Molecular phylogeny of the subfamily Stevardiinae Gill, 1858 (Characiformes: Characidae): classification and the evolution of reproductive traits

Abstract Background The subfamily Stevardiinae is a diverse and widely distributed clade of freshwater fishes from South and Central America, commonly known as “tetras” (Characidae). The group was named “clade A” when first proposed as a monophyletic unit of Characidae and later designated as a subfamily. Stevardiinae includes 48 genera and around 310 valid species with many species presenting inseminating reproductive strategy. No global hypothesis of relationships is available for this group and currently many genera are listed as incertae sedis or are suspected to be non-monophyletic. Results We present a molecular phylogeny with the largest number of stevardiine species analyzed so far, including 355 samples representing 153 putative species distributed in 32 genera, to test the group’s monophyly and internal relationships. The phylogeny was inferred using DNA sequence data from seven gene fragments (mtDNA: 12S, 16S and COI; nuclear: RAG1, RAG2, MYH6 and PTR). The results support the Stevardiinae as a monophyletic group and a detailed hypothesis of the internal relationships for this subfamily. Conclusions A revised classification based on the molecular phylogeny is proposed that includes seven tribes and also defines monophyletic genera, including a resurrected genus Eretmobrycon, and new definitions for Diapoma, Hemibrycon, Bryconamericus sensu stricto, and Knodus sensu stricto, placing some small genera as junior synonyms. Inseminating species are distributed in several clades suggesting that reproductive strategy is evolutionarily labile in this group of fishes.http://deepblue.lib.umich.edu/bitstream/2027.42/134621/1/12862_2015_Article_403.pd

A Visual Data Mining Tool that Facilitates Reconstruction of Transcription Regulatory Networks

Background: Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clustering methods can be used to identify groups of genes with similar expression patterns, and genes with unknown function can be provisionally annotated based on the concept of ‘‘guilt by association’’, where function is tentatively inferred from the known functions of genes with similar expression patterns. These methods frequently suffer from two limitations: (1) visualization usually only gives access to group membership, rather than specific information about nearest neighbors, and (2) the resolution or quality of the relationships are not easily inferred. Methodology/Principal Findings: We have addressed these issues by improving the precision of similarity detection over that of a single experiment and by creating a tool to visualize tractable association networks: we (1) performed metaanalysis computation of correlation coefficients for all gene pairs in a heterogeneous data set collected from 2,145 publicly available micorarray samples in mouse, (2) filtered the resulting distribution of over 130 million correlation coefficients to build new, more tractable distributions from the strongest correlations, and (3) designed and implemented a new Web based tool (StarNet

LOVTRAP: an optogenetic system for photoinduced protein dissociation

Here we introduce LOVTRAP, an optogenetic approach for reversible, light-induced protein dissociation. LOVTRAP is based on protein A fragments that bind to the LOV domain only in the dark, with tunable kinetics and a >150-fold change in Kd. By reversibly sequestering proteins at mitochondria, we precisely modulated the proteins’ access to the cell edge, demonstrating a naturally occurring 3 mHz cell edge oscillation driven by interactions of Vav2, Rac1 and PI3K

Replication and Virus-Induced Transcriptome of HAdV-5 in Normal Host Cells versus Cancer Cells - Differences of Relevance for Adenoviral Oncolysis

Adenoviruses (Ads), especially HAdV-5, have been genetically equipped with tumor-restricted replication potential to enable applications in oncolytic cancer therapy. Such oncolytic adenoviruses have been well tolerated in cancer patients, but their anti-tumor efficacy needs to be enhanced. In this regard, it should be considered that cancer cells, dependent on their tissue of origin, can differ substantially from the normal host cells to which Ads are adapted by complex virus-host interactions. Consequently, viral replication efficiency, a key determinant of oncolytic activity, might be suboptimal in cancer cells. Therefore, we have analyzed both the replication kinetics of HAdV-5 and the virus-induced transcriptome in human bronchial epithelial cells (HBEC) in comparison to cancer cells. This is the first report on genome-wide expression profiling of Ads in their native host cells. We found that E1A expression and onset of viral genome replication are most rapid in HBEC and considerably delayed in melanoma cells. In squamous cell lung carcinoma cells, we observed intermediate HAdV-5 replication kinetics. Infectious particle production, viral spread and lytic activity of HAdV-5 were attenuated in melanoma cells versus HBEC. Expression profiling at the onset of viral genome replication revealed that HAdV-5 induced the strongest changes in the cellular transcriptome in HBEC, followed by lung cancer and melanoma cells. We identified prominent regulation of genes involved in cell cycle and DNA metabolism, replication and packaging in HBEC, which is in accord with the necessity to induce S phase for viral replication. Strikingly, in melanoma cells HAdV-5 triggered opposing regulation of said genes and, in contrast to lung cancer cells, no weak S phase induction was detected when using the E2F promoter as reporter. Our results provide a rationale for improving oncolytic adenoviruses either by adaptation of viral infection to target tumor cells or by modulating tumor cell functions to better support viral replication

Active learning and optimal climate policy

This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education

Sonification and Music as Support to the Communication of Alcohol-Related Health Risks to Young People : Study design and results

Excessive consumption of alcohol has been recognised as a significant risk factor impacting the health of young people. Effective communication of such risk is considered to be one key step to improve behaviour. We evaluated an innovative multimedia intervention that utilised audio (sonification—using sound to display data—and music) and interactivity to support the visual communication of alcohol health risk data. A 3-arm pilot experiment was undertaken. The trial measures included health knowledge, alcohol risk perception and user experience of the intervention. Ninety-six subjects participated in the experiment. At 1 month follow-up, alcohol knowledge and alcohol risk perception improved significantly in the whole sample. However, there was no difference between the intervention groups that experienced (1) visual presentation with interactivity (VI-Exp group) and, (2) visual presentation with audio (sonification and music) and interactivity (VAI-Exp group), when compared to the control group which experienced a (3) visual only presentation (V-Cont group). Participants reported enjoying the presentations and found them educational. The majority of participants indicated that the audio, music and sonification helped to convey the information well, and, although a larger sample size is needed to fully establish the effectiveness of the different interventions, this study provides a useful model for future similar studies

Deaminase-Independent Inhibition of Parvoviruses by the APOBEC3A Cytidine Deaminase

The APOBEC3 proteins form a multigene family of cytidine deaminases with inhibitory activity against viruses and retrotransposons. In contrast to APOBEC3G (A3G), APOBEC3A (A3A) has no effect on lentiviruses but dramatically inhibits replication of the parvovirus adeno-associated virus (AAV). To study the contribution of deaminase activity to the antiviral activity of A3A, we performed a comprehensive mutational analysis of A3A. By mutation of non-conserved residues, we found that regions outside of the catalytic active site contribute to both deaminase and antiviral activities. Using A3A point mutants and A3A/A3G chimeras, we show that deaminase activity is not required for inhibition of recombinant AAV production. We also found that deaminase-deficient A3A mutants block replication of both wild-type AAV and the autonomous parvovirus minute virus of mice (MVM). In addition, we identify specific residues of A3A that confer activity against AAV when substituted into A3G. In summary, our results demonstrate that deaminase activity is not necessary for the antiviral activity of A3A against parvoviruses

Previous Lung Diseases and Lung Cancer Risk: A Systematic Review and Meta-Analysis

In order to review the epidemiologic evidence concerning previous lung diseases as risk factors for lung cancer, a meta-analysis and systematic review was conducted.Relevant studies were identified through MEDLINE searches. Using random effects models, summary effects of specific previous conditions were evaluated separately and combined. Stratified analyses were conducted based on smoking status, gender, control sources and continent.A previous history of COPD, chronic bronchitis or emphysema conferred relative risks (RR) of 2.22 (95% confidence interval (CI): 1.66, 2.97) (from 16 studies), 1.52 (95% CI: 1.25, 1.84) (from 23 studies) and 2.04 (95% CI: 1.72, 2.41) (from 20 studies), respectively, and for all these diseases combined 1.80 (95% CI: 1.60, 2.11) (from 39 studies). The RR of lung cancer for subjects with a previous history of pneumonia was 1.43 (95% CI: 1.22-1.68) (from 22 studies) and for subjects with a previous history of tuberculosis was 1.76 (95% CI=1.49, 2.08), (from 30 studies). Effects were attenuated when restricting analysis to never smokers only for COPD/emphysema/chronic bronchitis (RR=1.22, 0.97-1.53), however remained significant for pneumonia 1.36 (95% CI: 1.10, 1.69) (from 8 studies) and tuberculosis 1.90 (95% CI: 1.45, 2.50) (from 11 studies).Previous lung diseases are associated with an increased risk of lung cancer with the evidence among never smokers supporting a direct relationship between previous lung diseases and lung cancer

Is Cortisol Excretion Independent of Menstrual Cycle Day? A Longitudinal Evaluation of First Morning Urinary Specimens

Background Cortisol is frequently used as a marker of physiologic stress levels. Using cortisol for that purpose, however, requires a thorough understanding of its normal longitudinal variability. The current understanding of longitudinal variability of basal cortisol secretion in women is very limited. It is often assumed, for example, that basal cortisol profiles do not vary across the menstrual cycle. This is a critical assumption: if cortisol were to follow a time dependent pattern during the menstrual cycle, then ignoring this cyclic variation could lead to erroneous imputation of physiologic stress. Yet, the assumption that basal cortisol levels are stable across the menstrual cycle rests on partial and contradictory evidence. Here we conduct a thorough test of that assumption using data collected for up to a year from 25 women living in rural Guatemala. Methodology We apply a linear mixed model to describe longitudinal first morning urinary cortisol profiles, accounting for differences in both mean and standard deviation of cortisol among women. To that aim we evaluate the fit of two alternative models. The first model assumes that cortisol does not vary with menstrual cycle day. The second assumes that cortisol mean varies across the menstrual cycle. Menstrual cycles are aligned on ovulation day (day 0). Follicular days are assigned negative numbers and luteal days positive numbers. When we compared Models 1 and 2 restricting our analysis to days between −14 (follicular) and day 14 (luteal) then day of the menstrual cycle did not emerge as a predictor of urinary cortisol levels (p-value >0.05). Yet, when we extended our analyses beyond that central 28-day-period then day of the menstrual cycle become a statistically significant predictor of cortisol levels. Significance The observed trend suggests that studies including cycling women should account for day dependent variation in cortisol in cycles with long follicular and luteal phases

Scientometric Analysis and Combined Density-Equalizing Mapping of Environmental Tobacco Smoke (ETS) Research

Background: Passive exposure to environmental tobacco smoke (ETS) is estimated to exert a major burden of disease. Currently, numerous countries have taken legal actions to protect the population against ETS. Numerous studies have been conducted in this field. Therefore, scientometric methods should be used to analyze the accumulated data since there is no such approach available so far. Methods and Results: A combination of scientometric methods and novel visualizing procedures were used, including density-equalizing mapping and radar charting techniques. 6,580 ETS-related studies published between 1900 and 2008 were identified in the ISI database. Using different scientometric approaches, a continuous increase of both quantitative and qualitative parameters was found. The combination with density-equalizing calculations demonstrated a leading position of the United States (2,959 items published) in terms of quantitative research activities. Charting techniques demonstrated that there are numerous bi- and multilateral networks between different countries and institutions in this field. Again, a leading position of American institutions was found. Conclusions: This is the first comprehensive scientometric analysis of data on global scientific activities in the field o