First Institute of Oceanography

Sensitive platform: The use of graphene oxide (GO) as a platform for the sensitive and selective detection of DNA and proteins is presented. The interaction of GO and dye-labeled single-stranded DNA leads to quenching of the dye fluorescence. Conversely, the presence of a target DNA or protein leads to the binding of the dye-labeled DNA and target, releasing the DNA from GO, thereby restoring the dye fluorescence (see picture).

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

Instantaneous frequency (IF) is necessary for understanding the detailed mechanisms for nonlinear and nonstationary processes. Historically, IF was computed from analytic signal (AS) through the Hilbert transform. This paper offers an overview of the difficulties involved in using AS, and two new methods to overcome the difficulties for computing IF. The first approach is to compute the quadrature (defined here as a simple 90° shift of phase angle) directly. The second approach is designated as the normalized Hilbert transform (NHT), which consists of applying the Hilbert transform to the empirically determined FM signals. Additionally, we have also introduced alternative methods to compute local frequency, the generalized zero-crossing (GZC), and the teager energy operator (TEO) methods. Through careful comparisons, we found that the NHT and direct quadrature gave the best overall performance. While the TEO method is the most localized, it is limited to data from linear processes, the GZC method is the most robust and accurate although limited to the mean frequency over a quarter wavelength of temporal resolution. With these results, we believe most of the problems associated with the IF determination are resolved, and a true time–frequency analysis is thus taking another step toward maturity.

published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire

Abstract Auf Graphenoxid (GO) beruht ein empfindliches und selektives Verfahren zum DNA‐ und Proteinnachweis. Durch die Wechselwirkung von GO mit einer farbstoffmarkierten Einzelstrang‐DNA wird die Fluoreszenz des Farbstoffs gelöscht. Sind Ziel‐DNAs oder Zielproteine vorhanden, binden sie an die farbstoffmarkierte DNA und spalten sie von GO ab, sodass sie erneut fluoresziert (siehe Bild). magnified image

The simultaneous entrapment of biological macromolecules and nanostructured silica-coated magnetite in sol-gel materials using a reverse-micelle technique leads to a bioactive, mechanically stable, nanometer-sized, and magnetically separable particles. These spherical particles have a typical diameter of 53 +/- 4 nm, a large surface area of 330 m(2)/g, an average pore diameter of 1.5 nm, a total pore volume of 1.427 cm(3)/g and a saturated magnetization (M(S)) of 3.2 emu/g. Peroxidase entrapped in these particles shows Michaelis-Mentan kinetics and high activity. The catalytic reaction will take place immediately after adding these particles to the reaction solution. These enzyme entrapping particles catalysts can be easily separated from the reaction mixture by simply using an external magnetic field. Experiments have proved that these catalysts have a long-term stability toward temperature and pH change, as compared to free enzyme molecules. To further prove the application of this novel magnetic biomaterial in analytical chemistry, a magnetic-separation immunoassay system was also developed for the quantitative determination of gentamicin. The calibration for gentamicin has a working range of 200-4000 ng/mL, with a detection limit of 160 ng/mL, which is close to that of the fluorescent polarization immunoassay (FPIA) using the same reactants.

Abstract. The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs.OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

A multi-dimensional ensemble empirical mode decomposition (MEEMD) for multi-dimensional data (such as images or solid with variable density) is proposed here. The decomposition is based on the applications of ensemble empirical mode decomposition (EEMD) to slices of data in each and every dimension involved. The final reconstruction of the corresponding intrinsic mode function (IMF) is based on a comparable minimal scale combination principle. For two-dimensional spatial data or images, f(x,y), we consider the data (or image) as a collection of one-dimensional series in both x-direction and y-direction. Each of the one-dimensional slices is decomposed through EEMD with the slice of the similar scale reconstructed in resulting two-dimensional pseudo-IMF-like components. This new two-dimensional data is further decomposed, but the data is considered as a collection of one-dimensional series in y-direction along locations in x-direction. In this way, we obtain a collection of two-dimensional components. These directly resulted components are further combined into a reduced set of final components based on a minimal-scale combination strategy. The approach for two-dimensional spatial data can be extended to multi-dimensional data. EEMD is applied in the first dimension, then in the second direction, and then in the third direction, etc., using the almost identical procedure as for the two-dimensional spatial data. A similar comparable minimal-scale combination strategy can be applied to combine all the directly resulted components into a small set of multi-dimensional final components. For multi-dimensional temporal-spatial data, EEMD is applied to time series of each spatial location to obtain IMF-like components of different time scales. All the ith IMF-like components of all the time series of all spatial locations are arranged to obtain ith temporal-spatial multi-dimensional IMF-like component. The same approach to the one used in temporal-spatial data decomposition is used to obtain the resulting two-dimensional IMF-like components. This approach could be extended to any higher dimensional temporal-spatial data.

The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s (IPCC in Climate change 2007: the scientific basis, Cambridge University Press, Cambridge, 2007). In Wu et al. (Proc Natl Acad Sci USA 104:14889–14894, 2007) we showed that the rapidity of the warming in the late twentieth century was a result of concurrence of a secular warming trend and the warming phase of a multidecadal (~65-year period) oscillatory variation and we estimated the contribution of the former to be about 0.08°C per decade since ~1980. Here we demonstrate the robustness of those results and discuss their physical links, considering in particular the shape of the secular trend and the spatial patterns associated with the secular trend and the multidecadal variability. The shape of the secular trend and rather globally-uniform spatial pattern associated with it are both suggestive of a response to the buildup of well-mixed greenhouse gases. In contrast, the multidecadal variability tends to be concentrated over the extratropical Northern Hemisphere and particularly over the North Atlantic, suggestive of a possible link to low frequency variations in the strength of the thermohaline circulation. Depending upon the assumed importance of the contributions of ocean dynamics and the time-varying aerosol emissions to the observed trends in global-mean surface temperature, we estimate that up to one third of the late twentieth century warming could have been a consequence of natural variability.

From the Reynolds stress expression, the wave‐induced vertical viscosity (or diffusivity) Bv is defined, which can be used as a parameter to estimate the strength of wave‐induced mixing. In addition, a parameter D 5 is introduced to represent a wave‐induced mixing penetration depth. The global distribution of Bv averaged over the upper 20 m is calculated and its latitudinal transects in boreal summer and winter is discussed. The results show that in summer the wave‐induced mixing is strong in the southern oceans south of 30°S, and in winter it is strong in the north Pacific and the north Atlantic north of 30°N, as well as in the southern oceans south of 40°S. Adding Bv to the vertical diffusivity in a global ocean circulation model yields a temperature structure in the upper 100 m that is closer to the observed climatology than a model without the wave‐induced mixing.

We have proved that functionalized nanoscale graphene oxide can protect oligonucleotides from enzymatic cleavage and efficiently deliver oligonucleotides into cells.

In this communication, we report a simple, but highly adaptable, method of constructing selective target-responsive hydrogels using DNA aptamers. The simplicity of the design is accomplished by using linear polymer chains as the hydrogel backbone and a DNA aptamer as the cross-linker. In this design, competitive binding of target to the aptamer causes the decrease of cross-linking density and, hence, dissolution of the hydrogel. The adaptability of this strategy for therapeutic applications was demonstrated using two different types of targets, small molecules and proteins. Our results indicated that this molecular engineering provides a highly selective and controllable release system whereby efficient release of therapeutic agents can occur at specific environments in which the target biomarker is found.

We revisit the challenges and prospects for ocean circulation models following Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models Fox-Kemper et al. Ocean Circulation Models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.

Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth, upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.

The impacts of microplastics on coral reefs are gaining attention due to findings that microplastics affect coral health. This work investigated the distribution and characteristics of microplastics in the seawater, fish, and corals in 3 atolls from the Xisha Islands of South China Sea. In the seawater samples, microplastics were detected in the outer reef slopes, reef flats, and lagoons with abundances ranging from 0.2 to 11.2, 1.0 to 12.2, and 1.0 to 45.2 items L–1, respectively. Microplastic abundance was 0–12.0 items individual–1 (0–4.7 items g–1) in fish and 1.0–44.0 items individual–1(0.02–1.3 items g–1) in coral. The predominant shape and polymer of microplastics in seawater, fish, and coral were fibrous rayon and polyethylene terephthalate (PET). Microplastic sizes primarily ranged from 20–330 μm in both the seawater and fish, while there were relatively more 1–5 mm microplastics in the corals. The shape, size, color, and polymer type distribution patterns of microplastics in seawater more closely resembled those in fish gills than those in fish gastrointestinal tracts or coral samples. This study shows that microplastics are abundant in these coral reef systems and they are captured by fish or “trapped” by corals.

This communication describes the design of a novel and general bioresponsive controlled-release mesoporous silica (MS) nanoparticles system based on aptamer-target interactions. In this system, the pores of MS were capped with Au nanoparticles modified with aptamer (ATP aptamer in this case). By a competitive displacement reaction, the Au nanoparticles were uncapped in the presence of ATP molecule, and the cargo was released. Our results demonstrated that the aptamer-target interaction may be a promising route for the design of custom-made controlled-release nanodevices specifically governed by target biomolecules. Since aptamers have been obtained for a broad range of targets, including several cancer biomarkers, we believe that this aptamer-based controlled-release system should have an equally broad spectrum of applications.

green tides in the Yellow Sea, China, which have been occurring since 2007, are a serious environmental problem attracting worldwide attention. Despite extensive research, the outbreak mechanisms have not been fully understood. Comprehensive analysis of anthropogenic and natural biotic and abiotic factors reveals that human activities, regional physicochemical conditions and algal physiological characteristics as well as ocean warming and biological interactions (with microorganism or other macroalgae) are closely related to the occurrence of green tides. Dynamics of these factors and their interactions could explain why green tides suddenly occurred in 2007 and decreased abruptly in 2017. Moreover, the consequence of green tides is serious. The decay of macroalgal biomass could result in hypoxia and acidification, possibly induce red tide and even have a long-lasting impact on coastal carbon cycles and the ecosystem. Accordingly, corresponding countermeasures have been proposed in our study for future reference in ecosystem management strategies and sustainable development policy.

It has been predicted that the Arctic Ocean will sequester much greater amounts of carbon dioxide (CO2) from the atmosphere as a result of sea ice melt and increasing primary productivity. However, this prediction was made on the basis of observations from either highly productive ocean margins or ice-covered basins before the recent major ice retreat. We report here a high-resolution survey of sea-surface CO2 concentration across the Canada Basin, showing a great increase relative to earlier observations. Rapid CO2 invasion from the atmosphere and low biological CO2 drawdown are the main causes for the higher CO2, which also acts as a barrier to further CO2 invasion. Contrary to the current view, we predict that the Arctic Ocean basin will not become a large atmospheric CO2 sink under ice-free conditions.

In this work, we report a facile approach for imprinting protein based on self-polymerization of dopamine in the presence of template protein on the Fe3O4 nanoparticles (NPs) surface. Dopamine, commonly known as a neurotransmitter, is also a small-molecule mimic of the adhesive proteins of mussels. Self-polymerization of dopamine can produce a thin polydopamine (PDA) layer on Fe3O4 NPs surface. During the self-polymerization of dopamine, some template protein molecules were embedded in the PDA layer. After the removal of these embedded protein molecules, the protein imprinted sites are created. The prepared imprinted Fe3O4@PDA NPs shows high binding capacity and acceptable specific recognition behavior towards template proteins.

In this paper, we present a technique for the preparation of polymer nanowires with the protein molecule imprinted and binding sites at surface. These surface imprinting nanowires exhibit highly selective recognition for a variety of template proteins, including albumin, hemoglobin, and cytochrome c. This recognition may be through a multistep adsorption, with the specificity conferred by hydrogen bonding and shape selectivity. Due to the protein imprinted sites are located at, or close to, the surface; these imprinted nanowires have a good site accessibility toward the target protein molecules. Furthermore, the large surface area of the nanowires results in large protein molecule binding capacity of the imprinted nanowires.