6 resultados para Physiological variables

em Duke University


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-Transgenic mouse models have been developed to manipulate beta-adrenergic receptor (betaAR) signal transduction. Although several of these models have altered betaAR subtypes, the specific functional sequelae of betaAR stimulation in murine heart, particularly those of beta2-adrenergic receptor (beta2AR) stimulation, have not been characterized. In the present study, we investigated effects of beta2AR stimulation on contraction, [Ca2+]i transient, and L-type Ca2+ currents (ICa) in single ventricular myocytes isolated from transgenic mice overexpressing human beta2AR (TG4 mice) and wild-type (WT) littermates. Baseline contractility of TG4 heart cells was increased by 3-fold relative to WT controls as a result of the presence of spontaneous beta2AR activation. In contrast, beta2AR stimulation by zinterol or isoproterenol plus a selective beta1-adrenergic receptor (beta1AR) antagonist CGP 20712A failed to enhance the contractility in TG4 myocytes, and more surprisingly, beta2AR stimulation was also ineffective in increasing contractility in WT myocytes. Pertussis toxin (PTX) treatment fully rescued the ICa, [Ca2+]i, and contractile responses to beta2AR agonists in both WT and TG4 cells. The PTX-rescued murine cardiac beta2AR response is mediated by cAMP-dependent mechanisms, because it was totally blocked by the inhibitory cAMP analog Rp-cAMPS. These results suggest that PTX-sensitive G proteins are responsible for the unresponsiveness of mouse heart to agonist-induced beta2AR stimulation. This was further corroborated by an increased incorporation of the photoreactive GTP analog [gamma-32P]GTP azidoanilide into alpha subunits of Gi2 and Gi3 after beta2AR stimulation by zinterol or isoproterenol plus the beta1AR blocker CGP 20712A. This effect to activate Gi proteins was abolished by a selective beta2AR blocker ICI 118,551 or by PTX treatment. Thus, we conclude that (1) beta2ARs in murine cardiac myocytes couple to concurrent Gs and Gi signaling, resulting in null inotropic response, unless the Gi signaling is inhibited; (2) as a special case, the lack of cardiac contractile response to beta2AR agonists in TG4 mice is not due to a saturation of cell contractility or of the cAMP signaling cascade but rather to an activation of beta2AR-coupled Gi proteins; and (3) spontaneous beta2AR activation may differ from agonist-stimulated beta2AR signaling.

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Imagery and concreteness norms and percentage noun usage were obtained on the 1,080 verbal items from the Toronto Word Pool. Imagery was defined as the rated ease with which a word aroused a mental image, and concreteness was defined in relation to level of abstraction. The degree to which a word was functionally a noun was estimated in a sentence generation task. The mean and standard deviation of the imagery and concreteness ratings for each item are reported together with letter and printed frequency counts for the words and indications of sex differences in the ratings. Additional data in the norms include a grammatical function code derived from dictionary definitions, a percent noun judgment, indexes of statistical approximation to English, and an orthographic neighbor ratio. Validity estimates for the imagery and concreteness ratings are derived from comparisons with scale values drawn from the Paivio, Yuille, and Madigan (1968) noun pool and the Toglia and Battig (1978) norms. © 1982 Psychonomic Society, Inc.

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Body size and development time are important life history traits because they are often highly correlated with fitness. Although the developmental mechanisms that control growth have been well studied, the mechanisms that control how a species-characteristic body size is achieved remain poorly understood. In insects adult body size is determined by the number of larval molts, the size increment at each molt, and the mechanism that determines during which instar larval growth will stop. Adult insects do not grow, so the size at which a larva stops growing determines adult body size. Here we develop a quantitative understanding of the kinetics of growth throughout larval life of Manduca sexta, under different conditions of nutrition and temperature, and for genetic strains with different adult body sizes. We show that the generally accepted view that the size increment at each molt is constant (Dyar's Rule) is systematically violated: there is actually a progressive increase in the size increment from instar to instar that is independent of temperature. In addition, the mass-specific growth rate declines throughout the growth phase in a temperature-dependent manner. We show that growth within an instar follows a truncated Gompertz trajectory. The critical weight, which determines when in an instar a molt will occur, and the threshold size, which determines which instar is the last, are different in genetic strains with different adult body sizes. Under nutrient and temperature stress Manduca has a variable number of larval instars and we show that this is due to the fact that more molts at smaller increments are taken before threshold size is reached. We test whether the new insight into the kinetics of growth and size determination are sufficient to explain body size and development time through a mathematical model that incorporates our quantitative findings.

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OBJECTIVES: Two factors have been considered important contributors to tooth wear: dietary abrasives in plant foods themselves and mineral particles adhering to ingested food. Each factor limits the functional life of teeth. Cross-population studies of wear rates in a single species living in different habitats may point to the relative contributions of each factor. MATERIALS AND METHODS: We examine macroscopic dental wear in populations of Alouatta palliata (Gray, 1849) from Costa Rica (115 specimens), Panama (19), and Nicaragua (56). The sites differ in mean annual precipitation, with the Panamanian sites receiving more than twice the precipitation of those in Costa Rica or Nicaragua (∼3,500 mm vs. ∼1,500 mm). Additionally, many of the Nicaraguan specimens were collected downwind of active plinian volcanoes. Molar wear is expressed as the ratio of exposed dentin area to tooth area; premolar wear was scored using a ranking system. RESULTS: Despite substantial variation in environmental variables and the added presence of ash in some environments, molar wear rates do not differ significantly among the populations. Premolar wear, however, is greater in individuals collected downwind from active volcanoes compared with those living in environments that did not experience ash-fall. DISCUSSION: Volcanic ash seems to be an important contributor to anterior tooth wear but less so in molar wear. That wear is not found uniformly across the tooth row may be related to malformation in the premolars due to fluorosis. A surge of fluoride accompanying the volcanic ash may differentially affect the premolars as the molars fully mineralize early in the life of Alouatta.

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MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.