Metal–Air Batteries with High Energy Density: Li–Air versus Zn–Air

In the past decade, there have been exciting developments in the field of lithium ion batteries as energy storage devices, resulting in the application of lithium ion batteries in areas ranging from small portable electric devices to large power systems such as hybrid electric vehicles. However, the maximum energy density of current lithium ion batteries having topatactic chemistry is not sufficient to meet the demands of new markets in such areas as electric vehicles. Therefore, new electrochemical systems with higher energy densities are being sought, and metal‐air batteries with conversion chemistry are considered a promising candidate. More recently, promising electrochemical performance has driven much research interest in Li‐air and Zn‐air batteries. This review provides an overview of the fundamentals and recent progress in the area of Li‐air and Zn‐air batteries, with the aim of providing a better understanding of the new electrochemical systems.     

Disruptive physiology: olfaction and the microbiome–gut–brain axis

This review covers the field of olfaction and chemosensation of odorants and puts this information into the context of interactions between microbes and behaviour; the microbiome–gut–brain axis (MGBA). Recent emphasis has also been placed on the concept of the holobiome which states that no single aspect of an organism should be viewed separately and thus must include examination of their associated microbial populations and their influence. While it is known that the microbiome may be involved in the modulation of animal behaviour, there has been little systematized effort to incorporate into such studies the rapidly developing knowledge of the wide range of olfactory systems. The classical olfactory system is evolutionarily conserved in multiple taxa from insects through to fish, reptiles and mammals, and is represented by the largest gene families in vertebrates. Mice have over 1000 different olfactory receptors and humans about 400. They are distributed throughout the body and are even found in spermatozoa where they function in chemotaxis. Each olfactory receptor has the unique functional capability of high‐affinity binding to several different molecular ligands. These and other properties render the cataloguing of odorants (odorome) with specific actions a difficult task. Some ectopic olfactory receptors have been shown to have functional effects in the gut and kidney, highlighting the complexity of the systems engaged by odorants. However, there are, in addition to classical olfactory receptors, at least two other families of receptors involved in olfaction that are also widely found expressed on tissues in many different organs in addition to the nervous system and brain: the trace‐amine associated and formyl peptide receptors. Bacteria can make many if not most odorants and are responsible for recognition of species and relative relatedness, as well as predator presence, among many other examples. Activation of different combinations of olfactory receptors by bacterial products such as β‐phenylethylamine have been shown even to control expression of emotions such as fear and aggression. The number of examples of bacterial products and volatile odorants influencing brain function and behaviour is expanding rapidly. Since it is recognized that many different bacterial products and metabolites also function as social cues, and may themselves be directly or indirectly causative of behavioural change, it becomes ever more important to include olfaction into studies of the MGBA. Clearly there are broader implications for the involvement of olfaction in this rapidly evolving field. These include improvement in our understanding of the pathways engaged in various behaviours, and the identification of novel approaches and new targets in efforts to modulate behavioural changes.     

Prey capture in lizards: differences in jaw–neck–forelimb coordination

Fish body muscles are arranged along the vertebral column in three‐dimensional W‐shaped blocks, called myomeres. Each myomere is separated from its neighbours by a collagenous sheet, the myoseptum, and embedded in these myosepta and in positions that are conserved throughout gnathostome evolution are distinct tendons. Within teleosts these tendons often ossify. Ossification is usually intramembranous but cartilaginous structures within the tendons have also been reported. Ossified myoseptal tendons are homologous to intermuscular bones and appear only in teleosts. The phylogenetic signal of myoseptal tendon ossfication has not been tested previously, although the presence and morphology of intermuscular bones have been used to infer phylogenetic relationships. We sample over a broad phylogenetic range of teleost fishes to test for (1) the effects of phylogenetic history on the presence of intermuscular bones and (2) morphological correlations with the presence of intermuscular bones. Body shape and fin position as well as vertebral number and aspect ratio are characters that are likely to affect the distribution of stresses along myoseptal tendons, and are therefore good functional predictors of myoseptal tendon ossification. We use the summary information by Patterson & Johnson for a list of species with intermuscular bones and reanalyse the homology of intermuscular bones to myoseptal tendons. We find that there is a phylogenetic signal in the distribution of four out of six ossified tendons, but that after correcting for phylogenetic relationships there are still morphological predictors for the presence of all ossified tendons. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 106 , 607–622.     

CRS–MIS in Candida glabrata: sphingolipids modulate echinocandin–Fks interaction

Infections with the azole‐refractory yeast Candida glabrata are now commonly treated with the echinocandins caspofungin (CSF) or micafungin (MCF). True resistance (> 32‐fold decreased susceptibility) to these lipopeptide inhibitors of cell wall synthesis is rare and strictly associated with mutations in integral membrane proteins Fks1 or Fks2. In contrast, mutants exhibiting 4‐ to 32‐fold CSF reduced susceptibility (CRS) were readily selected in vitro, and surprisingly demonstrated 4‐ to 32‐fold MCF increased susceptibility (MIS). Sequencing and gene deletion demonstrated that CRS–MIS is Fks‐independent. To explore alternative mechanisms, we initially employed Saccharomyces cerevisiae, and observed that CRS was conferred by multiple mutations (fen1Δ, sur4Δ, cka2Δ and tsc10‐ts) disrupting sphingolipid biosynthesis. Following this lead, C. glabrata fen1Δ and cka2Δ deletants were constructed, and shown to exhibit CRS–MIS. Sphingolipid analysis of CRS–MIS laboratory mutants and clinical isolates demonstrated elevated dihydrosphingosine (DHS) and phytosphingosine (PHS) levels, and consistent with this sequencing revealed fen1, sur4, ifa38 and sur2 mutations. Moreover, exogenous DHS or PHS conferred a CRS–MIS phenotype on wild‐type C. glabrata. Exogenous PHS failed, however, to suppress CRS–MIS in a sur2 mutant blocked in conversion of DHS to PHS, implying that accumulation of these intermediates confers CRS–MIS. We conclude that membrane sphingolipids modulate echinocandin–Fks interaction.     

Species–area and species–sampling effort relationships: disentangling the effects

Species numbers tend to increase with both the area surveyed (species–area relationship, SAR) and the number of samples taken (species–sampling effort relationship, SSER). These two relationships differ in their nature and underlying mechanisms but are not clearly distinguished in field studies. To discriminate the effects of area (spatial extent) and sampling effort (SE) on species richness, several models explicitly involving both variables were proposed and tested against 13 datasets from marine micro‐, meio‐ and macrobenthos. A combination of power SSER and piecewise power SAR terms was found to have the best fit. The effects of area and SE were both significant, but the former one was noticeably weaker. The SSERs were roughly linear in log‐log space, whereas the SARs demonstrated scale‐dependent behavior with a noticeable threshold (slope breakpoint). Species richness was almost area‐independent below this threshold (the “small area effect”, SAE) but followed typical power‐law SAR beyond the threshold. This effect was similar to the “small island effect” but occurred for arbitrarily delineated areas within continuous habitats. Parameters of the SAR curves depended on organism size. The upper limit of the SAE increased from microorganisms to meiofauna to macrofauna. Also, SAR curves for unicellular groups had significantly lower slopes. SAE is supposed to indicate a spatial range of statistical homogeneity in species composition. Its upper limit corresponds to the characteristic size of a local community (a single habitat occupied by a common species pool). Interpretations of SAR and SSER parameters in terms of α‐ and β‐diversity are proposed. Both SAR and SSER slopes obtained from univariate regressions are overestimated. This upward bias depends on sampling design, decreasing for SAR but increasing for SSER with more unequally spaced samples. Both spatial extent and sampling effort should be taken into account to disentangle properly their effects on diversity.     

Cormack–Jolly–Seber model with environmental covariates: A P‐spline approach

In capture–recapture models, survival and capture probabilities can be modelled as functions of time‐varying covariates, such as temperature or rainfall. The Cormack–Jolly–Seber (CJS) model allows for flexible modelling of these covariates; however, the functional relationship may not be linear. We extend the CJS model by semi‐parametrically modelling capture and survival probabilities using a frequentist approach via P‐splines techniques. We investigate the performance of the estimators by conducting simulation studies. We also apply and compare these models with known semi‐parametric Bayesian approaches on simulated and real data sets.     

Active‐Site Imprinting: Preparation of Fe–N–C Catalysts from Zinc Ion–Templated Ionothermal Nitrogen‐Doped Carbons

Atomically dispersed Fe–N–C catalysts are considered the most promising precious‐metal‐free alternative to state‐of‐the‐art Pt‐based oxygen reduction electrocatalysts for proton‐exchange membrane fuel cells. The exceptional progress in the field of research in the last ≈30 years is currently limited by the moderate active site density that can be obtained. Behind this stands the dilemma of metastability of the desired FeN₄ sites at the high temperatures that are believed to be a requirement for their formation. It is herein shown that Zn²⁺ ions can be utilized in the novel concept of active‐site imprinting based on a pyrolytic template ion reaction throughout the formation of nitrogen‐doped carbons. As obtained atomically dispersed Zn–N–Cs comprising ZnN₄ sites as well as metal‐free N₄ sites can be utilized for the coordination of Fe²⁺ and Fe³⁺ ions to form atomically dispersed Fe–N–C with Fe loadings as high as 3.12 wt%. The Fe–N–Cs are active electocatalysts for the oxygen reduction reaction in acidic media with an onset potential of E₀ = 0.85 V versus RHE in 0.1 m HClO₄. Identical location atomic resolution transmission electron microscopy imaging, as well as in situ electrochemical flow cell coupled to inductively coupled plasma mass spectrometry measurements, is employed to directly prove the concept of the active‐site imprinting approach.     

Open Capture–Recapture Models with Heterogeneity: II. Jolly–Seber Model

Summary Estimation of abundance is important in both open and closed population capture–recapture analysis, but unmodeled heterogeneity of capture probability leads to negative bias in abundance estimates. This article defines and develops a suite of open population capture–recapture models using finite mixtures to model heterogeneity of capture and survival probabilities. Model comparisons and parameter estimation use likelihood‐based methods. A real example is analyzed, and simulations are used to check the main features of the heterogeneous models, especially the quality of estimation of abundance, survival, recruitment, and turnover. The two major advances in this article are the provision of realistic abundance estimates that take account of heterogenetiy of capture, and an appraisal of the amount of overestimation of survival arising from conditioning on the first capture when heterogeneity of survival is present.     

Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis

Summary With increasing frequency, epidemiologic studies are addressing hypotheses regarding gene‐environment interaction. In many well‐studied candidate genes and for standard dietary and behavioral epidemiologic exposures, there is often substantial prior information available that may be used to analyze current data as well as for designing a new study. In this article, first, we propose a proper full Bayesian approach for analyzing studies of gene–environment interaction. The Bayesian approach provides a natural way to incorporate uncertainties around the assumption of gene–environment independence, often used in such an analysis. We then consider Bayesian sample size determination criteria for both estimation and hypothesis testing regarding the multiplicative gene–environment interaction parameter. We illustrate our proposed methods using data from a large ongoing case–control study of colorectal cancer investigating the interaction of N‐acetyl transferase type 2 (NAT2) with smoking and red meat consumption. We use the existing data to elicit a design prior and show how to use this information in allocating cases and controls in planning a future study that investigates the same interaction parameters. The Bayesian design and analysis strategies are compared with their corresponding frequentist counterparts.     

1,10‐Phenanthroline–H2O2–KSCN–CuSO4–NaOH oscillating chemiluminescence system

In this paper, oscillating chemiluminescence (CL), 1,10‐phenanthroline H₂O₂–KSCN–CuSO₄–NaOH system, was studied in a batch reactor. The system described is a novel, slowly damped oscillating CL system, generated by coupling the well‐known Epstein–Orban, H₂O₂–KSCN–CuSO₄–NaOH chemical oscillator reaction with the CL reaction involving the oxidation of 1,10‐phenanthroline by hydrogen peroxide, catalyzed by copper(II) in alkaline medium. In this system, the CL reaction acts as a detector or indicator system of the far‐from‐equilibrium dynamic system. Narrow and slightly asymmetric light pulses of 1.2 s half‐width are emitted at 440 nm with an emitted light time of 200–1000 s, induction period of 3.5–357 s and oscillation period of 28–304 s depending on the reagent concentrations. In this report the effect of the concentration variation of components involved in the oscillating CL system on the induction period, the oscillation period and amplitude was investigated and the parameters were plotted with respect to reagent concentrations. Copper concentration showed a significant effect on the oscillation period. The possible mechanism for the oscillating CL reaction was also discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

From central–peripheral to adaxial–abaxial

Higher plants are constructed of three organs – the stem, the root and the leaf. The stem and the root have two axes, apical–basal and central–peripheral, which cross orthogonally. Leaves develop from the shoot apical meristem as lateral organs that have three different axes, apical–basal, adaxial–abaxial and right–left. Recent data point to the possibility that the adaxial–abaxial axis in the leaf is formed from the central–peripheral axis in the stem.