PRODUCT TESTING 2: MODELING VERSUS MAPPING AND THEIR INTEGRATION

Evaluations of multiple products in a category proceed with two different, unstated objectives, and two distinct analytic approaches. The first objective is to "map" the category - viz., to put the products in a category onto some type of geometrical map with the property that products lying close to each other on the map share aspects in common. Researchers use mapping to identify which products compete with each other, as well as to discover whether or not there exist in the category unfilled "holes" that have promise. Researchers use modeling, in contrast, to identify the salient dimensions along which consumers differentiate products in the category. Modeling assumes that the researcher will create a relation between two or more attributes in the category. The analysis generates equations (or even only correlations) rather than maps. Mapping and modeling are complementary, yet often one approach is used to the exclusion of the other because of internal biases and points of view held by the researcher. This paper shows how the two are used, and how they can be integrated to create a more powerful analytic approach.     

Application of relative warp analysis to the evaluation of two-dimensional gels in proteomics: studying isoelectric point and relative molecular mass variation

We propose a geometric-morphometrics method (relative warp analysis) to be used in proteomic comparisons. This approach was applied to a dataset from a comparison between 5 controls and 5 patients with colorectal cancer disease published elsewhere. The spots in the 2-D maps were used as landmarks in a morphometric study, and the differences in shape (spot distribution) among them were obtained. The shape variables were used to compare controls and patients. These components mostly ignore random or experimental effects affecting all the proteins in any of the two dimensions studied. Furthermore, the method allows the researcher to find those proteins which contributed the most to the local shape component detected. Applying this approach, we detected variations in the position (isoelectric point and/or relative molecular mass) of some spots that may reflect differences in the amino acidic sequence or post-translational modifications.     

Modeling valley fever (coccidioidomycosis) incidence on the basis of climate conditions

Valley fever (coccidioidomycosis) is a disease endemic to arid regions within the Western Hemisphere, and is caused by a soil-dwelling fungus, Coccidioides immitis. Incidence data for Pima County, reported to the Arizona Department of Health Services as new cases of valley fever, were used to conduct exploratory analyses and develop monthly multivariate models of relationships between valley fever incidence and climate conditions and variability in Pima County, Arizona, USA. Bivariate and compositing analyses conducted during the exploratory portion of the study revealed that antecedent temperature and precipitation in different seasons are important predictors of incidence. These results were used in the selection of candidate variables for multivariate predictive modeling, which was designed to predict deviation from mean incidence on the basis of past, current, and forecast climate conditions. The models were specified using a backward stepwise procedure, and were most sensitive to key predictor variables in the winter season and variables that were time-lagged 1 year or more prior to the month being predicted. Model accuracy was generally moderate ( r(2) values for the monthly models, tested on independent data, ranged from 0.15 to 0.50), and months with high incidence can be predicted more accurately than months with low incidence.     

Before the storm: antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events

While the influence of antecedent conditions on watershed function is widely recognized under typical hydrologic regimes, gaps remain in the context of extreme climate events (ECEs). ECEs are those events that far exceed seasonal norms of intensity, duration, or impact upon the physical environment or ecosystem. In this synthesis, we discuss the role of source availability and hydrologic connectivity on antecedent conditions and propose a conceptual framework to characterize system response to ECEs at the watershed scale. We present four case studies in detail that span a range of types of antecedent conditions and type of ECE to highlight important controls and feedbacks. Because ECEs have the potential to export large amounts of water and materials, their occurrence in sequence can disproportionately amplify the response. In fact, multiple events may not be considered extreme in isolation, but when they occur in close sequence they may lead to extreme responses in terms of both supply and transport capacity. Therefore, to advance our understanding of these complexities, we need continued development of a mechanistic understanding of how antecedent conditions set the stage for ECE response across multiple regions and climates, particularly since monitoring of these rare events is costly and difficult to obtain. Through focused monitoring of critical ecosystems during rare events we will also be able to extend and validate modeling studies. Cross-regional comparisons are also needed to define characteristics of resilient systems. These monitoring, modeling, and synthesis efforts are more critical than ever in light of changing climate regimes, intensification of human modifications of the landscape, and the disproportionate impact of ECEs in highly populated regions.     

Determinants and interindividual variation of R-R interval dynamics in healthy middle-aged subjects

Determinants and intersubject variations of fractal and complexity measures of R-R interval variability were studied in a random population of 200 healthy middle-aged women (age 51 +/- 6 yr) and 189 men (age 50 +/- 6 yr) during controlled conditions in the supine and sitting positions. The short-term fractal exponent (alpha(1)) was lower in women than men in both the supine (1.18 +/- 0.20 vs. 1.12 +/- 0.17, P < 0.01) and sitting position (P < 0.001). Approximate entropy (ApEn), a measure of complexity, was higher in women in the sitting position (1.16 +/- 0.17 vs. 1.07 +/- 0.19, P < 0.001), but no gender-related differences were observed in ApEn in the supine position. Fractal and complexity measures were not related to any other demographic, laboratory, or lifestyle factors. Intersubject variations in a fractal measure, alpha(1) (e.g., 1.15 +/- 0.20 in the supine position, z value 1.24, not significant), and in a complexity measure, ApEn (e.g., 1.14 +/- 0.18 in the supine position, z value 1.44, not significant), were generally smaller and more normally distributed than the variations in the traditional measures of heart rate variability (e.g., standard deviation of R-R intervals 49 +/- 21 ms in the supine position, z value 2.53, P < 0.001). These results in a large random population sample show that healthy subjects express relatively little interindividual variation in the fractal and complexity measures of heart rate behavior and, unlike the traditional measures of heart rate variability, they are not related to lifestyle, metabolic, or demographic variables. However, subtle gender-related differences are also present in fractal and complexity measures of heart rate behavior.     

Olfactory discrimination among sex pheromone stereoisomers: chirality recognition by pink hibiscus mealybug males

Our previous field studies suggested that the two chiral centers in the sex pheromone of pink hibiscus mealybug, Maconellicoccus hirsutus, could elicit different male responses. The chiral center in the acid moiety of the pheromone seemed to be more critical than the alcohol portion of the pheromone molecule for attractiveness. The objective of the current study was to test this hypothesis by deploying stereoisomeric blends in pheromone traps. Captures of male M. hirsutus showed that pheromone with the naturally occurring (R)-maconelliyl (S)-2-methylbutanoate and (R)-lavandulyl (S)-2-methylbutanoate [R-S configuration] was most attractive and that pheromone with the unnatural S-S configuration was less attractive. In addition, the RS-R blend (containing R-R and S-R stereoisomers) yielded captures of male M. hirsutus that were comparable to blank controls, and an inhibitory effect was observed when R-R and S-R were combined with naturally occurring R-S blend. These results suggest a unique chirality recognition mechanism; olfactory discrimination among different pheromone stereoisomers depends upon both asymmetric centers. The S configuration on the acid moiety elicits attraction, whereas the R configuration induces inhibition. However, the attractive activity shows some degree of tolerance toward chirality change in the alcohol portion of the pheromone molecules.     

基于复杂性度量的心率变异信号非线性分析

假设心率变异信号是累积－发放模型（Ｉｎｔｅｇｒａｔｅ－ｆｉｒｅ）与非线性动力学系统耦合产生的峰电位链（ＳｐｉｋｅＴｒａｉｎ）。以符号动力学为基础,提出利用峰电位间隔（ｉｎｔｅｒｓｐｉｋｅｉｎｔｅｒｖａｌ,ＩＳＩ）及其随机替代数据的Ｃ１、Ｃ２复杂度来定量刻划非线性动力学系统特性。结果表明：确定性驱动产生的峰电位间隔序列可以与随机性驱动产生的峰电位间隔序列区分开。因此,在噪声干扰较强的生理信号中,尤其是在不清楚非线性动力系统变量和峰电位间隔序列之间是否存在微分同胚的情况下,以复杂性度量来代替以Ｔａｋｅｎｓ嵌入定理为基础的关联维数、Ｌｙａｐｎｏｖ指数等描述动力系统特征的方法是合适的。最后通过２类共３７个个体,每个个体的心电数据为１０００个Ｒ－Ｒ间期的微分序列检验心率变异信号的非线性结构。     

Interpreting parameters in the logistic regression model with random effects

Logistic regression with random effects is used to study the relationship between explanatory variables and a binary outcome in cases with nonindependent outcomes. In this paper, we examine in detail the interpretation of both fixed effects and random effects parameters. As heterogeneity measures, the random effects parameters included in the model are not easily interpreted. We discuss different alternative measures of heterogeneity and suggest using a median odds ratio measure that is a function of the original random effects parameters. The measure allows a simple interpretation, in terms of well-known odds ratios, that greatly facilitates communication between the data analyst and the subject-matter researcher. Three examples from different subject areas, mainly taken from our own experience, serve to motivate and illustrate different aspects of parameter interpretation in these models.     

Local ecological footprint using Principal Component Analysis: A case study of localities in Andalusia (Spain)

The quantity and quality of available information is one of the major constraints for the calculation of the ecological footprint, particularly for sub-national or sub-regional territorial levels. At the national or even regional level, the information that allows for computing the ecological footprint is generally available. However, when trying to calculate the footprint for lower-level territorial realities (e.g., cities or municipalities), this information is insufficient or non-existent. In this article, we propose an indirect method for calculating the ecological footprint of such territorial spaces through Principal Component Analysis. The case study utilises the ecological footprint of Andalusia (a Spanish region) as a starting point for footprint assignment to each of the 771 municipalities included in the Andalusian region. A set of variables related to the consumption levels in these municipalities has been utilised and is expressed in physical units. These variables make it possible to obtain a weighting factor to determine the ecological footprint of each municipality. This procedure also makes it possible to identify which variables or indicators have the greatest impact on the ecological footprint for a given territory. According to the results, the method also shows how inappropriate it is to consider the population as a way to distribute the ecological footprint; there are relevant differences between the weight of the population in municipalities and their generated footprint. There are also significant differences between the magnitude of economic indicators, such as GDP, and the estimated ecological footprint; for municipalities with higher income levels, the ecological impact is more than proportional to the weight of the monetary indicators.     

Reliability and Validity of the Transport and Physical Activity Questionnaire (TPAQ) for Assessing Physical Activity Behaviour

Background

No current validated survey instrument allows a comprehensive assessment of both physical activity and travel behaviours for use in interdisciplinary research on walking and cycling. This study reports on the test-retest reliability and validity of physical activity measures in the transport and physical activity questionnaire (TPAQ).

Methods

The TPAQ assesses time spent in different domains of physical activity and using different modes of transport for five journey purposes. Test-retest reliability of eight physical activity summary variables was assessed using intra-class correlation coefficients (ICC) and Kappa scores for continuous and categorical variables respectively. In a separate study, the validity of three survey-reported physical activity summary variables was assessed by computing Spearman correlation coefficients using accelerometer-derived reference measures. The Bland-Altman technique was used to determine the absolute validity of survey-reported time spent in moderate-to-vigorous physical activity (MVPA).

Results

In the reliability study, ICC for time spent in different domains of physical activity ranged from fair to substantial for walking for transport (ICC = 0.59), cycling for transport (ICC = 0.61), walking for recreation (ICC = 0.48), cycling for recreation (ICC = 0.35), moderate leisure-time physical activity (ICC = 0.47), vigorous leisure-time physical activity (ICC = 0.63), and total physical activity (ICC = 0.56). The proportion of participants estimated to meet physical activity guidelines showed acceptable reliability (k = 0.60). In the validity study, comparison of survey-reported and accelerometer-derived time spent in physical activity showed strong agreement for vigorous physical activity (r = 0.72, p<0.001), fair but non-significant agreement for moderate physical activity (r = 0.24, p = 0.09) and fair agreement for MVPA (r = 0.27, p = 0.05). Bland-Altman analysis showed a mean overestimation of MVPA of 87.6 min/week (p = 0.02) (95% limits of agreement −447.1 to +622.3 min/week).

Conclusion

The TPAQ provides a more comprehensive assessment of physical activity and travel behaviours and may be suitable for wider use. Its physical activity summary measures have comparable reliability and validity to those of similar existing questionnaires.     

No fitness cost for wheat's H gene-mediated resistance to Hessian fly (Diptera: Cecidomyiidae)

Resistance (R) genes have a proven record for protecting plants against biotic stress. A problem is parasite adaptation via Avirulence (Avr) mutations, which allows the parasite to colonize the R gene plant. Scientists hope to make R genes more durable by stacking them in a single cultivar. However, stacking assumes that R gene-mediated resistance has no fitness cost for the plant. We tested this assumption for wheat's resistance to Hessian fly, Mayetiola destructor (Say) (Diptera: Cecidomyiidae). Our study included ten plant fitness measures and four wheat genotypes, one susceptible, and three expressing either the H6, H9, or H13 resistance gene. Because R gene-mediated resistance has two components, we measured two types of costs: the cost of the constitutively-expressed H gene, which functions in plant surveillance, and the cost of the downstream induced responses, which were triggered by Hessian fly larvae rather than a chemical elicitor. For the constitutively expressed Hgene, some measures indicated costs, but a greater number of measures indicated benefits of simply expressing the H gene. For the induced resistance, instead of costs, resistant plants showed benefits of being attacked. Resistant plants were more likely to survive attack than susceptible plants, and surviving resistant plants produced higher yield and quality. We discuss why resistance to the Hessian fly has little or no cost and propose that tolerance is important, with compensatory growth occurring after H gene-mediated resistance kills the larva. We end with a caution: Given that plants were given good growing conditions, fitness costs may be found under conditions of greater biotic or abiotic stress.     

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

Modeling of signal transduction pathways plays a major role in understanding cells'' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.     

The maximum likelihood identification method applied to insect morphometric data

To distinguish species or populations using morphometric data is generally processed through multivariate analyses,in particular the discriminant analysis.We explored another approach based on the maximum likelihood method.Simple statistics based on the assumption of normal distribution at a single variable allows to compute the chance of observing a particular data (or sample) in a given reference group.When data are described by more than one variable,the maximum likelihood (MLi) approach allows to combine these chances to fmd the best fit for the data.Such approach assumes independence between variables.The assumptions of normal distribution of variables and independence between them are frequently not met in morphometrics,but improvements may be obtained after some mathematical transformations.Provided there is strict anatomical correspondence of variables between unknown and reference data,the MLi classification produces consistent classification.We explored this approach using various input data,and compared validated classification scores with the ones obtained after the Mahalanobis distance-based classification.The simplicity of the method,its fast computation,performance and versatility,make it an interesting complement to other classification techniques.     

Hematology and blood biochemistry in infant baboons (Papio hamadryas)

Although published normative reference standards for hematologic and clinical chemistry measures are available for adult baboons, their applicability to infants has not been addressed. We analyzed these measures in 110 infant baboons (55 females and 55 males) from a large breeding colony at the Southwest Regional Primate Research Center in San Antonio, Texas. The sample consists of olive baboons and olive/yellow baboon hybrids, 1 week to 12 months of age. We produced cross-sectional reference values and examined the effects of age, sex, and subspecies on these variables. Hematology reference ranges for infant baboons are similar to, but wider than, those for adults. Reference ranges for blood biochemistry measures are generally more dissimilar to adults, indicating that for many variables, reference ranges for adult baboons are not adequate for infants. Although sex and subspecies differences are rare, age accounts for more than 10% of the variance in many of the variables.     

Direct effect of Pa(CO2) on respiratory sinus arrhythmia in conscious humans

Respiratory sinus arrhythmia (RSA) may improve the efficiency of pulmonary gas exchange by matching the pulmonary blood flow to lung volume during each respiratory cycle. If so, an increased demand for pulmonary gas exchange may enhance RSA magnitude. We therefore tested the hypothesis that CO2 directly affects RSA in conscious humans even when changes in tidal volume (V(T)) and breathing frequency (F(B)), which indirectly affect RSA, are prevented. In seven healthy subjects, we adjusted end-tidal PCO2 (PET(CO2)) to 30, 40, or 50 mmHg in random order at constant V(T) and F(B). The mean amplitude of the high-frequency component of R-R interval variation was used as a quantitative assessment of RSA magnitude. RSA magnitude increased progressively with PET(CO2) (P < 0.001). Mean R-R interval did not differ at PET(CO2) of 40 and 50 mmHg but was less at 30 mmHg (P < 0.05). Because V(T) and F(B) were constant, these results support our hypothesis that increased CO2 directly increases RSA magnitude, probably via a direct effect on medullary mechanisms generating RSA.     

QTc Interval (Cardiac Repolarization): Lengthening After Meals

NAGY, DAVID, RONALD DeMEERSMAN, DYMPNA GALLAGHER, ANGELO PIETROBELLI, ADRIENNE S ZION, DEBORAH DALY, STEVEN B HEYMSFIELD. QTc interval (cardiac repolarization): lengthening after meals. Weight reduction, either by dietary or surgical means, is associated with prolongation of the heart rate corrected QT interval (QTc=QT/R-R^0–5 and, on occasion, sudden death. Screening subjects with obesity before weight loss for prolonged QTc intervals is an accepted practice, although at present, there are no guidelines for whether subjects should be fasting before electrocardiogram (EKG) evaluation. The aim of this study was to test the hypothesis that EKG QTc interval duration is independent of meal ingestion. The hypothesis was tested in 11 healthy subjects who ingested a 500-kcal formula meal. A small decrease in absolute QT interval and a steady decline in R-R interval were observed for up to 60 minutes after formula ingestion. The QTc interval increased above baseline at 15 minutes (p<0. 007) after meal, a change that persisted for the 1-hour postmeal observation period. Spectral analysis of EKG R-R intervals (low-/high-frequency amplitude ratio) indicated a change in cardiac autonomic flow after meal ingestion. The QTc interval did not lengthen and R-R low-/highfrequency amplitude ratio remained unchanged in eight subjects evaluated in a similar manner but in whom isovolumic amounts of water replaced the meal. These observations suggest that (1) cardiac repolarization changes with fasting and feeding, (2) the QTc interval is influenced by meal intake, and (3) the autonomic nervous system may play a role in meal-related QTc changes. These findings have implications for the evaluation of patients with obesity before starting and during weight loss treatment.     

A genetic-algorithm-based approach to optimization of bioprocesses described by fuzzy rules

A new approach to optimization of bioprocesses described by fuzzy rules is introduced in the paper. It is based on genetic algorithms (GA) and allows to determine optimal values or profiles of control variables and to optimize fuzzy rules (parameters of membership functions). The process can be described by linguistic variables and fuzzy rules. An algorithm and related software was developed. The approach was applied to an industrial antibiotic fermentation. The optimal profile of a physical variable of the preculture was determined which leads to an increasing output product concentration in the main culture of about 5%.     

Song and immunological condition in male barn swallows (Hirundo rustica)

Male secondary sexual characters may have evolved as intra-or intersexual signals of male phenotypic or genetic quality.In birds, singing performance may have the function to honestlyreveal health and vigor of individual males. Infectious diseasesand poor body conditions would therefore be expected to negativelyinfluence singing performance. Since bird pathogens are knownto elicit both a humoral and a cell-mediated immune response,it can be predicted that a negative relationship exists betweensinging performance and activity of the immune system. Thisprediction was tested for the first time in this correlationalstudy. The relationships between song rate and features andhematological variables (concentration of leukocytes in peripheralblood, ratio of gamma-globulins to total plasma proteins, bloodcell sedimentation rate, hematocrit) and body condition wereanalyzed in a population of bam swallows (Hirundo rustica).Song rate was negatively correlated with lymphocyte concentrationand with the ratio of gamma-globulins to plasma proteins. Spectrographicanalysis showed that features of song were not significantlycorrelated with hematological variables or body condition. Thelevel of circulating testosterone was not correlated with songrate nor hematological variables. This study is the first toshow a correlation between a bird's singing performance andhematological profile and suggests that song rate of male barnswallows may reflect their health status. Song in this speciesmight thus have evolved because it allows prospecting femalesto assess aspects of phenotypic and/or genetic quality of potentialmates     

Changes in R-R and Q-T intervals following cardiac vagotomy in neonatal swine

Asymmetric innervation of the myocardium, especially a predominance of sympathetic innervation, may establish conditions whereby electrical instability could result. Using a swine animal model, we studied the effect of right cardiac vagal denervation on the variability of R-R and Q-T intervals. Newborn pigs were assigned randomly to two groups: sham-operated controls (C), or denervation of the right cardiac vagus nerve (RCVX). EKGs were recorded weekly until the two groups exhibited significant heart rate differences. Analysis of the EKG included measurements of R-R and Q-T intervals and corrected Q-T intervals (QTc). Poincaré plots were used to display age-related differences in R-R and Q-T intervals. For RCVX animals, decreased QTc and R-R intervals were noted at 6 and 7 weeks after denervation, respectively. Unexpectedly, one RCVX animal exhibited marked sudden pauses in sinus rhythm. These data indicated that reduced vagal cardiac modulation during development might alter cardiac electrical stability in conscious swine.