Load effect characterization under traffic flow has received tremendous attention in bridge engineering, and uncertainty quantification (UQ) of load effect is critical in the inference process. Bayesian probabilistic approach is developed to overcome the unreliable issue caused by negligence of uncertainty of parametric and modeling aspects. Stochastic traffic load simulation is conducted by embedding the random inflow component into the Nagel–Schreckenberg (NS) model, and load effects are calculated by stochastic traffic load samples and influence lines. Two levels of UQ are performed for traffic load effect characterization: at parametric level of UQ, not only the optimal parameter values but also the associated uncertainties are identified; at model level of UQ, rather than using a single prescribed probability model for load effects, a set of probability distribution model candidates is proposed, and model probability of each candidate is evaluated for selecting the most suitable/plausible probability distribution model. Analytic work was done to give closed-form solutions for the expression involved in both parametric and model UQ. In the simulated examples, the efficiency and robustness of the proposed approach are firstly validated, and UQ are performed to different load effect data achieved by varying the structural span length under the changing total traffic volume. It turns out that the uncertainties of load effects are traffic-specific and response-specific, so it is important to conduct UQ of load effects under different traffic scenarios by using the developed approach.
Purpose
Osseointegration at the titanium surface-bone interface is one of the key factors affecting the success rate of dental implants. However, the titanium surface always forms a passive oxide layer and impacts bone marrow–derived mesenchymal stem cell (BMSC) osteogenic differentiation after exposure to the atmosphere, which further leads to poor osseointegration. Given that wet storage helps prevent titanium aging and that weakly alkaline conditions stimulate BMSC osteogenic differentiation, the aim of the present study was to explore whether sodium bicarbonate, a well-known hydrogen ion (pH) buffer, forms an alkaline microenvironment on titanium surfaces to promote BMSC osteogenic differentiation.
Material and methods
In this work, sand-blasted and acid-etched (SLA) titanium discs were soaked in 20 mM, 50 mM, 100 mM, and 200 mM sodium bicarbonate at room temperature for 5 min without rinsing. The influence of this surface modification on BMSC adhesion, proliferation, and osteogenic differentiation was measured. Additionally, cellular osteogenic differentiation–associated signaling pathways were evaluated.
Results
We showed that titanium discs treated with sodium bicarbonate created an extracellular environment with a higher pH for BMSCs than the normal physiological value for 5 days, strongly promoting BMSC osteogenic differentiation via the activation of integrin-focal adhesion kinase-alkaline phosphatase (Itg-FAK-ALP). In addition, the proliferation and adhesion of BMSCs were increased after alkaline treatment. These cellular effects were most significant with 100 mM sodium bicarbonate.
Conclusion
The results indicated that the titanium surface treated with sodium bicarbonate improved BMSC osteogenic differentiation mainly by creating an alkaline microenvironment, which further activated the Itg-FAK-ALP signaling pathway.
Clinical relevance
Surfaces modified with 100 mM sodium bicarbonate had the highest initial pH value and thus showed the greatest potential to improve BMSC performance on titanium surfaces, identifying a novel conservation method for dental implants.
Nano-engineering-based tissue regeneration and local therapeutic delivery strategies show significant potential to reduce the health and economic burden associated with craniofacial defects, including traumas and tumours. Critical to the success of such nano-engineered non-resorbable craniofacial implants include load-bearing functioning and survival in complex local trauma conditions. Further, race to invade between multiple cells and pathogens is an important criterion that dictates the fate of the implant. In this pioneering review, we compare the therapeutic efficacy of nano-engineered titanium-based craniofacial implants towards maximised local therapy addressing bone formation/resorption, soft-tissue integration, bacterial infection and cancers/tumours. We present the various strategies to engineer titanium-based craniofacial implants in the macro-, micro- and nano-scales, using topographical, chemical, electrochemical, biological and therapeutic modifications. A particular focus is electrochemically anodised titanium implants with controlled nanotopographies that enable tailored and enhanced bioactivity and local therapeutic release. Next, we review the clinical translation challenges associated with such implants. This review will inform the readers of the latest developments and challenges related to therapeutic nano-engineered craniofacial implants.
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