The action of isoprenaline on the electrophysiological properties of hypertrophied left ventricular myocytes.

The electrophysiological effects of the beta-agonist, isoprenaline, on hypertrophied left ventricular myocardium were measured to understand better the arrhythmic effects of beta-stimulation on the hypertrophied heart. Left ventricular hypertrophy was induced in guinea-pigs by constriction of the thoracic aorta. An age-matched sham-operated group served as controls. Isolated myocytes were held under voltage- and current clamp and the effect of isoprenaline on the L-type Ca2+ current, I(Ca), a Cl- current, I(Cl), and action potential morphology were measured. Cardiac growth was mirrored by cellular hypertrophy. I(Ca) and I(Cl) current density were reduced as myocyte hypertrophy progressed. The augmentation of I(Ca) and I(Cl) by isoprenaline was also reduced in hypertrophy, but no other characteristics of the two currents, or the dose-dependency of the action of isoprenaline were a function of cardiac growth. Isoprenaline prolonged the action potential, but to a smaller extent in hypertrophied myocytes. This difference in action potential prolongation was abolished by glibenclamide. The changes to I(Ca) and I(Cl) in hypertrophy would not tend to increase triggered activity in this situation. Under maximum inotropic stimulation hypertrophied myocytes show action potential changes which are consistent with intracellular ATP depletion, and which could enhance the likelihood of re-entrant circuits. A simple diffusion model for oxygen is constructed to demonstrate the possibility of cellular hypoxia in hypertrophied myocytes.     

Origin of tetracycline efflux proteins: conclusions from nucleotide sequence analysis

The sequences of six tetracycline efflux proteins and three transport proteins which have some resemblance to them were compared. The tetracycline efflux proteins fall into three families: (i) those encoded by pBR322, RP1, and Tn10 (Escherichia coli); (ii) pT181 (Staphylococcus aureus) and pTHT15 (Bacillus subtilis); and (iii) tet347 (Streptomyces rimosus). There is global sequence homology within each of the first two families, but there is none between the families. The pT181/pTHT15 family shares close homology with the N-terminal half of the methylenomycin A efflux protein (Streptomyces coelicor), while tet347 resembles the C-terminal half. Portions of the N-terminal half of the Tn10-encoded protein show significant resemblance to portions in the N-terminal half of the pT181/pTHT15 family, but this sometimes occurs among transport proteins which do not have a common substrate. Tetracycline efflux proteins, therefore, appear to have arisen on at least two, or possibly three, separate occasions, probably from other transport proteins.     

Modulation of the uptake and retention of estradiol-17beta in the ovine corpus luteum by luteinizing hormone.

The uptake and retention of 3H-estradiol by the ovine corpus luteum (induced by superovulation) was maximal through days 8-12 of the cycle with little or no uptake and retention during luteinization or regression. LH, but not FSH or prolactin, inhibited the uptake and retention of estradiol via stimulation of progesterone synthesis.     

PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks

Preferential attachment is a stochastic process that has been proposed to explain certain topological features characteristic of complex networks from diverse domains. The systematic investigation of preferential attachment is an important area of research in network science, not only for the theoretical matter of verifying whether this hypothesized process is operative in real-world networks, but also for the practical insights that follow from knowledge of its functional form. Here we describe a maximum likelihood based estimation method for the measurement of preferential attachment in temporal complex networks. We call the method PAFit, and implement it in an R package of the same name. PAFit constitutes an advance over previous methods primarily because we based it on a nonparametric statistical framework that enables attachment kernel estimation free of any assumptions about its functional form. We show this results in PAFit outperforming the popular methods of Jeong and Newman in Monte Carlo simulations. What is more, we found that the application of PAFit to a publically available Flickr social network dataset yielded clear evidence for a deviation of the attachment kernel from the popularly assumed log-linear form. Independent of our main work, we provide a correction to a consequential error in Newman’s original method which had evidently gone unnoticed since its publication over a decade ago.     

Familial Clustering of Abdominal Visceral Fat and Total Fat Mass: The Québec Family Study

The evidence for common familial factors underlying total fat mass (estimated from underwater weighing) and abdominal visceral fat (assessed from CT scan) was examined in families participating in phase 2 of the Québec Family Study (QFS) using a bivariate familial correlation model. Previous QFS investigations suggest that both genetic (major and polygenic) and familial environmental factors influence each phenotype, accounting for between 55% to 71% of the phenotypic variance in fat mass, and between 55% to 72% for abdominal visceral fat The current study suggests that the bivariate familial effect ranges from 29% to 50%. This pattern suggests that there may be common familial determinants for abdominal visceral fat and total fat mass, as well as additional familial factors which are specific to each. The relatively high spouse cross-trait correlations usually suggest that a large percent of the bivariate familial effect may be environmental in origin. However, if mating is not random, then the spouse resemblance may reflect either genetic or environmental causes, depending on the source [i.e., through similar genes or cohabitation (environmental) effects]. Finally, there are significant sex differences in the magnitude of the familial cross-trait correlations involving parents, but not offspring, suggesting complex generation (i.e., age) and sex effects. For example, genes may turn on or off as a function of age and sex, and/or there may be an accumulation over time of effects due to the environment which may vary by sex. Whether the common familial factors are genetic (major and/or polygenic), environmental, or some combination of both, and whether the familial expression depends on sex and/or age warrants further investigation using more complex models.