SPECULOOS exoplanet search and its prototype on TRAPPIST

One of the most significant goals of modern science is establishing whether life exists around other suns. The most direct path towards its achievement is the detection and atmospheric characterization of terrestrial exoplanets with potentially habitable surface conditions. The nearest ultracool dwarfs (UCDs), i.e. very-low-mass stars and brown dwarfs with effective temperatures lower than 2700 K, represent a unique opportunity to reach this goal within the next decade. The potential of the transit method for detecting potentially habitable Earth-sized planets around these objects is drastically increased compared to Earth-Sun analogs. Furthermore, only a terrestrial planet transiting a nearby UCD would be amenable for a thorough atmospheric characterization, including the search for possible biosignatures, with near-future facilities such as the James Webb Space Telescope. In this chapter, we first describe the physical properties of UCDs as well as the unique potential they offer for the detection of potentially habitable Earth-sized planets suitable for atmospheric characterization. Then, we present the SPECULOOS ground-based transit survey, that will search for Earth-sized planets transiting the nearest UCDs, as well as its prototype survey on the TRAPPIST telescopes. We conclude by discussing the prospects offered by the recent detection by this prototype survey of a system of seven temperate Earth-sized planets transiting a nearby UCD, TRAPPIST-1.Comment: Submitted as a chapter in the "Handbook of Exoplanets" (editors: H. Deeg & J.A. Belmonte; Section Editor: N. Narita). 16 pages, 4 figure

Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples

Amygdala function is implicated in the pathogenesis of autism spectrum disorder (ASD) and anxiety. We investigated associations between early trajectories of amygdala growth and anxiety and ASD outcomes at school age in two longitudinal studies: high- and low-familial likelihood for ASD, Infant Brain Imaging Study (IBIS, n = 257) and typically developing (TD) community sample, Early Brain Development Study (EBDS, n = 158). Infants underwent MRI scanning at up to 3 timepoints from neonate to 24 months. Anxiety was assessed at 6-12 years. Linear multilevel modeling tested whether amygdala volume growth was associated with anxiety symptoms at school age. In the IBIS sample, children with higher anxiety showed accelerated amygdala growth from 6 to 24 months. ASD diagnosis and ASD familial likelihood were not significant predictors. In the EBDS sample, amygdala growth from birth to 24 months was associated with anxiety. More anxious children had smaller amygdala volume and slower rates of amygdala growth. We explore reasons for the contrasting results between high-familial likelihood for ASD and TD samples, grounding results in the broader literature of variable associations between early amygdala volume and later anxiety. Results have the potential to identify mechanisms linking early amygdala growth to later anxiety in certain groups

Geographical limits to species-range shifts are suggested by climate velocity

The reorganization of patterns of species diversity driven by anthropogenic climate change, and the consequences for humans, are not yet fully understood or appreciated. Nevertheless, changes in climate conditions are useful for predicting shifts in species distributions at global and local scales. Here we use the velocity of climate change to derive spatial trajectories for climatic niches from 1960 to 2009 (ref. 7) and from 2006 to 2100, and use the properties of these trajectories to infer changes in species distributions. Coastlines act as barriers and locally cooler areas act as attractors for trajectories, creating source and sink areas for local climatic conditions. Climate source areas indicate where locally novel conditions are not connected to areas where similar climates previously occurred, and are thereby inaccessible to climate migrants tracking isotherms: 16% of global surface area for 1960 to 2009, and 34% of ocean for the \u27business as usual\u27 climate scenario (representative concentration pathway (RCP) 8.5) representing continued use of fossil fuels without mitigation. Climate sink areas are where climate conditions locally disappear, potentially blocking the movement of climate migrants. Sink areas comprise 1.0% of ocean area and 3.6% of land and are prevalent on coasts and high ground. Using this approach to infer shifts in species distributions gives global and regional maps of the expected direction and rate of shifts of climate migrants, and suggests areas of potential loss of species richness

Ocean community warming responses explained by thermal affinities and temperature gradients

As ocean temperatures rise, species distributions are tracking towards historically cooler regions in line with their thermal affinity1,2. However, different responses of species to warming and changed species interactions make predicting biodiversity redistribution and relative abundance a challenge3,4. Here, we use three decades of fish and plankton survey data to assess how warming changes the relative dominance of warm-affinity and cold-affinity species5,6. Regions with stable temperatures (for example, the Northeast Pacific and Gulf of Mexico) show little change in dominance structure, while areas with warming (for example, the North Atlantic) see strong shifts towards warm-water species dominance. Importantly, communities whose species pools had diverse thermal affinities and a narrower range of thermal tolerance showed greater sensitivity, as anticipated from simulations. The composition of fish communities changed less than expected in regions with strong temperature depth gradients. There, species track temperatures by moving deeper2,7, rather than horizontally, analogous to elevation shifts in land plants8. Temperature thus emerges as a fundamental driver for change in marine systems, with predictable restructuring of communities in the most rapidly warming areas using metrics based on species thermal affinities. The ready and predictable dominance shifts suggest a strong prognosis of resilience to climate change for these communities

Global‐scale species distributions predict temperature‐related changes in species composition of rocky shore communities in Britain

Changes in rocky shore community composition as responses to climatic fluctuations and anthropogenic warming can be shown by changes in average species thermal affinities. In this study, we derived thermal affinities for European Atlantic rocky intertidal species by matching their known distributions to patterns in average annual sea surface temperature. Average thermal affinities (the Community Temperature Index, CTI) tracked patterns in sea surface temperature from Portugal to Norway, but CTI for communities of macroalgae and plant species changed less than those composed of animal species. This reduced response was in line with the expectation that communities with a smaller range of thermal affinities among species would change less in composition along thermal gradients and over time. Local‐scale patterns in CTI over wave exposure gradients suggested that canopy macroalgae allow species with ranges centred in cooler than local temperatures (‘cold‐affinity’) to persist in otherwise too‐warm conditions. In annual surveys of rocky shores, communities of animal species in Shetland showed a shift in dominance towards warm‐affinity species (‘thermophilization’) with local warming from 1980 to 2018 but the community of plant and macroalgal species did not. From 2002 to 2018, communities in southwest Britain showed the reverse trend in CTI: declining average thermal affinities over a period of modest temperature decline. Despite the cooling, trends in species abundance were in line with the general mechanism of direction and magnitude of long‐term trends depending on the difference between species thermal affinities and local temperatures. Cold‐affinity species increased during cooling and warm‐affinity ones decreased. The consistency of responses across different communities and with general expectations based on species thermal characteristics suggests strong predictive accuracy of responses of community composition to anthropogenic warming

Translational models for vascular cognitive impairment: a review including larger species.

BACKGROUND: Disease models are useful for prospective studies of pathology, identification of molecular and cellular mechanisms, pre-clinical testing of interventions, and validation of clinical biomarkers. Here, we review animal models relevant to vascular cognitive impairment (VCI). A synopsis of each model was initially presented by expert practitioners. Synopses were refined by the authors, and subsequently by the scientific committee of a recent conference (International Conference on Vascular Dementia 2015). Only peer-reviewed sources were cited. METHODS: We included models that mimic VCI-related brain lesions (white matter hypoperfusion injury, focal ischaemia, cerebral amyloid angiopathy) or reproduce VCI risk factors (old age, hypertension, hyperhomocysteinemia, high-salt/high-fat diet) or reproduce genetic causes of VCI (CADASIL-causing Notch3 mutations). CONCLUSIONS: We concluded that (1) translational models may reflect a VCI-relevant pathological process, while not fully replicating a human disease spectrum; (2) rodent models of VCI are limited by paucity of white matter; and (3) further translational models, and improved cognitive testing instruments, are required

“We live in a plural world”: a framework for rapid interdisciplinary and community engagement

Designing effective products and services requires a sensitive understanding of the people for whom you are designing. There are a number of established approaches for achieving this, all of which are predicated on notions of community participation in research and development work. However, such participatory approaches are often deemed to be too specialized and time-consuming to be used at scale. Taking the opportunity generated by four concurrent RiseWise secondments in Guimarães, Portugal, we developed, trialled, and evaluated a framework for working together across disciplines and levels of experience, and with a local community of older adults. This chapter details this work and makes two key contributions. In describing our approach to engaging with a diverse group of older people through their local community association, we first provide a framework for inclusive and efficient community involvement. Secondly, we reflect on the experience of consolidating approaches and knowledge across disciplines within the research team, and on the impact that working closely with the community had on the research team.RiseWise (Marie Skłodowska-Curie Research and Innovation Staff Exchange under grant agreement 690874

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

SAW: A Method to Identify Splicing Events from RNA-Seq Data Based on Splicing Fingerprints

Splicing event identification is one of the most important issues in the comprehensive analysis of transcription profile. Recent development of next-generation sequencing technology has generated an extensive profile of alternative splicing. However, while many of these splicing events are between exons that are relatively close on genome sequences, reads generated by RNA-Seq are not limited to alternative splicing between close exons but occur in virtually all splicing events. In this work, a novel method, SAW, was proposed for the identification of all splicing events based on short reads from RNA-Seq. It was observed that short reads not in known gene models are actually absent words from known gene sequences. An efficient method to filter and cluster these short reads by fingerprint fragments of splicing events without aligning short reads to genome sequences was developed. Additionally, the possible splicing sites were also determined without alignment against genome sequences. A consensus sequence was then generated for each short read cluster, which was then aligned to the genome sequences. Results demonstrated that this method could identify more than 90% of the known splicing events with a very low false discovery rate, as well as accurately identify, a number of novel splicing events between distant exons