consumption (peak V̇o2) in patients with heart failure with preserved ejection fraction (HFpEF). However, it remains unknown whether differing modes of exercise have different effects. To determine whether high-intensity interval training, moderate continuous training, and guideline-based advice on physical activity have different effects on change in peak V̇o2 in patients with HFpEF. Randomized clinical trial at 5 sites (Berlin, Leipzig, and Munich, Germany; Antwerp, Belgium; and Trondheim, Norway) from July 2014 to September 2018. From 532 screened patients, 180 sedentary patients with chronic, stable HFpEF were enrolled. Outcomes were analyzed by core laboratories blinded to treatment groups; however, the patients and staff conducting the evaluations were not blinded. Patients were randomly assigned (1:1:1; n = 60 per group) to high-intensity interval training (3 × 38 minutes/week), moderate continuous training (5 × 40 minutes/week), or guideline control (1-time advice on physical activity according to guidelines) for 12 months (3 months in clinic followed by 9 months telemedically supervised home-based exercise). Primary end point was change in peak V̇o2 after 3 months, with the minimal clinically important difference set at 2.5 mL/kg/min. Secondary end points included changes in metrics of cardiorespiratory fitness, diastolic function, and natriuretic peptides after 3 and 12 months. Among 180 patients who were randomized (mean age, 70 years; 120 women [67%]), 166 (92%) and 154 (86%) completed evaluation at 3 and 12 months, respectively. Change in peak V̇o2 over 3 months for high-intensity interval training vs guideline control was 1.1 vs -0.6 mL/kg/min (difference, 1.5 [95% CI, 0.4 to 2.7]); for moderate continuous training vs guideline control, 1.6 vs -0.6 mL/kg/min (difference, 2.0 [95% CI, 0.9 to 3.1]); and for high-intensity interval training vs moderate continuous training, 1.1 vs 1.6 mL/kg/min (difference, -0.4 [95% CI, -1.4 to 0.6]). No comparisons were statistically significant after 12 months. There were no significant changes in diastolic function or natriuretic peptides. Acute coronary syndrome was recorded in 4 high-intensity interval training patients (7%), 3 moderate continuous training patients (5%), and 5 guideline control patients (8%). Among patients with HFpEF, there was no statistically significant difference in change in peak V̇o2 at 3 months between those assigned to high-intensity interval vs moderate continuous training, and neither group met the prespecified minimal clinically important difference compared with the guideline control. These findings do not support either high-intensity interval training or moderate continuous training compared with guideline-based physical activity for patients with HFpEF. ClinicalTrials.gov Identifier: NCT02078947.

An end-to-end approach and tool for BPMN process discovery

Information systems daily register a large amount of data in event logs. All these data can be used for the organizations to automatically discover their process models. However, the automatic construction of simple process models with consistently high and balanced fitness and precision remains a challenging task, which has attracted the attention in the scientific and organizational communities to develop suitable methods for creating high-quality business process models. In this paper, we present an approach to discover the model of a business process based on the Business Process Model and Notation (BPMN) standard from its behavior observed in event logs. Particularly, we propose: (1) a method to detect outlier behavior in a given event log; (2) a set of heuristic rules to discover join gateways associated with the closing of each of the split gateways in conformance with the rules of BPMN models; and (3) P-Miner, a tool that realizes our proposed approach to automatically discover and visualize process models. We use a state of the art process discovery technique as a basis for discovering XOR/AND gateways in the models. A set of experiments was carried out on real and artificial event logs for evaluating our proposal, considering the fitness and precision metrics to determine the quality of the built models. The amount of gateways in the resulting BPMN model and the time required to build the process models were estimated. The results reveal that the process models derived by our proposed approach exhibited competitive and more balanced results in fitness and precision than those derived with other discovery techniques.

The Effects of Cardiorespiratory and Motor Skill Fitness on Intrinsic Functional Connectivity of Neural Networks in Individuals with Parkinson's Disease.

Background:Studies in aging older adults have shown the positive association between cognition and exercise related fitness, particularly cardiorespiratory fitness. These reports have also demonstrated the association of high cardiorespiratory fitness, as well as other types of fitness, on the reversal of age-related decline in neural network connectivity, highlighting the potential role of fitness on age- and disease-related brain changes. While the clinical benefits of exercise are well-documented in Parkinson’s disease (PD), the extent to which cardiorespiratory fitness (assessed by estimated VO2max testing) or motor skill fitness (assessed by the Physical Performance Test (PPT)) affects neural network connectivity in PD remains to be investigated. The purpose of this study was to explore the hypothesis that higher fitness level is associated with an increase in the intrinsic network connectivity of cognitive networks commonly affected in PD.Methods:In this cross-sectional resting state fMRI, we used a multivariate statistical approach based on high-dimensional independent component analysis (ICA) to investigate the association between two independent fitness metrics (estimated VO2max and PPT) and resting state network connectivity.Results:We found that increased estimated VO2max was associated with increased within network connectivity in cognitive networks known to be impaired in PD, including those sub-serving memory and executive function. There was a similar trend for high levels of PPT to be associated with increased within network connectivity in distinct resting state networks. The between functional network connectivity analysis revealed that cardiorespiratory fitness was associated with increased functional connectivity between somatosensory motor network and several cognitive networks sub-serving memory, attention, and executive function.Conclusion:This study provides important empirical data supporting the potential association between two forms of fitness and multiple resting state networks impacting PD cognition. Linking fitness to circuit specific modulation of resting state network connectivity will help establish a neural basis for the positive effects of fitness and specific exercise modalities and provide a foundation to identify underlying mechanisms to promote repair.

Bias correction of climate model outputs influences watershed model nutrient load predictions

Waterbodies around the world experience problems associated with elevated phosphorus (P) and nitrogen (N) loads. While vital for ecosystem functioning, when present in excess amounts these nutrients can impair water quality and create symptoms of eutrophication, including harmful algal blooms. Under a changing climate, nutrient loads are likely to change. While climate models can serve as inputs to watershed models, the climate models often do not adequately represent the distribution of observed data, generating uncertainties that can be addressed to some degree with bias correction. However, the impacts of bias correction on nutrient models are not well understood. This study compares 4 univariate and 3 multivariate bias correction methods, which correct precipitation and temperature variables from 4 climate models in the historical (1980–1999) and mid-century future (2046–2065) time periods. These variables served as inputs to a calibrated Soil and Water Assessment Tool (SWAT) model of Lake Erie's Maumee River watershed. We compared the performance of SWAT outputs driven with climate model outputs that were bias-corrected (BC) and not bias-corrected (no-BC) for dissolved reactive P, total P, and total N. Results based on graphical comparisons and goodness of fit metrics showed that the choice of BC method impacts both the direction of change and magnitude of nutrient loads and hydrological processes. While the Delta method performed best, it should be used with caution since it considers historical variable relationships as the basis for predictions, which may not hold true under future climate. Quantile Delta Mapping (QDM) and Multivariate Bias Correction N-dimensional probability density function transform (MBCn) BC methods also performed well and work well for non-stationary climate scenarios. Furthermore, results suggest that February–July cumulative load in the Maumee basin is likely to decrease in the mid-century as runoff and snowfall decrease, and evapotranspiration increases with warming temperatures.

A meta-analysis of construct reliability indices and measurement model fit metrics

The present research examined the distributional properties of construct reliability indices and model fit metrics, explored relationships between and among the indices and metrics, and investigated variables influencing the relative magnitudes of the indices and metrics in structural equation measurement models. A broad-based meta-analysis of reported construct reliability indices and selected model fit metrics revealed modest relationships among reliability indices, minimal relationships among model fit metrics, and a virtual absence of relationships between reliability indices and model fit metrics. Differences in magnitudes of selected reliability indices and model fit metrics were found to primarily be a function of the (total) number of items employed in a measurement model. The implications of the findings suggest that the current practice of indiscriminately computing and reporting of reliability indices and model fit metrics based only on arbitrary heuristics should be abolished and replaced by theoretically justified indices and metrics.

Impact of Sarcopenia on Survival in Patients With Early-Stage Lung Cancer Treated With Stereotactic Body Radiation Therapy.

BackgroundSarcopenia has been associated with poor survival among cancer patients. Normalized total psoas area (NTPA) has been used as a surrogate for defining sarcopenia. Few data exist characterizing the impact of sarcopenia and other metrics of fitness on clinical outcomes in patients with early-stage non-small cell lung cancer (NSCLC) treated non-invasively with stereotactic body radiotherapy (SBRT).MethodsTo assess the association between sarcopenia and clinical outcomes, we conducted a retrospective analysis of consecutive patients treated with SBRT from 2013 to 2019 . Overall survival (OS), local failure free survival (LFS), distant failure free survival (DFS), NTPA, body mass index (BMI), and Charlson comorbidity index (CCI) were included for analysis. NTPA was calculated by measuring the psoas volume at the L3 vertebra and normalizing for patient height and gender. Survival functions were evaluated using the Kaplan-Meier method. Log-rank test and Cox-proportional hazards were performed for categorical and continuous variables, respectively. Significance was set as p < 0.05.ResultsA total of 91 patients met the criteria. The median age was seven years and Karnofsky Performance Status score (KPS) was 80 (range: 60-100). Approximately 79% of patients had T1 tumors. Median radiation dose and number of fractions were 60 Gy (range: 45-60) and 5 fractions (range: 3-5). Median NTPA was 531.16 mm2/m2 (range: 90.4-1356.2). After normalization (sarcopenia: <385 mm2/m2, female; <585 mm2/m2, male), 39 patients (42.8%) had sarcopenia. NTPA had no association with OS (p = 0.7), LFS (p = 0.9), or DFS (p = 0.5). Increasing BMI was associated with improved OS (HR 0.90, 95% CI 0.83-0.98). With a median follow-up of 23.4 months, median OS was 60, 60, and 45.9 months (p = 0.37) in all patients, non-sarcopenic patients, and sarcopenic patients, respectively.ConclusionSarcopenia was not associated with OS, LFS, or DFS. Increasing BMI is associated with improved OS. Future, prospective work is needed to define the impact of sarcopenia and other fitness metrics on clinical outcomes among NSCLC patients treated non-invasively with SBRT.

Contrasting cumulative risk and multiple individual risk models of the relationship between Adverse Childhood Experiences (ACEs) and adult health outcomes

BackgroundA very large body of research documents relationships between self-reported Adverse Childhood Experiences (srACEs) and adult health outcomes. Despite multiple assessment tools that use the same or similar questions, there is a great deal of inconsistency in the operationalization of self-reported childhood adversity for use as a predictor variable. Alternative conceptual models are rarely used and very limited evidence directly contrasts conceptual models to each other. Also, while a cumulative numeric ‘ACE Score’ is normative, there are differences in the way it is calculated and used in statistical models. We investigated differences in model fit and performance between the cumulative ACE Score and a ‘multiple individual risk’ (MIR) model that enters individual ACE events together into prediction models. We also investigated differences that arise from the use of different strategies for coding and calculating the ACE Score.MethodsWe merged the 2011–2012 BRFSS data (N = 56,640) and analyzed 3 outcomes. We compared descriptive model fit metrics and used Vuong’s test for model selection to arrive at best fit models using the cumulative ACE Score (as both a continuous or categorical variable) and the MIR model, and then statistically compared the best fit models to each other.ResultsThe multiple individual risk model was a better fit than the categorical ACE Score for the ‘lifetime history of depression’ outcome. For the outcomes of obesity and cardiac disease, the cumulative risk and multiple individual risks models were of comparable fit, but yield different and complementary inferences.ConclusionsAdditional information-rich inferences about ACE-health relationships can be obtained from including a multiple individual risk modeling strategy. Results suggest that investigators working with large srACEs data sources could empirically derive the number of items, as well as the exposure coding strategy, that are a best fit for the outcome under study. A multiple individual risk model could also be considered in addition to the cumulative risk model, potentially in place of estimation of unadjusted ACE-outcome relationships.

Protein metabolism and physical fitness are physiological determinants of body condition in Southern European carnivores

The physiological significance of biometric body condition indices (bBCI) is poorly understood. We hypothesized that bBCI are composite metrics of nutritional physiology, physical fitness and health. To test this hypothesis, we first compared the performance of eight bBCI, using 434 Southern European carnivores from six species as a model system; and then identified, by non-destructive methods, the hematology and serum biochemistry correlates of three selected bBCI. Fulton’s K Index, Major Axis Regression Residuals and Scaled Mass Index were the only bBCI insensitive to the effect of sex and age. The most informative physiological parameters in explaining the variation of these bBCI were the albumin (Effect Size (ES) = − 1.66 to − 1.76), urea (ES = 1.61 to 1.85) and total bilirubin (ES = − 1.62 to − 1.79). Hemoglobin and globulins (positive) and cholesterol (negative) were moderately informative (0.9 <|ES|< 1.5). This study shows that most bBCI do not control for the effect of age and sex in Southern European carnivores. Our results support that bBCI are composite measures of physiologic processes, reflecting a positive gradient from protein-poor to protein-rich diets, accompanied by increased physical fitness. Biometric body condition indices allow the integration of ecologically relevant physiological aspects in an easily obtained metric.

Science-Driven Societal Transformation, Part I: Worldview

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches to reduce risk are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached. As part of this, it advances a formal mechanics with which to model and understand self-organizing societies of individuals. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview, built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory, which is intended to serve as the foundation for the R&amp;D program. Subsequent papers in the series build on the worldview to address fitness metrics, system design, and other topics.

Detecting Hierarchical and Overlapping Network Communities Based on Opinion Dynamics

It is common for communities in real-world networks to possess hierarchical and overlapping structures, which make community detection even more challenging. In this paper, by investigating consensus process of the classical DeGroot model in opinion dynamics, we propose a novel method based on the cumulative opinion distance (COD) to discover hierarchical and overlapping communities. It is shown that this method is different from those classical algorithms relying on static fitness metrics that depict the inhomogeneous connectivity across the network. The proposed method is validated from two aspects. First, by estimating the eigenvectors of adjacency matrices, we investigate the detectability limit of our algorithms on random networks, which together with the results concerning the convergence speed of consensus guarantees the performance of our method theoretically. Second, experiments on both \tcb{large scale} real-world networks and artificial benchmarks show that our method is very effective and competitive on hierarchical modular graphs. In particular, it outperforms the state-of-the-art algorithms on overlapping community detection.

Physical fitness and white matter microstructure in children with overweight or obesity: the ActiveBrains project

Recent studies investigated the association of cardiorespiratory fitness with white matter microstructure in children, yet little work has explored to what extent other components of physical fitness (i.e., muscular or motor fitness) are associated with white matter microstructure. Indeed, this association has not been previously explored in children with overweight/obesity who present a different white matter development. Therefore, we aimed to examine associations between physical fitness components and white matter microstructure in children with overweight/obesity. In total, 104 (10.04 ± 1.15 years old; 43 girls) children were included in this cross-sectional study. Physical fitness was assessed using the ALPHA-fitness test battery. Fractional anisotropy (FA) and mean diffusivity were derived from diffusion tensor imaging (DTI). No association was found between physical fitness and global DTI metrics (all P > 0.082). Within individual tracts, all associations became non-significant when analyses were adjusted for multiple comparisons. Using the voxel-wise approach, we identified a small cluster in the left lateral frontal lobe where children with greater upper-body muscular fitness showed higher FA (PFWE-corrected = 0.042). Although our results cannot conclude physical fitness is related to white matter microstructure in children with overweight/obesity; those findings indicate that the association of muscular fitness with white matter microstructure might be more focal on frontal areas of the brain, as opposed to global differences.

Bayesian Tip-Dated Phylogenetics in Paleontology: Topological Effects and Stratigraphic Fit.

The incorporation of stratigraphic data into phylogenetic analysis has a long history of debate but is not currently standard practice for paleontologists. Bayesian tip-dated (or morphological clock) phylogenetic methods have returned these arguments to the spotlight, but how tip dating affects the recovery of evolutionary relationships has yet to be fully explored. Here I show, through analysis of several data sets with multiple phylogenetic methods, that topologies produced by tip dating are outliers as compared to topologies produced by parsimony and undated Bayesian methods, which retrieve broadly similar trees. Unsurprisingly, trees recovered by tip dating have better fit to stratigraphy than trees recovered by other methods under both the Gap Excess Ratio (GER) and the Stratigraphic Completeness Index (SCI). This is because trees with better stratigraphic fit are assigned a higher likelihood by the fossilized birth-death tree model. However, the degree to which the tree model favors tree topologies with high stratigraphic fit metrics is modulated by the diversification dynamics of the group under investigation. In particular, when net diversification rate is low, the tree model favors trees with a higher GER compared to when net diversification rate is high. Differences in stratigraphic fit and tree topology between tip dating and other methods are concentrated in parts of the tree with weaker character signal, as shown by successive deletion of the most incomplete taxa from two data sets. These results show that tip dating incorporates stratigraphic data in an intuitive way, with good stratigraphic fit an expectation that can be overturned by strong evidence from character data. [fossilized birth-death; fossils; missing data; morphological clock; morphology; parsimony; phylogenetics.].

Assessment Of Cardiorespiratory Fitness In Older Adults With Cognitive Impairment

Interest in the potential benefits of physical activity (PA) and exercise on cognition in late life has grown exponentially in the past decade. Peak oxygen uptake (VO2) is one of the most widely used metrics of physical fitness. The most accurate measure of VO2 is cardiopulmonary testing (CPX); however, this method may not be easily accessible in many settings nor appropriate for all populations, including older adults. Self-report measures of PA are easily administered and readily available, yet these measures rely on an accurate recall of past activity. This may be difficult for older adults with even mild forms of cognitive impairment. Identifying alternative methods that accurately estimate a patient’s physical fitness are essential. PURPOSE: To evaluate the use of multiple measures of physical fitness in a sample of older adults with amnestic Mild Cognitive Impairment (aMCI). METHODS: The sample included 105 older adults who were diagnosed with aMCI (93.3% male, aged = 71.2 ± 9.2 years). Measures of physical fitness included CPX, 6-minute walk test (6MWT), and the Yale Physical Activity Survey (YPAS). Analysis included comparison of the sub-maximal measures of physical fitness (6MWT) and self-report measures (YPAS) with directly-measured cardiorespiratory fitness on key measures on physiologic measures of fitness (e.g., peak VO2, resting blood pressure (BP), BMI). RESULTS: The 6MWT demonstrated a stronger correlation with directly-measured peak VO2 (r = 0.62, p = 0.00) compared to YPAS. The YPAS activity dimensions summary index (composed of questions on vigorous activity, leisurely walking, moving, sitting, and standing) correlated marginally with VO2max (r = 0.28; P = 0.01). The YPAS index of vigorous activity was slightly correlated with VO2max (r = 0.21; P = 0.03). CPX was inversely correlated with BMI (r=-0.21; P=0.03) and non-significantly with resting BP. Resting BP and BMI was not significantly associated with 6MWT nor the YPAS indices. CONCLUSION: The present analysis suggests that even mild forms of cognitive impairment impact the validity of self-report measures of physical fitness. Sub-maximal tests of aerobic capacity, such as the 6MWT, provide more accurate estimates of cardiorespiratory fitness and are easily administered in a variety of settings in which older adults receive health care.

Validation Of The Humon Hex Lactate Threshold Estimate

Fitness trackers track a wide range of fitness and physiological metrics, including muscle oxygen saturation and lactate threshold (LT). The Humon Hex (HH) is a low-cost wearable device that uses continuous-wave near-infrared spectroscopy (NIRS) to determine muscle oxygen saturation. The HH is unique in its ability to estimate LT based on muscle oxygen saturation during a threshold test. PURPOSE: The purpose of this study was to determine the validity and accuracy of predicting LT from continuous-wave NIRS compared to lab-based measurements. METHODS: 15 healthy, recreational runners (6 male, 9 female, 26.1 ± 6.4yrs, 67.9 ± 16.3kg, 173.3 ± 9.5cm, 31.6 ± 21.5km/week) participated in a single threshold test on a treadmill. The protocol was dictated by the HH device (“Threshold Test” in the app) and involved increasing treadmill velocity by 0.22 m/s (0.5 mph) every 3 min until volitional exhaustion. At the end of each stage, participants would straddle the treadmill while researchers collected and analyzed the blood lactate levels using a Lactate Scout portable lactate analyzer (Lactate.com). The HH LT estimate was provided by the Humon website. Blood lactate levels were recorded and graphed, and LT was derived by identifying the point immediately prior to where lactate levels had a greater than 1mmol/L jump from the previous stage that also placed the total lactate concentration above 4mmol/L. A 2-tailed, paired t-test, mean absolute percentage error (MAPE), single measures Intraclass Correlations (ICC), and Bland-Altman analysis with accompanying bias and Limits of Agreement were performed, calculated and plotted. RESULTS: There was no difference between the HH estimated LT velocity compared to the lab-based methods (12.5 ± 2.0km and 12.7 ± 1.3km/hr, respectively). There was a MAPE of 9.00% and an ICC of 0.652 with a 95% confidence interval of -0.222 to 0.869 (F(15,15) = 4.546, p = 0.004) when comparing the variables. CONCLUSION: Although there was no difference between HH estimated LT velocity compared to laboratory testing, the MAPE was above 5% and ICC slightly below 0.7 with a significant relationship. This data suggests that the HH does not produce a completely valid estimate of LT compared to lab-based tests; however, it still may be useful in situations where laboratory testing may not be available or practical.

Relative importance analysis with multivariate models: Shifting the focus from independent variables to parameter estimates

Conclusions regarding the relative importance of different independent variables in a statistical model have meaningful implications for theory and practice. However, methods for determining relative importance have yet to extend beyond statistical models with a single dependent variable and a limited set of multivariate models. To accommodate multivariate models, the current work proposes shifting away from the concept of independent variable relative importance toward that of parameter estimate relative importance (PERI). This paper illustrates the PERI approach by comparing it to the evaluation of regression slopes and independent variable relative importance (IVRI) statistics to show the interpretive and methodological advantages of the new concept and associated methods. PERI’s advantages above standardized slopes stem from the same fit metric that is used to compute PERI statistics; this makes them more comparable to one another than standardized slopes. PERI’s advantages over IVRI stem from situations where independent variables do not predict all dependent variables; hence, PERI permits importance determination in situations where independent variables are nested in dependent variables they predict. We also provide recommendations for implementing PERI using dominance analysis with statistical models that can be estimated with maximum likelihood estimation combined with a series of model constraints using two examples.

Predicting greenhouse gas benefits of improved nitrogen management in North American maize.

Farmers, food supply companies, and policymakers need practical yet scientifically robust methods to quantify how improved nitrogen (N) fertilizer management can reduce nitrous oxide (N2 O) emissions. To meet this need, we developed an empirical model based on published field data for predicting N2 O emission from rainfed maize (Zea mays L.) fields managed with inorganic N fertilizer in the United States and Canada. Nitrous oxide emissions ranged widely on an area basis (0.03-32.9kg N ha-1 yr-1 ) and a yield-scaled basis (0.006-4.8kg N Mg-1 grain yr-1 ). We evaluated multiple modeling approaches and variables using three metrics of model fit (Akaike information criteria corrected for small sample sizes [AICc], RMSE, and R2 ). Our model explains 32.8% of the total observed variation and 50% of observed site-level variation. Soil clay content was very important for predicting N2 O emission and predicting the change in N2 O emission due to a change in N balance, with the addition of a clay fixed effect explaining 37% of site-level variation. Sites with higher clay content showed greater reductions in N2 O emission for a given reduction in N balance. Therefore, high-clay sites are particularly important targets for reducing N2 O emissions. Our linear mixed model is more suitable for predicting the effect of improved N management on N2 O emission in maize fields than other published models because it (a) requires only input data readily available on working farms, (b) is derived from field observations, (c) correctly represents differences among sites using a mixed modeling approach, and (d) includes soil texture because it strongly influences N2 O emissions.

The initial engraftment of tumor cells is critical for the future growth pattern: a mathematical study based on simulations and animal experiments

BackgroundXenograft mouse tumor models are used to study mechanisms of tumor growth and metastasis formation and to investigate the efficacy of different therapeutic interventions. After injection the engrafted cells form a local tumor nodule. Following an initial lag period of several days, the size of the tumor is measured periodically throughout the experiment using calipers. This method of determining tumor size is error prone because the measurement is two-dimensional (calipers do not measure tumor depth). Primary tumor growth can be described mathematically by suitable growth functions, the choice of which is not always obvious. Growth parameters provide information on tumor growth and are determined by applying nonlinear curve fitting.MethodsWe used self-generated synthetic data including random measurement errors to research the accuracy of parameter estimation based on caliper measured tumor data. Fit metrics were investigated to identify the most appropriate growth function for a given synthetic dataset. We studied the effects of measuring tumor size at different frequencies on the accuracy and precision of the estimated parameters. For curve fitting with fixed initial tumor volume, we varied this fixed initial volume during the fitting process to investigate the effect on the resulting estimated parameters. We determined the number of surviving engrafted tumor cells after injection using ex vivo bioluminescence imaging, to demonstrate the effect on experiments of incorrect assumptions about the initial tumor volume.ResultsTo select a suitable growth function, measurement data from at least 15 animals should be considered. Tumor volume should be measured at least every three days to estimate accurate growth parameters. Daily measurement of the tumor volume is the most accurate way to improve long-term predictability of tumor growth. The initial tumor volume needs to have a fixed value in order to achieve meaningful results. An incorrect value for the initial tumor volume leads to large deviations in the resulting growth parameters.ConclusionsThe actual number of cancer cells engrafting directly after subcutaneous injection is critical for future tumor growth and distinctly influences the parameters for tumor growth determined by curve fitting.

Finding the Sweet Spot: Sub-Ambient Light Increases Fitness and Kleptoplast Survival in the Sea Slug Plakobranchus cf. ianthobaptus Gould, 1852.

Sacoglossans, or "sap-sucking" sea slugs, are primarily algivorous, with many taxa exhibiting kleptoplasty, the feeding and retaining of photosynthetically active chloroplasts from algae. The Plakobranchus species complex exhibits some of the longest kleptoplast retention and survival times under starvation conditions, but the contributions of these kleptoplasts to their survival and overall fitness have been widely debated. In this study we assessed the effects of starvation and light on the fitness of Plakobranchus cf. ianthobaptus and its kleptoplasts by placing starved individuals in eight daily average light treatments, ranging from near dark (2 µmol photon m-2 s-1) to ambient light (470 µmol photon m-2 s-1). Slug weight was used as a metric of fitness, and kleptoplast photosynthetic activity was determined via maximum quantum yield (Fv/Fm) by pulse-amplitude modulated fluorometry as a proxy for kleptoplast health. Plakobranchus individuals in near-dark and highlight treatments (>160 µmol photon m-2 s-1) experienced significantly greater weight loss than those in low light (65 µmol photon m-2 s-1) and moderate light treatments (95-135 µmol photon m-2 s-1). Additionally, individuals in high light treatments experienced a rapid decline in kleptoplast photosynthetic activity, while all other treatments experienced minimal decline. This relationship between kleptoplast degradation and weight loss suggests an important link between fitness and kleptoplasty. Given the significant negative effects of ambient conditions, regular refreshment and replenishment of kleptoplasts or physiological or behavioral adjustments are likely employed for the benefits of kleptoplasty to be maintained.