The Physio-Chemical Properties for the Interior of Enceladus

We have reviewed the current physical and chemical conditions of the Enceladus sub-surface environment, including the composition, temperature, pH and pressure. Here we have defined some of these parameters and, through the aid of modelling, will define and refine the remaining parameters needed for our experimental work. Simulations of the chemical reactions occurring within Enceladus can then be carried out to advance our understanding of the internal environment of Enceladus and help evaluate its potential habitability. Once a better understanding of the chemical reactions occurring at the rock-water interface has been carried out, then potential analogues on Earth can be evaluated and known microbial life can be tested to see if it could survive the conditions of Enceladus

Processfolio: uniting Academic Literacies and Critical Emancipatory Action Research for practitioner-led inquiry into EAP writing assessment

This paper reports on the design and implementation of an alternative form of writing assessment on a UK English for Academic Purposes (EAP) presessional course. The assessment, termed processfolio, was a response to research inquiry into how writing assessment in a local context negated student agency and inculcated disempowering models of teaching and learning academic writing. The project merged an Academic Literacies approach to writing (Lea and Street, 1998) with a Critical Emancipatory Action Research (Carr and Kemmis, 1986) framework and a Critical Realist(Bhaskar, 1989) perspective. Data collected from the folios and interviews with students and teachers on their experiences of the processfolio found that a small scale intervention has potential for agency to be exercised within the highly constrained context of a UK EAP pre-sessional. New directions in research are proposed which can engage students and teachers to work for change in UK EAP assessment within their internal and external constraints

Evolutionary Relationships of Wild Hominids Recapitulated by Gut Microbial Communities

Although bacteria are continually acquired over the lifetime of an individual, the phylogenetic relationships of great ape species is mirrored in the compositions of their gut microbial communities

The evolutionary signal in metagenome phyletic profiles predicts many gene functions

Background. The function of many genes is still not known even in model organisms. An increasing availability of microbiome DNA sequencing data provides an opportunity to infer gene function in a systematic manner. Results. We evaluated if the evolutionary signal contained in metagenome phyletic profiles (MPP) is predictive of a broad array of gene functions. The MPPs are an encoding of environmental DNA sequencing data that consists of relative abundances of gene families across metagenomes. We find that such MPPs can accurately predict 826 Gene Ontology functional categories, while drawing on human gut microbiomes, ocean metagenomes, and DNA sequences from various other engineered and natural environments. Overall, in this task, the MPPs are highly accurate, and moreover they provide coverage for a set of Gene Ontology terms largely complementary to standard phylogenetic profiles, derived from fully sequenced genomes. We also find that metagenomes approximated from taxon relative abundance obtained via 16S rRNA gene sequencing may provide surprisingly useful predictive models. Crucially, the MPPs derived from different types of environments can infer distinct, non-overlapping sets of gene functions and therefore complement each other. Consistently, simulations on > 5000 metagenomes indicate that the amount of data is not in itself critical for maximizing predictive accuracy, while the diversity of sampled environments appears to be the critical factor for obtaining robust models. Conclusions. In past work, metagenomics has provided invaluable insight into ecology of various habitats, into diversity of microbial life and also into human health and disease mechanisms. We propose that environmental DNA sequencing additionally constitutes a useful tool to predict biological roles of genes, yielding inferences out of reach for existing comparative genomics approaches

Mitigating the Effect of Language in the Assessment of Science:A study of English-language learners in primary classrooms in the United Kingdom

Children coming from homes where English is not the primary language constitute a significant and increasing proportion of classrooms worldwide. Providing these English language learners (ELLs) with equitable assessment opportunities is a challenge. We analyse the performance of 485 students, both English native speakers and ELLs, across 5 schools within the UK in the 7-11 year age group on standardized Science assessment tasks. Logistic regression with random effects assesses the impact of English language proficiency, and its interactions with question traits, on performance. Traits investigated were: question focus; need for active language production; presence/absence of visuals; and question difficulty. Results demonstrated that, while ELLs persistently performed more poorly, the gap to their native speaking peers depended significantly upon assessment traits. ELLs were particularly disadvantaged when responses required active language production and/or when assessed on specific scientific vocabulary. Visual prompts did not help ELL performance. There was no evidence of an interaction between topic difficulty and language ability suggesting lower ELL performance is not related to capacity to understand advanced topics. We propose assessment should permit flexibility in language choice for ELLs with low English language proficiency; while simultaneously recommend subject-specific teaching of scientific language begins at lower stages of schooling

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio