The early evolution of land plants, from fossils to genomics: a commentary on Lang (1937) ‘On the plant-remains from the Downtonian of England and Wales'

© 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. The file attached is the published version of the article

Impaired glucose tolerance in adults with Duchenne and Becker muscular dystrophy

The aim of this study was to determine the response to an oral glucose tolerance test (OGTT) in adult males with Becker muscular dystrophy (BMD) and Duchenne muscular dystrophy (DMD), and to investigate whether body composition contributes to any variance in the glucose response. Twenty-eight adult males with dystrophinopathy (BMD, n = 13; DMD, n = 15) and 12 non-dystrophic controls, ingested 75 g oral anhydrous glucose solution. Fingertip capillary samples were assessed for glucose at 30-min intervals over 2-h post glucose ingestion. Fat free mass relative to body mass (FFM/BM) and body fat (BF%) was assessed using bioelectrical impedance. Vastus lateralis muscle anatomical cross sectional area (VL ACSA) was measured using B-mode ultrasonography. Blood glucose was higher in MD groups than control at 60, 90 and 120 min post ingestion of glucose. Compared to controls, FFM/BM and VL ACSA were lower in MD groups compared to controls (p < 0.001). Glucose tolerance values at 120 min were correlated with FFM/BM and BF% in the BMD group only. Our results suggest that glucose tolerance is impaired following OGTT in adult males with BMD and DMD. It is recommended that adults with BMD and DMD undertake routine glucose tolerance assessments to allow early detection of impaired glucose tolerance

Effects of comorbidities on quality of life in Filipino people with tuberculosis.

BACKGROUND: We investigated health-related quality of life (HrQoL) in Filipino people undergoing TB treatment, and whether HrQoL was negatively impacted by comorbidity with undernutrition, diabetes (DM) and anaemia.METHODS: Adult participants were enrolled in public facilities in Metro Manila (three sites) and Negros Occidental (two sites). Multivariate linear regression was used to model the four correlated domain scores from a WHOQOL-BREF questionnaire (physical, psychological, social, environmental). A forward-stepwise approach was used to select a final multivariable model with inclusion based on global tests of significance at P < 0.1.RESULTS: In 446 people on drug-susceptible TB treatment, DM and moderate/severe anaemia were not associated with HrQoL. After adjustment for age, sex, education, food insecurity, treatment adherence, inflammation, Category I or II TB treatment, treatment phase, current side effects and inhibited ability to work, moderate/severe undernutrition (body mass index < 17 kg/m²) was associated with lower HrQoL (P = 0.003) with reduced psychological (coefficient: -1.02, 95% CI -1.54 to -0.51), physical (-0.62, 95% CI -1.14 to -0.09) and environmental domain scores (-0.45, 95% CI -0.88 to -0.01). In 225 patients with known HIV status in Metro Manila, HIV was associated with modestly reduced HrQoL (P = 0.014).CONCLUSION: Nutritional status and food insecurity represent modifiable risk factors for poor HrQoL that may be alleviated through interventions

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

ALONE: A Dataset for Toxic Behavior among Adolescents on Twitter

The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting mental health and, in some cases, resulting in suicide. These communications exhibit complex linguistic and contextual characteristics, making recognition of such narratives challenging. In this paper, we provide a multimodal dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr), along with descriptive explanation. Each instance of interaction includes tweets, images, emoji and related metadata. Our observations show that individual tweets do not provide sufficient evidence for toxic behavior, and meaningful use of context in interactions can enable highlighting or exonerating tweets with purported toxicity.Comment: Accepted: Social Informatics 202

Maternal corticotropin-releasing hormone is associated with LEP DNA methylation at birth and in childhood: an epigenome-wide study in Project Viva

BackgroundCorticotropin-releasing hormone (CRH) plays a central role in regulating the secretion of cortisol which controls a wide range of biological processes. Fetuses overexposed to cortisol have increased risks of disease in later life. DNA methylation may be the underlying association between prenatal cortisol exposure and health effects. We investigated associations between maternal CRH levels and epigenome-wide DNA methylation of cord blood in offsprings and evaluated whether these associations persisted into mid-childhood.MethodsWe investigated mother-child pairs enrolled in the prospective Project Viva pre-birth cohort. We measured DNA methylation in 257 umbilical cord blood samples using the HumanMethylation450 Bead Chip. We tested associations of maternal CRH concentration with cord blood cells DNA methylation, adjusting the model for maternal age at enrollment, education, maternal race/ethnicity, maternal smoking status, pre-pregnancy body mass index, parity, gestational age at delivery, child sex, and cell-type composition in cord blood. We further examined the persistence of associations between maternal CRH levels and DNA methylation in children's blood cells collected at mid-childhood (n = 239, age: 6.7-10.3 years) additionally adjusting for the children's age at blood drawn.ResultsMaternal CRH levels are associated with DNA methylation variability in cord blood cells at 96 individual CpG sites (False Discovery Rate &lt;0.05). Among the 96 CpG sites, we identified 3 CpGs located near the LEP gene. Regional analyses confirmed the association between maternal CRH and DNA methylation near LEP. Moreover, higher maternal CRH levels were associated with higher blood-cell DNA methylation of the promoter region of LEP in mid-childhood (P &lt; 0.05, β = 0.64, SE = 0.30).ConclusionIn our cohort, maternal CRH was associated with DNA methylation levels in newborns at multiple loci, notably in the LEP gene promoter. The association between maternal CRH and LEP DNA methylation levels persisted into mid-childhood

Assessing Internet addiction using the parsimonious Internet addiction components model - a preliminary study [forthcoming]

Internet usage has grown exponentially over the last decade. Research indicates that excessive Internet use can lead to symptoms associated with addiction. To date, assessment of potential Internet addiction has varied regarding populations studied and instruments used, making reliable prevalence estimations difficult. To overcome the present problems a preliminary study was conducted testing a parsimonious Internet addiction components model based on Griffiths’ addiction components (2005), including salience, mood modification, tolerance, withdrawal, conflict, and relapse. Two validated measures of Internet addiction were used (Compulsive Internet Use Scale [CIUS], Meerkerk et al., 2009, and Assessment for Internet and Computer Game Addiction Scale [AICA-S], Beutel et al., 2010) in two independent samples (ns = 3,105 and 2,257). The fit of the model was analysed using Confirmatory Factor Analysis. Results indicate that the Internet addiction components model fits the data in both samples well. The two sample/two instrument approach provides converging evidence concerning the degree to which the components model can organize the self-reported behavioural components of Internet addiction. Recommendations for future research include a more detailed assessment of tolerance as addiction component

METANNOGEN: compiling features of biochemical reactions needed for the reconstruction of metabolic networks

BACKGROUND: One central goal of computational systems biology is the mathematical modelling of complex metabolic reaction networks. The first and most time-consuming step in the development of such models consists in the stoichiometric reconstruction of the network, i. e. compilation of all metabolites, reactions and transport processes relevant to the considered network and their assignment to the various cellular compartments. Therefore an information system is required to collect and manage data from different databases and scientific literature in order to generate a metabolic network of biochemical reactions that can be subjected to further computational analyses. RESULTS: The computer program METANNOGEN facilitates the reconstruction of metabolic networks. It uses the well-known database of biochemical reactions KEGG of biochemical reactions as primary information source from which biochemical reactions relevant to the considered network can be selected, edited and stored in a separate, user-defined database. Reactions not contained in KEGG can be entered manually into the system. To aid the decision whether or not a reaction selected from KEGG belongs to the considered network METANNOGEN contains information of SWISSPROT and ENSEMBL and provides Web links to a number of important information sources like METACYC, BRENDA, NIST, and REACTOME. If a reaction is reported to occur in more than one cellular compartment, a corresponding number of reactions is generated each referring to one specific compartment. Transport processes of metabolites are entered like chemical reactions where reactants and products have different compartment attributes. The list of compartmentalized biochemical reactions and membrane transport processes compiled by means of METANNOGEN can be exported as an SBML file for further computational analysis. METANNOGEN is highly customizable with respect to the content of the SBML output file, additional data-fields, the graphical input form, highlighting of project specific search terms and dynamically generated Web-links. CONCLUSION: METANNOGEN is a flexible tool to manage information for the design of metabolic networks. The program requires Java Runtime Environment 1.4 or higher and about 100 MB of free RAM and about 200 MB of free HD space. It does not require installation and can be directly Java-webstarted from