Sensitivity Analysis and Optimal Shape Design for Bone-Prosthesis Interfaces in a Femoral Head Surface Replacement

A numerical optimization procedure has been applied for the shape optimal design of a femoral head surface replacement. The failure modes of the prosthesis that were considered in the formulation of the objective functions concerned the interface stress magnitude and the bone remodelling activity beneath the implant. In order to find a compromising solution between different requirements demanded by the two objective functions, a two step optimization procedure has been developed. Through step 1 the minimization of interface stress was achieved, through step 2 the minimization of bone remodelling was achieved with constraints on interface stresses. The results obtained provided an optimal design that generates limited bone remodelling activity with controlled interface stress distribution. The computational procedure was based on the application of the finite element method, linked to a mathematical programming package and a design sensitivity analysis package.     

Bone remodelling around the tibia due to total ankle replacement: effects of implant material and implant–bone interfacial conditions

Abstract

One of the major causes of implant loosening is due to excessive bone resorption surrounding the implant due to bone remodelling. The objective of the study is to investigate the effects of implant material and implant–bone interface conditions on bone remodelling around tibia bone due to total ankle replacement. Finite element models of intact and implanted ankles were developed using CT scan data sets. Bone remodelling algorithm was used in combination with FE analysis to predict the bone density changes around the ankle joint. Dorsiflexion, neutral, and plantar flexion positions were considered, along with muscle force and ligaments. Implant–bone interfacial conditions were assumed as debonded and bonded to represent non-osseointegration and fully osseointegration at the porous coated surface of the implant. To investigate the effect of implant material, three finite element models having different material combinations of the implant were developed. For model 1, tibial and talar components were made of Co–Cr–Mo, and meniscal bearing was made of UHMWPE. For model 2, tibial and talar components were made of ceramic and meniscal bearing was made of UHMWPE. For model 3, tibial and talar components were made of ceramic and meniscal bearing was made of CFR-PEEK. Changes in implant material showed no significant changes in bone density due to bone remodelling. Therefore, ceramic appears to be a viable alternative to metal and CFR-PEEK can be used in place of UHMWPE. This study also indicates that proper bonding between implant and bone is essential for long-term survival of the prosthetic components.     

Crystallization and preliminary X-ray analysis of membrane-bound pyrophosphatases

Abstract

Membrane-bound pyrophosphatases (M-PPases) are enzymes that enhance the survival of plants, protozoans and prokaryotes in energy constraining stress conditions. These proteins use pyrophosphate, a waste product of cellular metabolism, as an energy source for sodium or proton pumping. To study the structure and function of these enzymes we have crystallized two membrane-bound pyrophosphatases recombinantly produced in Saccharomyces cerevisae: the sodium pumping enzyme of Thermotoga maritima (TmPPase) and the proton pumping enzyme of Pyrobaculum aerophilum (PaPPase). Extensive crystal optimization has allowed us to grow crystals of TmPPase that diffract to a resolution of 2.6 Å. The decisive step in this optimization was in-column detergent exchange during the two-step purification procedure. Dodecyl maltoside was used for high temperature solubilization of TmPPase and then exchanged to a series of different detergents. After extensive screening, the new detergent, octyl glucose neopentyl glycol, was found to be the optimal for TmPPase but not PaPPase.     

Finite Element Analysis of Interbody Cages in a Human Lumbar Spine

Abstract

An innovative surgical procedure is vertebral stabilization by interbody cages. It is currently being used to separate and stabilize vertebral bodies and to promote bony fusion of the vertebrae onto or through the cages. This surgery, at some spine levels, can be performed through a laparoscope as an outpatient procedure with low morbidity. Because the procedure is new, little structural information is available on the interbody cages. The objective of this study was to evaluate the human lumbar spine stabilized by interbody cages biomechanically. The finite element method was used to compare cage designs by considering stresses in the cage and in the bone as well as relative displacements between the cage and the adjacent bone at the interface. The biomechanical evaluation considered different bone densities and considered axial, torsional, and bending loads on the lumbar spine. Stress analysis predicts local regions of stress concentration that could be damaging to cancellous bone and will likely require a remodeling response for local damage. This study predicts relative micromotion that could cause the bone resorption and fibrous tissue formation on the contact surfaces of the cage. The geometric constraints caused by the use of two cages will reduce the relative motion and therefore be more likely to allow bone ingrowth at the posterocentral contact region. Finite element analysis suggests that cages are a promising method for separation and stabilization of the vertebral bodies.     

Stomatal response functions to environmental stress of dominant species in the tropical Andean páramo

ABSTRACT

Background: Stomatal response functions of dominant plant species can provide insights into the behaviour of ecosystems under environmental stress, and provide tools for modelling their response to climate change. However, they remain little studied in tropical Alpine ecosystems.

Aims: Our objective was to formulate and compare stomatal response functions for two dominant páramo species with different adaptive strategies to drought, the stress-tolerant shrub Hypericum laricifolium, and the stress avoiding giant rosette Espeletia schultzii and thus enable making projections as to their future fitness in a changing climate.

Methods: A reanalysis of data found in the literature and new ecophysiological and micrometeorological measurements were used to fit and test new stomatal response functions to environmental variables for these two species.

Results: The response functions of vapour pressure differences between leaf and air showed an exponential decrease for both species, while for photosynthetically active radiation (PAR), peak-form response functions provided the best fit. The response function for leaf water potential was linear for the drought-tolerant shrub and decreased exponentially for the stress avoiding giant rosette. Several thresholds prior to stomatal closure were also included in the functions.

Conclusions: Although stress-avoiding and stress-tolerant strategies are both successful in the Andean páramo, the response functions suggest that the tolerant shrub could be more resistant to more intense drought.     

Model uncertainty analysis using data analytics for life-cycle assessment (LCA) applications

Purpose

Objective uncertainty quantification (UQ) of a product life-cycle assessment (LCA) is a critical step for decision-making. Environmental impacts can be measured directly or by using models. Underlying mathematical functions describe a model that approximate the environmental impacts during various LCA stages. In this study, three possible uncertainty sources of a mathematical model, i.e., input variability, model parameter (differentiate from input in this study), and model-form uncertainties, were investigated. A simple and easy to implement method is proposed to quantify each source.

Methods

Various data analytics methods were used to conduct a thorough model uncertainty analysis; (1) Interval analysis was used for input uncertainty quantification. A direct sampling using Monte Carlo (MC) simulation was used for interval analysis, and results were compared to that of indirect nonlinear optimization as an alternative approach. A machine learning surrogate model was developed to perform direct MC sampling as well as indirect nonlinear optimization. (2) A Bayesian inference was adopted to quantify parameter uncertainty. (3) A recently introduced model correction method based on orthogonal polynomial basis functions was used to evaluate the model-form uncertainty. The methods are applied to a pavement LCA to propagate uncertainties throughout an energy and global warming potential (GWP) estimation model; a case of a pavement section in Chicago metropolitan area was used.

Results and discussion

Results indicate that each uncertainty source contributes to the overall energy and GWP output of the LCA. Input uncertainty was shown to have significant impact on overall GWP output; for the example case study, GWP interval was around 50%. Parameter uncertainty results showed that an assumption of ±?10% uniform variation in the model parameter priors resulted in 28% variation in the GWP output. Model-form uncertainty had the lowest impact (less than 10% variation in the GWP). This is because the original energy model is relatively accurate in estimating the energy. However, sensitivity of the model-form uncertainty showed that even up to 180% variation in the results can be achieved due to lower original model accuracies.

Conclusions

Investigating each uncertainty source of the model indicated the importance of the accurate characterization, propagation, and quantification of uncertainty. The outcome of this study proposed independent and relatively easy to implement methods that provide robust grounds for objective model uncertainty analysis for LCA applications. Assumptions on inputs, parameter distributions, and model form need to be justified. Input uncertainty plays a key role in overall pavement LCA output. The proposed model correction method as well as interval analysis were relatively easy to implement. Research is still needed to develop a more generic and simplified MCMC simulation procedure that is fast to implement.

     

Consequential LCA and LCC using linear programming: an illustrative example of biorefineries

Purpose

This paper aims to demonstrate how LCA can be improved by the use of linear programming (LP) (i) to determine the optimal choice between new technologies, (ii) to identify the optimal region for supplying the feedstock, and (iii) to deal with multifunctional processes without specifying a certain main product. Furthermore, the contribution of LP in the context of consequential LCA and LCC is illustrated.

Methods

We create a mixed integer linear program (MILP) for the environmental and economic assessment of new technologies. The model is applied in order to analyze two residual beech wood-based biorefinery concepts in Germany. In terms of the optimal consequences for the system under study, the principle of the program is to find a scaling vector that minimizes the life cycle impact indicator results of the system. We further transform the original linear program to extend the assessment by life cycle costing (LCC). Thereby, two multi-objective programming methods are used, weighted goal programming and epsilon constraint method.

Results and discussion

The consequential case studies demonstrate the possibility to determine optimal locations of newly developed technologies. A high number of potential system modifications can be studied simultaneously without matrix inversion. The criteria for optimal choices are represented by the objective functions and the additional constraints such as the available feedstock in a region. By combining LCA and LCC targets within a multi-objective programming approach, it is possible to address environmental and economic trade-offs in consequential decision-making.

Conclusions

This article shows that linear programming can be used to extend standard LCA in the field of technological choices. Additional consequential research questions can be addressed such as the determination of the optimal number of new production plants and the optimal regions for supplying the resources. The modifications of the program by additional profit requirements (LCC) into a goal program and Pareto optimization problem have been identified as promising steps toward a comprehensive multi-objective LCSA.

     

An integrated environmental and cost assessment method based on LCA and LCC for automobile interior and exterior trim design scheme optimization

Purpose

This paper provided an integrated method to evaluate environmental impact and life cycle cost (LCC) of various alternative design schemes in the early design and development stages of complex mechanical product; an optimization method of product design schemes based on life cycle assessment (LCA) and LCC is proposed as a supporting design tool to achieve optimal integration of environmental impact and cost of the design.

Methods

The applied research methods include product level deconstruction model, LCA/LCC integrated analysis model, and the product design scheme optimization method. In the life cycle environmental assessment, GaBi software and CML2001 evaluation method are used to evaluate product environmental impact. In terms of product design configuration scheme optimization, the TOPSIS method is used to optimize the design schemes generated. Taking the internal and external trim of automobile as an example, the specific implementation process of the method is illustrated.

Results and discussion

The case study indicates that, when comprehensively considering the environmental impact and cost, the composite indices of the optimal and worst schemes are 0.8667 and 0.3001, respectively; their costs are ¥164.87 and ¥179.68, respectively; and the eco points of environmental impact are 14.74 and 39.78, respectively. The cost of the two schemes are not much different, but the environmental impact of the optimal scheme is only 37.1% of the worst scheme’s; When cost is the only factor to be considered, the lowest cost design scheme is about 36.7% of the maximum scheme’s cost, and the environmental impact of the lowest cost design scheme is about 1.6 times of the maximum cost scheme’s. When environmental impact is the only factor to be considered, the least environmental impact of design scheme accounts about 31.7% of the largest; the cost of design scheme with the least environmental impact accounts for about 58.1% of the largest one’s. Integrating LCA and LCC, scientific suggestions can be provided from several perspectives.

Conclusions

By considering the environmental impact and LCC, this paper proposes a method of product design scheme optimization as a supporting design tool which could evaluate the design options of the product and identify the preferred option in the early stage of product design. It is helpful to realize the sustainability of the product. In order to improve the applicability of this method, the weighting factors of environmental impact and cost could be adjusted according to the requirements of energy saving and emission reduction of different enterprises.

     

Maxillary expansion treatment using bone anchors: development and validation of a 3D finite element model

Objective: Develop a finite element (FE) model of a skull to perform biomechanical studies of maxillary expansion using bone anchors (BA).

Materials and methods: A skull model was developed and assigned material properties based on Hounsfield unit (HU) values of cone-beam computerized tomography (CBCT) images. A 3 mm diameter cylindrical BA was modelled and inserted in the palatal bone. A 4 mm transverse displacement was applied on the anchor. An evaluation on the effect on local stresses of BA implantation inclination angle was performed.

Results: Proper displacement results and strain–stress trends for the expansion process were present. Stress distribution patterns were similar as reported in the literature. No significant difference between BA inclination angles was found.

Conclusion: This work leads to a better understanding and prediction of craniofacial and maxillary bone remodelling during ME with BA treatments and is a first step towards the development of patient specific treatments.     

Kinetics of gene expression and bone remodelling in the clinical phase of collagen-induced arthritis

IntroductionPathological bone changes differ considerably between inflammatory arthritic diseases and most studies have focused on bone erosion. Collagen-induced arthritis (CIA) is a model for rheumatoid arthritis, which, in addition to bone erosion, demonstrates bone formation at the time of clinical manifestations. The objective of this study was to use this model to characterise the histological and molecular changes in bone remodelling, and relate these to the clinical disease development.MethodsA histological and gene expression profiling time-course study on bone remodelling in CIA was linked to onset of clinical symptoms. Global gene expression was studied with a gene chip array system.ResultsThe main histopathological changes in bone structure and inflammation occurred during the first two weeks following the onset of clinical symptoms in the joint. Hereafter, the inflammation declined and remodelling of formed bone dominated.Global gene expression profiling showed simultaneous upregulation of genes related to bone changes and inflammation in week 0 to 2 after onset of clinical disease. Furthermore, we observed time-dependent expression of genes involved in early and late osteoblast differentiation and function, which mirrored the histopathological bone changes. The differentially expressed genes belong to the bone morphogenetic pathway (BMP) and, in addition, include the osteoblast markers integrin-binding sialoprotein (Ibsp), bone gamma-carboxyglutamate protein (Bglap1), and secreted phosphoprotein 1 (Spp1). Pregnancy-associated protein A (Pappa) and periostin (Postn), differentially expressed in the early disease phase, are proposed to participate in bone formation, and we suggest that they play a role in early bone formation in the CIA model. Comparison to human genome-wide association studies (GWAS) revealed differential expression of several genes associated with human arthritis.ConclusionsIn the CIA model, bone formation in the joint starts shortly after onset of clinical symptoms, which results in bony fusion within one to two weeks. This makes it a candidate model for investigating the relationship between inflammation and bone formation in inflammatory arthritis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0531-7) contains supplementary material, which is available to authorized users.     

Modeling intracranial aneurysm stability and growth: an integrative mechanobiological framework for clinical cases

We present a novel patient-specific fluid-solid-growth framework to model the mechanobiological state of clinically detected intracranial aneurysms (IAs) and their evolution. The artery and IA sac are modeled as thick-walled, non-linear elastic fiber-reinforced composites. We represent the undulation distribution of collagen fibers: the adventitia of the healthy artery is modeled as a protective sheath whereas the aneurysm sac is modeled to bear load within physiological range of pressures. Initially, we assume the detected IA is stable and then consider two flow-related mechanisms to drive enlargement: (1) low wall shear stress; (2) dysfunctional endothelium which is associated with regions of high oscillatory flow. Localized collagen degradation and remodelling gives rise to formation of secondary blebs on the aneurysm dome. Restabilization of blebs is achieved by remodelling of the homeostatic collagen fiber stretch distribution. This integrative mechanobiological modelling workflow provides a step towards a personalized risk-assessment and treatment of clinically detected IAs.

     

Mutagenesis of echinocandin B overproducing Aspergillus nidulans capable of using starch as main carbon source

Abstract

Echinocandin B, a kind of antimycotic with cyclic lipo-hexapeptides, was produced by fermentation with Aspergillus nidulans using fructose as main carbon source. The objective of this study was to screen a high-yield mutant capable of using cheap starch as main carbon source by atmospheric and room temperature plasma (ARTP) treatment in order to decrease the production cost of echinocandin B. A stable mutant A. nidulans ZJB19033, which can use starch as optimal carbon source instead of expensive fructose, was selected from two thousands isolates after several cycles of ARTP mutagenesis. To further increase the production of echinocandin B, the optimization of fermentation medium was performed by response surface methodology (RSM), employing Plackett-Burman design (PBD) followed by Box-Behnken design (BBD). The optimized fermentation medium provided the optimal yield of echinocandin B, 2425.9?±?43.8?mg/L, 1.3-fold compared to unoptimized medium. The results indicated that the mutant could achieve high echinocandin B production using cheap starch as main carbon source, and the cost of carbon sources in fermentation medium reduced dramatically by about 45%.     

Integration of life cycle assessment,artificial neural networks,and metaheuristic optimization algorithms for optimization of tomato-based cropping systems in Iran

Purpose

The main purpose of this study was to evaluate the use of an integrated life cycle assessment (LCA), artificial neural network, and metaheuristic optimization model to improve the sustainability of tomato-based cropping systems in Iran. The model outputs the combination of input usage in a tomato cropping system, which leads to the highest economic output and the least environmental impact.

Methods

The LCA inventory was created using data from 114 open-field tomato farms in the Alborz Province of Iran during one growing period in 2015. Among all management components, the main focus was on irrigation management systems. The optimization problem was designed by integrating three indicators: carbon footprint (CF), benefit-cost ratio (BCR), and energy use efficiency (EUE) as the objective of field tomato production. The functional unit was 1 kg of tomato aligned with the system boundary of the cradle to market life cycle. Three artificial neural networks (ANNs) were applied to model relationships between the inputs and three indices (CF, BCR, and EUE) as the objective functions. Multi-objective genetic algorithm (MOGA) and multi-objective particle swarm optimization (MOPSO) were used to minimize the CF and maximize the BCR and EUE indicators. The abovementioned aims have been pursued by developing codes in MATLAB software.

Results and discussion

CF, BCR, and EUE were calculated to be 0.26 kg CO_2?eq (kg tomato)^?1, 1.8, and 0.5, respectively. MOGA results envisage the possibility of an increase of 86% and 50% in the EUE and BCR and a 43% reduction in the CF of tomato production systems. Moreover, EUE and BCR increased by 83% and 49%, and CF was reduced by 39% from the optimum results obtained from the MOPSO algorithm. It was revealed that in order to optimize field tomato production with the target objectives of this study, a large additional use for irrigation pipes, plastic, and machinery in comparison to current situation is required, while a large reduction of biocide, chemical fertilizer, and electricity consumption is indispensable.

Conclusions

According to the results of our study, it was concluded that the optimal solutions require a modernization of irrigation systems and a decrease in the consumption of chemical fertilizers and pesticides. The implementation of management options for such solutions is discussed.

     

Acetopyruvate hydrolase production by Pseudomonas putida O1--optimization of batch and fed-batch fermentations

The main objective of this work was the optimization of the production of the beta-ketolase, acetopyruvate hydrolase, from Pseudomonas putida O1. Orcinol was used as an inducer for enzyme production. The growth medium was optimized in two steps. In the first step, screening for optimal glucose concentration was performed. In the second step, a central composite design was used to optimize carbon and nitrogen sources in the medium. After this optimization procedure, a medium was obtained which produced seven times more biomass than the initial medium. Acetopyruvate hydrolase enzyme production was optimized by determining the optimal time of feed and amount of orcinol, using statistical methods. In a subsequent step, the maximal orcinol-degradation rate was determined. The results obtained were used to find an optimal feeding profile for enzyme production. By using the optimized fed-batch process, acetopyruvate hydrolase activity was enhanced from 10 units l(-1)to 400 units l(-1), in comparison with previously reported fermentation experiments. Productivity could even be increased by a factor of 75, to a value of 20 units l(-1 )h(-1).     

The physiological basis for a flexible condylar tibial plateau design

Knee resurfacing is a successful treatment for osteo- and rheumatoid arthritis in elderly patients. The application of this treatment to younger more active and obese persons has the potential to produce premature wear, loosening, and undesirable bone remodelling. A new generation of more physiologically compatible components is required for these situations. This paper discusses the design and analysis of a prototype tibial base plate aimed at physiological load transfer. Incorporated in the design are mechanisms to alleviate lift-off phenomena, bone stress concentrations, stress shielding, and micromotion at the bone-implant interface. The design requires viable cancellous bone stock, so that the bone may respond by remodelling to the dynamic loading during normal ambulatory activities.     

A method for the staining of intraosseous nerve fibers using Sihler’s staining technique

Abstract

Understanding nerve fiber distribution in the jaw bone is important when performing invasive surgical treatments. Both microscopic and macroscopic anatomical techniques have been developed to study innervation. Conventional methods of removing and staining these structures, however, often alter structure and lack reproducibility of the resulting specimens. We sought to optimize Sihler’s staining technique to stain intraosseous nerves in mandibles. Four cadaver specimens were used. The best staining of intraosseous nerve fibers was achieved by using the Plank-Rychlo solution. When the Styrene monomer was used, the resulting transparency was better than that obtained with glycerin under the same conditions. No significant differences were found between Sihler's staining procedure performed according to the conventional method and the procedure in which the second decalcification step was omitted. Our results demonstrate that applying Sihler’s staining technique to bones makes them transparent and allows observation of nerves while preserving the external shape of the bone and maintaining the position of intraosseous nerve fibers. Our findings suggest our Sihler staining method for intraosseous nerve fibers can provide an intermediate resolution between macroscopic and microscopic techniques.     

Quantitative Approach for the Prediction of Tooth Movement During Orthodontic Treatment

The orthodontic treatment is aimed to displace and/or rotate the teeth to obtain the functionally correct occlusion and the best aesthetics and consists in applying forces and/or couples to tooth crowns. The applied loads are generated by the elastic recovery of metallic wires linked to the tooth crowns by brackets. These loads generate a stress state into the periodontal ligament and hence, in the alveolar bone, causing the bone remodeling responsible for the tooth movement. The orthodontic appliance is usually designed on the basis of the clinical experience of the orthodontist. In this work, a quantitative approach for the prediction of the tooth movement is presented that has been developed as a first step to build up a computer tool to aid the orthodontist in designing the orthodontic appliance. The model calculates the tooth movement through time with respect to a fixed Cartesian frame located in the middle of the dental arch. The user interface panel has been designed to allow the orthodontist to manage the standard geometrical references and parameters usually adopted to design the treatment. Simulations of specific cases are reported for which the parameters of the model are selected in order to reproduce forecasts of tooth movement matching data published in experimental works.     

Design of Adjustable Frame-Type Prosthetic Socket for Lower Limb

ObjectivesProsthetic socket is the contact interface between the stump and the prosthesis, and also the interface component that transmits forces from the stump to the prosthesis distal. The current prosthetic socket fit is a major factor affecting rehabilitation, especially with the stump volume fluctuations. The main goal of this article is to design an adjustable frame-type prosthetic socket with constant force to adapt to the stump volume fluctuations.Materials and methodsIn this paper, an adjustable frame-type prosthetic socket with constant force is designed. The constant force device is designed based on the superelasticity of the shape memory alloy for maintaining constant stump-socket interface stress and automatically adapting to certain volume fluctuations. The constant force extrusion performance of this prosthetic socket was verified and optimized by finite element analysis.ResultsThe results suggest that the constant force unit may maintain constant interface stress. According to the optimization results, the shape memory alloy dimensional parameters could be selected according to different requirements.ConclusionThe adjustable frame-type prosthetic socket allows the user to adjust the socket volume through the cable system and has a large heat dissipation area. The constant force unit maintains constant interface stress and automatically adapts to stump volume fluctuations.     

Human dental pulp cells exhibit bone cell-like responsiveness to fluid shear stress

Background aimsFor engineering bone tissue to restore, for example, maxillofacial defects, mechanosensitive cells are needed that are able to conduct bone cell-specific functions, such as bone remodelling. Mechanical loading affects local bone mass and architecture in vivo by initiating a cellular response via loading-induced flow of interstitial fluid. After surgical removal of ectopically impacted third molars, human dental pulp tissue is an easily accessible and interesting source of cells for mineralized tissue engineering. The aim of this study was to determine whether human dental pulp-derived cells (DPC) are responsive to mechanical loading by pulsating fluid flow (PFF) upon stimulation of mineralization in vitro.MethodsHuman DPC were incubated with or without mineralization medium containing differentiation factors for 3 weeks. Cells were subjected to 1-h PFF (0.7 ± 0.3Pa, 5Hz) and the response was quantified by measuring nitric oxide (NO) and prostaglandin E₂ (PGE₂) production, and gene expression of cyclooxygenase (COX)-1 and COX-2.ResultsWe found that DPC are intrinsically mechanosensitive and, like osteogenic cells, respond to PFF-induced fluid shear stress. PFF stimulated NO and PGE₂ production, and up-regulated COX-2 but not COX-1 gene expression. In DPC cultured under mineralizing conditions, the PFF-induced NO, but not PGE₂, production was significantly enhanced.ConclusionsThese data suggest that human DPC, like osteogenic cells, acquire responsiveness to pulsating fluid shear stress in mineralizing conditions. Thus DPC might be able to perform bone-like functions during mineralized tissue remodeling in vivo, and therefore provide a promising new tool for mineralized tissue engineering to restore, for example, maxillofacial defects.