Environmental stress alters genetic regulation of novelty seeking in vervet monkeys.

Considerable attention has been paid to identifying genetic influences and gene-environment interactions that increase vulnerability to environmental stressors, with promising but inconsistent results. A nonhuman primate model is presented here that allows assessment of genetic influences in response to a stressful life event for a behavioural trait with relevance for psychopathology. Genetic and environmental influences on free-choice novelty seeking behaviour were assessed in a pedigreed colony of vervet monkeys before and after relocation from a low stress to a higher stress environment. Heritability of novelty seeking scores, and genetic correlations within and between environments were conducted using variance components analysis. The results showed that novelty seeking was markedly inhibited in the higher stress environment, with effects persisting across a 2-year period for adults but not for juveniles. There were significant genetic contributions to novelty seeking scores in each year (h(2) = 0.35-0.43), with high genetic correlations within each environment (rhoG > 0.80) and a lower genetic correlation (rhoG = 0.35, non-significant) between environments. There were also significant genetic contributions to individual change scores from before to after the move (h(2) = 0.48). These results indicate that genetic regulation of novelty seeking was modified by the level of environmental stress, and they support a role for gene-environment interactions in a behavioural trait with relevance for mental health

How to democratize Internet of Things devices. A participatory design research

The global introduction of affordable Internet of Things (IoT) devices offers an opportunity to empower a large variety of users with different needs. However, many off-the-shelf digital products are still not widely adopted by people who are hesitant technology users or by older adults, notwithstanding that the design and user-interaction of these devices is recognized to be user-friendly. In view of the potential of IoT-based devices, how can we reduce the obstacles of a cohort with low digital literacy and technology anxiety and enable them to be equal participants in the digitalized world? This article shows the method and results achieved in a community-stakeholder workshop, developed through the participatory design methodology, aiming at brainstorming problems and scenarios through a focus group and a structured survey. The research activity focused on understanding factors to increase the usability of off-the-shelf IoT devices for hesitant users and identify strategies for improving digital literacy and reducing technology anxiety. A notable result was a series of feedback items pointing to the importance of creating learning resources to support individuals with different abilities, age, gender expression, to better adopt off-the-shelf IoT-based solutions.Comment: 8 pages, 5 figure

An exact expression to calculate the derivatives of position-dependent observables in molecular simulations with flexible constraints

In this work, we introduce an algorithm to compute the derivatives of physical observables along the constrained subspace when flexible constraints are imposed on the system (i.e., constraints in which the hard coordinates are fixed to configuration-dependent values). The presented scheme is exact, it does not contain any tunable parameter, and it only requires the calculation and inversion of a sub-block of the Hessian matrix of second derivatives of the function through which the constraints are defined. We also present a practical application to the case in which the sought observables are the Euclidean coordinates of complex molecular systems, and the function whose minimization defines the constraints is the potential energy. Finally, and in order to validate the method, which, as far as we are aware, is the first of its kind in the literature, we compare it to the natural and straightforward finite-differences approach in three molecules of biological relevance: methanol, N-methyl-acetamide and a tri-glycine peptideComment: 13 pages, 8 figures, published versio

The effect of S-substitution at the O6-guanine site on the structure and dynamics of a DNA oligomer containing a G:T mismatch

The effect of S-substitution on the O6 guanine site of a 13-mer DNA duplex containing a G:T mismatch is studied using molecular dynamics. The structure, dynamic evolution and hydration of the S-substituted duplex are compared with those of a normal duplex, a duplex with Ssubstitution on guanine, but no mismatch and a duplex with just a G:T mismatch. The S-substituted mismatch leads to cell death rather than repair. One suggestion is that the G:T mismatch recognition protein recognises the S-substituted mismatch (GS:T) as G:T. This leads to a cycle of futile repair ending in DNA breakage and cell death. We find that some structural features of the helix are similar for the duplex with the G:T mismatch and that with the S-substituted mismatch, but differ from the normal duplex, notably the helical twist. These differences arise from the change in the hydrogen-bonding pattern of the base pair. However a marked feature of the S-substituted G:T mismatch duplex is a very large opening. This showed considerable variability. It is suggested that this enlarged opening would lend support to an alternative model of cell death in which the mismatch protein attaches to thioguanine and activates downstream damage-response pathways. Attack on the sulphur by reactive oxygen species, also leading to cell death, would also be aided by the large, variable opening

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

Background: Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. Methods: This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. Results: The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. Conclusions: In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it

Optimizing Optical Flow Cytometry for Cell Volume-Based Sorting and Analysis

Cell size is a defining characteristic central to cell function and ultimately to tissue architecture. The ability to sort cell subpopulations of different sizes would facilitate investigation at genomic and proteomic levels of mechanisms by which cells attain and maintain their size. Currently available cell sorters, however, cannot directly measure cell volume electronically, and it would therefore be desirable to know which of the optical measurements that can be made in such instruments provide the best estimate of volume. We investigated several different light scattering and fluorescence measurements in several different cell lines, sorting cell fractions from the high and low end of distributions, and measuring volume electronically to determine which sorting strategy yielded the best separated volume distributions. Since we found that different optical measurements were optimal for different cell lines, we suggest that following this procedure will enable other investigators to optimize their own cell sorters for volume-based separation of the cell types with which they work

Eradication of chronic myeloid leukemia stem cells: a novel mathematical model predicts no therapeutic benefit of adding G-CSF to imatinib

Imatinib mesylate induces complete cytogenetic responses in patients with chronic myeloid leukemia (CML), yet many patients have detectable BCR-ABL transcripts in peripheral blood even after prolonged therapy. Bone marrow studies have shown that this residual disease resides within the stem cell compartment. Quiescence of leukemic stem cells has been suggested as a mechanism conferring insensitivity to imatinib, and exposure to the Granulocyte-Colony Stimulating Factor (G-CSF), together with imatinib, has led to a significant reduction in leukemic stem cells in vitro. In this paper, we design a novel mathematical model of stem cell quiescence to investigate the treatment response to imatinib and G-CSF. We find that the addition of G-CSF to an imatinib treatment protocol leads to observable effects only if the majority of leukemic stem cells are quiescent; otherwise it does not modulate the leukemic cell burden. The latter scenario is in agreement with clinical findings in a pilot study administering imatinib continuously or intermittently, with or without G-CSF (GIMI trial). Furthermore, our model predicts that the addition of G-CSF leads to a higher risk of resistance since it increases the production of cycling leukemic stem cells. Although the pilot study did not include enough patients to draw any conclusion with statistical significance, there were more cases of progression in the experimental arms as compared to continuous imatinib. Our results suggest that the additional use of G-CSF may be detrimental to patients in the clinic

Adaptation of gastrointestinal nematode parasites to host genotype: single locus simulation models

Background: Breeding livestock for improved resistance to disease is an increasingly important selection goal. However, the risk of pathogens adapting to livestock bred for improved disease resistance is difficult to quantify. Here, we explore the possibility of gastrointestinal worms adapting to sheep bred for low faecal worm egg count using computer simulation. Our model assumes sheep and worm genotypes interact at a single locus, such that the effect of an A allele in sheep is dependent on worm genotype, and the B allele in worms is favourable for parasitizing the A allele sheep but may increase mortality on pasture. We describe the requirements for adaptation and test if worm adaptation (1) is slowed by non-genetic features of worm infections and (2) can occur with little observable change in faecal worm egg count. Results: Adaptation in worms was found to be primarily influenced by overall worm fitness, viz. the balance between the advantage of the B allele during the parasitic stage in sheep and its disadvantage on pasture. Genetic variation at the interacting locus in worms could be from de novo or segregating mutations, but de novo mutations are rare and segregating mutations are likely constrained to have (near) neutral effects on worm fitness. Most other aspects of the worm infection we modelled did not affect the outcomes. However, the host-controlled mechanism to reduce faecal worm egg count by lowering worm fecundity reduced the selection pressure on worms to adapt compared to other mechanisms, such as increasing worm mortality. Temporal changes in worm egg count were unreliable for detecting adaptation, despite the steady environment assumed in the simulations. Conclusions: Adaptation of worms to sheep selected for low faecal worm egg count requires an allele segregating in worms that is favourable in animals with improved resistance but less favourable in other animals. Obtaining alleles with this specific property seems unlikely. With support from experimental data, we conclude that selection for low faecal worm egg count should be stable over a short time frame (e.g. 20 years). We are further exploring model outcomes with multiple loci and comparing outcomes to other control strategies

A Molecular Study on the Prevalence and Virulence Potential of Aeromonas spp. Recovered from Patients Suffering from Diarrhea in Israel

Background: Species of the genus Aeromonas are native inhabitants of aquatic environments and have recently been considered emerging human pathogens. Although the gastrointestinal tract is by far the most common anatomic site from which aeromonads are recovered, their role as etiologic agents of bacterial diarrhea is still disputed. Aeromonas-associated diarrhea is a phenomenon occurring worldwide; however, the exact prevalence of Aeromonas infections on a global scale is unknown. Methodology/Principal Findings: The prevalence and virulence potential of Aeromonas in patients suffering from diarrhea in Israel was studied using molecular methods. 1,033 diarrheal stools were sampled between April and September 2010 and Aeromonas species were identified in 17 (,2%) patients by sequencing the rpoD gene. Aeromonas species identity and abundance was: A. caviae (65%), A. veronii (29%) and Aeromonas taiwanensis (6%). This is the first clinical record of A. taiwanensis as a diarrheal causative since its recent discovery from a wound infection in a patient in Taiwan. Most of the patients (77%) from which Aeromonas species were isolated were negative for any other pathogens. The patients ranged from 1 to 92 years in age. Aeromonas isolates were found to possess different virulence-associated genes: ahpB (88%), pla/ lip/lipH3/apl-1 (71%), act/hlyA/aerA (35%), alt (18%), ast (6%), fla (65%), lafA (41%), TTSS ascV (12%), TTSS ascF-ascG (12%), TTSS-dependent ADP-ribosylating toxins aexU (41%) and aexT (6%) in various combinations. Most of the identified strain