A new phase in the production of quality-controlled sea level data

Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections

An Improved and Homogeneous Altimeter Sea Level Record from the ESA Climate Change Initiative

Sea Level is a very sensitive index of climate change since it integrates the impacts of ocean warming and ice mass loss from glaciers and the ice sheets. Sea Level has been listed as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). During the past 25 years, the sea level ECV has been measured from space by different altimetry missions that have provided global and regional observations of sea level variations. As part of the Climate Change Initiative (CCI) program of the European Space Agency (ESA) (established in 2010), the Sea Level project (SL_cci) aimed at providing an accurate and homogeneous long-term satellite-based sea level record. At the end of the first phase of the project (2010-2013), an initial version (v1.1) of the sea level ECV has been made available to users (Ablain et al., 2015). During the second phase (2014-2017), improved altimeter standards have been selected to produce new sea level products (called SL_cci v2.0) based on 9 altimeter missions for the period 1993-2015 (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). Corresponding orbit solutions, geophysical corrections and altimeter standards used in this v2.0 dataset are described in details in Quartly et al. (2017). The present paper focuses on the description of the SL_cci v2.0 ECV and associated uncertainty and discusses how it has been validated. Various approaches have been used for the quality assessment such as internal validation, comparisons with sea level records from other groups and with in-situ measurements, sea level budget closure analyses and comparisons with model outputs. Compared to the previous version of the sea level ECV, we show that use of improved geophysical corrections, careful bias reduction between missions and inclusion of new altimeter missions lead to improved sea level products with reduced uncertainties at different spatial and temporal scales. However, there is still room for improvement since the uncertainties remain larger than the GCOS requirements. Perspectives for subsequent evolutions are also discussed

Uncertainty information in climate data records from Earth observation

Climate data records (CDRs) derived from Earth observation (EO) should include rigorous uncertainty information, to support application of the data in policy, climate modelling and numerical weather prediction reanalysis. Uncertainty, error and quality are distinct concepts, and CDR products should follow international norms for presenting quantified uncertainty. Ideally, uncertainty should be quantified per datum in a CDR, and the uncertainty estimates should be able to discriminate more and less certain data with confidence. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence held in the uncertainty estimate provided, or indicators of conditions violating retrieval assumptions). Errors have many sources and some are correlated across a wide range of time and space scales. Error effects that contribute negligibly to the total uncertainty in a single satellite measurement can be the dominant sources of uncertainty in a CDR on large space and long time scales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. Characterisation of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation, where possible. These principles are quite general, but the form of uncertainty information appropriate to different essential climate variables (ECVs) is highly variable, as confirmed by a quick review of the different approaches to uncertainty taken across different ECVs in the European Space Agency’s Climate Change Initiative. User requirements for uncertainty information can conflict with each other, and again a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight recommendations for good practice in providing and communicating uncertainty in EO-based climate data records

Massively parallel reporter assays of melanoma risk variants identify MX2 as a gene promoting melanoma

Genome-wide association studies (GWAS) have identified ~20 melanoma susceptibility loci, most of which are not functionally characterized. Here we report an approach integrating massively-parallel reporter assays (MPRA) with cell-type-specific epigenome and expression quantitative trait loci (eQTL) to identify susceptibility genes/variants from multiple GWAS loci. From 832 high-LD variants, we identify 39 candidate functional variants from 14 loci displaying allelic transcriptional activity, a subset of which corroborates four colocalizing melanocyte cis-eQTL genes. Among these, we further characterize the locus encompassing the HIV-1 restriction gene, MX2 (Chr21q22.3), and validate a functional intronic variant, rs398206. rs398206 mediates the binding of the transcription factor, YY1, to increase MX2 levels, consistent with the cis-eQTL of MX2 in primary human melanocytes. Melanocyte-specific expression of human MX2 in a zebrafish model demonstrates accelerated melanoma formation in a BRAFV600E background. Our integrative approach streamlines GWAS follow-up studies and highlights a pleiotropic function of MX2 in melanoma susceptibility

Induction of autophagy is a key component of all-trans-retinoic acid-induced differentiation in leukemia cells and a potential target for pharmacological modulation

Acute myeloid leukemia (AML) is characterized by the accumulation of immature blood cell precursors in the bone marrow. Pharmacologically overcoming the differentiation block in this condition is an attractive therapeutic avenue, which has achieved success only in a subtype of AML, acute promyelocytic leukemia (APL). Attempts to emulate this success in other AML subtypes have thus far been unsuccessful. Autophagy is a conserved protein degradation pathway with important roles in mammalian cell differentiation, particularly within the hematopoietic system. In the study described here, we investigated the functional importance of autophagy in APL cell differentiation. We found that autophagy is increased during all-trans-retinoic acid (ATRA)-induced granulocytic differentiation of the APL cell line NB4 and that this is associated with increased expression of LC3II and GATE-16 proteins involved in autophagosome formation. Autophagy inhibition, using either drugs (chloroquine/3-methyladenine) or short-hairpin RNA targeting the essential autophagy gene ATG7, attenuates myeloid differentiation. Importantly, we found that enhancing autophagy promotes ATRA-induced granulocytic differentiation of an ATRA-resistant derivative of the non-APL AML HL60 cell line (HL60-Diff-R). These data support the development of strategies to stimulate autophagy as a novel approach to promote differentiation in AML

Neuronal activity disrupts myelinated axon integrity in the absence of NKCC1b

Through a genetic screen in zebrafish, we identified a mutant with disruption to myelin in both the CNS and PNS caused by a mutation in a previously uncharacterized gene, slc12a2b, predicted to encode a Na+, K+, and Cl− (NKCC) cotransporter, NKCC1b. slc12a2b/NKCC1b mutants exhibited a severe and progressive pathology in the PNS, characterized by dysmyelination and swelling of the periaxonal space at the axon–myelin interface. Cell-type–specific loss of slc12a2b/NKCC1b in either neurons or myelinating Schwann cells recapitulated these pathologies. Given that NKCC1 is critical for ion homeostasis, we asked whether the disruption to myelinated axons in slc12a2b/NKCC1b mutants is affected by neuronal activity. Strikingly, we found that blocking neuronal activity completely prevented and could even rescue the pathology in slc12a2b/NKCC1b mutants. Together, our data indicate that NKCC1b is required to maintain neuronal activity–related solute homeostasis at the axon–myelin interface, and the integrity of myelinated axons

Stress from Nucleotide Depletion Activates the Transcriptional Regulator HEXIM1 to Suppress Melanoma

Studying cancer metabolism gives insight into tumorigenic survival mechanisms and susceptibilities. In melanoma, we identify HEXIM1, a transcription elongation regulator, as a melanoma tumor suppressor that responds to nucleotide stress. HEXIM1 expression is low in melanoma. Its overexpression in a zebrafish melanoma model suppresses cancer formation, while its inactivation accelerates tumor onset in vivo. Knockdown of HEXIM1 rescues zebrafish neural crest defects and human melanoma proliferation defects that arise from nucleotide depletion. Under nucleotide stress, HEXIM1 is induced to form an inhibitory complex with P-TEFb, the kinase that initiates transcription elongation, to inhibit elongation at tumorigenic genes. The resulting alteration in gene expression also causes anti-tumorigenic RNAs to bind to and be stabilized by HEXIM1. HEXIM1 plays an important role in inhibiting cancer cell-specific gene transcription while also facilitating anti-cancer gene expression. Our study reveals an important role for HEXIM1 in coupling nucleotide metabolism with transcriptional regulation in melanoma

Comparative study of fungal cell disruption—scope and limitations of the methods

Simple and effective protocols of cell wall disruption were elaborated for tested fungal strains: Penicillium citrinum, Aspergillus fumigatus, Rhodotorula gracilis. Several techniques of cell wall disintegration were studied, including ultrasound disintegration, homogenization in bead mill, application of chemicals of various types, and osmotic shock. The release of proteins from fungal cells and the activity of a cytosolic enzyme, glucose-6-phosphate dehydrogenase, in the crude extracts were assayed to determine and compare the efficacy of each method. The presented studies allowed adjusting the particular method to a particular strain. The mechanical methods of disintegration appeared to be the most effective for the disintegration of yeast, R. gracilis, and filamentous fungi, A. fumigatus and P. citrinum. Ultrasonication and bead milling led to obtaining fungal cell-free extracts containing high concentrations of soluble proteins and active glucose-6-phosphate dehydrogenase systems

Zebrafish: a vertebrate tool for studying basal body biogenesis, structure, and function.

Understanding the role of basal bodies (BBs) during development and disease has been largely overshadowed by research into the function of the cilium. Although these two organelles are closely associated, they have specific roles to complete for successful cellular development. Appropriate development and function of the BB are fundamental for cilia function. Indeed, there are a growing number of human genetic diseases affecting ciliary development, known collectively as the ciliopathies. Accumulating evidence suggests that BBs establish cell polarity, direct ciliogenesis, and provide docking sites for proteins required within the ciliary axoneme. Major contributions to our knowledge of BB structure and function have been provided by studies in flagellated or ciliated unicellular eukaryotic organisms, specifically Tetrahymena and Chlamydomonas. Reproducing these and other findings in vertebrates has required animal in vivo models. Zebrafish have fast become one of the primary organisms of choice for modeling vertebrate functional genetics. Rapid ex-utero development, proficient egg laying, ease of genetic manipulation, and affordability make zebrafish an attractive vertebrate research tool. Furthermore, zebrafish share over 80 % of disease causing genes with humans. In this article, we discuss the merits of using zebrafish to study BB functional genetics, review current knowledge of zebrafish BB ultrastructure and mechanisms of function, and consider the outlook for future zebrafish-based BB studies

Causes of the regional variability in observed sea level, sea surface temperature and ocean colour over the period 1993-2011

We analyse the regional variability in observed sea surface height (SSH), sea surface temperature (SST) and ocean colour (OC) from the ESA Climate Change Initiative (CCI) datasets over the period 1993-2011. The analysis focuses on the signature of the ocean large-scale climate fluctuations driven by the atmospheric forcing and do not address the mesoscale variability. We use the ECCO version 4 ocean reanalysis to unravel the role of ocean transport and surface buoyancy fluxes in the observed SSH, SST and OC variability. We show that the SSH regional variability is dominated by the steric effect (except at high latitude) and is mainly shaped by ocean heat transport divergences with some contributions from the surface heat fluxes forcing that can be significant regionally (confirming earlier results). This is in contrast with the SST regional variability, which is the result of the compensation of surface heat fluxes by ocean heat transport in the mixed layer and arises from small departures around this background balance. Bringing together the results of SSH and SST analyses, we show that SSH and SST bear some common variability. This is because both SSH and SST variability show significant contributions from the surface heat fluxes forcing. It is evidenced by the high correlation between SST and buoyancy forced SSH almost everywhere in the ocean except at high latitude. OC, which is determined by phytoplankton biomass, is governed by the availability of light and nutrients that essentially depend on climate fluctuations. For this reason OC show significant correlation with SST and SSH. We show that the correlation with SST display the same pattern as the correlation with SSH with a negative correlation in the tropics and subtropics and a positive correlation at high latitude. We discuss the reasons for this pattern