Olive phenology as a sensitive indicator of future climatic warming in the Mediterranean

Experimental and modelling work suggests a strong dependence of olive flowering date on spring temperatures. Since airborne pollen concentrations reflect the flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated future temperature simulations for the western Mediterranean from a coupled ocean-atmosphere general circulation model (GCM). The GCM temperatures rose by 4·5 °C between 1990 and 2099 with a 1% per year increase in greenhouse gases, and modelled flowering date advanced at a rate of 6·2 d per °C. The results indicated that this long-term regional trend in phenology might be statistically significant as early as 2030, but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and 2030s advancing by 3–23 d. Future monitoring of airborne olive pollen may therefore provide an early biological indicator of climatic warming in the Mediterranean

Dynamics of Parasite Clearance in Cutaneous Leishmaniasis Patients Treated with Miltefosine

Parasite loads were quantified in repeated skin biopsies from lesions of 2 patients with Old-World cutaneous leishmaniasis (CL) caused by Leishmania major and L. infantum during and after treatment with miltefosine. Miltefosine induced a rapid therapeutic effect on both infections with an initial decline of parasites of ∼1 log/week for the L. major infection. These observations illustrate the usability of quantifying parasite loads in skin lesions as a pharmacodynamic measure and quantitative descriptor of drug effect for CL supporting clinical assessment

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning

Bacillus cereus Spores Release Alanine that Synergizes with Inosine to Promote Germination

spores germinate in the presence of a single germinant, inosine, yet with a significant lag period. spores. spores appear to have developed a unique quorum-sensing feedback mechanism to monitor spore density and to coordinate germination

Whole-genome phylogenies of the family Bacillaceae and expansion of the sigma factor gene family in the Bacillus cereus species-group

<p>Abstract</p> <p>Background</p> <p>The <it>Bacillus cereus </it><it>sensu lato </it>group consists of six species (<it>B. anthracis</it>, <it>B. cereus</it>, <it>B. mycoides</it>, <it>B. pseudomycoides</it>, <it>B. thuringiensis</it>, and <it>B. weihenstephanensis</it>). While classical microbial taxonomy proposed these organisms as distinct species, newer molecular phylogenies and comparative genome sequencing suggests that these organisms should be classified as a single species (thus, we will refer to these organisms collectively as the <it>Bc </it>species-group). How do we account for the underlying similarity of these phenotypically diverse microbes? It has been established for some time that the most rapidly evolving and evolutionarily flexible portions of the bacterial genome are regulatory sequences and transcriptional networks. Other studies have suggested that the sigma factor gene family of these organisms has diverged and expanded significantly relative to their ancestors; sigma factors are those portions of the bacterial transcriptional apparatus that control RNA polymerase recognition for promoter selection. Thus, examining sigma factor divergence in these organisms would concurrently examine both regulatory sequences and transcriptional networks important for divergence. We began this examination by comparison to the sigma factor gene set of <it>B. subtilis</it>.</p> <p>Results</p> <p>Phylogenetic analysis of the <it>Bc </it>species-group utilizing 157 single-copy genes of the family <it>Bacillaceae </it>suggests that several taxonomic revisions of the genus <it>Bacillus </it>should be considered. Within the <it>Bc </it>species-group there is little indication that the currently recognized species form related sub-groupings, suggesting that they are members of the same species. The sigma factor gene family encoded by the <it>Bc </it>species-group appears to be the result of a dynamic gene-duplication and gene-loss process that in previous analyses underestimated the true heterogeneity of the sigma factor content in the <it>Bc </it>species-group.</p> <p>Conclusions</p> <p>Expansion of the sigma factor gene family appears to have preferentially occurred within the extracytoplasmic function (ECF) sigma factor genes, while the primary alternative (PA) sigma factor genes are, in general, highly conserved with those found in <it>B. subtilis</it>. Divergence of the sigma-controlled transcriptional regulons among various members of the <it>Bc </it>species-group likely has a major role in explaining the diversity of phenotypic characteristics seen in members of the <it>Bc </it>species-group.</p

Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning

Characterization in vitro and in vivo of a pandemic H1N1 influenza virus from a fatal case

Pandemic 2009 H1N1 (pH1N1) influenza viruses caused mild symptoms in most infected patients. However, a greater rate of severe disease was observed in healthy young adults and children without co-morbid conditions. Here we tested whether influenza strains displaying differential virulence could be present among circulating pH1N1 viruses. The biological properties and the genotype of viruses isolated from a patient showing mild disease (M) or from a fatal case (F), both without known co-morbid conditions were compared in vitro and in vivo. The F virus presented faster growth kinetics and stronger induction of cytokines than M virus in human alveolar lung epithelial cells. In the murine model in vivo, the F virus showed a stronger morbidity and mortality than M virus. Remarkably, a higher proportion of mice presenting infectious virus in the hearts, was found in F virus-infected animals. Altogether, the data indicate that strains of pH1N1 virus with enhanced pathogenicity circulated during the 2009 pandemic. In addition, examination of chemokine receptor 5 (CCR5) genotype, recently reported as involved in severe influenza virus disease, revealed that the F virus-infected patient was homozygous for the deleted form of CCR5 receptor (CCR5Δ32).Funding Statement: This work was supported by Instituto de Salud Carlos III (Programa especial de investigación sobre la gripe pándemica GR09/0023, GR09/0040, GR09/0039) and Ciber de Enfermedades Respiratorias. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.S

What should an ideal spinal injury classification system consist of? A methodological review and conceptual proposal for future classifications

Since Böhler published the first categorization of spinal injuries based on plain radiographic examinations in 1929, numerous classifications have been proposed. Despite all these efforts, however, only a few have been tested for reliability and validity. This methodological, conceptual review summarizes that a spinal injury classification system should be clinically relevant, reliable and accurate. The clinical relevance of a classification is directly related to its content validity. The ideal content of a spinal injury classification should only include injury characteristics of the vertebral column, is primarily based on the increasingly routinely performed CT imaging, and is clearly distinctive from severity scales and treatment algorithms. Clearly defined observation and conversion criteria are crucial determinants of classification systems’ reliability and accuracy. Ideally, two principle spinal injury characteristics should be easy to discern on diagnostic images: the specific location and morphology of the injured spinal structure. Given the current evidence and diagnostic imaging technology, descriptions of the mechanisms of injury and ligamentous injury should not be included in a spinal injury classification. The presence of concomitant neurologic deficits can be integrated in a spinal injury severity scale, which in turn can be considered in a spinal injury treatment algorithm. Ideally, a validation pathway of a spinal injury classification system should be completed prior to its clinical and scientific implementation. This review provides a methodological concept which might be considered prior to the synthesis of new or modified spinal injury classifications