TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer

In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All together 1,715 samples of ten independent datasets were integrated into the system. As a demonstration, we used the tool to validate 21 previously published survival associated biomarkers. Of these, survival was best predicted by CDK1 (p<1E-16), CD24 (p<1E-16) and CADM1 (p = 7E-12) in adenocarcinomas and by CCNE1 (p = 2.3E-09) and VEGF (p = 3.3E-10) in all NSCLC patients. Additional genes significantly correlated to survival include RAD51, CDKN2A, OPN, EZH2, ANXA3, ADAM28 and ERCC1. In summary, we established an integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

Extracellular matrix interactions have essential roles in normal physiology and many pathological processes. Although the importance of extracellular matrix interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel-screening platform capable of measuring phenotypic responses to combinations of extracellular matrix molecules. Using a genetic mouse model of lung adenocarcinoma, we measure the extracellular matrix-dependent adhesion of tumour-derived cells. Hierarchical clustering of the adhesion profiles differentiates metastatic cell lines from primary tumour lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8 or laminin. We show that these molecules correlate with human disease and that their interactions are mediated in part by α3β1 integrin. Thus, our platform allowed us to interrogate interactions between metastatic cells and their microenvironments, and identified extracellular matrix and integrin interactions that could serve as therapeutic targets.National Institutes of Health (U.S.) (Grant K99-CA151968)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service AwardStand Up To Cancer (SU2C/AACR)David H. Koch Institute for Integrative Cancer Research at MIT (CTC Project)Harvard Stem Cell Institute (SG-0046-08-00)National Cancer Center (Postdoctoral Fellowship)National Cancer Institute (U.S.) (U54CA126515)National Cancer Institute (U.S.) (U54CA112967)Howard Hughes Medical InstituteMassachusetts Institute of Technology. Ludwig Center for Molecular Oncolog

The physiological responses of cacao to the environment and the implications for climate change resilience. A review

Cacao (Theobroma cacao L.) is a tropical perennial crop which is of great economic importance to the confectionary industry and to the economies of many countries of the humid tropics where it is grown. Some recent studies have suggested climate change could severely impact cacao production in West Africa. It is essential to incorporate our understanding of the physiology and genetic variation within cacao germplasm when discussing the implications of climate change on cacao productivity and developing strategies for climate resilience in cacao production. Here we review the current research on the physiological responses of cacao to various climate factors. Our main findings are 1) water limitation causes significant yield reduction in cacao but genotypic variation in sensitivity is evident, 2) in the field cacao experiences higher temperatures than is often reported in the literature, 3) the complexity of the cacao/ shade tree interaction can lead to contradictory results, 4) elevated CO2 may alleviate some negative effects of climate change 5) implementation of mitigation strategies can help reduce environmental stress, 6) significant gaps in the research need addressing to accelerate the development of climate resilience. Harnessing the significant genetic variation apparent within cacao germplasm is essential to develop modern varieties capable of high yields in non-optimal conditions. Mitigation strategies will also be essential but to use shading to best effect shade tree selection is crucial to avoid resource competition. Cacao is often described as being sensitive to climate change but genetic variation, adaptive responses, appropriate mitigation strategies and interactive climate effects should all be considered when predicting the future of cacao production. Incorporating these physiological responses to various environmental conditions and developing a deeper understanding of the processes underlying these responses will help to accelerate the development of a more resource use efficient tree ensuring sustainable production into the future

The “Flexi-Chamber”: A Novel Cost-Effective In Situ Respirometry Chamber for Coral Physiological Measurements

Coral reefs are threatened worldwide, with environmental stressors increasingly affecting the ability of reef-building corals to sustain growth from calcification (G), photosynthesis (P) and respiration (R). These processes support the foundation of coral reefs by directly influencing biogeochemical nutrient cycles and complex ecological interactions and therefore represent key knowledge required for effective reef management. However, metabolic rates are not trivial to quantify and typically rely on the use of cumbersome in situ respirometry chambers and/or the need to remove material and examine ex situ, thereby fundamentally limiting the scale, resolution and possibly the accuracy of the rate data. Here we describe a novel low-cost in situ respirometry bag that mitigates many constraints of traditional glass and plexi-glass incubation chambers. We subsequently demonstrate the effectiveness of our novel "Flexi-Chamber" approach via two case studies: 1) the Flexi-Chamber provides values of P, R and G for the reef-building coral Siderastrea cf. stellata collected from reefs close to Salvador, Brazil, which were statistically similar to values collected from a traditional glass respirometry vessel; and 2) wide-scale application of obtaining P, R and G rates for different species across different habitats to obtain inter- and intra-species differences. Our novel cost-effective design allows us to increase sampling scale of metabolic rate measurements in situ without the need for destructive sampling and thus significantly expands on existing research potential, not only for corals as we have demonstrated here, but also other important benthic groups

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Methane-carbon flow into the benthic food web at cold seeps – a case study from the Costa Rica subduction zone

Cold seep ecosystems can support enormous biomasses of free-living and symbiotic chemoautotrophic organisms that get their energy from the oxidation of methane or sulfide. Most of this biomass derives from animals that are associated with bacterial symbionts, which are able to metabolize the chemical resources provided by the seeping fluids. Often these systems also harbor dense accumulations of non-symbiotic megafauna, which can be relevant in exporting chemosynthetically fixed carbon from seeps to the surrounding deep sea. Here we investigated the carbon sources of lithodid crabs (Paralomis sp.) feeding on thiotrophic bacterial mats at an active mud volcano at the Costa Rica subduction zone. To evaluate the dietary carbon source of the crabs, we compared the microbial community in stomach contents with surface sediments covered by microbial mats. The stomach content analyses revealed a dominance of epsilonproteobacterial 16S rRNA gene sequences related to the free-living and epibiotic sulfur oxidiser Sulfurovum sp. We also found Sulfurovum sp. as well as members of the genera Arcobacter and Sulfurimonas in mat-covered surface sediments where Epsilonproteobacteria were highly abundant constituting 10% of total cells. Furthermore, we detected substantial amounts of bacterial fatty acids such as i-C15:0 and C17:1ω6c with stable carbon isotope compositions as low as −53‰ in the stomach and muscle tissue. These results indicate that the white microbial mats at Mound 12 are comprised of Epsilonproteobacteria and that microbial mat-derived carbon provides an important contribution to the crab's nutrition. In addition, our lipid analyses also suggest that the crabs feed on other 13C-depleted organic matter sources, possibly symbiotic megafauna as well as on photosynthetic carbon sources such as sedimentary detritus

Serum neurofilament light in atrial fibrillation: clinical, neuroimaging and cognitive correlates

Emerging evidence suggests that atrial fibrillation is associated with cognitive dysfunction independently of stroke, but the underlying mechanisms remain unclear. In this cross-sectional analysis from the Swiss-atrial fibrillation Study (NCT02105844), we investigated the association of serum neurofilament light protein, a neuronal injury biomarker, with (i) the CHA; 2; DS; 2; -VASc score (congestive heart failure, hypertension, age 65-74 or >75 years, diabetes mellitus, stroke or transient ischaemic attack, vascular disease, sex), clinical and neuroimaging parameters and (ii) cognitive measures in atrial fibrillation patients. We measured neurofilament light in serum using an ultrasensitive single-molecule array assay in a sample of 1379 atrial fibrillation patients (mean age, 72 years; female, 27%). Ischaemic infarcts, small vessel disease markers and normalized brain volume were assessed on brain MRI. Cognitive testing included the Montreal cognitive assessment, trail-making test, semantic verbal fluency and digit symbol substitution test, which were summarized using principal component analysis. Results were analysed using univariable and multivariable linear regression. Neurofilament light was associated with the CHA; 2; DS; 2; -VASc score, with an average 19.2% [95% confidence interval (17.2%, 21.3%)] higher neurofilament per unit CHA; 2; DS; 2; -VASc increase. This association persisted after adjustment for age and MRI characteristics. In multivariable analyses, clinical parameters associated with neurofilament light were higher age [32.5% (27.2%, 38%) neurofilament increase per 10 years], diabetes mellitus, heart failure and peripheral artery disease [26.8% (16.8%, 37.6%), 15.7% (8.1%, 23.9%) and 19.5% (6.8%, 33.7%) higher neurofilament, respectively]. Mean arterial pressure showed a curvilinear association with neurofilament, with evidence for both an inverse linear and a U-shaped association. MRI characteristics associated with neurofilament were white matter lesion volume and volume of large non-cortical or cortical infarcts [4.3% (1.8%, 6.8%) and 5.5% (2.5%, 8.7%) neurofilament increase per unit increase in log-volume of the respective lesion], as well as normalized brain volume [4.9% (1.7%, 8.1%) higher neurofilament per 100 cm; 3; smaller brain volume]. Neurofilament light was inversely associated with all cognitive measures in univariable analyses. The effect sizes diminished after adjusting for clinical and MRI variables, but the association with the first principal component was still evident. Our results suggest that in atrial fibrillation patients, neuronal loss measured by serum neurofilament light is associated with age, diabetes mellitus, heart failure, blood pressure and vascular brain lesions, and inversely correlates with normalized brain volume and cognitive function