222 research outputs found

    Nanocomposites with functionalised polysaccharide nanocrystals through aqueous free radical polymerisation promoted by ozonolysis

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    Cellulose nanocrystals (CNC) and starch nanocrystals (SNC) were grafted by ozone-initiated free-radical polymerisation of styrene in a heterogeneous medium. Surface functionalisation was confirmed by infrared spectroscopy, contact angle measurements, and thermogravimetric and elemental analysis. X-ray diffraction and scanning electron microscopy showed that there was no significant change in the morphology or crystallinity of the nanoparticles following ozonolysis. The grafting efficiency, quantified by 13C NMR, was greater for SNC, with a styrene/anhydroglucose ratio of 1.56 compared to 0.25 for CNC. The thermal stability improved by 100 °C. The contact angles were 97° and 78° following the SNC and CNC grafting, respectively, demonstrating the efficiency of the grafting in changing the surface properties even at low levels of surface substitution. The grafting increased the compatibility with the polylactide, and produced nanocomposites with improved water vapour barrier properties. Ozone-mediated grafting is thus a promising approach for surface functionalisation of polysaccharide nanocrystals

    Turbulent Oscillating Channel Flow Subjected to Wind Stress

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    Using machine learning and Biogeochemical-Argo (BGC-Argo) floats to assess biogeochemical models and optimize observing system design

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    Numerical models of ocean biogeochemistry are becoming the major tools used to detect and predict the impact of climate change on marine resources and to monitor ocean health. However, with the continuous improvement of model structure and spatial resolution, incorporation of these additional degrees of freedom into fidelity assessment has become increasingly challenging. Here, we propose a new method to provide information on the model predictive skill in a concise way. The method is based on the conjoint use of a k-means clustering technique, assessment metrics, and Biogeochemical-Argo (BGC-Argo) observations. The k-means algorithm and the assessment metrics reduce the number of model data points to be evaluated. The metrics evaluate either the model state accuracy or the skill of the model with respect to capturing emergent properties, such as the deep chlorophyll maximums and oxygen minimum zones. The use of BGC-Argo observations as the sole evaluation data set ensures the accuracy of the data, as it is a homogenous data set with strict sampling methodologies and data quality control procedures. The method is applied to the Global Ocean Biogeochemistry Analysis and Forecast system of the Copernicus Marine Service. The model performance is evaluated using the model efficiency statistical score, which compares the model–observation misfit with the variability in the observations and, thus, objectively quantifies whether the model outperforms the BGC-Argo climatology. We show that, overall, the model surpasses the BGC-Argo climatology in predicting pH, dissolved inorganic carbon, alkalinity, oxygen, nitrate, and phosphate in the mesopelagic and the mixed layers as well as silicate in the mesopelagic layer. However, there are still areas for improvement with respect to reducing the model–data misfit for certain variables such as silicate, pH, and the partial pressure of CO2 in the mixed layer as well as chlorophyll-a-related, oxygen-minimum-zone-related, and particulate-organic-carbon-related metrics. The method proposed here can also aid in refining the design of the BGC-Argo network, in particular regarding the regions in which BGC-Argo observations should be enhanced to improve the model accuracy via the assimilation of BGC-Argo data or process-oriented assessment studies. We strongly recommend increasing the number of observations in the Arctic region while maintaining the existing high-density of observations in the Southern Oceans. The model error in these regions is only slightly less than the variability observed in BGC-Argo measurements. Our study illustrates how the synergic use of modeling and BGC-Argo data can both provide information about the performance of models and improve the design of observing systems.</p

    Activity Dependent Protein Degradation Is Critical for the Formation and Stability of Fear Memory in the Amygdala

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    Protein degradation through the ubiquitin-proteasome system [UPS] plays a critical role in some forms of synaptic plasticity. However, its role in memory formation in the amygdala, a site critical for the formation of fear memories, currently remains unknown. Here we provide the first evidence that protein degradation through the UPS is critically engaged at amygdala synapses during memory formation and retrieval. Fear conditioning results in NMDA-dependent increases in degradation-specific polyubiquitination in the amygdala, targeting proteins involved in translational control and synaptic structure and blocking the degradation of these proteins significantly impairs long-term memory. Furthermore, retrieval of fear memory results in a second wave of NMDA-dependent polyubiquitination that targets proteins involved in translational silencing and synaptic structure and is critical for memory updating following recall. These results indicate that UPS-mediated protein degradation is a major regulator of synaptic plasticity necessary for the formation and stability of long-term memories at amygdala synapses

    E-cadherin expression and bromodeoxyuridine incorporation during development of ovarian inclusion cysts in age-matched breeder and incessantly ovulated CD-1 mice

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    BACKGROUND: Female CD-1/Swiss Webster mice subjected to incessant ovulation for 8 months and 12-month breeder mice both developed ovarian inclusion cysts similar to serous cystadenomas. The majority of cysts appeared to be dilated rete ovarii tubules, but high ovulation number resulted in more cortical inclusion cysts. We hypothesized that comparison of inclusion cyst pathology in animals of the same age, but with differences in total lifetime ovulation number, might allow us to determine distinguishing characteristics of the two types of cyst. METHODS: Ovaries from breeder mice (BR) or females subjected to incessant ovulation (IO) were compared at 6-, 9- and 12-months of age. Ovaries were serially sectioned and cysts characterized with regard to location and histology, E-cadherin immunoreactivity and rates of BrdU incorporation. RESULTS: Inclusion cysts developed with age in BR and IO ovaries. The majority of cysts were connected to the ovarian hilus. Two cortical inclusion cysts were observed in ten IO ovaries and one in ten BR ovaries. Low or no E-cadherin immuno-staining was seen in the OSE of all mice studied. Conversely, strong membrane immuno-staining was observed in rete ovarii epithelial cells. Variable E-cadherin immunoreactivity was seen in cells of hilar inclusion cysts, with strong staining observed in cuboidal ciliated cells and little or no staining in flat epithelial cells. Two of the three cortical cysts contained papillae, which showed E-cadherin immuno-staining at the edge of cells. However hilar and cortical cysts were not distinguishable by morphology, cell type or E-cadherin immunoreactivity. BrdU incorporation in cyst cells (1.4% [95% CI: 1.0 to 2.1]) was greater than in OSE (0.7% [95% CI: 0.4 to 1.2]) and very few BrdU-labeled cells were observed in rete ovarii at any age. Incessant ovulation significantly increased BrdU incorporation in OSE of older animals. CONCLUSION: These experiments confirm ovarian inclusion cysts develop with age in the CD-1 mouse strain, irrespective of total ovulation burden. We conclude longer periods of incessant ovulation do not lead to significant changes in inclusion cyst formation or steroidogenesis in CD-1 mice and inclusion cyst type can not be distinguished by morphology, cell proliferation rate or E-cadherin immunoreactivity
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