Identification of novel subgroup a variants with enhanced receptor binding and replicative capacity in primary isolates of anaemogenic strains of feline leukaemia virus

<b>BACKGROUND:</b> The development of anaemia in feline leukaemia virus (FeLV)-infected cats is associated with the emergence of a novel viral subgroup, FeLV-C. FeLV-C arises from the subgroup that is transmitted, FeLV-A, through alterations in the amino acid sequence of the receptor binding domain (RBD) of the envelope glycoprotein that result in a shift in the receptor usage and the cell tropism of the virus. The factors that influence the transition from subgroup A to subgroup C remain unclear, one possibility is that a selective pressure in the host drives the acquisition of mutations in the RBD, creating A/C intermediates with enhanced abilities to interact with the FeLV-C receptor, FLVCR. In order to understand further the emergence of FeLV-C in the infected cat, we examined primary isolates of FeLV-C for evidence of FeLV-A variants that bore mutations consistent with a gradual evolution from FeLV-A to FeLV-C.<p></p> <b>RESULTS:</b> Within each isolate of FeLV-C, we identified variants that were ostensibly subgroup A by nucleic acid sequence comparisons, but which bore mutations in the RBD. One such mutation, N91D, was present in multiple isolates and when engineered into a molecular clone of the prototypic FeLV-A (Glasgow-1), enhanced replication was noted in feline cells. Expression of the N91D Env on murine leukaemia virus (MLV) pseudotypes enhanced viral entry mediated by the FeLV-A receptor THTR1 while soluble FeLV-A Env bearing the N91D mutation bound more efficiently to mouse or guinea pig cells bearing the FeLV-A and -C receptors. Long-term in vitro culture of variants bearing the N91D substitution in the presence of anti-FeLV gp70 antibodies did not result in the emergence of FeLV-C variants, suggesting that additional selective pressures in the infected cat may drive the subsequent evolution from subgroup A to subgroup C.<p></p> <b>CONCLUSIONS:</b> Our data support a model in which variants of FeLV-A, bearing subtle differences in the RBD of Env, may be predisposed towards enhanced replication in vivo and subsequent conversion to FeLV-C. The selection pressures in vivo that drive the emergence of FeLV-C in a proportion of infected cats remain to be established

Assessing Performance of Orthology Detection Strategies Applied to Eukaryotic Genomes

Orthology detection is critically important for accurate functional annotation, and has been widely used to facilitate studies on comparative and evolutionary genomics. Although various methods are now available, there has been no comprehensive analysis of performance, due to the lack of a genomic-scale ‘gold standard’ orthology dataset. Even in the absence of such datasets, the comparison of results from alternative methodologies contains useful information, as agreement enhances confidence and disagreement indicates possible errors. Latent Class Analysis (LCA) is a statistical technique that can exploit this information to reasonably infer sensitivities and specificities, and is applied here to evaluate the performance of various orthology detection methods on a eukaryotic dataset. Overall, we observe a trade-off between sensitivity and specificity in orthology detection, with BLAST-based methods characterized by high sensitivity, and tree-based methods by high specificity. Two algorithms exhibit the best overall balance, with both sensitivity and specificity>80%: INPARANOID identifies orthologs across two species while OrthoMCL clusters orthologs from multiple species. Among methods that permit clustering of ortholog groups spanning multiple genomes, the (automated) OrthoMCL algorithm exhibits better within-group consistency with respect to protein function and domain architecture than the (manually curated) KOG database, and the homolog clustering algorithm TribeMCL as well. By way of using LCA, we are also able to comprehensively assess similarities and statistical dependence between various strategies, and evaluate the effects of parameter settings on performance. In summary, we present a comprehensive evaluation of orthology detection on a divergent set of eukaryotic genomes, thus providing insights and guides for method selection, tuning and development for different applications. Many biological questions have been addressed by multiple tests yielding binary (yes/no) outcomes but no clear definition of truth, making LCA an attractive approach for computational biology

Clinical factors associated with a conservative gait pattern in older male veterans with diabetes

<p>Abstract</p> <p>Background</p> <p>Patients with diabetes and peripheral neuropathy are at higher risk for falls. People with diabetes sometimes adopt a more conservative gait pattern with decreased walking speed, widened base, and increased double support time. The purpose of this study was to use a multivariate approach to describe this conservative gait pattern.</p> <p>Methods</p> <p>Male veterans (mean age = 67 years; SD = 9.8; range 37–86) with diabetes (n = 152) participated in this study from July 2000 to May 2001 at the Veterans Affairs Medical Center, White River Junction, VT. Various demographic, clinical, static mobility, and plantar pressure measures were collected. Conservative gait pattern was defined by visual gait analysis as failure to demonstrate a heel-to-toe gait during the propulsive phase of gait.</p> <p>Results</p> <p>Patients with the conservative gait pattern had lower walking speed and decreased stride length compared to normal gait. (0.68 m/s v. 0.91 m/s, <it>p </it>< 0.001; 1.04 m v. 1.24 m, <it>p </it>< 0.001) Age, monofilament insensitivity, and Romberg's sign were significantly higher; and ankle dorsiflexion was significantly lower in the conservative gait pattern group. In the multivariate analysis, walking speed, age, ankle dorsiflexion, and callus were retained in the final model describing 36% of the variance. With the inclusion of ankle dorsiflexion in the model, monofilament insensitivity was no longer an independent predictor.</p> <p>Conclusion</p> <p>Our multivariate investigation of conservative gait in diabetes patients suggests that walking speed, advanced age, limited ankle dorsiflexion, and callus describe this condition more so than clinical measures of neuropathy.</p

The stellar halo of the Galaxy

Stellar halos may hold some of the best preserved fossils of the formation history of galaxies. They are a natural product of the merging processes that probably take place during the assembly of a galaxy, and hence may well be the most ubiquitous component of galaxies, independently of their Hubble type. This review focuses on our current understanding of the spatial structure, the kinematics and chemistry of halo stars in the Milky Way. In recent years, we have experienced a change in paradigm thanks to the discovery of large amounts of substructure, especially in the outer halo. I discuss the implications of the currently available observational constraints and fold them into several possible formation scenarios. Unraveling the formation of the Galactic halo will be possible in the near future through a combination of large wide field photometric and spectroscopic surveys, and especially in the era of Gaia.Comment: 46 pages, 16 figures. References updated and some minor changes. Full-resolution version available at http://www.astro.rug.nl/~ahelmi/stellar-halo-review.pd

Rationale, design and methods for a community-based study of clustering and cumulative effects on chronic disease process and their effects on ageing: the Busselton healthy ageing study

Background: The global trend of increased life expectancy and increased prevalence of chronic and degenerative diseases will impact on health systems. To identify effective intervention and prevention strategies, greater understanding of the risk factors for and cumulative effects of chronic disease processes and their effects on function and quality of life is needed. The Busselton Healthy Ageing Study aims to enhance understanding of ageing by relating the clustering and interactions of common chronic conditions in adults to function. Longitudinal (3–5 yearly) follow-up is planned. Methods/design: Phase I (recruitment) is a cross-sectional community-based prospective cohort study involving up to 4,000 ‘Baby Boomers’ (born from 1946 to 1964) living in the Busselton Shire, Western Australia. The study protocol involves a detailed, self-administered health and risk factor questionnaire and a range of physical assessments including body composition and bone density measurements, cardiovascular profiling (blood pressure, ECG and brachial pulse wave velocity), retinal photography, tonometry, auto-refraction, spirometry and bronchodilator responsiveness, skin allergy prick tests, sleep apnoea screening, tympanometry and audiometry, grip strength, mobility, balance and leg extensor strength. Cognitive function and reserve, semantic memory, and pre-morbid intelligence are assessed. Participants provide a fasting blood sample for assessment of lipids, blood glucose, C-reactive protein and renal and liver function, and RNA, DNA and serum are stored. Clinically relevant results are provided to all participants. The prevalence of risk factors, symptoms and diagnosed illness will be calculated and the burden of illness will be estimated based on the observed relationships and clustering of symptoms and illness within individuals. Risk factors for combinations of illness will be compared with those for single illnesses and the relation of combinations of illness and symptoms to cognitive and physical function will be estimated. Discussion: This study will enable a thorough characterization of multiple disease processes and their risk factors within a community-based sample of individuals to determine their singular, interactive and cumulative effects on ageing. The project will provide novel cross-sectional data and establish a cohort that will be used for longitudinal analyses of the genetic, lifestyle and environmental factors that determine whether an individual ages well or with impairment

Tetraploid Wheat Landraces in the Mediterranean Basin: Taxonomy, Evolution and Genetic Diversity

The geographic distribution of genetic diversity and the population structure of tetraploid wheat landraces in the Mediterranean basin has received relatively little attention. This is complicated by the lack of consensus concerning the taxonomy of tetraploid wheats and by unresolved questions regarding the domestication and spread of naked wheats. These knowledge gaps hinder crop diversity conservation efforts and plant breeding programmes. We investigated genetic diversity and population structure in tetraploid wheats (wild emmer, emmer, rivet and durum) using nuclear and chloroplast simple sequence repeats, functional variations and insertion site-based polymorphisms. Emmer and wild emmer constitute a genetically distinct population from durum and rivet, the latter seeming to share a common gene pool. Our population structure and genetic diversity data suggest a dynamic history of introduction and extinction of genotypes in the Mediterranean fields

Towards a Physiology-Based Measure of Pain: Patterns of Human Brain Activity Distinguish Painful from Non-Painful Thermal Stimulation

Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessment has long been self-report. Because the inability to verbally communicate can prevent effective pain management, research efforts have focused on the development of a tool that accurately assesses pain without depending on self-report. Those previous efforts have not proven successful at substituting self-report with a clinically valid, physiology-based measure of pain. Recent neuroimaging data suggest that functional magnetic resonance imaging (fMRI) and support vector machine (SVM) learning can be jointly used to accurately assess cognitive states. Therefore, we hypothesized that an SVM trained on fMRI data can assess pain in the absence of self-report. In fMRI experiments, 24 individuals were presented painful and nonpainful thermal stimuli. Using eight individuals, we trained a linear SVM to distinguish these stimuli using whole-brain patterns of activity. We assessed the performance of this trained SVM model by testing it on 16 individuals whose data were not used for training. The whole-brain SVM was 81% accurate at distinguishing painful from non-painful stimuli (p<0.0000001). Using distance from the SVM hyperplane as a confidence measure, accuracy was further increased to 84%, albeit at the expense of excluding 15% of the stimuli that were the most difficult to classify. Overall performance of the SVM was primarily affected by activity in pain-processing regions of the brain including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex. Region of interest (ROI) analyses revealed that whole-brain patterns of activity led to more accurate classification than localized activity from individual brain regions. Our findings demonstrate that fMRI with SVM learning can assess pain without requiring any communication from the person being tested. We outline tasks that should be completed to advance this approach toward use in clinical settings