Emergence of light-driven protometabolism on recruitment of a photocatalytic cofactor by a self-replicator

Establishing how life can emerge from inanimate matter is among the grand challenges of contemporary science. Chemical systems that capture life’s essential characteristics—replication, metabolism and compartmentalization—offer a route to understanding this momentous process. The synthesis of life, whether based on canonical biomolecules or fully synthetic molecules, requires the functional integration of these three characteristics. Here we show how a system of fully synthetic self-replicating molecules, on recruiting a cofactor, acquires the ability to transform thiols in its environment into disulfide precursors from which the molecules can replicate. The binding of replicator and cofactor enhances the activity of the latter in oxidizing thiols into disulfides through photoredox catalysis and thereby accelerates replication by increasing the availability of the disulfide precursors. This positive feedback marks the emergence of light-driven protometabolism in a system that bears no resemblance to canonical biochemistry and constitutes a major step towards the highly challenging aim of creating a new and completely synthetic form of life. [Figure not available: see fulltext.]

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (tracemetal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation

The impact of firms’ social media initiatives on operational efficiency and innovativeness

Social media have been increasingly adopted for organizational purposes but their operational implications are not well understood. Firms’ social media initiatives might facilitate information flow and knowledge sharing within and across organizations, strengthening firm‐customer interaction, and improving internal and external collaboration. In this research we empirically examine the impact of social media initiatives on firms’ operational efficiency and innovativeness. Taking the resource‐based view of firms’ information capability, we consider firms’ social media initiatives as strategic resources for operational improvement. We posit that firms’ social media initiatives enhance dynamic knowledge‐sharing routines through an information‐rich social network, leading to both operational efficiency and innovativeness. Collecting secondary data in a longitudinal setting from multiple sources, we construct dynamic panel data (DPD) models. Based on system generalized method of moments (GMM) estimation, we show that firms’ social media initiatives improve operational efficiency and innovativeness. We identify the importance of an information‐rich social network to the creation of knowledge‐based advantage through firms’ social media initiatives, and discuss the theoretical and managerial implications from the perspective of operations management

Probabilistic Reconstruction of Ancestral Protein Sequences

Using a maximum-likelihood formalism, we have developed a method with which to reconstruct the sequences of ancestral proteins. Our approach allows the calculation of not only the most probable ancestral sequence but also of the probability of any amino acid at any given node in the evolutionary tree. Because we consider evolution on the amino acid level, we are better able to include effects of evolutionary pressure and take advantage of structural information about the protein through the use of mutation matrices that depend on secondary structure and surface accessibility. The computational complexity of this method scales linearly with the number of homologous proteins used to reconstruct the ancestral sequence.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42365/1/239-42-2-313_42n2p313.pd

The cys-loop ligand-gated ion channel gene superfamily of the nematode, Caenorhabditis elegans

The nematode, Caenorhabditis elegans, possesses the most extensive known superfamily of cys-loop ligand-gated ion channels (cys-loop LGICs) consisting of 102 subunit-encoding genes. Less than half of these genes have been functionally characterised which include cation-permeable channels gated by acetylcholine (ACh) and γ-aminobutyric acid (GABA) as well as anion-selective channels gated by ACh, GABA, glutamate and serotonin. Following the guidelines set for genetic nomenclature for C. elegans, we have designated unnamed subunits as lgc genes (ligand-gated ion channels of the cys-loop superfamily). Phylogenetic analysis shows that several of these lgc subunits form distinct groups which may represent novel cys-loop LGIC subtypes

Factors that influence nurses' assessment of patient acuity and response to acute deterioration.

BACKGROUND: nurses play a crucial role in the early recognition and management of the deteriorating patient. They are responsible for the care they provide to their patients, part of which is the monitoring of vital signs (blood pressure, pulse, respiratory rate and temperature), which are fundamental in the surveillance of deterioration. The aim of this study was to discover what factors influence how nurses assess patient acuity and their response to acute deterioration. METHODS: a generic qualitative approach was used. Some 10 nurses working in an acute NHS trust were interviewed using a semi- structured approach, with equal representation from medical and surgical inpatient wards. RESULTS: the main themes identified were collegial relationships, intuition, and interpretation of the MEWS system (Modified Early Warning Score). Collegial relationships with the medical staff had some influence on the nurses' assessment, as they tended to accept the medical peers' assessment as absolute, rather than their own assessment. It was also highlighted that nurses relied on the numerical escalation of the MEWS system to identify the deteriorating patient, instead of their own clinical judgement of the situation. Interestingly, the nurses found no difficulty in escalating the patient's care to medical staff when the patient presented with a high MEWS score. The difficulty arose when the MEWS score was low-the participants found it challenging to authenticate their findings. CONCLUSION: this study has identified several confounding factors that influence the ways in which nurses assess patient acuity and their response to acute deterioration. The information provides a crucial step forward in identifying strategies to develop further training

Mindfulness-Based Childbirth and Parenting Education: Promoting Family Mindfulness During the Perinatal Period

We present the conceptual and empirical foundation and curriculum content of the Mindfulness-Based Childbirth and Parenting (MBCP) program and the results of a pilot study of n = 27 pregnant women participating in MBCP during their third trimester of pregnancy. MBCP is a formal adaptation of the Mindfulness-Based Stress Reduction program and was developed and refined over the course of 11 years of clinical practice with 59 groups of expectant couples. MBCP is designed to promote family health and well-being through the practice of mindfulness during pregnancy, childbirth, and early parenting. Quantitative results from the current study include statistically significant increases in mindfulness and positive affect, and decreases in pregnancy anxiety, depression, and negative affect from pre- to post-test (p < .05). Effect sizes for changes in key hypothesized intervention mediators were large (d > .70), suggesting that MBCP is achieving its intended effects on maternal well-being during pregnancy. Qualitative reports from participants expand upon the quantitative findings, with the majority of participants reporting perceived benefits of using mindfulness practices during the perinatal period and early parenting. Our future research will involve conducting a randomized controlled trial of MBCP to test effects on psychophysiological stress mechanisms and to examine effects on birth outcomes, family relationship quality, and child development outcomes

Capturing judgement strategies in risk assessments with improved quality of clinical information: How nurses' strategies differ from the ecological model

Background: Nurses' risk assessments of patients at risk of deterioration are sometimes suboptimal. Advances in clinical simulation mean higher quality information can be used as an alternative to traditional paper-based approaches as a means of improving judgement. This paper tests the hypothesis that nurses' judgement strategies and policies change as the quality of information used by nurses in simulation changes. Methods: Sixty-three student nurses and 34 experienced viewed 25 paper-case based and 25 clinically simulated scenarios, derived from real cases, and judged whether the (simulated) patient was at 'risk' of acute deterioration. Criteria of judgement "correctness" came from the same real cases. Information relative weights were calculated to examine judgement policies of individual nurses. Group comparisons of nurses and students under both paper and clinical simulation conditions were undertaken using non parametric statistical tests. Judgment policies were also compared to the ecological statistical model. Cumulative relative weights were calculated to assess how much information nurses used when making judgements. Receiver operating characteristic (ROC) curves were generated to examine predictive accuracy amongst the nurses. Results: There were significant variations between nurses' judgement policies and those optimal policies determined by the ecological model. Nurses significantly underused the cues of consciousness level, respiration rate, and systolic blood pressure than the ecological model requires. However, in clinical simulations, they tended to make appropriate use of heart rate, with non-significant difference in the relative weights of heart rate between clinical simulations and the ecological model. Experienced nurses paid substantially more attention to respiration rate in the simulated setting compared to paper cases, while students maintained a similar attentive level to this cue. This led to a non-significant difference in relative weights of respiration rate between experienced nurses and students. Conclusions: Improving the quality of information by clinical simulations significantly impacted on nurses' judgement policies of risk assessments. Nurses' judgement strategies also varied with the increased years of experience. Such variations in processing clinical information may contribute to nurses' suboptimal judgements in clinical practice. Constructing predictive models of common judgement situations, and increasing nurses' awareness of information weightings in such models may help improve judgements made by nurses