Arabidopsis Ovate Family Proteins, a Novel Transcriptional Repressor Family, Control Multiple Aspects of Plant Growth and Development

, AtOFP4 has been shown to regulate secondary cell wall formation by interact with KNOTTED1-LIKE HOMEODOMAIN PROTEIN 7 (KNAT7), and AtOFP5 has been shown to regulate the activity of a BEL1-LIKEHOMEODOMAIN 1(BLH1)-KNAT3 complex during early embryo sac development, but little is known about the function of other AtOFPs. genes may also have diverse functions in regulating plant growth and development. Further analysis suggested that AtOFP1 regulates cotyledon development in a postembryonic manner, and global transcript profiling revealed that it suppress the expression of many other genes.Our results showed that AtOFPs function as transcriptional repressors and they regulate multiple aspects of plant growth and development. These results provided the first overview of a previously unknown transcriptional repressor family, and revealed their possible roles in plant growth and development

Large Scale Application of Neural Network Based Semantic Role Labeling for Automated Relation Extraction from Biomedical Texts

To reduce the increasing amount of time spent on literature search in the life sciences, several methods for automated knowledge extraction have been developed. Co-occurrence based approaches can deal with large text corpora like MEDLINE in an acceptable time but are not able to extract any specific type of semantic relation. Semantic relation extraction methods based on syntax trees, on the other hand, are computationally expensive and the interpretation of the generated trees is difficult. Several natural language processing (NLP) approaches for the biomedical domain exist focusing specifically on the detection of a limited set of relation types. For systems biology, generic approaches for the detection of a multitude of relation types which in addition are able to process large text corpora are needed but the number of systems meeting both requirements is very limited. We introduce the use of SENNA (“Semantic Extraction using a Neural Network Architecture”), a fast and accurate neural network based Semantic Role Labeling (SRL) program, for the large scale extraction of semantic relations from the biomedical literature. A comparison of processing times of SENNA and other SRL systems or syntactical parsers used in the biomedical domain revealed that SENNA is the fastest Proposition Bank (PropBank) conforming SRL program currently available. 89 million biomedical sentences were tagged with SENNA on a 100 node cluster within three days. The accuracy of the presented relation extraction approach was evaluated on two test sets of annotated sentences resulting in precision/recall values of 0.71/0.43. We show that the accuracy as well as processing speed of the proposed semantic relation extraction approach is sufficient for its large scale application on biomedical text. The proposed approach is highly generalizable regarding the supported relation types and appears to be especially suited for general-purpose, broad-scale text mining systems. The presented approach bridges the gap between fast, cooccurrence-based approaches lacking semantic relations and highly specialized and computationally demanding NLP approaches

The effectiveness of health appraisal processes currently in addressing health and wellbeing during spatial plan appraisal: a systematic review

<p>Abstract</p> <p>Background</p> <p>Spatial planning affects the built environment, which in turn has the potential to have a significant impact on health, for good or ill. One way of ensuring that spatial plans take due account of health is through the inclusion of health considerations in the statutory and non statutory appraisal processes linked to plan-making processes.</p> <p>Methods</p> <p>A systematic review to identify evaluation studies of appraisals or assessments of plans where health issues were considered from 1987 to 2010.</p> <p>Results</p> <p>A total of 6161 citations were identified: 6069 from electronic databases, 57 fromwebsite searches, with a further 35 citations from grey literature, of which 20 met the inclusion criteria. These 20 citations reported on a total of 135 different case studies: 11 UK HIA; 11 non UK high income countries HIA, 5 UK SEA or other integrated appraisal; 108 non UK high income SEA or other integrated appraisal. All studies were in English. No relevant studies were identified reporting on low or middle income countries.</p> <p>The studies were limited by potential bias (no independent evaluation, with those undertaking the appraisal also responsible for reporting outcomes), lack of detail and a lack of triangulation of results. Health impact assessments generally covered the four specified health domains (physical activity, mental health and wellbeing, environmental health issues such as pollution and noise, injury) more comprehensively than SEA or other integrated appraisals, although mental health and wellbeing was an underdeveloped area. There was no evidence available on the incorporation of health in Sustainability Appraisal, limited evidence that the recommendations from any type of appraisal were implemented, and almost no evidence that the recommendations had led to the anticipated outcomes or improvements in health postulated.</p> <p>Conclusion</p> <p>Research is needed to assess (i) the degree to which statutory plan appraisal processes (SA in the UK) incorporate health; (ii) whether recommendations arising from health appraisal translate into the development process and (iii) whether outcomes are as anticipated.</p

Two Seemingly Homologous Noncoding RNAs Act Hierarchically to Activate glmS mRNA Translation

Small noncoding RNAs (sRNA) can function as posttranscriptional activators of gene expression to regulate stress responses and metabolism. We here describe the mechanisms by which two sRNAs, GlmY and GlmZ, activate the Escherichia coli glmS mRNA, coding for an essential enzyme in amino-sugar metabolism. The two sRNAs, although being highly similar in sequence and structure, act in a hierarchical manner. GlmZ, together with the RNA chaperone, Hfq, directly activates glmS mRNA translation by an anti-antisense mechanism. In contrast, GlmY acts upstream of GlmZ and positively regulates glmS by antagonizing GlmZ RNA inactivation. We also report the first example, to our knowledge, of mRNA expression being controlled by the poly(A) status of a chromosomally encoded sRNA. We show that in wild-type cells, GlmY RNA is unstable due to 3′ end polyadenylation; whereas in an E. coli pcnB mutant defective in RNA polyadenylation, GlmY is stabilized and accumulates, which in turn stabilizes GlmZ and causes GlmS overproduction. Our study reveals hierarchical action of two well-conserved sRNAs in a complex regulatory cascade that controls the glmS mRNA. Similar cascades of noncoding RNA regulators may operate in other organisms

Corpus annotation for mining biomedical events from literature

<p>Abstract</p> <p>Background</p> <p>Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention in the bio-medical domain. For such attempts to succeed, text annotation from the biological point of view is indispensable. However, due to the complexity of the task, semantic annotation has never been tried on a large scale, apart from relatively simple term annotation.</p> <p>Results</p> <p>We have completed a new type of semantic annotation, event annotation, which is an addition to the existing annotations in the GENIA corpus. The corpus has already been annotated with POS (Parts of Speech), syntactic trees, terms, etc. The new annotation was made on half of the GENIA corpus, consisting of 1,000 Medline abstracts. It contains 9,372 sentences in which 36,114 events are identified. The major challenges during event annotation were (1) to design a scheme of annotation which meets specific requirements of text annotation, (2) to achieve biology-oriented annotation which reflect biologists' interpretation of text, and (3) to ensure the homogeneity of annotation quality across annotators. To meet these challenges, we introduced new concepts such as Single-facet Annotation and Semantic Typing, which have collectively contributed to successful completion of a large scale annotation.</p> <p>Conclusion</p> <p>The resulting event-annotated corpus is the largest and one of the best in quality among similar annotation efforts. We expect it to become a valuable resource for NLP (Natural Language Processing)-based TM in the bio-medical domain.</p

A Small RNA Controls Expression of the Chitinase ChiA in Listeria monocytogenes

In recent years, more than 60 small RNAs (sRNAs) have been identified in the gram-positive human pathogen Listeria monocytogenes, but their putative roles and mechanisms of action remain largely unknown. The sRNA LhrA was recently shown to be a post-transcriptional regulator of a single gene, lmo0850, which encodes a small protein of unknown function. LhrA controls the translation and degradation of the lmo0850 mRNA by an antisense mechanism, and it depends on the RNA chaperone Hfq for efficient binding to its target. In the present study, we sought to gain more insight into the functional role of LhrA in L. monocytogenes. To this end, we determined the effects of LhrA on global-wide gene expression. We observed that nearly 300 genes in L. monocytogenes are either positively or negatively affected by LhrA. Among these genes, we identified lmo0302 and chiA as direct targets of LhrA, thus establishing LhrA as a multiple target regulator. Lmo0302 encodes a hypothetical protein with no known function, whereas chiA encodes one of two chitinases present in L. monocytogenes. We show here that LhrA acts as a post-transcriptional regulator of lmo0302 and chiA by interfering with ribosome recruitment, and we provide evidence that both LhrA and Hfq act to down-regulate the expression of lmo0302 and chiA. Furthermore, in vitro binding experiments show that Hfq stimulates the base pairing of LhrA to chiA mRNA. Finally, we demonstrate that LhrA has a negative effect on the chitinolytic activity of L. monocytogenes. In marked contrast to this, we found that Hfq has a stimulating effect on the chitinolytic activity, suggesting that Hfq plays multiple roles in the complex regulatory pathways controlling the chitinases of L. monocytogenes

The governors of school markets? : Local education authorities, school choice and equity in Finland and Sweden

As one of the key elements of the Nordic welfare model, education systems are based on the idea of providing equal educational opportunities, regardless of gender, social class and geographic origin. Since the 1990s, Nordic welfare states have undergone a gradual but wide-ranging transformation towards a more market-based mode of public service delivery. Along this trajectory, the advent of school choice policy and the growing variation in the between-school achievement results have diversified the previously homogenous Nordic education systems. The aim of our paper is to analyse how Finnish and Swedish local education authorities comprehend and respond to the intertwinement of the market logic of school choice and the ideology of equality. The data consist of two sets of in-depth thematic interviews with staff from the local providers of education, municipal education authorities. The analysis discloses the ways in which national legislation has authorized municipal authorities to govern the provision of education.Peer reviewe

Metagenomic identification of severe pneumonia pathogens in mechanically-ventilated patients:a feasibility and clinical validity study

BACKGROUND: Metagenomic sequencing of respiratory microbial communities for pathogen identification in pneumonia may help overcome the limitations of culture-based methods. We examined the feasibility and clinical validity of rapid-turnaround metagenomics with Nanopore™ sequencing of clinical respiratory specimens. METHODS: We conducted a case-control study of mechanically-ventilated patients with pneumonia (nine culture-positive and five culture-negative) and without pneumonia (eight controls). We collected endotracheal aspirates and applied a microbial DNA enrichment method prior to metagenomic sequencing with the Oxford Nanopore MinION device. For reference, we compared Nanopore results against clinical microbiologic cultures and bacterial 16S rRNA gene sequencing. RESULTS: Human DNA depletion enabled in depth sequencing of microbial communities. In culture-positive cases, Nanopore revealed communities with high abundance of the bacterial or fungal species isolated by cultures. In four cases with resistant clinical isolates, Nanopore detected antibiotic resistance genes corresponding to the phenotypic resistance in antibiograms. In culture-negative pneumonia, Nanopore revealed probable bacterial pathogens in 1/5 cases and Candida colonization in 3/5 cases. In controls, Nanopore showed high abundance of oral bacteria in 5/8 subjects, and identified colonizing respiratory pathogens in other subjects. Nanopore and 16S sequencing showed excellent concordance for the most abundant bacterial taxa. CONCLUSIONS: We demonstrated technical feasibility and proof-of-concept clinical validity of Nanopore metagenomics for severe pneumonia diagnosis, with striking concordance with positive microbiologic cultures, and clinically actionable information obtained from sequencing in culture-negative samples. Prospective studies with real-time metagenomics are warranted to examine the impact on antimicrobial decision-making and clinical outcomes