A tellurium-based cathepsin B inhibitor: Molecular structure, modelling, molecular docking and biological evaluation

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A tellurium-based cathepsin B inhibitor: Molecular structure, modelling, molecular docking and biological evaluation

The crystallographically determined structure of biologically active 4,4-dichloro-1,3-diphenyl-4-telluraoct-2-en-1-one, 3, shows the coordination geometry for Te to be distorted psi-pentagonal bipyramidal based on a C2OCl3(lone pair) donor set. Notable is the presence of an intramolecular axial Te center dot center dot center dot O (carbonyl) interaction, a design element included to reduce hydrolysis. Raman and molecular modelling studies indicate the persistence of the Te center dot center dot center dot O(carbonyl) interaction in the solution (CHCl3) and gasphases, respectively. Docking studies of 3' (i.e. original 3 less one chloride) with Cathepsin B reveals a change in the configuration about the vinyl C = C bond. i.e. to E from Z (crystal structure). This isomerism allows the optimisation of interactions in the complex which features a covalent Te-SGCys29 bond. Crucially, the E configuration observed for 3' allows for the formation of a hypervalent Te center dot center dot center dot O interaction as well as an O center dot center dot center dot H-O hydrogen bond with the Gly27 and Glu122 residues, respectively. Additional stabilisation is afforded by a combination of interactions spanning the S1, S2, S1' and S2' sub-sites of Cathepsin B. The greater experimental inhibitory activity of 3 compared with analogues is rationalised by the additional interactions formed between 3' and the His110 and His111 residues in the occluding loop, which serve to hinder the entrance to the active site. (C) 2012 Elsevier B.V. All rights reserved.

Complexity in the Optimisation of ATM Performance Metrics

Today's motivation for autonomous systems research stems out of the fact that networked environments have reached a level of complexity and heterogeneity that make their control and management by solely human administrators more and more difficult. The optimisation of performance metrics for the air traffic management system, like in other networked system, has become more complex with increasing number of flights, capacity constraints, environmental factors and safety regulations. It is anticipated that a new structure of planning layers and the introduction of higher levels of automation will reduce complexity and will optimise the performance metrics of the air traffic management system. This paper discusses the complexity of optimising air traffic management performance metrics and proposes a way forward based on higher levels of automation.

Lipoplexes formulation and optimisation:in vitro transfection studies reveal no correlation with in vivo vaccination studies

The aim of these studies was to compare the effect of liposome composition on physico-chemical characteristics and transfection efficacy of cationic liposomes both in vitro and in vivo. Comparison between 4 popularly used cationic lipids, showed 3b-N-(dimethylaminoethyl)carbamate (DC-Chol) to promote the highest transfect levels in cells in vitro with levels being at least 6 times higher than those of 1,2-di-O-octadecenyl-3-trimethylammonium propane (DOTMA). 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP), and dimethyldioctadecylammonium (DDA) and approximately twice as efficient as dipalmitoyl-trimethylammonium-propane (DPTAP). To establish the role of the helper lipid, DC-Chol liposomes were formulated in combination with either 1,2-dioleoyl-sn-glycero-3-phosphatidylethanolamine (DOPE) or cholesterol (Chol) (1:1 molar ratio) with and without the addition of phosphatidyl choline. The choice of helper lipid incorporated within the bilayer was found to influence the formation of complexes, their resultant structure and their transfection efficiency in vitro, with SUV-DNA complexes containing optimum levels of DOPE giving higher transfection than those containing cholesterol. The inclusion of PC within the formulation also reduced transfection efficiency in vitro. However, when administered in vivo, SUV-DNA complexes composed of PC:Chol:DC-Chol at a molar ratio of 16:8:4 micromole/ml were the most effective at inducing splenocyte proliferation upon exposure to antigen in comparison to control spleens. These results demonstrate that there is no in vitro/in vivo correlation between the transfection efficacy of these liposome formulations and in vitro transfection in the above cell model cannot be taken as a reliable indicator for in vivo efficacy of DNA vaccines.

Liposome formulation of poorly water soluble drugs:optimisation of drug loading and ESEM analysis of stability

Liposomes due to their biphasic characteristic and diversity in design, composition and construction, offer a dynamic and adaptable technology for enhancing drug solubility. Starting with equimolar egg-phosphatidylcholine (PC)/cholesterol liposomes, the influence of the liposomal composition and surface charge on the incorporation and retention of a model poorly water soluble drug, ibuprofen was investigated. Both the incorporation and the release of ibuprofen were influenced by the lipid composition of the multi-lamellar vesicles (MLV) with inclusion of the long alkyl chain lipid (dilignoceroyl phosphatidylcholine (C 24PC)) resulting in enhanced ibuprofen incorporation efficiency and retention. The cholesterol content of the liposome bilayer was also shown to influence ibuprofen incorporation with maximum ibuprofen incorporation efficiency achieved when 4 μmol of cholesterol was present in the MLV formulation. Addition of anionic lipid dicetylphosphate (DCP) reduced ibuprofen drug loading presumably due to electrostatic repulsive forces between the carboxyl group of ibuprofen and the anionic head-group of DCP. In contrast, the addition of 2 μmol of the cationic lipid stearylamine (SA) to the liposome formulation (PC:Chol - 16 μmol:4 μmol) increased ibuprofen incorporation efficiency by approximately 8%. However further increases of the SA content to 4 μmol and above reduced incorporation by almost 50% compared to liposome formulations excluding the cationic lipid. Environmental scanning electron microscopy (ESEM) was used to dynamically follow the changes in liposome morphology during dehydration to provide an alternative assay of liposome stability. ESEM analysis clearly demonstrated that ibuprofen incorporation improved the stability of PC:Chol liposomes as evidenced by an increased resistance to coalescence during dehydration. These finding suggest a positive interaction between amphiphilic ibuprofen molecules and the bilayer structure of the liposome. © 2004 Elsevier B.V. All rights reserved.

Territorial administrative reorganization as a strategy for optimizing the structure of local government

Through the tough economic and social situation and the lack of values that has been experienced in recent years, local governments especially in Greece, Portugal, Italy and Spain have been forced to strongly consider the structure and size of their public sector. Despite some initiative to reduce the number of municipalities and provinces, little substantive progress has been made in improving the management of the local public Administration during this crisis. In this study a territorial administrative reorganization is proposed as a strategy to optimize the structure of local government, analyzing the Spanish situation in general, and an autonomous community in particular.

Modélisation du comportement des bétons fibrés à ultra-hautes performances par la micromécanique : Effet de l'orientation des fibres à l'échelle de la structure

Cette thèse s’inscrit dans le contexte d’une optimisation industrielle et économique des éléments de structure en BFUP permettant d’en garantir la ductilité au niveau structural, tout en ajustant la quantité de fibres et en optimisant le mode de fabrication. Le modèle développé décrit explicitement la participation du renfort fibré en traction au niveau local, en enchaînant une phase de comportement écrouissante suivie d’une phase adoucissante. La loi de comportement est fonction de la densité, de l’orientation des fibres vis-à-vis des directions principales de traction, de leur élancement et d’autres paramètres matériaux usuels liés aux fibres, à la matrice cimentaire et à leur interaction. L’orientation des fibres est prise en compte à partir d’une loi de probabilité normale à une ou deux variables permettant de reproduire n’importe quelle orientation obtenue à partir d’un calcul représentatif de la mise en oeuvre du BFUP frais ou renseignée par analyse expérimentale sur prototype. Enfin, le modèle reproduit la fissuration des BFUP sur le principe des modèles de fissures diffuses et tournantes. La loi de comportement est intégrée au sein d’un logiciel de calcul de structure par éléments finis, permettant de l’utiliser comme un outil prédictif de la fiabilité et de la ductilité globale d’éléments en BFUP. Deux campagnes expérimentales ont été effectuées, une à l’Université Laval de Québec et l’autre à l’Ifsttar, Marne-la-Vallée. La première permet de valider la capacité du modèle reproduire le comportement global sous des sollicitations typiques de traction et de flexion dans des éléments structurels simples pour lesquels l’orientation préférentielle des fibres a été renseignée par tomographie. La seconde campagne expérimentale démontre les capacités du modèle dans une démarche d’optimisation, pour la fabrication de plaques nervurées relativement complexes et présentant un intérêt industriel potentiel pour lesquels différentes modalités de fabrication et des BFUP plus ou moins fibrés ont été envisagés. Le contrôle de la répartition et de l’orientation des fibres a été réalisé à partir d’essais mécaniques sur prélèvements. Les prévisions du modèle ont été confrontées au comportement structurel global et à la ductilité mis en évidence expérimentalement. Le modèle a ainsi pu être qualifié vis-à-vis des méthodes analytiques usuelles de l’ingénierie, en prenant en compte la variabilité statistique. Des pistes d’amélioration et de complément de développement ont été identifiées.

'Bayesian Optimisation for Nurse Scheduling'

A Bayesian optimisation algorithm for a nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse's assignment. When a human scheduler works, he normally builds a schedule systematically following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not yet completed, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this paper, we design a more human-like scheduling algorithm, by using a Bayesian optimisation algorithm to implement explicit learning from past solutions. A nurse scheduling problem from a UK hospital is used for testing. Unlike our previous work that used Genetic Algorithms to implement implicit learning [1], the learning in the proposed algorithm is explicit, i.e. we identify and mix building blocks directly. The Bayesian optimisation algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, new rule strings have been obtained. Sets of rule strings are generated in this way, some of which will replace previous strings based on fitness. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. For clarity, consider the following toy example of scheduling five nurses with two rules (1: random allocation, 2: allocate nurse to low-cost shifts). In the beginning of the search, the probabilities of choosing rule 1 or 2 for each nurse is equal, i.e. 50%. After a few iterations, due to the selection pressure and reinforcement learning, we experience two solution pathways: Because pure low-cost or random allocation produces low quality solutions, either rule 1 is used for the first 2-3 nurses and rule 2 on remainder or vice versa. In essence, Bayesian network learns 'use rule 2 after 2-3x using rule 1' or vice versa. It should be noted that for our and most other scheduling problems, the structure of the network model is known and all variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus, learning can amount to 'counting' in the case of multinomial distributions. For our problem, we use our rules: Random, Cheapest Cost, Best Cover and Balance of Cost and Cover. In more detail, the steps of our Bayesian optimisation algorithm for nurse scheduling are: 1. Set t = 0, and generate an initial population P(0) at random; 2. Use roulette-wheel selection to choose a set of promising rule strings S(t) from P(t); 3. Compute conditional probabilities of each node according to this set of promising solutions; 4. Assign each nurse using roulette-wheel selection based on the rules' conditional probabilities. A set of new rule strings O(t) will be generated in this way; 5. Create a new population P(t+1) by replacing some rule strings from P(t) with O(t), and set t = t+1; 6. If the termination conditions are not met (we use 2000 generations), go to step 2. Computational results from 52 real data instances demonstrate the success of this approach. They also suggest that the learning mechanism in the proposed approach might be suitable for other scheduling problems. Another direction for further research is to see if there is a good constructing sequence for individual data instances, given a fixed nurse scheduling order. If so, the good patterns could be recognized and then extracted as new domain knowledge. Thus, by using this extracted knowledge, we can assign specific rules to the corresponding nurses beforehand, and only schedule the remaining nurses with all available rules, making it possible to reduce the solution space. Acknowledgements The work was funded by the UK Government's major funding agency, Engineering and Physical Sciences Research Council (EPSRC), under grand GR/R92899/01. References [1] Aickelin U, "An Indirect Genetic Algorithm for Set Covering Problems", Journal of the Operational Research Society, 53(10): 1118-1126,

A III-V channel field effect transistor for non-classical CMOS: process optimisation for improved gate stack function

This thesis describes a collection of studies into the electrical response of a III-V MOS stack comprising metal/GaGdO/GaAs layers as a function of fabrication process variables and the findings of those studies. As a result of this work, areas of improvement in the gate process module of a III-V heterostructure MOSFET were identified. Compared to traditional bulk silicon MOSFET design, one featuring a III-V channel heterostructure with a high-dielectric-constant oxide as the gate insulator provides numerous benefits, for example: the insulator can be made thicker for the same capacitance, the operating voltage can be made lower for the same current output, and improved output characteristics can be achieved without reducing the channel length further. It is known that transistors composed of III-V materials are most susceptible to damage induced by radiation and plasma processing. These devices utilise sub-10 nm gate dielectric films, which are prone to contamination, degradation and damage. Therefore, throughout the course of this work, process damage and contamination issues, as well as various techniques to mitigate or prevent those have been investigated through comparative studies of III-V MOS capacitors and transistors comprising various forms of metal gates, various thicknesses of GaGdO dielectric, and a number of GaAs-based semiconductor layer structures. Transistors which were fabricated before this work commenced, showed problems with threshold voltage control. Specifically, MOSFETs designed for normally-off (VTH > 0) operation exhibited below-zero threshold voltages. With the results obtained during this work, it was possible to gain an understanding of why the transistor threshold voltage shifts as the gate length decreases and of what pulls the threshold voltage downwards preventing normally-off device operation. Two main culprits for the negative VTH shift were found. The first was radiation damage induced by the gate metal deposition process, which can be prevented by slowing down the deposition rate. The second was the layer of gold added on top of platinum in the gate metal stack which reduces the effective work function of the whole gate due to its electronegativity properties. Since the device was designed for a platinum-only gate, this could explain the below zero VTH. This could be prevented either by using a platinum-only gate, or by matching the layer structure design and the actual gate metal used for the future devices. Post-metallisation thermal anneal was shown to mitigate both these effects. However, if post-metallisation annealing is used, care should be taken to ensure it is performed before the ohmic contacts are formed as the thermal treatment was shown to degrade the source/drain contacts. In addition, the programme of studies this thesis describes, also found that if the gate contact is deposited before the source/drain contacts, it causes a shift in threshold voltage towards negative values as the gate length decreases, because the ohmic contact anneal process affects the properties of the underlying material differently depending on whether it is covered with the gate metal or not. In terms of surface contamination; this work found that it causes device-to-device parameter variation, and a plasma clean is therefore essential. This work also demonstrated that the parasitic capacitances in the system, namely the contact periphery dependent gate-ohmic capacitance, plays a significant role in the total gate capacitance. This is true to such an extent that reducing the distance between the gate and the source/drain ohmic contacts in the device would help with shifting the threshold voltages closely towards the designed values. The findings made available by the collection of experiments performed for this work have two major applications. Firstly, these findings provide useful data in the study of the possible phenomena taking place inside the metal/GaGdO/GaAs layers and interfaces as the result of chemical processes applied to it. In addition, these findings allow recommendations as to how to best approach fabrication of devices utilising these layers.

'Bayesian Optimisation for Nurse Scheduling'

A Bayesian optimisation algorithm for a nurse scheduling problem is presented, which involves choosing a suitable scheduling rule from a set for each nurse's assignment. When a human scheduler works, he normally builds a schedule systematically following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not yet completed, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this paper, we design a more human-like scheduling algorithm, by using a Bayesian optimisation algorithm to implement explicit learning from past solutions. A nurse scheduling problem from a UK hospital is used for testing. Unlike our previous work that used Genetic Algorithms to implement implicit learning [1], the learning in the proposed algorithm is explicit, i.e. we identify and mix building blocks directly. The Bayesian optimisation algorithm is applied to implement such explicit learning by building a Bayesian network of the joint distribution of solutions. The conditional probability of each variable in the network is computed according to an initial set of promising solutions. Subsequently, each new instance for each variable is generated by using the corresponding conditional probabilities, until all variables have been generated, i.e. in our case, new rule strings have been obtained. Sets of rule strings are generated in this way, some of which will replace previous strings based on fitness. If stopping conditions are not met, the conditional probabilities for all nodes in the Bayesian network are updated again using the current set of promising rule strings. For clarity, consider the following toy example of scheduling five nurses with two rules (1: random allocation, 2: allocate nurse to low-cost shifts). In the beginning of the search, the probabilities of choosing rule 1 or 2 for each nurse is equal, i.e. 50%. After a few iterations, due to the selection pressure and reinforcement learning, we experience two solution pathways: Because pure low-cost or random allocation produces low quality solutions, either rule 1 is used for the first 2-3 nurses and rule 2 on remainder or vice versa. In essence, Bayesian network learns 'use rule 2 after 2-3x using rule 1' or vice versa. It should be noted that for our and most other scheduling problems, the structure of the network model is known and all variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus, learning can amount to 'counting' in the case of multinomial distributions. For our problem, we use our rules: Random, Cheapest Cost, Best Cover and Balance of Cost and Cover. In more detail, the steps of our Bayesian optimisation algorithm for nurse scheduling are: 1. Set t = 0, and generate an initial population P(0) at random; 2. Use roulette-wheel selection to choose a set of promising rule strings S(t) from P(t); 3. Compute conditional probabilities of each node according to this set of promising solutions; 4. Assign each nurse using roulette-wheel selection based on the rules' conditional probabilities. A set of new rule strings O(t) will be generated in this way; 5. Create a new population P(t+1) by replacing some rule strings from P(t) with O(t), and set t = t+1; 6. If the termination conditions are not met (we use 2000 generations), go to step 2. Computational results from 52 real data instances demonstrate the success of this approach. They also suggest that the learning mechanism in the proposed approach might be suitable for other scheduling problems. Another direction for further research is to see if there is a good constructing sequence for individual data instances, given a fixed nurse scheduling order. If so, the good patterns could be recognized and then extracted as new domain knowledge. Thus, by using this extracted knowledge, we can assign specific rules to the corresponding nurses beforehand, and only schedule the remaining nurses with all available rules, making it possible to reduce the solution space. Acknowledgements The work was funded by the UK Government's major funding agency, Engineering and Physical Sciences Research Council (EPSRC), under grand GR/R92899/01. References [1] Aickelin U, "An Indirect Genetic Algorithm for Set Covering Problems", Journal of the Operational Research Society, 53(10): 1118-1126,

Changes In Chromatin Structure In Nih 3t3 Cells Induced By Valproic Acid And Trichostatin A.

Valproic acid (VPA) and trichostatin A (TSA) are known histone deacetylase inhibitors (HDACIs) with epigenetic activity that affect chromatin supra-organization, nuclear architecture, and cellular proliferation, particularly in tumor cells. In this study, chromatin remodeling with effects extending to heterochromatic areas was investigated by image analysis in non-transformed NIH 3T3 cells treated for different periods with different doses of VPA and TSA under conditions that indicated no loss of cell viability. Image analysis revealed chromatin decondensation that affected not only euchromatin but also heterochromatin, concomitant with a decreased activity of histone deacetylases and a general increase in histone H3 acetylation. Heterochromatin protein 1-α (HP1-α), identified immunocytochemically, was depleted from the pericentromeric heterochromatin following exposure to both HDACIs. Drastic changes affecting cell proliferation and micronucleation but not alteration in CCND2 expression and in ratios of Bcl-2/Bax expression and cell death occurred following a 48-h exposure of the NIH 3T3 cells particularly in response to higher doses of VPA. Our results demonstrated that even low doses of VPA (0.05 mM) and TSA (10 ng/ml) treatments for 1 h can affect chromatin structure, including that of the heterochromatin areas, in non-transformed cells. HP1-α depletion, probably related to histone demethylation at H3K9me3, in addition to the effect of VPA and TSA on histone H3 acetylation, is induced on NIH 3T3 cells. Despite these facts, alterations in cell proliferation and micronucleation, possibly depending on mitotic spindle defects, require a longer exposure to higher doses of VPA and TSA.

Polyphenol Extraction Optimisation From Ceylon Gooseberry (dovyalis Hebecarpa) Pulp.

Originally from Asia, Dovyalis hebecarpa is a dark purple/red exotic berry now also produced in Brazil. However, no reports were found in the literature about phenolic extraction or characterisation of this berry. In this study we evaluate the extraction optimisation of anthocyanins and total phenolics in D. hebecarpa berries aiming at the development of a simple and mild analytical technique. Multivariate analysis was used to optimise the extraction variables (ethanol:water:acetone solvent proportions, times, and acid concentrations) at different levels. Acetone/water (20/80 v/v) gave the highest anthocyanin extraction yield, but pure water and different proportions of acetone/water or acetone/ethanol/water (with >50% of water) were also effective. Neither acid concentration nor time had a significant effect on extraction efficiency allowing to fix the recommended parameters at the lowest values tested (0.35% formic acid v/v, and 17.6 min). Under optimised conditions, extraction efficiencies were increased by 31.5% and 11% for anthocyanin and total phenolics, respectively as compared to traditional methods that use more solvent and time. Thus, the optimised methodology increased yields being less hazardous and time consuming than traditional methods. Finally, freeze-dried D. hebecarpa showed high content of target phytochemicals (319 mg/100g and 1,421 mg/100g of total anthocyanin and total phenolic content, respectively).

Matrix Metalloproteinases And Left Ventricular Function And Structure In Spinal Cord Injured Subjects.

Subjects with spinal cord injury (SCI) exhibit impaired left ventricular (LV) diastolic function, which has been reported to be attenuated by regular physical activity. This study investigated the relationship between circulating matrix metalloproteinases (MMPs) and tissue inhibitors of MMPs (TIMPs) and echocardiographic parameters in SCI subjects and the role of physical activity in this regard. Forty-two men with SCI [19 sedentary (S-SCI) and 23 physically-active (PA-SCI)] were evaluated by clinical, anthropometric, laboratory, and echocardiographic analysis. Plasmatic pro-MMP-2, MMP-2, MMP-8, pro-MMP-9, MMP-9, TIMP-1 and TIMP-2 levels were determined by enzyme-linked immunosorbent assay and zymography. PA-SCI subjects presented lower pro-MMP-2 and pro-MMP-2/TIMP-2 levels and improved markers of LV diastolic function (lower E/Em and higher Em and E/A values) than S-SCI ones. Bivariate analysis showed that pro-MMP-2 correlated inversely with Em and directly with E/Em, while MMP-9 correlated directly with LV mass index and LV end-diastolic diameter in the whole sample. Following multiple regression analysis, pro-MMP-2, but not physical activity, remained associated with Em, while MMP-9 was associated with LV mass index in the whole sample. These findings suggest differing roles for MMPs in LV structure and function regulation and an interaction among pro-MMP-2, diastolic function and physical activity in SCI subjects.

Growth Factor Stimulation Improves The Structure And Properties Of Scaffold-free Engineered Auricular Cartilage Constructs.

The reconstruction of the external ear to correct congenital deformities or repair following trauma remains a significant challenge in reconstructive surgery. Previously, we have developed a novel approach to create scaffold-free, tissue engineering elastic cartilage constructs directly from a small population of donor cells. Although the developed constructs appeared to adopt the structural appearance of native auricular cartilage, the constructs displayed limited expression and poor localization of elastin. In the present study, the effect of growth factor supplementation (insulin, IGF-1, or TGF-β1) was investigated to stimulate elastogenesis as well as to improve overall tissue formation. Using rabbit auricular chondrocytes, bioreactor-cultivated constructs supplemented with either insulin or IGF-1 displayed increased deposition of cartilaginous ECM, improved mechanical properties, and thicknesses comparable to native auricular cartilage after 4 weeks of growth. Similarly, growth factor supplementation resulted in increased expression and improved localization of elastin, primarily restricted within the cartilaginous region of the tissue construct. Additional studies were conducted to determine whether scaffold-free engineered auricular cartilage constructs could be developed in the 3D shape of the external ear. Isolated auricular chondrocytes were grown in rapid-prototyped tissue culture molds with additional insulin or IGF-1 supplementation during bioreactor cultivation. Using this approach, the developed tissue constructs were flexible and had a 3D shape in very good agreement to the culture mold (average error <400 µm). While scaffold-free, engineered auricular cartilage constructs can be created with both the appropriate tissue structure and 3D shape of the external ear, future studies will be aimed assessing potential changes in construct shape and properties after subcutaneous implantation.