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Contraction Of Tissue Engineered Oral Mucosa Add in library

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Describe about the Contraction of Tissue Engineered Oral Mucosa?


1. Tissue Engineered Oral Mucosa Models

An Oral mucosa which is artificially engineered consisting full thickness generally resembles the normal oral mucosa. It consists of several components as identical to the natural element (Barbagli and Lazzeri, 2015).

  • A lamina propria was comprising of the three-dimensional scaffold, which is infiltrated by fibroblasts. These fibroblasts produces extracellular matrix (Heller et al. 2015). This structure can be effectively mimicked by seeding the oral fibroblasts in a biocompatible porous scaffold. This is followed by a long-term culturing protocol in the fibroblast differentiation medium (Bhargava et al. 2011). A researcher might have trouble such as reduced fibroblast infiltration, lack of porosity, shrinkage of scaffold along with rapid biodegradation of scaffold (Amemiya et al. 2015).

  • A Continuous Basement Membrane (CBM) which separates the epithelia with lamina propia is involved in the engineering protocol. The associated basement membrane is characterized by the Transmission Electron Microscope (TEM), which clearly highlights the lamina lucida, anchoring fibers, and the lamina densa (Bucchieri et al 2012). The Immunostaining technique for the basement membrane antigens (e.g., type IV collagen, Laminin, Bullous Pemiphigoid Antigen, Fibronectin and Integrin) are considered quite useful for the characterization method (Cheng and Xie, 2012).

  • A Stratified Squamous Epithelium is associated with the packed keratinocytes which is consist of basement membrane, undergoes migration to the surface of the buccal cavity. This structure can be efficiently imitated by the growth influence of in vitro keratinocytes of the oral cavity at an air and liquid interface within a transparent medium (containing keratinocyte growth factors, including Epidermal Growth Factor- EGF). The significant factors, which need to be highlighted, include the construction of keratinocyte invasion within the connective tissue layer (Bhargava et al. 2011).

In order to speak to the difficulties and for the optimization in the construction of oral mucosa with full thickness, several factors need to be considered. This includes the following:

i) Scaffolds

ii) Cell Source

iii) Culture Medium

The detailed analysis of each of these structures are highlighted below:

i) Scaffolds

The scaffold is considered as in an important element of the oral mucosa. It helps to support the cells of associated to the surface. Thereby, choosing the suitable scaffold would be highly recommendable. An appropriate scaffold would include effective biocompatibility, biostability, porosity along with efficient mechanical properties(Amemiya et al. 2015).

The scaffolds, which are used in the oral mucosa along with the skin reconstruction techniques, are found to be associated with several distinct categories. These are as follows;

The details of each of the structures are mentioned below:

a) Fibroblast-populated skin substitutes

b)Naturally derived Scaffolds (acellular dermis and the amniotic membrane)

c) Collagen-based scaffolds

d) Fibrin based materials

e) Gelatin based scaffolds

f) Hybrid Scaffolds

g) Synthetic Scaffolds (polymers)


Naturally Derived Scaffolds

Acellular Dermis

Acellular Cadaveric Dermis under the brand name AlloDermTM is a scaffold, which is generally used for tissue engineering especially in the oral mucosa. It is non-immunogenic which has dual polarity. One side consists of the basal lamina, which is suitable for the epithelial cells. On the other hand, the perfect channels of the vessel are influenced by the fibroblast infiltration (Dickhuth et al. 2015).

The De-Epidermalized Dermis (DED) are used for the preparation of epidermal-dermal composites. It is subsequently used for reconstruction of hard palate mucosal epithelium samples. The De-Epidermalized Bovine Tongue Mucosa is used as a substrate for the keratinocyte culture (Amemiya et al. 2015). The De-Epidermalized Dermis is generally prepared from the thickned skin with split texture on removing the epidermis and the dermal fibroblasts. The basic advantages of De-Epidermalized Dermis (DED) are as follows:

a) Ability to retain the structural properties (even at low temperature or frozen)

b) Lyophilization

c) Ability to remain preserved in glycerol solution

Collagen-based Scaffolds

Pure Collagen Scaffolds

Various scientists and researchers have developed the in vitro oral mucosal model by culturing normal keratinocytes on skin collagen isolated from the bovines in gels containing fibroblasts. Further, this set up was co-cultured in reconstruction medium (Barbagli and Lazzeri, 2015). By developing this technique, they have made a well defined mucosal model that is similar to the local tissues. In further research works scientists developed this model and they cultured oral mucosal tissue by using a telopeptide type I mixed with sponge matrix of contracted bovine skin collagen gels (CCG). This model was composed of lamina propia and fibroblasts embedded in CCG and collagen sponge and cell layers of stratified cell layers present in the surface of the lamina propia (Gauvin et al. 2012). The advantage of this model is that it provides a substrate and base for the formation of keratinocyte multilayer (Barbagli and Lazzeri, 2015). The significant finding of this research model was the detection of laminin expression between the epithelium tissue and lamina propia. However, expression of type IV collagen and hemodesmosome is not recognized and found during this experiment. Moreover, it was found that higher amount of extracellular matrix (ECM) was synthesized in three dimensional porous scaffold model (Heller et al. 2015). This scaffold model was named after the founder and is known as Moriyama’s model. In further research and experiments, Roubhia and Deslauriers carried out another technique in which they mixed bovine skin collagen with the oral fibroblasts of the normal human being and produced engineered lamina propia (Dickhuth et al. 2015). They further seeded oral epithelial cells on this matrix and allowed them to grow and proliferate in an air-liquid interface. However, to track the proliferation rate of the oral epithelial cells the increase in the production of marker Ki-67 and cytokeratins K14, K19, K10 was measured (Barbagli and Lazzeri, 2015). It has been found that Keratinocytes interacts by producing laminarin basement proteins and integrins with the fibroblast. Moreover, this experiment also showed that oral mucosa can produce TNF-α (tumor necrosis factor alpha), interleukins like IL-1β and IL-8, metalloproteases like gelatinase A and gelatinase B. However, it was found that collagen-based scaffolds have poor mechanical properties and cross linking of collagen tissues results in calcification (Bhargava et al. 2011).

i) Cell Source

Apart from the Scaffold, the other important factor, which needs to be considered in oral mucosa, is the type and origin of keratinocytes and fibroblasts. The fibroblasts are generally isolated on the primary dermal layer of skin by an oral mucosal biopsy. These tissues are used for early passage associated with the tissue engineering (Lanzaet al. 2011). This is because the extracellular matrix production that provided by the dermal fibroblasts tends to decrease, as the passage number increases. The Keratinocytes are found to be obtained from different sites in an oral cavity (e.g. hard palate). The usual active human keratinocytes need to be used at the early passage. However, the immortalized keratinocytes (e.g. HaCaT cells or TR146 cells) can be efficiently used in the reconstruction of oral mucosal test models in respect to its extended passage (Barbagli and Lazzeri, 2015). On the other hand, the epidermal differentiation associated with the transformed keratinocytes is considered imperfect as the decisive steps of terminal differentiation does not take place. The tumor cells are considered anomalous and thereby it is not used for any clinical usage (Gil et al. 2015).

ii) Culture Medium

Frequently used cultural medium associated with the oral mucosa reconstruction is the Dulbecco’s Modified Eagle Medium (DMEM)-Ham’s F-12 Medium (3:1). This is usually supplemented with the Fetal Calf Serum (FCS) along with other elements such as Glutamine, Adenine, Insulin, Epidermal Growth Factor (EGF), Transferrin, Tri-Iodothyronine, Hydrocortisone, Fungizone, Streptomycin, and Penicillin (Heller et al. 2015).

Human Oral Mucosa which is formed by tissue engineering, was found to be equivalent to the Serum-free culture medium, was considered as an efficient protocol, associated with the context (Dickhuth et al. 2015). The elimination of the usage of serum and thereby the irradiation of mouse fibroblast feeder layers are associated with this memorandum, which minimized the exposure of human grafts recipients. This is related to the effect of the xenogeneic DNA which is present in the irradiates mouse 3T3 cells and the serum. It can be analyzed that the same techniques were followed for the human conjunctiva along with the oral mucosa corresponding (Cheng and Xie, 2012).

The demonstration was based on the fact that the keratinocytes of oral mucosa and its perfusion is associated with the medium. Moreover, it is observed that it enhances the viability of the cell along with the proliferation while cultured in porous three-dimensional (3D) matrix of collagen-GAG. This provides a cross-linkage between the glutaraldehyde structures associated with the model (Brauchle and Schenke‐Layland, 2013).

Contraction of the tissue highlights towards the movement of the muscles, which is mainly regulated by several co-factors. Myofibroblast plays a cruicial role in the contraction mechanism. It helps to decrease the size of the muscle by gripping towards the edges of the muscles. This is mostly present within the smooth muscle cells. Both the effects of cell proliferation along with apoptosis is monitored by the phenomenon of contraction, which is effectively monitored in this experiment (Osman et al 2015).


2. Spectral Profile of Controlled and Drug Induced Model

Proper monitoring of the tissue-engineered constructs is considered as an important component for the successful implementation of any tissue engineered techniques. To demonstrate and monitor the visible biochemical changes within the collagen cross-links of both controlled and drug-induced tissue engineered model, Raman spectroscopy is primarily used (Brauchle and Schenke‐Layland, 2013). Raman spectroscopy provides a simple and rapid method for monitoring the quality of the tissue-engineered components and thus contains information regarding the biochemical properties of the cells and tissues (Gauvin et al. 2012). The application of the infrared Raman spectroscopy may be demonstrated by monitoring the tissue engineered constructs, which are stressed by high temperature and are exposed to a high concentration of calcium (much higher than the normal value) (Gauvin et al. 2012). Thus, analyzing the Raman spectra helps in understanding the correlation of the CH2 deformation ratio about the phenylalanine ring. The histology and the morphological changes of the tissue-engineered mucosa provide the data regarding the concentration of the glucose consumption that helps in revealing information regarding the specific and sensitive changes in the secondary structure of the protein. Tissue-engineered oral mucosa cells have been treated with a particular antibiotic rapamycin, which helps in understanding the proliferation and capacity of the cells (Cheng and Xie, 2012). A separate set of control has also been kept for making a clear distinction between the control and the rapamycin treated tissue engineered cells (Cheng and Xie, 2012).   

Figure 1.Raman spectroscopy showing the change in wavelength

Introduction of a sugar molecule (for example mannitol, sorbitol, and glucose) during the process of tissue engineering has been analyzed by implementing the method of FTIR (Fourier Transform Infrared Spectroscopy). The studies helps in understanding the interaction between the chitostana and the gelatin fibres present which helps in the formation of the ionic and covalent bonds. The bonding helps in making strong collagen fibres, which helped in revealing the structure of the collagen fibres (Cheng and Xie, 2012). Thus spectral analysis by FTIR helps in understanding and revealing the nature and bonding of the collagen fibres during the process of tissue engineering (Votteler et al. 2012). Tissue engineering is considered as one of the most dynamic and important method for assisting tissue engineering of oral mucosa. The analysis by Raman spectra also reveals the data in response to the present of an antibiotic. Thus, it can be stated that in presence of an antibiotic rapamycin there is a change little increase in the wavelength in presence of an antibiotic (Brauchle and Schenke‐Layland, 2013). The Raman spectroscopy has been supported by the FTIR analysis, which helps in understanding regarding the various surface properties associated with the introduction of the antibiotic. The FTIR analysis also helps in understanding regarding the change in wave number in accordance with the spectral data produced and thus helps in facilitating the proper tissue engineering techniques in terms of oral cell mucosa (Gauvin et al. 2012). This also helps to assess the various numbers of biochemical changes produced in normal skin caused by the tissue engineered oral cell mucosa. Cluster analysis helps in the evaluation of the vibration modes, which is associated in understanding and revealing the structure of the associated protein, which indicates changes in the secondary conformation of the various changes in the tissue. FTIR spectra are primarily acquired in aspect of three experimental configuration which includes transmission, reflection-absorption and total reflection which includes the fraction of total attenuated radiation (ATR). The spectral analysis also helps in understanding of the various anatompophological characteristics of both the control and the antibiotic treated tissue cells (Heller et al. 2015). Thus, the present change in the wavelength and wave numbers of a particular tissue represents a valuable data for organ and tissue reconstruction (Barbagli and Lazzeri, 2015). The control has been subjected to two different kinds of stress, which includes thermal changes and increase in the concentration of the calcium. The changes helped in understanding regarding the various changes in the value of the wavelength in terms of the data obtained with the help of Raman spectroscopy and FTIR. The CH2 band ratios also helped in revealing the ratio of the phenylalanine bonds in terms of thermal stress and higher concentration of the calcium molecules. Thus, because of small variation in execution of the productive protocol, the specific variability in the tissue engineered cells can be understood (Cheng and Xie, 2012).

Thus, both Raman and FTIR provide effective data in understanding the overall change in the wavelength produced in response to the presence of antibiotic rapamycin. The antibiotic rapamycin thus disrupts the various bonds and thereby leads to an overall increase in the wavelength of the resulting spectroscopy analysis (Dickhuth et al. 2015).

3. Monitoring the effects of B-APN

The effect of APN on a drug induced model is described in the graph presented below:

It can be analyzed from this graphical interpretation that there is a considerable increase in the slope. The activity of absorbance doubles itself within 60 minutes, which highlights towards the higher efficiency of the graphical analysis (Heller et al. 2015).


4. Constructing a Chemo-metric Modeling system

Chemo-metrics would be an effective parameter related to the article.  It reflects towards the usage of statistical and mathematical protocol in order to improve the understanding of chemical information and thereby correlate the quality parameters associated to it. The patterns of the data are modeled, which are routinely applied to the future data to predict the same quality parameters (Cheng and Xie, 2012). The result attained from the chemo-metric approach focuses towards gaining efficiencies in assessing the product quality. More efficient laboratory practices are highlighted through this quality control system. Hence, for constructing the chemo-metric modeling system for analyzing the spectral data, an appropriate instrumentation along with an effective and interconnectivity software (for interpreting the patterns of the obtained data) needs to be implemented on the primary basis (Bhargava et al. 2011).

Chemo-metrics provides the spectroscopists the various ways to solve the calibration issues, which are interrelated to the spectral data. It is recommendable that the construction of chemo-metric modeling system should be monitored is such a way that helps to enhance the developmental methods significantly and thereby make effective routine use of the statistical models for data analysis(Amemiya et al. 2015). Implementing Unscrambler® for analyzing the spectroscopic data, modeling, classifying the data analyzed and thereby predicting to meet the protocol of quality assurance and monitoring would be an effective step related to the context. The researcher would be requiring other equipments for constructing an effective chemo-metric system which are stated below:

  • A Spectroscopic data pre processing unit, which would help to reduce and thereby rectify the interferences such as overlapped bands, scattering, baseline drifts and the path length variations is considered as the primary equipment associated to the research study (Gauvin et al. 2012). Recommending Multiplicative Scatter Correction (MSC) pretreatment device would be effective as it would focus towards building a reliable relationship between the cell structure content present within the tissue engineered oral mucosa and the spectral data for scatter correction (Brauchle and Schenke‐Layland, 2013).

  • Establishing an effective Calibration and Diagnostic means of sample from the tissue engineered oral mucosa would be effective for the system. Variable selection of the sample would be helpful in deducing an effective result calculation and thereby rebuilding representative and reliable model (Gil et al. 2015).

  • Model integration along with Model Validation would be helpful in develop the rigorous prediction system. Considerable it would be helpful in measuring the Quality Control (QC) and formulating the relative time product quality and protocol monitoring (Cheng and Xie, 2012).

Apart from these requirements, the spectroscopists would be requiring the following chemo-metric software package in order to deduce the data associated to the context. This includes the following:

  • Principal Component Analysis (PCA)

  • SIMCA and PLS-DA Classification

  • Regression (PLS, PCR, MLR, 3-way PLS) and Prediction (Heller et al. 2015)

After gathering all the equipments along with the software package, the basic data analysis process is carried out in a systematic order.

Figure: Flowchart representing the protocol for Chemo-metric System (Gil et al. 2015)

Data input is considered as the most overlooked stage associated to the protocol. This is the main crucial stage in the entire instrumentation (Gauvin et al. 2012). The data, which is analyzed, is efficiently transferred into the software device. The proprietary collection software converts this protocol in a complex manner. The outliers are removed subsequently, which is considered as a delicate procedure. This is followed by a Grubbs test, which mainly helps to detect the outliers. The false outliers, which are present at the extreme point f the system and thereby appear infrequently within the data are subsequently removed (Amemiya et al. 2015). On the other hand, the true outliers (samples and variables which are statistically different from one another) are effectively removed (Barbagli and Lazzeri, 2015).

The next stage involves the protocol of Preprocessing. The main goal associated to the preprocessing stage involves the removal of variation within the data, which does not pertain to the analytical information (Brauchle and Schenke‐Layland, 2013). The typical preprocessing methods, which can be analyzed for evaluating the cell lines of oral mucosa, would include the following:

  • Baseline Correction
  • Mean Centering
  • Normalization
  • Orthogonal Signal Correction
  • Multiplicative Scatter Correction
  • Savitsky-Golay Derivatisation

The output, which is attained from this experimental setup, is mainly classified into two types, i.e. Qualitative and Quantitative segments. The Qualitative model would mainly highlight the classified models, effects of classification and the evidences behind classification error. On the other hand, the Quantitative segment would focus towards the prediction models and the involvement of RMSEC and RMSEP (Bhargava et al. 2011).



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