Designer Supersurafaces via Bioinspiration and Biomimetics for Dental materials and Structures

The design of surfaces and interfaces gives rise to superior qualities and properties to materials and structures. The interface between biology and materials in nature is being closely examined at the smallest scales for a number of significant reasons. It is recognised that the properties of surfaces have definite biological effects that can be harnessed in clinical regeneration biology. Also the deeper understanding of surface interactions between cells and matrices in human biology is spurring the fabrication of biomimetic and bioinspired versions of these natural designs. The new emerging science of bioinspired surface engineering is helping to improve clinical performances for biomaterials and biostructures because it resolves the problems necessary to optimise integration of implant biomaterials and structures. One of the major developments is the use of surface topography, which is now being exploited for microbial control, steering stem cell behaviours in proliferation and differentiation and adhesive surfaces for better bonding with tissues. In this Chapter we will explore the status of these super surfaces and examine the possibilities for the next generation of dental biomaterials and implants.published_or_final_versio

High Quality Bioreplication of Intricate nanostructures from a Fragile Gecko Skin Surface with Bactericidal Properties

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Estimating Entropy of Liquids from Atom-Atom Radial Distribution Functions: Silica, Beryllium Fluoride and Water

Molecular dynamics simulations of water, liquid beryllium fluoride and silica melt are used to study the accuracy with which the entropy of ionic and molecular liquids can be estimated from atom-atom radial distribution function data. All three systems are known to display similar liquid-state thermodynamic and kinetic anomalies due to a region of anomalous excess entropy behaviour where entropy rises on isothermal compression. The pair correlation entropy is demonstrated to be sufficiently accurate that the density-temperature regime of anomalous behaviour as well as the strength of the entropy anomaly can be predicted reliably for both ionic melts as well as different rigid-body pair potentials for water. Errors in the total thermodynamic entropy for ionic melts due to the pair correlation approximation are of the order of 10% or less for most state points but can be significantly larger in the anomalous regime at very low temperatures. In the case of water, as expected given the rigid-body constraints for a molecular liquids, the pair correlation approximation causes significantly larger errors, between 20 and 30%, for most state points. Comparison of the excess entropy, Se, of ionic melts with the pair correlation entropy, S2, shows that the temperature dependence of Se is well described by T ??2=5 scaling across both the normal and anomalous regimes, unlike in the case of S2. As a function of density, the Se(rho) curves shows only a single maximum while the S2(rho) curves show both a maximum and a minimum. These differences in the behaviour of S2 and Se are due to the fact that the residual multiparticle entropy, delta(S) = Se - S2, shows a strong negative correlation with tetrahedral order in the anomalous regime.Comment: 30 pages, 8 figure

Satellite observations are needed to understand ocean acidification and multi-stressor impacts on fish stocks in a changing Arctic Ocean

This is the final version. Available from Frontiers Media via the DOI in this record. It is widely projected that under future climate scenarios the economic importance of Arctic Ocean fish stocks will increase. The Arctic Ocean is especially vulnerable to ocean acidification and already experiences low pH levels not projected to occur on a global scale until 2100. This paper outlines how ocean acidification must be considered with other potential stressors to accurately predict movement of fish stocks toward, and within, the Arctic and to inform future fish stock management strategies. First, we review the literature on ocean acidification impacts on fish, next we identify the main obstacles that currently preclude ocean acidification from Arctic fish stock projections. Finally, we provide a roadmap to describe how satellite observations can be used to address these gaps: improve knowledge, inform experimental studies, provide regional assessments of vulnerabilities, and implement appropriate management strategies. This roadmap sets out three inter-linked research priorities: (1) Establish organisms and ecosystem physiochemical baselines by increasing the coverage of Arctic physicochemical observations in both space and time; (2) Understand the variability of all stressors in space and time; (3) Map life histories and fish stocks against satellite-derived observations of stressors.European Space AgencyAXA XL Ocean Risk Scholarshi

Adverse prognostic and predictive significance of low DNA-dependent protein kinase catalytic subunit (DNA-PKcs) expression in early-stage breast cancers

Background: DNA-dependent protein kinase catalytic subunit (DNA-PKcs), a serine threonine kinase belonging to the PIKK family (phosphoinositide 3-kinase-like-family of protein kinase), is a critical component of the non-homologous end joining (NHEJ) pathway required for the repair of DNA double strand breaks. DNA-PKcs may be involved in breast cancer pathogenesis. Methods: We evaluated clinicopathological significance of DNA-PKcs protein expression in 1161 tumours and DNA-PKcs mRNA expression in 1950 tumours. We correlated DNA-PKcs to other markers of aggressive phenotypes, DNA repair, apoptosis and cell cycle regulation. Results: Low DNA-PKcs protein expression was associated with higher tumour grade, higher mitotic index, tumour de-differentiation and tumour type (ps<0.05). Absence of BRCA1, low XRCC1/SMUG1/APE1/Polβ were also more likely in low DNA-PKcs expressing tumours (ps<0.05). Low DNA-PKcs protein expression was significantly associated with worse breast cancer specific survival (BCCS) in univariate and multivariate analysis (ps<0.01). At the mRNA level, low DNA-PKcs was associated with PAM50.Her2 and PAM50.LumA molecular phenotypes (ps<0.01) and poor BCSS. In patients with ER positive tumours who received endocrine therapy, low DNA-PKcs (protein and mRNA) was associated with poor survival. In ER negative patients, low DNA-PKcs mRNA remains significantly associated with adverse outcome. Conclusions: Our study suggests that low DNA-PKcs expression may have prognostic and predictive significance in breast cancers

Observing temporally varying synoptic‐scale total alkalinity and dissolved inorganic carbon in the Arctic Ocean

This is the final version. Available from Wiley via the DOI in this record. Data Availability Statement: The matchup database “OceanSODA-MDB” which was used in the algorithm evaluation is available at https:// data-cersat.ifremer.fr/data/ocean-carbonate/oceansoda-mmdb/ (Land et al., 2023; Land & Piollé, 2022). The python code used to run the analysis can be found at https://doi.org/10.5281/zenodo.10067204 (Green et al., 2023) and was adapted from DOI: https://doi.org/10.5281/zenodo.10069611 (Sims et al., 2022).The long-term absorption by the oceans of atmospheric carbon dioxide is leading to the slow decline of ocean pH, a process termed ocean acidification (OA). The Arctic is a challenging region to gather enough data to examine the changes in carbonate chemistry over sufficient scales. However, algorithms that calculate carbonate chemistry parameters from more frequently measured parameters, such as temperature and salinity, can be used to fill in data gaps. Here, these published algorithms were evaluated against in situ measurements using different data input types (data from satellites or in situ re-analysis climatologies) across the Arctic Ocean. With the lowest uncertainties in the Atlantic influenced Seas (AiS), where re-analysis inputs achieved total alkalinity estimates with Root Mean Squared Deviation (RMSD) of 21 μmol kg−1 and a bias of 2 μmol kg−1 (n = 162) and dissolved inorganic carbon RMSD of 24 μmol kg−1 and bias of −14 μmol kg−1 (n = 262). AiS results using satellite observation inputs show similar bias but larger RMSD, although due to the shorter time span of available satellite observations, more contemporary in situ data would provide further assessment and improvement. Synoptic-scale observations of surface water carbonate conditions in the Arctic are now possible to monitor OA, but targeted in situ data collection is needed to enable the full exploitation of satellite observation-based approaches.European Space AgencyAXA XLJoint Transnational Call on Next Generation Climate Science in Europe for the Ocea

Partonic description of a supersymmetric p-brane

We consider supersymmetric extensions of a recently proposed partonic description of a bosonic p-brane which reformulates the Nambu-Goto action as an interacting multi-particle action with Filippov-Lie algebra gauge symmetry. We construct a worldline supersymmetric action by postulating, among others, a p-form fermion. Demanding a local worldline supersymmetry rather than the full worldvolume supersymmetry, we circumvent a known no-go theorem against the construction of a Ramond-Neveu-Schwarz supersymmetric action for a p-brane of p>1. We also derive a spacetime supersymmetric Green-Schwarz extension from the preexisting kappa-symmetric action.Comment: 1+16 pages, no figure; References added and Concluding section expanded. Final version to appear in JHE

Application of immortalized mouse dental papilla cells for tooth bioengineering

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