The origin of large molecules in primordial autocatalytic reaction networks

Large molecules such as proteins and nucleic acids are crucial for life, yet their primordial origin remains a major puzzle. The production of large molecules, as we know it today, requires good catalysts, and the only good catalysts we know that can accomplish this task consist of large molecules. Thus the origin of large molecules is a chicken and egg problem in chemistry. Here we present a mechanism, based on autocatalytic sets (ACSs), that is a possible solution to this problem. We discuss a mathematical model describing the population dynamics of molecules in a stylized but prebiotically plausible chemistry. Large molecules can be produced in this chemistry by the coalescing of smaller ones, with the smallest molecules, the `food set', being buffered. Some of the reactions can be catalyzed by molecules within the chemistry with varying catalytic strengths. Normally the concentrations of large molecules in such a scenario are very small, diminishing exponentially with their size. ACSs, if present in the catalytic network, can focus the resources of the system into a sparse set of molecules. ACSs can produce a bistability in the population dynamics and, in particular, steady states wherein the ACS molecules dominate the population. However to reach these steady states from initial conditions that contain only the food set typically requires very large catalytic strengths, growing exponentially with the size of the catalyst molecule. We present a solution to this problem by studying `nested ACSs', a structure in which a small ACS is connected to a larger one and reinforces it. We show that when the network contains a cascade of nested ACSs with the catalytic strengths of molecules increasing gradually with their size (e.g., as a power law), a sparse subset of molecules including some very large molecules can come to dominate the system.Comment: 49 pages, 17 figures including supporting informatio

A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare

Objective: The aim of this study was to compare the acceptability, validity and concordance of discrete choice experiment (DCE) and best–worst scaling (BWS) stated preference approaches in health. Methods: A systematic search of EMBASE, Medline, AMED, PubMed, CINAHL, Cochrane Library and EconLit databases was undertaken in October to December 2016 without date restriction. Studies were included if they were published in English, presented empirical data related to the administration or findings of traditional format DCE and object-, profile- or multiprofile-case BWS, and were related to health. Study quality was assessed using the PREFS checklist. Results: Fourteen articles describing 12 studies were included, comparing DCE with profile-case BWS (9 studies), DCE and multiprofile-case BWS (1 study), and profile- and multiprofile-case BWS (2 studies). Although limited and inconsistent, the balance of evidence suggests that preferences derived from DCE and profile-case BWS may not be concordant, regardless of the decision context. Preferences estimated from DCE and multiprofile-case BWS may be concordant (single study). Profile- and multiprofile-case BWS appear more statistically efficient than DCE, but no evidence is available to suggest they have a greater response efficiency. Little evidence suggests superior validity for one format over another. Participant acceptability may favour DCE, which had a lower self-reported task difficulty and was preferred over profile-case BWS in a priority setting but not necessarily in other decision contexts. Conclusion: DCE and profile-case BWS may be of equal validity but give different preference estimates regardless of the health context; thus, they may be measuring different constructs. Therefore, choice between methods is likely to be based on normative considerations related to coherence with theoretical frameworks and on pragmatic considerations related to ease of data collection

Gateways to the FANTOM5 promoter level mammalian expression atlas

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0560-6) contains supplementary material, which is available to authorized users

MicroRNAs play critical roles during plant development and in response to abiotic stresses

MicroRNAs (miRNAs) have been identified as key molecules in regulatory networks. The fine-tuning role of miRNAs in addition to the regulatory role of transcription factors has shown that molecular events during development are tightly regulated. In addition, several miRNAs play crucial roles in the response to abiotic stress induced by drought, salinity, low temperatures, and metals such as aluminium. Interestingly, several miRNAs have overlapping roles with regard to development, stress responses, and nutrient homeostasis. Moreover, in response to the same abiotic stresses, different expression patterns for some conserved miRNA families among different plant species revealed different metabolic adjustments. The use of deep sequencing technologies for the characterisation of miRNA frequency and the identification of new miRNAs adds complexity to regulatory networks in plants. In this review, we consider the regulatory role of miRNAs in plant development and abiotic stresses, as well as the impact of deep sequencing technologies on the generation of miRNA data