A single evolutionary innovation drives the deep evolution of symbiotic N₂-fixation in angiosperms

Symbiotic associations occur in every habitat on earth, but we know very little about their evolutionary histories. Current models of trait evolution cannot adequately reconstruct the deep history of symbiotic innovation, because they assume homogenous evolutionary processes across millions of years. Here we use a recently developed, heterogeneous and quantitative phylogenetic framework to study the origin of the symbiosis between angiosperms and nitrogen-fixing (N2) bacterial symbionts housed in nodules. We compile the largest database of global nodulating plant species and reconstruct the symbiosis’ evolution. We identify a single, cryptic evolutionary innovation driving symbiotic N2-fixation evolution, followed by multiple gains and losses of the symbiosis, and the subsequent emergence of ‘stable fixers’ (clades extremely unlikely to lose the symbiosis). Originating over 100 MYA, this innovation suggests deep homology in symbiotic N2-fixation. Identifying cryptic innovations on the tree of life is key to understanding the evolution of complex traits, including symbiotic partnerships

Experiences of Self-Management Support Following a Stroke: A Meta-Review of Qualitative Systematic Reviews

Supporting self-management in stroke patients improves psychological and functional outcomes but evidence on how to achieve this is sparse. We aimed to synthesise evidence from systematic reviews of qualitative studies in an overarching meta-review to inform the delivery and development of self-management support interventions.We systematically searched eight electronic databases including MEDLINE, EMBASE and CINAHL for qualitative systematic reviews (published January 1993 to June 2012). We included studies exploring patients', carers' or health care professionals' experiences relevant to self-management support following a stroke, including studies describing the lived experience of surviving a stroke. We meta-synthesised the included review findings using a meta-ethnographic framework.Seven reviews, reporting 130 unique studies, were included. Themes emerging from the reviews were pertinent, consistent and showed data saturation; though explicit mention of self-management support was rare. Our meta-review highlighted the devastating impact of stroke on patients' self-image; the varying needs for self-management support across the trajectory of recovery; the need for psychological and emotional support throughout recovery particularly when physical recovery plateaus; the considerable information needs of patients and carers which also vary across the trajectory of recovery; the importance of good patient-professional communication; the potential benefits of goal-setting and action-planning; and the need for social support which might be met by groups for stroke survivors.The observed data saturation suggests that, currently, no further qualitative research simply describing the lived experience of stroke is needed; we propose that it would be more useful to focus on qualitative research informing self-management support interventions and their implementation. Our findings demonstrate both the on-going importance of self-management support and the evolving priorities throughout the stages of recovery following a stroke. The challenge now is to ensure these findings inform routine practice and the development of interventions to support self-management amongst stroke survivors

Induction of effective and antigen-specific antitumour immunity by a liposomal ErbB2/HER2 peptide-based vaccination construct

Efficient delivery of tumour-associated antigens to appropriate cellular compartments of antigen-presenting cells is of prime importance for the induction of potent, cell-mediated antitumour immune responses. We have designed novel multivalent liposomal constructs that co-deliver the p63–71 cytotoxic T Lymphocyte epitope derived from human ErbB2 (HER2), and HA307–319, a T-helper (Th) epitope derived from influenza haemagglutinin. Both peptides were conjugated to the surface of liposomes via a Pam3CSS anchor, a synthetic lipopeptide with potent adjuvant activity. In a murine model system, vaccination with these constructs completely protected BALB/c mice from subsequent s.c. challenge with ErbB2-expressing, but not ErbB2-negative, murine renal carcinoma (Renca) cells, indicating the induction of potent, antigen-specific immune responses. I.v. re-challenge of tumour-free animals 2 months after the first tumour cell inoculation did not result in the formation of lung tumour nodules, suggesting that long-lasting, systemic immunity had been induced. While still protecting the majority of vaccinated mice, a liposomal construct lacking the Th epitope was less effective than the diepitope construct, also correlating with a lower number of CD8+ IFN-γ+ T-cells identified upon ex vivo peptide restimulation of splenocytes from vaccinated animals. Importantly, in a therapeutic setting treatment with the liposomal vaccines resulted in cures in the majority of tumour-bearing mice and delayed tumour growth in the remaining ones. Our results demonstrate that liposomal constructs which combine Tc and Th peptide antigens and lipopeptide adjuvants can induce efficient, antigen-specific antitumour immunity, and represent promising synthetic delivery systems for the design of specific antitumour vaccines

Cross-cultural dataset for the evolution of religion and morality project

A considerable body of research cross-culturally examines the evolution of religious traditions, beliefs and behaviors. The bulk of this research, however, draws from coded qualitative ethnographies rather than from standardized methods specifically designed to measure religious beliefs and behaviors. Psychological data sets that examine religious thought and behavior in controlled conditions tend to be disproportionately sampled from student populations. Some cross-national databases employ standardized methods at the individual level, but are primarily focused on fully market integrated, state-level societies. The Evolution of Religion and Morality Project sought to generate a data set that systematically probed individual level measures sampling across a wider range of human populations. The set includes data from behavioral economic experiments and detailed surveys of demographics, religious beliefs and practices, material security, and intergroup perceptions. This paper describes the methods and variables, briefly introduces the sites and sampling techniques, notes inconsistencies across sites, and provides some basic reporting for the data set

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality

Manifold covering theory in biomimetic pattern recognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite manifold covering in biomimetic pattern recognition, and study its property. Furthermore, we propose this manifold covering algorithm based on Biomimetic Pattern Recognition. At last, the experimental results for face recognition demonstrates that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective

Mandarin speech emotion recognition based on high dimensional geometry theory

In this paper, a novel approach for mandarin speech emotion recognition, that is mandarin speech emotion recognition based on high dimensional geometry theory, is proposed. The human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. According to the characteristics of these emotional speech signals, the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. The new method called high dimensional geometry theory is applied for recognition. Compared with traditional GSVM model, the new method has some advantages. It is noted that this method has significant values for researches and applications henceforth

Cancer subtypes recognition and its gene expression profiles analysis based on geometrical learning

The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility

Finite element analysis of stress and strain distributions in InAs/GaAs quantum dots

In this paper, we perform systematic calculations of the stress and strain distributions in InAs/GaAs truncated pyramidal quantum dots (QDs) with different wetting layer (WL) thickness, using the finite element method (FEM). The stresses and strains are concentrated at the boundaries of the WL and QDs, are reduced gradually from the boundaries to the interior, and tend to a uniform state for the positions away from the boundaries. The maximal strain energy density occurs at the vicinity of the interface between the WL and the substrate. The stresses, strains and released strain energy are reduced gradually with increasing WL thickness. The above results show that a critical WL thickness may exist, and the stress and strain distributions can make the growth of QDs a growth of strained three-dimensional island when the WL thickness is above the critical value, and FEM can be applied to investigate such nanosystems, QDs, and the relevant results are supported by the experiments