Phosphorylation of K+ channels in the squid giant axon. A mechanistic analysis

Protein phosphorylation is an important mechanism in the modulation of voltage-dependent ionic channels. In squid giant axons, the potassium delayed rectifier channel is modulated by an ATP-mediated phosphorylation mechanism, producing important changes in amplitude and kinetics of the outward current. The characteristics and biophysical basis for the phosphorylation effects have been extensively studied in this preparation using macroscopic, single-channel and gating current experiments. Phosphorylation produces a shift in the voltage dependence of all voltage-dependent parameters including open probability, slow inactivation, first latency, and gating charge transferred. The locus of the effect seems to be located in a fast 20 pS channel, with characteristics of delayed rectifier, but at least another channel is phosphorylated under our experimental conditions. These results are interpreted quantitatively with a mechanistic model that explains all the data. In this model the shift in voltage dependence is produced by electrostatic interactions between the transferred phosphate and the voltage sensor of the channel.     

How do antiporters exchange substrates across the cell membrane? An atomic-level description of the complete exchange cycle in NarK

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Allometric constraints on Sr/Ca and Ba/Ca partitioning in terrestrial mammalian trophic chains

In biological systems, strontium (Sr) and barium (Ba) are two non-essential elements, in comparison to calcium (Ca) which is essential. The Sr/Ca and Ba/Ca ratios tend to decrease in biochemical pathways which include Ca as an essential element, and these processes are termed biopurification of Ca. The quantitative pathway of the biopurification of Ca in relation to Sr and Ba between two biological reservoirs (R _n and R_{n -1}) is measured with an observed ratio (OR) expressed by the (Sr/Ca) _Rn /(Sr/Ca) _Rn-1 and (Ba/Ca) _Rn /(Ba/Ca) _Rn-1 ratios. For a mammalian organism, during the whole biopurification of Ca starting with the diet to the ultimate reservoir of Ca which is the bone, the mean values for OR_Sr and OR_Ba are 0.25 and 0.2, respectively. In this study, published Sr/Ca and Ba/Ca ratios are used for three sets of soils, plants, and bones of herbivorous and carnivorous mammals, each comprising a trophic chain, to illustrate the biopurification of Ca at the level of trophic chains. Calculated OR_Sr and OR_Ba of herbivore bones in relation to plants and of bones of carnivores in relation to bones of herbivores give OR_Sr=0.30±0.08 and OR_Ba=0.16±0.08, thus suggesting that trophic chains reflect the Sr/Ca and Ba/Ca fluxes that are prevalent at the level of a mammalian organism. The slopes of the three regression equations of log(Sr/Ca) vs. log(Ba/Ca) are similar, indicating that the process of biopurification of Ca with respect to Sr and Ba is due to biological processes and is independent of the geological settings. Modifications of the logarithmic expression of the Sr/Ca and Ba/Ca relationship allow a new formula of the biopurification process to be deduced, leading to the general equation OR_Ba=OR_Sr^1.79±0.33,where the allometric coefficient is the mean of the slopes of the three regression equations. Some recent examples are used to illustrate this new analysis of predator-prey relations between mammals. This opens up new possibilities for the utilization of Ba/Ca and Sr/Ca in addition to stable isotope ratios (¹³C and ¹⁵N) for the determination of the relative contribution of different food sources to an animals diet.     

Phylogenetic Analyses Under Secondary Structure-Specific Substitution Models Outperform Traditional Approaches: Case Studies with Diploblast LSU

Many rDNA molecular phylogenetic studies result in trees that are incongruent to either alternative gene tree reconstructions and/or morphological assumptions. One reason for this outcome might be the application of suboptimal phylogenetic substitution models. While the most commonly implemented models describe the evolution of independently evolving characters fairly well, they do not account for character dependencies such as rRNA strands that form a helix in the ribosome. Such nonindependent sites require the use of models that take into account the coevolution of the complete nucleotide pair (doublet). We analyzed 28S rDNA (LSU) demosponge phylogenies using a “doublet” model for pairing sites (rRNA-helices) and compared our findings with the results of “standard” approaches using Bayes factors. We demonstrate that paired and unpaired sites of the same gene result in different reconstructions and that usage of a doublet model leads to more reliable demosponge trees. We show the influence of more sophisticated models on phylogenetic reconstructions of early-branching metazoans and the phylogenetic relationships of demosponge orders. [Reviewing Editor: Dr. Rasmus Nielsen]     

A New Computational Efficient Approach for Trabecular Bone Analysis using Beam Models Generated with Skeletonized Graph Technique

Micro-finite element (FE) analysis is a well established technique for the evaluation of the elastic properties of trabecular bone, but is limited in its application due to the large number of elements that it requires to represent the complex internal structure of the bone. In this paper, we present an alternative FE approach that makes use of a recently developed 3D-Line Skeleton Graph Analysis (LSGA) technique to represent the complex internal structure of trabecular bone as a network of simple straight beam elements in which the beams are assigned geometrical properties of the trabeculae that they represent. Since an enormous reduction of cputime can be obtained with this beam modeling approach, ranging from approximately 1,200 to 3,600 for the problems investigated here, we think that the FE modeling technique that we introduced could potentially constitute an interesting alternative for the evaluation of the elastic mechanical properties of trabecular bone.     

Sensitivity of marine fish thermal habitat models to fishery data sources

Statistical models built using different data sources and methods can exhibit conflicting patterns. We used the northern stock of black sea bass (Centropristis striata) as a case study to assess the impacts of using different fisheries data sources and laboratory‐derived physiological metrics in the development of thermal habitat models for marine fishes. We constructed thermal habitat models using generalized additive models (GAMs) based on various fisheries datasets as input, including the NOAA Northeast Fisheries Science Center (NEFSC) bottom trawl surveys, various inshore fisheries‐independent trawl surveys (state waters), NEFSC fisheries‐dependent observer data, and laboratory‐based physiological metrics. We compared each model''s GAM response curve and coupled them to historical ocean conditions in the U.S. Northeast Shelf using bias‐corrected ocean temperature output from a regional ocean model. Thermal habitat models based on shelf‐wide data (NEFSC fisheries‐dependent observer data and fisheries‐independent spring and fall surveys) explained the most variation in black sea bass presence/absence data at ~15% deviance explained. Models based on a narrower range of sampled thermal habitat from inshore survey data in the Northeast Area Monitoring and Assessment Program (NEAMAP) and the geographically isolated Long Island Sound data performed poorly. All models had similar lower thermal limits around 8.5℃, but thermal optima, when present, ranged from 16.7 to 24.8℃. The GAMs could reliably predict habitat from years excluded from model training, but due to strong seasonal temperature fluctuations in the region, could not be used to predict habitat in seasons excluded from training. We conclude that survey data source can greatly impact development and interpretation of thermal habitat models for marine fishes. We suggest that model development be based on data sources that sample the widest range of ocean temperature and physical habitat throughout multiple seasons when possible, and encourage thorough consideration of how data gaps may influence model uncertainty.     

Cluster detection based on spatial associations and iterated residuals in generalized linear mixed models

Summary .  Spatial clustering is commonly modeled by a Bayesian method under the framework of generalized linear mixed effect models (GLMMs). Spatial clusters are commonly detected by a frequentist method through hypothesis testing. In this article, we provide a frequentist method for assessing spatial properties of GLMMs. We propose a strategy that detects spatial clusters through parameter estimates of spatial associations, and assesses spatial aspects of model improvement through iterated residuals. Simulations and a case study show that the proposed method is able to consistently and efficiently detect the locations and magnitudes of spatial clusters.     

A General Model for the Dynamics of the Cell Volume

The conservation of the cell volume within values compatible with the overall cell functions represents an ubiquitous property, shared by cells comprising the whole biological world. Water transport across membranes constitutes the main process associated to the dynamics of the cell volume, its chronic and acute regulations therefore represent crucial aspects of cell homeostasis. In spite of the biological diversity, the dynamics of the cell volume exhibits common basic features in the diverse types of cells. The purpose of this study is to show that there is a general model capable to describe the basic aspects of the dynamics of the cell volume. It is demonstrated here that the steady states of this model represent asymptotically stable configurations. As illustrations, several cases of non-polarized (i.e., symmetrical) and polarized (e.g., epithelial) cells performing water transport are shown here to represent particular cases of the general model. From a biological perspective, the existence of a general model for the dynamics of the cell volume reveals that, in spite of physiological and morphological peculiarities, there is a basic common design of the membrane transport processes. In view of its stability properties, this basic design may represent an ancestral property that has proven to be successful regarding the overall homeostatic properties of cells.     

Assessing the anthropogenic impact on Lake Shira from antibiotic resistance of heterotrophic bacteria by neural networks methods

A general approach to assessing the anthropogenic impact on lake ecosystems is proposed and exemplified for the case of Lake Shira (Republic of Khakasia, Russia). The impact strength is estimated by applying neural network-based methods to samples of data on interdependent marking features of autochthonous and allochthonous bacteria isolated from the lake in 1997–2001. The proposed combination of analysis methods makes it possible to determine the state of an ecosystem from both small-and large-size samples of data having complex interrelations.