Rhinovirus Genome Variation during Chronic Upper and Lower Respiratory Tract Infections

Routine screening of lung transplant recipients and hospital patients for respiratory virus infections allowed to identify human rhinovirus (HRV) in the upper and lower respiratory tracts, including immunocompromised hosts chronically infected with the same strain over weeks or months. Phylogenetic analysis of 144 HRV-positive samples showed no apparent correlation between a given viral genotype or species and their ability to invade the lower respiratory tract or lead to protracted infection. By contrast, protracted infections were found almost exclusively in immunocompromised patients, thus suggesting that host factors rather than the virus genotype modulate disease outcome, in particular the immune response. Complete genome sequencing of five chronic cases to study rhinovirus genome adaptation showed that the calculated mutation frequency was in the range observed during acute human infections. Analysis of mutation hot spot regions between specimens collected at different times or in different body sites revealed that non-synonymous changes were mostly concentrated in the viral capsid genes VP1, VP2 and VP3, independent of the HRV type. In an immunosuppressed lung transplant recipient infected with the same HRV strain for more than two years, both classical and ultra-deep sequencing of samples collected at different time points in the upper and lower respiratory tracts showed that these virus populations were phylogenetically indistinguishable over the course of infection, except for the last month. Specific signatures were found in the last two lower respiratory tract populations, including changes in the 5′UTR polypyrimidine tract and the VP2 immunogenic site 2. These results highlight for the first time the ability of a given rhinovirus to evolve in the course of a natural infection in immunocompromised patients and complement data obtained from previous experimental inoculation studies in immunocompetent volunteers

Association of Kawasaki disease with tropospheric wind patterns

The causal agent of Kawasaki disease (KD) remains unknown after more than 40 years of intensive research. The number of cases continues to rise in many parts of the world and KD is the most common cause of acquired heart disease in childhood in developed countries. Analyses of the three major KD epidemics in Japan, major non-epidemic interannual fluctuations of KD cases in Japan and San Diego, and the seasonal variation of KD in Japan, Hawaii, and San Diego, reveals a consistent pattern wherein KD cases are often linked to large-scale wind currents originating in central Asia and traversing the north Pacific. Results suggest that the environmental trigger for KD could be wind-borne. Efforts to isolate the causative agent of KD should focus on the microbiology of aerosols

Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI

PURPOSE: We propose a fully automated method for detection and segmentation of the abnormal tissue associated with brain tumour (tumour core and oedema) from Fluid- Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Imaging (MRI). METHODS: The method is based on superpixel technique and classification of each superpixel. A number of novel image features including intensity-based, Gabor textons, fractal analysis and curvatures are calculated from each superpixel within the entire brain area in FLAIR MRI to ensure a robust classification. Extremely randomized trees (ERT) classifier is compared with support vector machine (SVM) to classify each superpixel into tumour and non-tumour. RESULTS: The proposed method is evaluated on two datasets: (1) Our own clinical dataset: 19 MRI FLAIR images of patients with gliomas of grade II to IV, and (2) BRATS 2012 dataset: 30 FLAIR images with 10 low-grade and 20 high-grade gliomas. The experimental results demonstrate the high detection and segmentation performance of the proposed method using ERT classifier. For our own cohort, the average detection sensitivity, balanced error rate and the Dice overlap measure for the segmented tumour against the ground truth are 89.48 %, 6 % and 0.91, respectively, while, for the BRATS dataset, the corresponding evaluation results are 88.09 %, 6 % and 0.88, respectively. CONCLUSIONS: This provides a close match to expert delineation across all grades of glioma, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management

The Evolution of Facultative Conformity Based on Similarity

Conformist social learning can have a pronounced impact on the cultural evolution of human societies, and it can shape both the genetic and cultural evolution of human social behavior more broadly. Conformist social learning is beneficial when the social learner and the demonstrators from whom she learns are similar in the sense that the same behavior is optimal for both. Otherwise, the social learner's optimum is likely to be rare among demonstrators, and conformity is costly. The trade-off between these two situations has figured prominently in the longstanding debate about the evolution of conformity, but the importance of the trade-off can depend critically on the flexibility of one's social learning strategy. We developed a gene-culture coevolutionary model that allows cognition to encode and process information about the similarity between naive learners and experienced demonstrators. Facultative social learning strategies that condition on perceived similarity evolve under certain circumstances. When this happens, facultative adjustments are often asymmetric. Asymmetric adjustments mean that the tendency to follow the majority when learners perceive demonstrators as similar is stronger than the tendency to follow the minority when learners perceive demonstrators as different. In an associated incentivized experiment, we found that social learners adjusted how they used social information based on perceived similarity, but adjustments were symmetric. The symmetry of adjustments completely eliminated the commonly assumed trade-off between cases in which learners and demonstrators share an optimum versus cases in which they do not. In a second experiment that maximized the potential for social learners to follow their preferred strategies, a few social learners exhibited an inclination to follow the majority. Most, however, did not respond systematically to social information. Additionally, in the complete absence of information about their similarity to demonstrators, social learners were unwilling to make assumptions about whether they shared an optimum with demonstrators. Instead, social learners simply ignored social information even though this was the only information available. Our results suggest that social cognition equips people to use conformity in a discriminating fashion that moderates the evolutionary trade-offs that would occur if conformist social learning was rigidly applied

Bacterial community development in experimental gingivitis.

Current knowledge of the microbial composition of dental plaque in early gingivitis is based largely on microscopy and cultural methods, which do not provide a comprehensive description of oral microbial communities. This study used 454-pyrosequencing of the V1-V3 region of 16S rRNA genes (approximately 500 bp), and bacterial culture, to characterize the composition of plaque during the transition from periodontal health to gingivitis. A total of 20 healthy volunteers abstained from oral hygiene for two weeks, allowing plaque to accumulate and gingivitis to develop. Plaque samples were analyzed at baseline, and after one and two weeks. In addition, plaque samples from 20 chronic periodontitis patients were analyzed for cross-sectional comparison to the experimental gingivitis cohort. All of the healthy volunteers developed gingivitis after two weeks. Pyrosequencing yielded a final total of 344,267 sequences after filtering, with a mean length of 354 bases, that were clustered into an average of 299 species-level Operational Taxonomic Units (OTUs) per sample. Principal coordinates analysis (PCoA) plots revealed significant shifts in the bacterial community structure of plaque as gingivitis was induced, and community diversity increased significantly after two weeks. Changes in the relative abundance of OTUs during the transition from health to gingivitis were correlated to bleeding on probing (BoP) scores and resulted in the identification of new health- and gingivitis-associated taxa. Comparison of the healthy volunteers to the periodontitis patients also confirmed the association of a number of putative periodontal pathogens with chronic periodontitis. Taxa associated with gingivitis included Fusobacterium nucleatum subsp. polymorphum, Lachnospiraceae [G-2] sp. HOT100, Lautropia sp. HOTA94, and Prevotella oulorum, whilst Rothia dentocariosa was associated with periodontal health. Further study of these taxa is warranted and may lead to new therapeutic approaches to prevent periodontal disease.BBSRC Industrial Case Studentship ref no. BB/G01714X/1 in collaboration with GlaxoSmithKline

A Nutrition and Conditioning Intervention for Natural Bodybuilding Contest Preparation: Case Study.

Bodybuilding competitions are becoming increasingly popular. Competitors are judged on their aesthetic appearance and usually exhibit a high level of muscularity and symmetry and low levels of body fat. Commonly used techniques to improve physique during the preparation phase before competitions include dehydration, periods of prolonged fasting, severe caloric restriction, excessive cardiovascular exercise and inappropriate use of diuretics and anabolic steroids. In contrast, this case study documents a structured nutrition and conditioning intervention followed by a 21 year-old amateur bodybuilding competitor to improve body composition, resting and exercise fat oxidation, and muscular strength that does not involve use of any of the above mentioned methods. Over a 14-week period, the Athlete was provided with a scientifically designed nutrition and conditioning plan that encouraged him to (i) consume a variety of foods; (ii) not neglect any macronutrient groups; (iii) exercise regularly but not excessively and; (iv) incorporate rest days into his conditioning regime. This strategy resulted in a body mass loss of 11.7 kg’s, corresponding to a 6.7 kg reduction in fat mass and a 5.0 kg reduction in fat-free mass. Resting metabolic rate decreased from 1993 kcal/d to 1814 kcal/d, whereas resting fat oxidation increased from 0.04 g/min to 0.06 g/min. His capacity to oxidize fat during exercise increased more than two-fold from 0.24 g/min to 0.59 g/min, while there was a near 3-fold increase in the corresponding exercise intensity that elicited the maximal rate of fat oxidation; 21% V̇ O2max to 60% V̇ O2max. Hamstring concentric peak torque decreased (1.7 to 1.5 Nm/kg), whereas hamstring eccentric (2.0 Nm/kg to 2.9 Nm/kg), quadriceps concentric (3.4 Nm/kg to 3.7 Nm/kg) and quadriceps eccentric (4.9 Nm/kg to 5.7 Nm/kg) peak torque all increased. Psychological mood-state (BRUMS scale) was not negatively influenced by the intervention and all values relating to the Athlete’s mood-state remained below average over the course of study. This intervention shows that a structured and scientifically supported nutrition strategy can be implemented to improve parameters relevant to bodybuilding competition and importantly the health of competitors, therefore questioning the conventional practices of bodybuilding preparation

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations

Maturation of GABAergic Inhibition Promotes Strengthening of Temporally Coherent Inputs among Convergent Pathways

Spike-timing-dependent plasticity (STDP), a form of Hebbian plasticity, is inherently stabilizing. Whether and how GABAergic inhibition influences STDP is not well understood. Using a model neuron driven by converging inputs modifiable by STDP, we determined that a sufficient level of inhibition was critical to ensure that temporal coherence (correlation among presynaptic spike times) of synaptic inputs, rather than initial strength or number of inputs within a pathway, controlled postsynaptic spike timing. Inhibition exerted this effect by preferentially reducing synaptic efficacy, the ability of inputs to evoke postsynaptic action potentials, of the less coherent inputs. In visual cortical slices, inhibition potently reduced synaptic efficacy at ages during but not before the critical period of ocular dominance (OD) plasticity. Whole-cell recordings revealed that the amplitude of unitary IPSCs from parvalbumin positive (Pv+) interneurons to pyramidal neurons increased during the critical period, while the synaptic decay time-constant decreased. In addition, intrinsic properties of Pv+ interneurons matured, resulting in an increase in instantaneous firing rate. Our results suggest that maturation of inhibition in visual cortex ensures that the temporally coherent inputs (e.g. those from the open eye during monocular deprivation) control postsynaptic spike times of binocular neurons, a prerequisite for Hebbian mechanisms to induce OD plasticity

Variations in the Difference between Mean Sea Level measured either side of Cape Hatteras and Their Relation to the North Atlantic Oscillation

We consider the extent to which the difference in mean sea level (MSL) measured on the North American Atlantic coast either side of Cape Hatteras varies as a consequence of dynamical changes in the ocean caused by fluctuations in the North Atlantic Oscillation (NAO). From analysis of tide gauge data, we know that changes in MSL-difference and NAO index are correlated on decadal to century timescales enabling a scale factor of MSL-difference change per unit change in NAO index to be estimated. Changes in trend in the NAO index have been small during the past few centuries (when measured using windows of order 60–120 years). Therefore, if the same scale factor applies through this period of time, the corresponding changes in trend in MSL-difference for the past few centuries should also have been small. It is suggested thereby that the sea level records for recent centuries obtained from salt marshes (adjusted for long-term vertical land movements) should have essentially the same NAO-driven trends south and north of Cape Hatteras, only differing due to contributions from other processes such as changes in the Meridional Overturning Circulation or ‘geophysical fingerprints’. The salt marsh data evidently support this interpretation within their uncertainties for the past few centuries, and perhaps even for the past millennium. Recommendations are made on how greater insight might be obtained by acquiring more measurements and by improved modelling of the sea level response to wind along the shelf

Temporal Analysis of the Honey Bee Microbiome Reveals Four Novel Viruses and Seasonal Prevalence of Known Viruses, Nosema, and Crithidia

Honey bees (Apis mellifera) play a critical role in global food production as pollinators of numerous crops. Recently, honey bee populations in the United States, Canada, and Europe have suffered an unexplained increase in annual losses due to a phenomenon known as Colony Collapse Disorder (CCD). Epidemiological analysis of CCD is confounded by a relative dearth of bee pathogen field studies. To identify what constitutes an abnormal pathophysiological condition in a honey bee colony, it is critical to have characterized the spectrum of exogenous infectious agents in healthy hives over time. We conducted a prospective study of a large scale migratory bee keeping operation using high-frequency sampling paired with comprehensive molecular detection methods, including a custom microarray, qPCR, and ultra deep sequencing. We established seasonal incidence and abundance of known viruses, Nosema sp., Crithidia mellificae, and bacteria. Ultra deep sequence analysis further identified four novel RNA viruses, two of which were the most abundant observed components of the honey bee microbiome (∼1011 viruses per honey bee). Our results demonstrate episodic viral incidence and distinct pathogen patterns between summer and winter time-points. Peak infection of common honey bee viruses and Nosema occurred in the summer, whereas levels of the trypanosomatid Crithidia mellificae and Lake Sinai virus 2, a novel virus, peaked in January