58 research outputs found
KERATIN-BASED 3D SCAFFOLD DESIGN FOR BONE TISSUE ENGINEERING
No full textIn questo lavoro di tesi è stato progettato e caratterizzato uno scaffold 3D di cheratina innovativo tramite un approccio bio-ingegneristico integrato che unisce anche lo stimolo bio-meccanico generato da un campo elettromagnetico pulsato (PEMF).
Lo scaffold è stato preparato mediante la fibrillazione di fibre di lana (cheratina) sfruttando i componenti istologici che le compongono (fibrille o cellule corticali), al fine di ottenere una struttura adatta alla rigenerazione ossea. E’ stato quindi progettato uno scaffold di cheratina (spugna di fibrille di lana) con micro e macro-porosità interconnesse di dimensione controllata, al fine di ospitare le cellule, favorendone l’adesione e guidando opportunamente la formazione di nuovo tessuto.
Crosslinks aggiuntivi impartiti alle catene cheratiniche hanno permesso di ottenere uno scaffold con eccellente stabilità in acqua nonostante l’elevato rigonfiamento, resilienza alla compressione e stabilità alla degradazione. La cheratina contiene sequenze di adesione cellulare che facilitano la crescita delle cellule. Infatti, cellule SAOS-2 coltivate sulle spugne di fibrille di lana in condizioni proliferative (PM) e osteoinduttive (OM), hanno mostrato rispettivamente una crescita e differenziamento ottimali. Il differenziamento, in termini di aumento della mineralizzazione e deposizione di proteine della matrice è stimolato dall’applicazione del PEMF. Lo stimolo bio-meccanico velocizza il processo di differenziamento in condizioni osteoinduttive, mostrando una perfetta sinergia tra gli stimoli biochimici e meccanici nell’accelerazione del processo differenziativo.
La valutazione della crescita di cellule staminali da midollo osseo su scaffold di cheratina 2D e 3D (film di fibrille di lana e idrogeli di cheratina) ha mostrato la loro efficacia nel supportare le cellule staminali; in particolare, i sistemi 3D, grazie al loro diverso tempo di degradazione, possono funzionare da cell-delivery system o da impalcatura a lungo termine.
L’elevato tempo di degradazione mostrato dalla spugna di fibrille di lana suggerisce che questo scaffold possa essere promettente come supporto a lungo termine per la formazione ossea in vivo.Novel keratin-based 3D scaffold for bone tissue engineering have been produced, characterized and tested, applying bio-mechanical stimuli generated by a pulsed electromagnetic field (PEMF). Controlled-size, interconnected porosity, tailored to match the natural bone tissue features, has been designed for cell guesting, proliferation and guided tissue formation, exploiting the natural histological structure of the wool fibers. Additional crosslinking of the keratin chains allowed obtaining excellent water stability and significant swelling due to the synergic contribution of hydrophilicity and porosity, associated to increased compression resilience and ageing resistance. Keratin contains cellular-binding motifs for cell attachment found in the native extra-cellular matrix which facilitate better growth, providing proliferation signals and minimising apoptotic cell death. Viability and consistent proliferation were observed for SAOS-2 human osteoblast cells cultured both in proliferative (PM) and osteogenic (OM) media, highlighted by PEMF application, especially in osteogenic conditions, with increased mineralization and higher ECM proteins deposition. PEMF stimulated an earlier differentiation in osteogenic conditions, showing a perfect synergy between biochemical and mechanical stimuli in acceleration of the differentiation process.
Evaluation of the attachment and growth of human bone marrow mesenchymal cells on different 2D and 3D keratin-based scaffolds, made with wool fibril films, sponges and hydrogels, showed that keratin-based materials are an effective support for stem cell growth. In particular, 3D systems gave the best results and, thanks to the different ageing time, they can be suitable as cell delivery system or for long-term scaffolding.
The longer degradation rate suggests that wool fibril sponges can be promising candidates for long-term support of bone formation in vivo
Natural Fibers Insulation Materials: Use of textile and agri-food waste in a circular economy perspective
No full textFibrous-based materials are among the most used for the thermal and acoustic insulation of building envelopes and among the ones with the best flexibility in use. In building construction, the demand for products with low environmental impact - in line with the Green Deal challenge of the European Community - is growing, but the building market is still mostly oriented towards traditional products, missing the many opportunities for using waste materials from existing industrial production. The paper presents the experimental results of new thermal and acoustic insulation products for building construction and interior design, based on previous experiences of the research group. They are entirely produced using waste sheep's wool as a "matrix" and other waste fibers, as "fillers". Proposed materials derive from textile and agro-industrial chains of Piedmont region and have no other uses, different from the thermal valorization as biomass. The panels have characteristics of rigidity, workability, and thermal conductivity that make them suitable for building envelope insulation
NATURAL FIBRE INSULATION MATERIALS: USE OF TEXTILE AND AGRI-FOOD WASTE IN A CIRCULAR ECONOMY PERSPECTIVE
No full textFibrous materials are among those most used for the thermal and acoustic insulation of building envelopes and are also suitable for a wide range of applications. In building construction, the demand for products with low environmental impact - in line with the Green Deal challenge of the European Community - is growing, but the building market is still mostly oriented towards traditional products, missing the many opportunities for using waste materials from existing industrial production. The paper presents the experimental results of new thermal and acoustic insulation products for building construction and interior design, based on previous experiences of the research group. They are produced entirely using waste sheep's wool as a "matrix" and other waste fibres, as “fillers”. The materials proposed originate from textile and agri-industrial chains in the Piedmont region and have no uses other than waste-to-heat biomass. The panels have characteristics of rigidity, workability, and thermal conductivity that make them suitable for building envelope insulation
APPLICATIONS OF BUILDING INSULATION PRODUCTS BASED ON NATURAL WOOL AND HEMP FIBERS
No full textFITNESs, Fibre Tessili Naturali per l'Edilizia Sostenibile (Natural Textile Fibers for Sustainable Building), is a research project concerning an experimental hemp and sheep wool insulation panel. The new panel has two main innovative features: unlike the already existing hemp and wool insulation mats, it is a semi-rigid product and has low environmental impact, as shown by the Life Cycle Assessment. FITNESs panels are particularly suitable for eco-building sector, as they are 100% natural, recyclable and made with by-products from local production chains (Piemonte Region). The paper presents the production process of the panel from wool and hemp fibers and some experimental applications for sustainable architecture
Keratin based materials with perspective biomedical applications
No full textThe natural composite assembly of wool, made of
cortical cells embedded in a highly crosslinked, sulphur-rich
keratin matrix, has been exploited to prepare keratin-based
biomaterials for tissue engineering. Disruption of the wool fibre
structure by ultra-sonication after mild alkali treatment,
produced a suspension of cortical cells in aqueous hydrolysed
protein solution, that was cast into films and sponges with
perspective for tissue engineering, in particular for bone
reconstruction
Physicochemical properties of keratin extracted from wool by various methods
No full textKeratin from wool fibers was extracted with different extraction methods, for example oxidation, reduction, sulfitolysis, and superheated water hydrolysis.
Different samples of extracted keratin were characterized by molecular weight determination, FT-IR and NIR spectroscopy, amino acid analysis, and thermal behavior.
While using oxidation, reduction, and sulfitolysis, only the cleavage of disulfide bonds takes place; keratin hydrolysis leads to the breaking of peptide bonds with the formation of low molecular weight proteins and peptides. In the FT-IR spectra of keratoses, the formation of cysteic acid appears, as well as the formation of Bunte salts (–S–SO3–) after the cleavage of disulfide bonds by sulfitolysis. The amino acid composition confirms the transformation of amino acid cystine, which is totally converted into cysteic acid following oxidative extraction and almost completely destroyed during superheated water hydrolysis. Thermal behavior shows that keratoses, which are characterized by stronger ionic interaction and higher molecular weight, are the most temperature stable keratin, while hydrolyzed wool shows a poor thermal stability
Preparation of keratin-based microcapsules for encapsulation of hydrophilic molecules
No full textThe interest towards microcapsules based on non-toxic, biodegradable and biocompatible polymers, such as proteins, is increasing considerably. In this work, microcapsules were prepared using water soluble keratin, known as keratoses, with the aim of encapsulating hydrophilic molecules. Keratoses were obtained via oxidizing extraction of pristine wool, previously degreased by Soxhlet. In order to better understand the shell part of microcapsules, pristine wool and obtained keratoses were investigated by FT-IR, gel-electrophoresis and HPLC. Production of the microcapsules was carried out by a sonication method. Thermal properties of microcapsules were investigated by DSC. Microencapsulation and dye encapsulation yields were obtained by UV-spectroscopy. Morphological structure of microcapsules was studied by light microscopy, SEM, and AFM. The molecular weights of proteins analyzed using gel-electrophoresis resulted in the range of 38–62 kDa. The results confirmed that the hydrophilic dye (Telon Blue) was introduced inside the keratoses shells by sonication and the final microcapsules diameter ranged from 0.5 to 4 μm. Light microscope investigation evidenced the presence of the dye inside the keratoses vesicles, confirming their capability of encapsulating hydrophilic molecules. The microcapsule yield and dye encapsulation yield were found to be 28.87 ± 3% and 83.62 ± 5% respectively
Segmentación semántica multiclase en la digitalización del patrimonio mueble utilizando técnicas de aprendizaje profundo
No full text[EN] Digitisation processes of movable heritage are becoming increasingly popular to document the artworks stored in our museums. An increasing number of strategies for the three-dimensional (3D) acquisition and modelling of these invaluable assets have been developed in the last few years, to efficiently respond to this documentation need and contribute to deepening the knowledge of the masterpieces investigated constantly by researchers operating in many fieldworks. Nowadays, one of the most effective solutions is represented by the development of image-based techniques, usually connected to a Structure-from-Motion (SfM) photogrammetric approach. However, while the acquisition of the images is relatively rapid, it is the processes connected to the data processing that are very time-consuming and require substantial manual involvement of the operator. The development of deep learning-based strategies can be an effective solution to enhance the level of automatism. In the case of the current research, which has been carried out in the framework of the digitisation of a collection of wooden maquettes stored in the ‘Museo Egizio di Torino’ using a photogrammetric approach, an automatic masking strategy using deep learning techniques is proposed, to increase the level of automatism and therefore, optimise the photogrammetric pipeline. Starting from a manually annotated dataset a neural network has been trained to automatically perform a semantic classification with the aim to isolate the maquettes from the background. The proposed methodology has allowed obtaining automatically segmented masks with a high degree of accuracy. The followed workflow is described (as regards acquisition strategies, dataset processing, and neural network training), and the accuracy of the results is evaluated and discussed. In addition, the possibility of performing a multiclass segmentation on the digital images to recognise different categories of objects in the images and define a semantic hierarchy is proposed to perform automatic classification of different elements in the acquired images.[ES] Los procesos de digitalización del patrimonio mueble son cada vez más populares para documentar las obras de arte almacenadas en nuestros museos. En los últimos años se han desarrollado un número creciente de estrategias de adquisición y modelado tridimensional (3D) de estos activos de valor incalculable, que responden de manera eficiente a esta necesidad de documentación y contribuyen a profundizar en el conocimiento de las obras maestras investigadas constantemente por investigadores que operan en muchos trabajos de campo. Hoy en día, una de las soluciones más efectivas está relacionada con el desarrollo de técnicas basadas en imágenes, generalmente conectadas a un enfoque fotogramétrico de estructura-y-movimiento (SfM). Sin embargo, si bien la adquisición de las imágenes es relativamente rápida, son los procesos relacionados con el procesamiento de los datos los que consumen mucho tiempo y requieren una participación manual sustancial del operador. El desarrollo de estrategias basadas en el aprendizaje profundo puede ser una solución eficaz para mejorar el nivel de automatismo. En el caso de la presente investigación, que se ha llevado a cabo en el marco de la digitalización de una colección de maquetas de madera almacenadas en el 'Museo Egizio di Torino' mediante un enfoque fotogramétrico, se propone una estrategia de enmascaramiento automático mediante técnicas de aprendizaje profundo, que incrementa el nivel de automatismo y por tanto optimiza el flujo fotogramétrico. A partir de un conjunto de datos anotados manualmente, se ha entrenado una red neuronal que realiza automáticamente una clasificación semántica con el objetivo de aislar las maquetas del fondo. La metodología propuesta ha permitido obtener más caras segmentadas automáticamente con alto grado de precisión. Se describe el flujo de trabajo seguido (en cuanto a estrategias de toma, procesamiento del conjuntos de datos y entrenamiento de las redes neuronales), y se evalúa y discute la precisión de los resultados. Además, se propone la posibilidad de realizar una segmentación multiclase sobre las imágenes digitales que permitan reconocer diferentes categorías de objetos en las imágenes y definir una jerarquía semántica que clasifique automáticamente diferentes elementos en la toma de las imágenes.The authors thank Volta® A.I. (and in particular Silvio Revelli) for the contribution to this work and for providing high-end hardware for neural network training.
In addition, they would like to thank Alessia Fassone of Museo Egizio di Torino and all the people involved in the B.A.C.K. TO T.H.E. F.U.T.U.RE. project (in particular, Fulvio Rinaudo, who coordinated the Geomatic team).
Finally, they wish to express their gratitude to Nannina Spanò and Filiberto Chiabrando for the helpful confrontation during the presented research.Patrucco, G.; Setragno, F. (2021). Multiclass semantic segmentation for digitisation of movable heritage using deep learning techniques. Virtual Archaeology Review. 12(25):85-98. https://doi.org/10.4995/var.2021.15329OJS85981225Adami, A., Balletti, C., Fassi, F., Fregonese, L., Guerra, F., Taffurelli, L., Vernier, P. (2015). The bust of Francesco II Gonzaga: From digital documentation to 3D printing. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-5/W3, 9-15. https://doi.org/10.5194/isprsannals-II-5-W3-9-2015Badrinarayanan, V., Kendall, A., Cipolla, R. (2017). Segnet: A deep convolutional encoder-decoder architecture for image segmentation. 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Superheated Water Hydrolysis of Waste Wool in a Semi-Industrial Reactor to Obtain Nitrogen Fertilizers
No full textSheep Wool for Sustainable Architecture
No full textSheep wool is a natural material, already used for thermal insulation of pitched roofs, in the form of soft mats. The paper presents a research project called Cartonlana, concerning a new sheep wool-based product with two main innovative features: it is a stiff panel, unlike the existing soft wool mats; it has a low environmental impact, using local recycled sheep wool, otherwise disposed as special waste. Physical and chemical properties of Cartonlana panel were determined by measurements, in order to demonstrate its effectiveness as insulation for buildings: thermal conductivity, acoustic absorption coefficient, absorption offormaldehyde, thermal transmittance of a wal
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