A Durable Alternative for Proton‐Exchange Membranes: Sulfonated Poly(Benzoxazole Thioether Sulfone)s

To develop a durable proton‐exchange membrane (PEM) for fuel‐cell applications, a series of sulfonated poly(benzoxazole thioether sulfone)s ( SPTESBOs) are designed and synthesized, with anticipated good dimensional stability (via acid–base cross linking), improved oxidative stability against free radicals (via incorporation of thioether groups), and enhanced inherent stability (via elimination of unstable end groups) of the backbone. The structures and the degree of sulfonation of the copolymers are characterized using Fourier‐transform infrared spectroscopy, and nuclear magnetic resonance spectroscopy (¹H NMR and ¹⁹F NMR). The electrochemical stabilities of the monomers are examined using cyclic voltammetry in a typical three‐electrode cell configuration. The physicochemical properties of the membranes vital to fuel‐cell performance are also carefully evaluated under conditions relevant to fuel‐cell operation, including chemical and thermal stability, proton conductivity, solubility in different solvents, water uptake, and swelling ratio. The new membranes exhibit low dimensional change at 25°C to 90°C and excellent thermal stability up to 250°C. Upon elimination of unstable end groups, the co‐polymers display enhanced chemical resistance and oxidative stability in Fenton's test. Further, the SPTESBO‐HFB‐60 (HFB‐60=hexafluorobenzene, 60 mol% sulfone) membrane displays comparable fuel‐cell performance to that of an NRE 212 membrane at 80°C under fully humidified condition, suggesting that the new membranes have the potential to be more durable but less expensive for fuel‐cell applications.     

Atomic Layer Deposition of CdS Quantum Dots for Solid‐State Quantum Dot Sensitized Solar Cells

Functioning quantum dot (QD) sensitized solar cells have been fabricated using the vacuum deposition technique atomic layer deposition (ALD). Utilizing the incubation period of CdS growth by ALD on TiO₂, we are able to grow QDs of adjustable size which act as sensitizers for solid‐state QD‐sensitized solar cells (ssQDSSC). The size of QDs, studied with transmission electron microscopy (TEM), varied with the number of ALD cycles from 1‐10 nm. Photovoltaic devices with the QDs were fabricated and characterized using a ssQDSSC device architecture with 2,2',7,7'‐tetrakis‐(N,N‐di‐p methoxyphenylamine) 9,9'‐spirobifluorene (spiro‐OMeTAD) as the solid‐state hole conductor. The ALD approach described here can be applied to fabrication of quantum‐confined structures for a variety of applications, including solar electricity and solar fuels. Because ALD provides the ability to deposit many materials in very high aspect ratio substrates, this work introduces a strategy by which material and optical properties of QD sensitizers may be adjusted not only by the size of the particles but also in the future by the composition.     

Combined analysis of Perca fluviatilis reproductive performance and oocyte proteomic profile

The success of reproduction depends greatly upon gamete quality, especially oocytes which carry most of the molecular material necessary for early embryogenesis. However, it remains difficult to find relevant morphologic and/or biochemical parameters to assess oocyte quality and thus have a reliable prediction of the reproduction performance. To understand which criteria are the most reliable to assess the reproductive success of the Eurasian perch (Perca fluviatilis), we measured 14 parameters characterizing female, spawn, oocyte, and embryonic or larval development on 20 independent spawn. A data analysis allowed the definition of two clusters of spawn with different larval characteristics: the first cluster was composed of spawn which led mainly to strong large larvae presenting a low deformity rate, while the second cluster rather corresponds to spawn leading to smaller and weaker larvae with a higher deformity rate. Moreover, a third cluster (unfertilized spawn) was studied. Our analysis revealed that most of the prefertilization biological traits that we studied appeared poorly relevant to predict larval features, proper embryonic development and deformity occurrences. We thus performed a large scale proteomic analysis to highlight proteins differently expressed in each spawn cluster. A 2D-DIGE study followed by an MS/MS spectrometry allowed the identification of 32 proteins involved in several biological functions and differently expressed between spawn clusters. Among them, proteins involved in cell response to the oxidative stress, as well as energetic metabolism, heat shock proteins and Vitellogenins are of particular interest. Several functions appear specific to a spawn cluster and could thus explain their corresponding reproduction performance. In the future, proteins involved in those cellular mechanisms may constitute molecular markers predictive of the reproduction performance in Perca fluviatilis.     

Morphological and molecular divergence of Indian hill trout,Barilius bendelisis (Hamilton, 1822) stocks from different Rivers in Indo‐Burma biodiversity hotspot: Does river altitude and Dam play a role?

The present study explains the intraspecific variation in Indian Hill trout (Barilius bendelisis) on the basis of image based truss network system and D‐loop region of mtDNA. A total of 210 samples were collected from three different rivers (Teesta, Kameng and Myntudu River) of North East India in Indo‐Burma Biodiversity Hotspot. By using the software applications (tpsDig version 2.1 and PAST), a total of 25 morphometric measurements were generated from 10 landmarks. The Analysis of Variance (ANOVA), Factor Analysis (FA) and Discriminate Function Analysis (DFA) showed, out of the total variations, factor 1 explained 46.74% while factor 2 and factor 3 explained 27.14% and 11.92%, respectively. Using these variables 83.33% of the cross‐validated specimens were classified into distinct groups. Analysis of Molecular Variance (AMOVA) and pairwise Fst value for D‐loop region of mtDNA also showed high to medium level of genetic variation among the stocks and within the stocks. We conclude that the observed discrete stocks might be the result of changing environmental conditions in different rivers of the hotspot as the rivers are present at different altitudinal labels. It is also believed that the variation might be due to the construction of barrages across the river which hinder the mixing among the stocks.     

Spatially explicit models of divergence and genome hitchhiking

Strong barriers to genetic exchange can exist at divergently selected loci, whereas alleles at neutral loci flow more readily between populations, thus impeding divergence and speciation in the face of gene flow. However, ‘divergence hitchhiking’ theory posits that divergent selection can generate large regions of differentiation around selected loci. ‘Genome hitchhiking’ theory suggests that selection can also cause reductions in average genome‐wide rates of gene flow, resulting in widespread genomic divergence (rather than divergence only around specific selected loci). Spatial heterogeneity is ubiquitous in nature, yet previous models of genetic barriers to gene flow have explored limited combinations of spatial and selective scenarios. Using simulations of secondary contact of populations, we explore barriers to gene flow in various selective and spatial contexts in continuous, two‐dimensional, spatially explicit environments. In general, the effects of hitchhiking are strongest in environments with regular spatial patterning of starkly divergent habitat types. When divergent selection is very strong, the absence of intermediate habitat types increases the effects of hitchhiking. However, when selection is moderate or weak, regular (vs. random) spatial arrangement of habitat types becomes more important than the presence of intermediate habitats per se. We also document counterintuitive processes arising from the stochastic interplay between selection, gene flow and drift. Our results indicate that generalization of results from two‐deme models requires caution and increase understanding of the genomic and geographic basis of population divergence.     

Characterization of phytoplankton assemblages in a tropical coastal environment using Kohonen self‐organizing map

This study was aimed at understanding the main abiotic environmental factors controlling the distribution patterns of abundance and composition of phytoplankton (size less than 10 μm) assemblages in the coastal waters of south‐eastern Côte d'Ivoire. Data were collected during two cruises, in January (low‐water period) and October (high‐water period) of 2014. A total of 67 species were identified and assigned to Bacillariophyceae (49%), Cyanophyceae (21%), Chlorophyceae (13%), Euglenophyceae (10%), Dinophyceae (4%) and Chrysophyceae (3%). Three biotic zones (I, IIA and IIB) were distinguishable on a Kohonen self‐organizing map after an unsupervised learning process. The diatom genera Eunotia sp., Navicula sp. and Actinoptychus senarius are significantly associated with I, IIA and IIB biotic zones, respectively. A clear seasonal cum salinity trend was apparent in phytoplankton distribution patterns. Turbidity and nitrate levels were the main abiotic factors controlling phytoplankton distribution in I, the upland tidal regions of the lagoon. In regions along the lagoon–sea continuum, phosphate and turbidity exert the most control during the low‐water season (IIA), while total dissolved solids control phytoplankton distribution during the high‐water season (IIB). These are climate‐sensitive parameters whose concentrations depend on prevailing hydroclimatic processes. Therefore, seasonality can have important consequences on phytoplankton community and inadvertently the productivity of these systems.     

RNA sequencing reveals two major classes of gene expression levels in metazoan cells

The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing (RNA‐seq) of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprised of lowly expressed and putatively non‐functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. These observations are confirmed in many other microarray and RNA‐seq data sets of metazoan cell types.