Towards understanding the myometrial physiome: approaches for the construction of a virtual physiological uterus

Premature labour (PTL) is the single most significant factor contributing to neonatal morbidity in Europe with enormous attendant healthcare and social costs. Consequently, it remains a major challenge to alleviate the cause and impact of this condition. Our ability to improve the diagnosis and treatment of women most at risk of PTL is, however, actually hampered by an incomplete understanding of the ways in which the functions of the uterine myocyte are integrated to effect an appropriate biological response at the multicellular whole organ system. The level of organization required to co-ordinate labouring uterine contractile effort in time and space can be considered immense. There is a multitude of what might be considered mini-systems involved, each with their own regulatory feedback cycles, yet they each, in turn, will influence the behaviour of a related system. These include, but are not exclusive to, gestational-dependent regulation of transcription, translation, post-translational modifications, intracellular signaling dynamics, cell morphology, intercellular communication and tissue level morphology. We propose that in order to comprehend how these mini-systems integrate to facilitate uterine contraction during labour (preterm or term) we must, in concert with biological experimentation, construct detailed mathematical descriptions of our findings. This serves three purposes: firstly, providing a quantitative description of series of complex observations; secondly, proferring a database platform that informs further testable experimentation; thirdly, advancing towards the establishment of a virtual physiological uterus and in silico clinical diagnosis and treatment of PTL

Knowledge to action for solving complex problems: insights from a review of nine international cases

Abstract Introduction: Solving complex problems such as preventing chronic diseases introduces unique challenges for the creation and application of knowledge, or knowledge to action (KTA). KTA approaches that apply principles of systems thinking are thought to hold promise, but practical strategies for their application are not well understood. In this paper we report the results of a scan of systems approaches to KTA with a goal to identify how to optimize their implementation and impact

The species composition of Antarctic phytoplankton interpreted in terms of Tilman's competition theory

An attempt was made, to test for the impact of resource competition on Antarctic marine phytoplankton. According to theory, species composition near competitive equilibrium should be determined by the ratios of limiting resources. Enrichment bioassays identified silicon and nitrogen as limiting nutrients for some of the most important phytoplankton species during early austral summer in the region near the Antarctic Peninsula. Together with the generally acknowledged limiting resource light, this gave three meaningful ratios of essential resources (Si:N, Si:light, N:light) and one ratio of substitutable resources (NO sub(3):NH sub(4)). Phytoplankton species assemblages were found to be well separated by the ratios of the essential resources and by mixing depth

Toward Human-Carnivore Coexistence: Understanding Tolerance for Tigers in Bangladesh

Fostering local community tolerance for endangered carnivores, such as tigers (Panthera tigris), is a core component of many conservation strategies. Identification of antecedents of tolerance will facilitate the development of effective tolerance-building conservation action and secure local community support for, and involvement in, conservation initiatives. We use a stated preference approach for measuring tolerance, based on the ‘Wildlife Stakeholder Acceptance Capacity’ concept, to explore villagers’ tolerance levels for tigers in the Bangladesh Sundarbans, an area where, at the time of the research, human-tiger conflict was severe. We apply structural equation modeling to test an a priori defined theoretical model of tolerance and identify the experiential and psychological basis of tolerance in this community. Our results indicate that beliefs about tigers and about the perceived current tiger population trend are predictors of tolerance for tigers. Positive beliefs about tigers and a belief that the tiger population is not currently increasing are both associated with greater stated tolerance for the species. Contrary to commonly-held notions, negative experiences with tigers do not directly affect tolerance levels; instead, their effect is mediated by villagers’ beliefs about tigers and risk perceptions concerning human-tiger conflict incidents. These findings highlight a need to explore and understand the socio-psychological factors that encourage tolerance towards endangered species. Our research also demonstrates the applicability of this approach to tolerance research to a wide range of socio-economic and cultural contexts and reveals its capacity to enhance carnivore conservation efforts worldwide

Cooperative secretions facilitate host range expansion in bacteria

The majority of emergent human pathogens are zoonotic in origin, that is, they can transmit to humans from other animals. Understanding the factors underlying the evolution of pathogen host range is therefore of critical importance in protecting human health. There are two main evolutionary routes to generalism: organisms can tolerate multiple environments or they can modify their environments to forms to which they are adapted. Here we use a combination of theory and a phylogenetic comparative analysis of 191 pathogenic bacterial species to show that bacteria use cooperative secretions that modify their environment to extend their host range and infect multiple host species. Our results suggest that cooperative secretions are key determinants of host range in bacteria, and that monitoring for the acquisition of secreted proteins by horizontal gene transfer can help predict emerging zoonoses

Belowground DNA-based techniques: untangling the network of plant root interactions

Contains fulltext : 91591.pdf (publisher's version ) (Closed access)7 p

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint.

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary outcome, these predictions of absolute individualized treatment effect require knowledge of the individual's risk without treatment and incorporation of a possibly differential treatment effect (ie, varying with patient characteristics). In this article, we lay out the causal structure of individualized treatment effect in terms of potential outcomes and describe the required assumptions that underlie a causal interpretation of its prediction. Subsequently, we describe regression models and model estimation techniques that can be used to move from average to more individualized treatment effect predictions. We focus mainly on logistic regression-based methods that are both well-known and naturally provide the required probabilistic estimates. We incorporate key components from both causal inference and prediction research to arrive at individualized treatment effect predictions. While the separate components are well known, their successful amalgamation is very much an ongoing field of research. We cut the problem down to its essentials in the setting of a randomized trial, discuss the importance of a clear definition of the estimand of interest, provide insight into the required assumptions, and give guidance with respect to modeling and estimation options. Simulated data illustrate the potential of different modeling options across scenarios that vary both average treatment effect and treatment effect heterogeneity. Two applied examples illustrate individualized treatment effect prediction in randomized trial data

The spectrum of Apert syndrome: phenotype, particularities in orthodontic treatment, and characteristics of orthognathic surgery

In the PubMed accessible literature, information on the characteristics of interdisciplinary orthodontic and surgical treatment of patients with Apert syndrome is rare. The aim of the present article is threefold: (1) to show the spectrum of the phenotype, in order (2) to elucidate the scope of hindrances to orthodontic treatment, and (3) to demonstrate the problems of surgery and interdisciplinary approach. Children and adolescents who were born in 1985 or later, who were diagnosed with Apert syndrome, and who sought consultation or treatment at the Departments of Orthodontics or Craniomaxillofacial Surgery at the Dental School of the University Hospital of Münster (n = 22; 9 male, 13 female) were screened. Exemplarily, three of these patients (2 male, 1 female), seeking interdisciplinary (both orthodontic and surgical treatment) are presented. Orthodontic treatment before surgery was performed by one experienced orthodontist (AH), and orthognathic surgery was performed by one experienced surgeon (UJ), who diagnosed the syndrome according to the criteria listed in OMIM™. In the sagittal plane, the patients suffered from a mild to a very severe Angle Class III malocclusion, which was sometimes compensated by the inclination of the lower incisors; in the vertical dimension from an open bite; and transversally from a single tooth in crossbite to a circular crossbite. All patients showed dentitio tarda, some impaction, partial eruption, idopathic root resorption, transposition or other aberrations in the position of the tooth germs, and severe crowding, with sometimes parallel molar tooth buds in each quarter of the upper jaw. Because of the severity of malocclusion, orthodontic treatment needed to be performed with fixed appliances, and mainly with superelastic wires. The therapy was hampered with respect to positioning of bands and brackets because of incomplete tooth eruption, dense gingiva, and mucopolysaccharide ridges. Some teeth did not move, or moved insufficiently (especially with respect to rotations and torque) irrespective of surgical procedures or orthodontic mechanics and materials applied, and without prognostic factors indicating these problems. Establishing occlusal contact of all teeth was difficult. Tooth movement was generally retarded, increasing the duration of orthodontic treatment. Planning of extractions was different from that of patients without this syndrome. In one patient, the sole surgical procedure after orthodontic treatment with fixed appliances in the maxilla and mandible was a genioplasty. Most patients needed two- jaw surgery (bilateral sagittal split osteotomy [BSSO] with mandibular setback and distraction in the maxilla). During the period of distraction, the orthodontist guided the maxilla into final position by means of bite planes and intermaxillary elastics. To our knowledge, this is the first article in the PubMed accessible literature describing the problems with respect to interdisciplinary orthodontic and surgical procedures. Although the treatment results are not perfect, patients undergoing these procedures benefit esthetically to a high degree. Patients need to be informed with respect to the different kinds of extractions that need to be performed, the increased treatment time, and the results, which may be reached using realistic expectations

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file