Three-Dimensional CFD Simulation of a Proton Exchange Membrane Electrolysis Cell

The energy shift towards carbon-free solutions is creating an ever-growing engineering interest in electrolytic cells, i.e., devices to produce hydrogen from water-splitting reactions. Among the available technologies, Proton Exchange Membrane (PEM) electrolysis is the most promising candidate for coping with the intermittency of renewable energy sources, thanks to the short transient period granted by the solid thin electrolyte. The well-known principle of PEM electrolysers is still unsupported by advanced engineering practices, such as the use of multidimensional simulations able to elucidate the interacting fluid dynamics, electrochemistry, and heat transport. A methodology for PEM electrolysis simulation is therefore needed. In this study, a model for the multidimensional simulation of PEM electrolysers is presented and validated against a recent literature case. The study analyses the impact of temperature and gas phase distribution on the cell performance, providing valuable insights into the understanding of the physical phenomena occurring inside the cell at the basis of the formation rate of hydrogen and oxygen. The simulations regard two temperature levels (333 K and 353 K) and the complete polarization curve is numerically predicted, allowing the analysis of the overpotentials break-up and the multi-phase flow in the PEM cell. An in-house developed model for macro-homogeneous catalyst layers is applied to PEM electrolysis, allowing independent analysis of overpotentials, investigation into their dependency on temperature and analysis of the cathodic gas–liquid stratification. The study validates a comprehensive multi-dimensional model for PEM electrolysis, relevantly proposing a methodology for the ever-growing urgency for engineering optimization of such devices

Mining livestock genome datasets for an unconventional characterization of animal DNA viromes

Whole genome sequencing (WGS) datasets, usually generated for the investigation of the individual animal genome, can be used for additional mining of the fraction of sequencing reads that remains unmapped to the respective reference genome. A significant proportion of these reads contains viral DNA derived from viruses that infected the sequenced animals. In this study, we mined more than 480 billion sequencing reads derived from 1471 WGS datasets produced from cattle, pigs, chickens and rabbits. We identified 367 different viruses among which 14, 11, 12 and 1 might specifically infect the cattle, pig, chicken and rabbit, respectively. Some of them are ubiquitous, avirulent, highly or potentially damaging for both livestock and humans. Retrieved viral DNA information provided a first unconventional and opportunistic landscape of the livestock viromes that could be useful to understand the distribution of some viruses with potential deleterious impacts on the animal food production systems

Investigation of ABO Gene Variants across More Than 60 Pig Breeds and Populations and Other Suidae Species Using Whole-Genome Sequencing Datasets

Polymorphisms in the human ABO gene determine the major blood classification system based on the three well-known forms: A; B; and O. In pigs that carry only two main alleles in this gene (A and O), we still need to obtain a more comprehensive distribution of variants, which could also impact its function. In this study, we mined more than 500 whole-genome sequencing datasets to obtain information on the ABO gene in different Suidae species, pig breeds, and populations and provide (i) a comprehensive distribution of the A and O alleles, (ii) evolutionary relationships of ABO gene sequences across Suidae species, and (iii) an exploratory evaluation of the effect of the different ABO gene variants on production traits and blood-related parameters in Italian Large White pigs. We confirmed that allele O is likely under balancing selection, present in all Sus species investigated, without being fixed in any of them. We reported a novel structural variant in perfect linkage disequilibrium with allele O that made it possible to estimate the evolutionary time window of occurrence of this functional allele. We also identified two single nucleotide polymorphisms that were suggestively associated with plasma magnesium levels in pigs. Other studies can also be constructed over our results to further evaluate the effect of this gene on economically relevant traits and basic biological functions

Genome-wide association studies for 30 haematological and blood clinical-biochemical traits in Large White pigs reveal genomic regions affecting intermediate phenotypes

Haematological and clinical-biochemical parameters are considered indicators of the physiological/health status of animals and might serve as intermediate phenotypes to link physiological aspects to production and disease resistance traits. The dissection of the genetic variability affecting these phenotypes might be useful to describe the resilience of the animals and to support the usefulness of the pig as animal model. Here, we analysed 15 haematological and 15 clinical-biochemical traits in 843 Italian Large White pigs, via three genome-wide association scan approaches (single-trait, multi-trait and Bayesian). We identified 52 quantitative trait loci (QTLs) associated with 29 out of 30 analysed blood parameters, with the most significant QTL identified on porcine chromosome 14 for basophil count. Some QTL regions harbour genes that may be the obvious candidates: QTLs for cholesterol parameters identified genes (ADCY8, APOB, ATG5, CDKAL1, PCSK5, PRL and SOX6) that are directly involved in cholesterol metabolism; other QTLs highlighted genes encoding the enzymes being measured [ALT (known also as GPT) and AST (known also as GOT)]. Moreover, the multivariate approach strengthened the association results for several candidate genes. The obtained results can contribute to define new measurable phenotypes that could be applied in breeding programs as proxies for more complex traits

Whole genome semiconductor based sequencing of farmed European sea bass (Dicentrarchus labrax) Mediterranean genetic stocks using a DNA pooling approach

European sea bass (Dicentrarchus labrax) is an important marine species for commercial and sport fisheries and aquaculture production. Recently, the European sea bass genome has been sequenced and assembled. This resource can open new opportunities to evaluate and monitor variability and identify variants that could contribute to the adaptation to farming conditions. In this work, two DNA pools constructed from cultivated European sea bass were sequenced using a next generation semiconductor sequencing approach based on Ion Proton sequencer. Using the first draft version of the D. labrax genome as reference, sequenced reads obtained a total of about 1.6 million of single nucleotide polymorphisms (SNPs), spread all over the chromosomes. Transition/transversion (Ti/Tv) was equal to 1.28, comparable to what was already reported in Salmon species. A pilot homozygosity analysis across the D. labrax genome using DNA pool sequence datasets indicated that this approach can identify chromosome regions with putative signatures of selection, including genes involved in ion transport and chloride channel functions, amino acid metabolism and circadian clock and related neurological systems. This is the first study that reported genome wide polymorphisms in a fish species obtained with the Ion Proton sequencer. Moreover, this study provided a methodological approach for selective sweep analysis in this species

Application of SNP reduction approaches and random forest for the identification of population informative markers in cosmopolitan and local cattle breeds

In livestock, single nucleotide polymorphism genotyping arrays have been used to differentiate breeds and populations for several downstream applications, including breed allocation of individuals, breeds of origin of crossbred animals, authentication of mono breed products, comparative analyses of selection signatures among several other uses. We already tested a combination of principal component analysis (PCA), used as preselection method, and random forest (RF) used as classification method to assign cosmopolitan Italian breeds with no or very low error rate. In this work, we increased the number of breeds and approaches, to have a more comprehensive view of the strategies available and the applicability to local Italian breeds. The most common cosmopolitan dairy or dual purpose breeds (Holstein, Brown, Simmental) and 3 local breeds subjected to limited or no breeding programs (Reggiana, Modicana and Cinisara) were analyzed comparing several methods of SNPs pre-selection (Delta, Fst and PCA) in addition to RF classifications. From these classifications, two panels of 96 and 48 SNPs that contained the most discriminant SNPs were created for each pre-selection method. The results showed that the 96-SNP panels were generally more able to discriminate all breeds, while for the 48- SNP panels the error rate increased mainly for autochthonous breeds, particularly for Cinisara. This was probably a consequence of limited selection pressure, admixed origin, and ascertain bias on the construction of the SNP chip that was not designed considering these breeds. Several selected SNPs are located nearby genes affecting breed-specific traits (e.g. coat color and stature) or associated to production traits. The 96-SNP panel obtained after a preselection chromosome by chromosome, and used in the previous work with cosmopolitan breeds only, could identify informative SNPs that were particularly useful for the assignment of minor breeds. This panel reached the lowest value of out of bag (OOB) error in the RF test even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Our results showed the usefulness and power of the combination of PCA pre-selection and RF also for the discrimination of local cattle breeds

Whole genome sequencing identifies candidate genes and mutations that can explain diluted and other colour varieties of domestic canaries (Serinus canaria)

The domestic canary (Serinus canaria) is one of the most common pet birds and has been extensively selected and bred over the last few centuries to constitute many different varieties. Plumage pigmentation is one of the main phenotypic traits that distinguish canary breeds and lines. Feather colours in these birds, similarly to other avian species, are mainly depended on the presence of two major types of pigments: carotenoids and melanins. In this study, we exploited whole genome sequencing (WGS) datasets produced from five canary lines or populations (Black Frosted Yellow, Opal, Onyx, Opal × Onyx and Mogno, some of which carrying different putative dilute alleles), complemented with other WGS datasets retrieved from previous studies, to identify candidate genes that might explain pigmentation variability across canary breeds and varieties. Sequencing data were obtained using a DNA pool-seq approach and genomic data were compared using window-based FST analyses. We identified signatures of selection in genomic regions harbouring genes involved in carotenoid-derived pigmentation variants (CYP2J19, EDC, BCO2 and SCARB1), confirming the results reported by previous works, and identified several other signatures of selection in the correspondence of melanogenesis-related genes (AGRP, ASIP, DCT, EDNRB, KITLG, MITF, MLPH, SLC45A2, TYRP1 and ZEB2). Two putative causative mutations were identified in the MLPH gene that may explain the Opal and Onyx dilute mutant alleles. Other signatures of selection were also identified that might explain additional phenotypic differences between the investigated canary populations

Sexual Fantasies and Stereotypical Gender Roles: The Influence of Sexual Orientation, Gender and Social Pressure in a Sample of Italian Young-Adults

Differences in gender and sexual orientation are suggested to be linked to differences in the way individuals think and behave. The aim of the current study is to evaluate the effect of gender and sexual orientation on sexual fantasies and gender roles in heterosexual and gay and lesbian people. The sample was composed of 547 participants, 246 men (Mage = 28.85; SD = 9,27) and 301 women (Mage = 25,97; SD = 7,141). Within this sample, 61.8% of men and 79.4% of women were heterosexual, whereas 38.2% of men and 20.6% of women were gay and lesbian. Participants completed an online battery of questionnaires to assess their sexual orientation, sexual fantasies, and gender roles on three different dimensions. It was hypothesized that the heterosexual group would report more normative sexual fantasies (H1) and that women in general would report androgynous characteristics, which would be linked to a low degree of reported feminine ideal roles and high social pressure to conform to feminine social expectations (H2). The results showed that lesbian women scored slightly higher than heterosexual women on transgressive sexual fantasies and lower on emotional-romantic ones. Moreover, heterosexual women, but not lesbian women, showed a pattern of high social pressure to conform to feminine expectations together with lower scores in the IRQ. We found the same results on gay men but not for heterosexual men. The overall results suggest that sexual fantasies and gender roles are relatively independent concepts and are influenced by different mechanisms

SUS-BAR: a database of pig proteins with statistically validated structural and functional annotation

Given the relevance of the pig proteome in different studies, including human complex maladies, a statistical validation of the annotation is required for a better understanding of the role of specific genes and proteins in the complex networks underlying biological processes in the animal. Presently, approximately 80% of the pig proteome is still poorly annotated, and the existence of protein sequences is routinely inferred automatically by sequence alignment towards preexisting sequences. In this article, we introduce SUS-BAR, a database that derives information mainly from UniProt Knowledgebase and that includes 26 206 pig protein sequences. In SUS-BAR, 16 675 of the pig protein sequences are endowed with statistically validated functional and structural annotation. Our statistical validation is determined by adopting a cluster-centric annotation procedure that allows transfer of different types of annotation, including structure and function. Each sequence in the database can be associated with a set of statistically validated Gene Ontologies (GOs) of the three main sub-ontologies (Molecular Function, Biological Process and Cellular Component), with Pfam functional domains, and when possible, with a cluster Hidden Markov Model that allows modelling the 3D structure of the protein. A database search allows some statistics demonstrating the enrichment in both GO and Pfam annotations of the pig proteins as compared with UniProt Knowledgebase annotation. Searching in SUS-BAR allows retrieval of the pig protein annotation for further analysis. The search is also possible on the basis of specific GO terms and this allows retrieval of all the pig sequences participating into a given biological process, after annotation with our system. Alternatively, the search is possible on the basis of structural information, allowing retrieval of all the pig sequences with the same structural characteristics