Reduced mechanical efficiency in left-ventricular trabeculae of the spontaneously hypertensive rat.

Long-term systemic arterial hypertension, and its associated compensatory response of left-ventricular hypertrophy, is fatal. This disease leads to cardiac failure and culminates in death. The spontaneously hypertensive rat (SHR) is an excellent animal model for studying this pathology, suffering from ventricular failure beginning at about 18 months of age. In this study, we isolated left-ventricular trabeculae from SHR-F hearts and contrasted their mechanoenergetic performance with those from nonfailing SHR (SHR-NF) and normotensive Wistar rats. Our results show that, whereas the performance of the SHR-F differed little from that of the SHR-NF, both SHR groups performed less stress-length work than that of Wistar trabeculae. Their lower work output arose from reduced ability to produce sufficient force and shortening. Neither their heat production nor their enthalpy output (the sum of work and heat), particularly the energy cost of Ca(2+) cycling, differed from that of the Wistar controls. Consequently, mechanical efficiency (the ratio of work to change of enthalpy) of both SHR groups was lower than that of the Wistar trabeculae. Our data suggest that in hypertension-induced left-ventricular hypertrophy, the mechanical performance of the tissue is compromised such that myocardial efficiency is reduced

Single-Component Electroactive Polymer Architectures for Non-Enzymatic Glucose Sensing.

Organic mixed ionic-electronic conductors (OMIECs) have emerged as promising materials for biological sensing, owing to their electrochemical activity, stability in an aqueous environment, and biocompatibility. Yet, OMIEC-based sensors rely predominantly on the use of composite matrices to enable stimuli-responsive functionality, which can exhibit issues with intercomponent interfacing. In this study, an approach is presented for non-enzymatic glucose detection by harnessing a newly synthesized functionalized monomer, EDOT-PBA. This monomer integrates electrically conducting and receptor moieties within a single organic component, obviating the need for complex composite preparation. By engineering the conditions for electrodeposition, two distinct polymer film architectures are developed: pristine PEDOT-PBA and molecularly imprinted PEDOT-PBA. Both architectures demonstrated proficient glucose binding and signal transduction capabilities. Notably, the molecularly imprinted polymer (MIP) architecture demonstrated faster stabilization upon glucose uptake while it also enabled a lower limit of detection, lower standard deviation, and a broader linear range in the sensor output signal compared to its non-imprinted counterpart. This material design not only provides a robust and efficient platform for glucose detection but also offers a blueprint for developing selective sensors for a diverse array of target molecules, by tuning the receptor units correspondingly

How predation and landscape fragmentation affect vole population dynamics

Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics

Geometry of Goodness-of-Fit Testing in High Dimensional Low Sample Size Modelling

We introduce a new approach to goodness-of-fit testing in the high dimensional, sparse extended multinomial context. The paper takes a computational information geometric approach, extending classical higher order asymptotic theory. We show why the Wald – equivalently, the Pearson X2 and score statistics – are unworkable in this context, but that the deviance has a simple, accurate and tractable sampling distribution even for moderate sample sizes. Issues of uniformity of asymptotic approximations across model space are discussed. A variety of important applications and extensions are noted

Scaling of Entanglement close to a Quantum Phase Transitions

In this Letter we discuss the entanglement near a quantum phase transition by analyzing the properties of the concurrence for a class of exactly solvable models in one dimension. We find that entanglement can be classified in the framework of scaling theory. Further, we reveal a profound difference between classical correlations and the non-local quantum correlation, entanglement: the correlation length diverges at the phase transition, whereas entanglement in general remains short ranged.Comment: 4 pages, 4 figures, revtex. Stylistic changes and format modifie

How do general practitioners experience providing care to refugees with mental health problems? A qualitative study from Denmark

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