ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.</p

Pro-fibrotic phenotype of bone marrow stromal cells in Modic type 1 changes

Modic type 1 changes (MC1) are painful vertebral bone marrow lesions frequently found in patients suffering from chronic low-back pain. Marrow fibrosis is a hallmark of MC1. Bone marrow stromal cells (BMSCs) are key players in other fibrotic bone marrow pathologies, yet their role in MC1 is unknown. The present study aimed to characterise MC1 BMSCs and hypothesised a pro-fibrotic role of BMSCs in MC1. BMSCs were isolated from patients undergoing lumbar spinal fusion from MC1 and adjacent control vertebrae. Frequency of colony-forming unit fibroblast (CFU-F), expression of stem cell surface markers, differentiation capacity, transcriptome, matrix adhesion, cell contractility as well as expression of pro-collagen type I alpha 1, α-smooth muscle actin, integrins and focal adhesion kinase (FAK) were compared. More CFU-F and increased expression of C-X-C-motif-chemokine 12 were found in MC1 BMSCs, possibly indicating overrepresentation of a perisinusoidal BMSC population. RNA sequencing analysis showed enrichment in extracellular matrix proteins and fibrosis-related signalling genes. Increases in pro-collagen type I alpha 1 expression, cell adhesion, cell contractility and phosphorylation of FAK provided further evidence for their pro-fibrotic phenotype. Moreover, a leptin receptor high expressing (LEPRhigh) BMSC population was identified that differentiated under transforming growth factor beta 1 stimulation into myofibroblasts in MC1 but not in control BMSCs. In conclusion, pro-fibrotic changes in MC1 BMSCs and a LEPRhigh MC1 BMSC subpopulation susceptible to myofibroblast differentiation were found. Fibrosis is a hallmark of MC1 and a potential therapeutic target. A causal link between the pro-fibrotic phenotype and clinical characteristics needs to be demonstrated

Role of C-reactive protein in the bone marrow of Modic type 1 changes

Modic type 1 changes (MC1) are vertebral bone marrow lesions and associate with low back pain. Increased serum C-reactive protein (CRP) has inconsistently been associated with MC1. We aimed to provide evidence for a role of CRP in the tissue pathophysiology of MC1 bone marrow. From thirteen MC1 patients undergoing spinal fusion at MC1 levels, vertebral bone marrow aspirates from MC1 and intra-patient control bone marrow were taken. Bone marrow CRP, IL-1, and IL-6 were measured with enzyme-linked immunosorbent assays; lactate dehydrogenase (LDH) was measured with a colorimetric assay. CRP, IL-1, and IL-6 were compared between MC1 and control bone marrow. Bone marrow CRP was correlated with blood CRP and with bone marrow IL-1, IL-6, and LDH. CRP expression by marrow cells was measured with PCR. Increased CRP in MC1 bone marrow (mean difference: +0.22 mg CRP/g protein, 95% CI [-0.04, 0.47], p=0.088) correlated with blood CRP (r=0.69, p=0.018), with bone marrow IL-1β (ρ=0.52, p=0.029) and IL-6 (ρ=0.51, p=0.031). Marrow cells did not express CRP. Increased LDH in MC1 bone marrow (143.1%, 95% CI [110.7%, 175.4%], p=0.014) indicated necrosis. A blood CRP threshold of 3.2 mg/L detected with 100% accuracy increased CRP in MC1 bone marrow. In conclusion, the association of CRP with inflammatory and necrotic changes in MC1 bone marrow provides evidence for a pathophysiological role of CRP in MC1 bone marrow. This article is protected by copyright. All rights reserved

Effect of microstructural evolution on magnetic properties of Ni thin films

Copyright © Indian Academy of Sciences.The magnetic properties of Ni thin films, in the range 20–500 nm, at the crystalline-nanocrystalline interface are reported. The effect of thickness, substrate and substrate temperature has been studied. For the films deposited at ambient temperatures on borosilicate glass substrates, the crystallite size, coercive field and magnetization energy density first increase and achieve a maximum at a critical value of thickness and decrease thereafter. At a thickness of 50 nm, the films deposited at ambient temperature onto borosilicate glass, MgO and silicon do not exhibit long-range order but are magnetic as is evident from the non-zero coercive field and magnetization energy. Phase contrast microscopy revealed that the grain sizes increase from a value of 30–50 nm at ambient temperature to 120–150 nm at 503 K and remain approximately constant in this range up to 593 K. The existence of grain boundary walls of width 30–50 nm is demonstrated using phase contrast images. The grain boundary area also stagnates at higher substrate temperature. There is pronounced shape anisotropy as evidenced by the increased aspect ratio of the grains as a function of substrate temperature. Nickel thin films of 50 nm show the absence of long-range crystalline order at ambient temperature growth conditions and a preferred [111] orientation at higher substrate temperatures. Thin films are found to be thermally relaxed at elevated deposition temperature and having large compressive strain at ambient temperature. This transition from nanocrystalline to crystalline order causes a peak in the coercive field in the region of transition as a function of thickness and substrate temperature. The saturation magnetization on the other hand increases with increase in substrate temperature.University Grants Commission for Centre of Advanced Studies in Physic

Large differences in regional precipitation change between a first and second 2 K of global warming

For adaptation and mitigation planning, stakeholders need reliable information about regional precipitation changes under different emissions scenarios and for different time periods. A significant amount of current planning effort assumes that each K of global warming produces roughly the same regional climate change. Here using 25 climate models, we compare precipitation responses with three 2 K intervals of global ensemble mean warming: a fast and a slower route to a first 2 K above pre-industrial levels, and the end-of-century difference between high-emission and mitigation scenarios. We show that, although the two routes to a first 2 K give very similar precipitation changes, a second 2 K produces quite a different response. In particular, the balance of physical mechanisms responsible for climate model uncertainty is different for a first and a second 2 K of warming. The results are consistent with a significant influence from nonlinear physical mechanisms, but aerosol and land-use effects may be important regionally

Partitioning clustering algorithms for protein sequence data sets

<p>Abstract</p> <p>Background</p> <p>Genome-sequencing projects are currently producing an enormous amount of new sequences and cause the rapid increasing of protein sequence databases. The unsupervised classification of these data into functional groups or families, clustering, has become one of the principal research objectives in structural and functional genomics. Computer programs to automatically and accurately classify sequences into families become a necessity. A significant number of methods have addressed the clustering of protein sequences and most of them can be categorized in three major groups: hierarchical, graph-based and partitioning methods. Among the various sequence clustering methods in literature, hierarchical and graph-based approaches have been widely used. Although partitioning clustering techniques are extremely used in other fields, few applications have been found in the field of protein sequence clustering. It is not fully demonstrated if partitioning methods can be applied to protein sequence data and if these methods can be efficient compared to the published clustering methods.</p> <p>Methods</p> <p>We developed four partitioning clustering approaches using Smith-Waterman local-alignment algorithm to determine pair-wise similarities of sequences. Four different sets of protein sequences were used as evaluation data sets for the proposed methods.</p> <p>Results</p> <p>We show that these methods outperform several other published clustering methods in terms of correctly predicting a classifier and especially in terms of the correctness of the provided prediction. The software is available to academic users from the authors upon request.</p

Long non-coding RNAs: spatial amplifiers that control nuclear structure and gene expression

Over the past decade, it has become clear that mammalian genomes encode thousands of long non-coding RNAs (lncRNAs), many of which are now implicated in diverse biological processes. Recent work studying the molecular mechanisms of several key examples — including Xist, which orchestrates X chromosome inactivation — has provided new insights into how lncRNAs can control cellular functions by acting in the nucleus. Here we discuss emerging mechanistic insights into how lncRNAs can regulate gene expression by coordinating regulatory proteins, localizing to target loci and shaping three-dimensional (3D) nuclear organization. We explore these principles to highlight biological challenges in gene regulation, in which lncRNAs are well-suited to perform roles that cannot be carried out by DNA elements or protein regulators alone, such as acting as spatial amplifiers of regulatory signals in the nucleus

A scientific critique of the two-degree climate change target

The world's governments agreed to limit global mean temperature change to below 2-derees C compared with pr-industrial levels in the years following the 2009 climate conference in Copenhagen. This 2-degrees C warming target is perceived by the pulic as a universally accepted goal, identified by scientists as a safe limit that avoids dangerous climate change. This perception is incorrect: no scientific assessment has clearly justified or defended the 2-degrees C target as a safe level of warming, and indeed, this is not a problem that science alone can address. We argue that global temperature is the best climate target quantity, but it is unclear what level can be consiered safe. The 2-degrees C target is useful for anchoring discussions, but has been ineffective in triggering the required emission reductions; debates on considering a lower target are strongly at odds with the current real-world level of action. These debates are moot, however, as the decisions that need to be taken now to limit warming to 1.5 or 2 degrees C are very similar. We need to agree how to start, not where to end mitigation

Allowable CO2 emissions based on regional and impact-related climate targets

This paper was accepted for publication in the journal Nature and the definitive published version is available at http://dx.doi.org/10.1038/nature16542© 2016 Macmillan Publishers Limited. All rights reserved. Global temperature targets, such as the widely accepted limit of an increase above pre-industrial temperatures of two degrees Celsius, may fail to communicate the urgency of reducing carbon dioxide (CO2) emissions. The translation of CO2 emissions into regional- and impact-related climate targets could be more powerful because such targets are more directly aligned with individual national interests. We illustrate this approach using regional changes in extreme temperatures and precipitation. These scale robustly with global temperature across scenarios, and thus with cumulative CO2 emissions. This is particularly relevant for changes in regional extreme temperatures on land, which are much greater than changes in the associated global mean