107 research outputs found
Modeling meiotic chromosomes indicates a size dependent contribution of telomere clustering and chromosome rigidity to homologue juxtaposition.
Meiosis is the cell division that halves the genetic component of diploid cells to form gametes or spores. To achieve this, meiotic cells undergo a radical spatial reorganisation of chromosomes. This reorganisation is a prerequisite for the pairing of parental homologous chromosomes and the reductional division, which halves the number of chromosomes in daughter cells. Of particular note is the change from a centromere clustered layout (Rabl configuration) to a telomere clustered conformation (bouquet stage). The contribution of the bouquet structure to homologous chromosome pairing is uncertain. We have developed a new in silico model to represent the chromosomes of Saccharomyces cerevisiae in space, based on a worm-like chain model constrained by attachment to the nuclear envelope and clustering forces. We have asked how these constraints could influence chromosome layout, with particular regard to the juxtaposition of homologous chromosomes and potential nonallelic, ectopic, interactions. The data support the view that the bouquet may be sufficient to bring short chromosomes together, but the contribution to long chromosomes is less. We also find that persistence length is critical to how much influence the bouquet structure could have, both on pairing of homologues and avoiding contacts with heterologues. This work represents an important development in computer modeling of chromosomes, and suggests new explanations for why elucidating the functional significance of the bouquet by genetics has been so difficult
Consensus-based antimicrobial resistance and stewardship competencies for UK undergraduate medical students.
BACKGROUND: In the UK there is limited coverage of antimicrobial stewardship across postgraduate curricula and evidence that final year medical students have insufficient and inconsistent antimicrobial stewardship teaching. A national undergraduate curriculum for antimicrobial resistance and stewardship is required to standardize an adequate level of understanding for all future doctors. OBJECTIVES: To provide a UK national consensus on competencies for antimicrobial resistance and stewardship for undergraduate medical education. METHODS: Using the modified Delphi method over two online survey rounds, an expert panel comprising leads for infection teaching from 25 UK medical schools reviewed competency descriptors for antimicrobial resistance and stewardship education. RESULTS: There was a response rate of 100% with all 28 experts who agreed to take part completing both survey rounds. Following the first-round survey, of the initial 55 descriptors, 43 reached consensus (78%). The second-round survey included the 12 descriptors from the first round in which agreement had not been reached, four amended descriptors and 12 new descriptors following qualitative feedback from the panel members. Following the second-round survey, a total of 58 consensus-based competency descriptors within six overarching domains were identified. CONCLUSIONS: The consensus-based competency descriptors defined here can be used to inform standards, design curricula, develop assessment tools and direct UK undergraduate medical education
Quantitative imaging of concentrated suspensions under flow
We review recent advances in imaging the flow of concentrated suspensions,
focussing on the use of confocal microscopy to obtain time-resolved information
on the single-particle level in these systems. After motivating the need for
quantitative (confocal) imaging in suspension rheology, we briefly describe the
particles, sample environments, microscopy tools and analysis algorithms needed
to perform this kind of experiments. The second part of the review focusses on
microscopic aspects of the flow of concentrated model hard-sphere-like
suspensions, and the relation to non-linear rheological phenomena such as
yielding, shear localization, wall slip and shear-induced ordering. Both
Brownian and non-Brownian systems will be described. We show how quantitative
imaging can improve our understanding of the connection between microscopic
dynamics and bulk flow.Comment: Review on imaging hard-sphere suspensions, incl summary of
methodology. Submitted for special volume 'High Solid Dispersions' ed. M.
Cloitre, Vol. xx of 'Advances and Polymer Science' (Springer, Berlin, 2009);
22 pages, 16 fig
Apical Transport of Influenza A Virus Ribonucleoprotein Requires Rab11-positive Recycling Endosome
Influenza A virus RNA genome exists as eight-segmented ribonucleoprotein complexes containing viral RNA polymerase and nucleoprotein (vRNPs). Packaging of vRNPs and virus budding take place at the apical plasma membrane (APM). However, little is known about the molecular mechanisms of apical transport of newly synthesized vRNP. Transfection of fluorescent-labeled antibody and subsequent live cell imaging revealed that punctate vRNP signals moved along microtubules rapidly but intermittently in both directions, suggestive of vesicle trafficking. Using a series of Rab family protein, we demonstrated that progeny vRNP localized to recycling endosome (RE) in an active/GTP-bound Rab11-dependent manner. The vRNP interacted with Rab11 through viral RNA polymerase. The localization of vRNP to RE and subsequent accumulation to the APM were impaired by overexpression of Rab binding domains (RBD) of Rab11 family interacting proteins (Rab11-FIPs). Similarly, no APM accumulation was observed by overexpression of class II Rab11-FIP mutants lacking RBD. These results suggest that the progeny vRNP makes use of Rab11-dependent RE machinery for APM trafficking
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
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
Barriers and facilitators to extended working lives in Europe : a gender focus
Background: There is a global imperative to respond to the challenge of a growing ‘old-age dependency ratio’ by ensuring the workforce is healthy enough to remain in work for longer. Currently more than half of older workers leave before the default retirement age, and in some countries (e.g. the United Kingdom) the time spent in retirement is increasing. At the same time across Europe there is a gender employment gap, with 14.5% fewer female workers between 55-64 years old, and a large variation in the participation of older women in the workforce (ranging from 30%-75%). As older women are under-represented in the workforce, increasing employment in this group has the propensity to go some way towards reducing the old-age dependency ratio to ensure continued economic growth.
Objectives: This review explores the barriers and facilitators to extended working lives in Europe, particularly those than impact on women.
Methods: A systematic mapping review process was undertaken using four electronic databases, Medline, PsychoInfo, Psych Extra via Ovid and Age Line via EBSCO, using the terms, ‘work’, ‘ageing’, ‘retirement’, ‘pension’, ‘old’, ‘barrier’, ‘extended working life’, ‘gender’, ‘health and wellbeing’. Hand searching was also carried out in the Journal of Aging and Human Development and the Journal of Ageing and Society.
Results: The search resulted in 15 English language studies published from 1st January 2005 to the current date that met the inclusion criteria.
Key findings: The key factors that influenced decisions to retire or extend working lives in Europe, were health; social factors; workplace factors; and financial security and pension arrangements.
Conclusions and implications of key findings: Health was found to be the most commonly cited barrier to extended working lives in Europe, and a number of social inequalities to work exist by gender. Structural factors exist, such as the gender pay gap, which disadvantage women, while the nature of work itself differs by gender and can have a negative impact on health. Currently women tend to exit the labour market earlier than men, however, changes in the state pension age are resulting in women being required to work for as long as men, in most countries. For women to remain healthy at work, workplaces need to consider a range of interventions, including flexible arrangements to both work and retirement to enable women to balance the demands of work with domestic and caring responsibilities that particularly impact on them
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
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