Swift's razor

The razors, knives and “tools for cutting” that appear so often in Jonathan Swift’s writings represent linguistic instruments for the performance of speech acts. Swift often imagines them being deployed for some identifiable purpose, typically the discouragement of “fools” or “knaves” by anatomization. Their sharpness is associated with linguistic acuity, and specifically with the refinement, keenness and power of Swift’s own writing. The focus of this article, however, is on another set of associations that Swift attaches to his blades. They tend also to involve ideas of latency, divagation, bluntness, and misappropriation.

Maternal weaning modulates emotional behavior and regulates the gut-brain axis

Evidence shows that nutritional and environmental stress stimuli during postnatal period influence brain development and interactions between gut and brain. In this study we show that in rats, prevention of weaning from maternal milk results in depressive-like behavior, which is accompanied by changes in the gut bacteria and host metabolism. Depressive-like behavior was studied using the forced-swim test on postnatal day (PND) 25 in rats either weaned on PND 21, or left with their mother until PND 25 (non-weaned). Non-weaned rats showed an increased immobility time consistent with a depressive phenotype. Fluorescence in situ hybridization showed non-weaned rats to harbor significantly lowered Clostridium histolyticum bacterial groups but exhibit marked stress-induced increases. Metabonomic analysis of urine from these animals revealed significant differences in the metabolic profiles, with biochemical phenotypes indicative of depression in the non-weaned animals. In addition, non-weaned rats showed resistance to stress-induced modulation of oxytocin receptors in amygdala nuclei, which is indicative of passive stress-coping mechanism. We conclude that delaying weaning results in alterations to the gut microbiota and global metabolic profiles which may contribute to a depressive phenotype and raise the issue that mood disorders at early developmental ages may reflect interplay between mammalian host and resident bacteria.

The COnvective Precipitation Experiment (COPE): investigating the origins of heavy precipitation in the southwestern UK

A recent field campaign in southwest England used numerical modeling integrated with aircraft and radar observations to investigate the dynamic and microphysical interactions that can result in heavy convective precipitation. The COnvective Precipitation Experiment (COPE) was a joint UK-US field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly due to the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the US. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve NWP model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the UK BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360-deg volume scans over 10 elevation angles approximately every 5 minutes, and was augmented by two UK Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper: (i) provides an overview of the COPE field campaign and the resulting dataset; (ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone; and (iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

Small global-mean cooling due to volcanic radiative forcing

In both the observational record and atmosphere-ocean general circulation model (AOGCM) simulations of the last ∼∼ 150 years, short-lived negative radiative forcing due to volcanic aerosol, following explosive eruptions, causes sudden global-mean cooling of up to ∼∼ 0.3 K. This is about five times smaller than expected from the transient climate response parameter (TCRP, K of global-mean surface air temperature change per W m−2 of radiative forcing increase) evaluated under atmospheric CO2 concentration increasing at 1 % yr−1. Using the step model (Good et al. in Geophys Res Lett 38:L01703, 2011. doi:10.​1029/​2010GL045208), we confirm the previous finding (Held et al. in J Clim 23:2418–2427, 2010. doi:10.​1175/​2009JCLI3466.​1) that the main reason for the discrepancy is the damping of the response to short-lived forcing by the thermal inertia of the upper ocean. Although the step model includes this effect, it still overestimates the volcanic cooling simulated by AOGCMs by about 60 %. We show that this remaining discrepancy can be explained by the magnitude of the volcanic forcing, which may be smaller in AOGCMs (by 30 % for the HadCM3 AOGCM) than in off-line calculations that do not account for rapid cloud adjustment, and the climate sensitivity parameter, which may be smaller than for increasing CO2 (40 % smaller than for 4 × CO2 in HadCM3).

The inositol-3-phosphate synthase biosynthetic enzyme has distinct catalytic and metabolic roles

Inositol levels, maintained by the biosynthetic enzyme inositol-3-phosphate synthase (Ino1), are altered in a range of disorders including bipolar disorder and Alzheimer's disease. To date, most inositol studies have focused on the molecular and cellular effects of inositol depletion without considering Ino1 levels. Here we employ a simple eukaryote, Dictyostelium, to demonstrate distinct effects of loss of Ino1 and inositol depletion. We show that loss of Ino1 results in inositol auxotrophy that can only be partially rescued by exogenous inositol. Removal of inositol supplementation from the ino1- mutant results in a rapid 56% reduction in inositol levels, triggering the induction of autophagy, reduced cytokinesis and substrate adhesion. Inositol depletion also caused a dramatic generalised decrease in phosphoinositide levels that was rescued by inositol supplementation. However, loss of Ino1 triggered broad metabolic changes consistent with the induction of a catabolic state that was not rescued by inositol supplementation. These data suggest a metabolic role for Ino1 independent of inositol biosynthesis. To characterise this role, an Ino1 binding partner containing SEL1L1 domains (Q54IX5) was identified with homology to mammalian macromolecular complex adaptor proteins. Our findings therefore identify a new role for Ino1, independent of inositol biosynthesis, with broad effects on cell metabolism.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.

Advancing polar prediction capabilities on daily to seasonal time scales

It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined. The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities.