9 resultados para Biomedical Applications X
em AMS Tesi di Laurea - Alm@DL - Università di Bologna
Resumo:
In the past decade the study of superparamagnetic nanoparticles has been intensively developed for many biomedical applications such as magnetically assisted drug delivery, MRI contrast agents, cells separation and hyperthermia therapy. All of these applications require nanoparticles with high magnetization, equipped also with a suitable surface coating which has to be non-toxic and biocompatible. In this master thesis, the silica coating of commercially available magnetic nanoparticles was investigated. Silica is a versatile material with many intrinsic features, such as hydrophilicity, low toxicity, proper design and derivatization yields particularly stable colloids even in physiological conditions. The coating process was applied to commercial magnetite particles dispersed in an aqueous solution. The formation of silica coated magnetite nanoparticles was performed following two main strategies: the Stöber process, in which the silica coating of the nanoparticle was directly formed by hydrolysis and condensation of suitable precursor in water-alcoholic mixtures; and the reverse microemulsions method in which inverse micelles were used to confine the hydrolysis and condensation reactions that bring to the nanoparticles formation. Between these two methods, the reverse microemulsions one resulted the most versatile and reliable because of the high control level upon monodispersity, silica shell thickness and overall particle size. Moving from low to high concentration, within the microemulsion region a gradual shift from larger particles to smaller one was detected. By increasing the amount of silica precursor the silica shell can also be tuned. Fluorescent dyes have also been incorporated within the silica shell by linking with the silica matrix. The structure of studied nanoparticles was investigated by using transmission electron microscope (TEM) and dynamic light scattering (DLS). These techniques have been used to monitor the syntetic procedures and for the final characterization of silica coated and silica dye doped nanoparticles. Finally, field dependent magnetization measurements showed the magnetic properties of core-shell nanoparticles were preserved. Due to a very well defined structure that combines magnetic and luminescent properties together with the possibility of further functionalization, these multifunctional nanoparticles are potentially useful platforms in biomedical fields such as labeling and imaging.
Resumo:
This thesis work has been developed in collaboration between the Department of Physics and Astronomy of the University of Bologna and the IRCCS Rizzoli Orthopedic Institute during an internship period. The study aims to investigate the sensitivity of single-sided NMR in detecting structural differences of the articular cartilage tissue and their correlation with mechanical behavior. Suitable cartilage indicators for osteoarthritis (OA) severity (e.g., water and proteoglycans content, collagen structure) were explored through four NMR parameters: T2, T1, D, and Slp. Structural variations of the cartilage among its three layers (i.e., superficial, middle, and deep) were investigated performing several NMR pulses sequences on bovine knee joint samples using the NMR-MOUSE device. Previously, cartilage degradation studies were carried out, performing tests in three different experimental setups. The monitoring of the parameters and the best experimental setup were determined. An NMR automatized procedure based on the acquisition of these quantitative parameters was implemented, tested, and used for the investigation of the layers of twenty bovine cartilage samples. Statistical and pattern recognition analyses on these parameters have been performed. The results obtained from the analyses are very promising: the discrimination of the three cartilage layers shows very good results in terms of significance, paving the way for extensive use of NMR single-sided devices for biomedical applications. These results will be also integrated with analyses of tissue mechanical properties for a complete evaluation of cartilage changes throughout OA disease. The use of low-priced and mobile devices towards clinical applications could concern the screening of diseases related to cartilage tissue. This could have a positive impact both economically (including for underdeveloped countries) and socially, providing screening possibilities to a large part of the population.
Resumo:
X-ray absorption spectroscopy (XAS) is a powerful means of investigation of structural and electronic properties in condensed -matter physics. Analysis of the near edge part of the XAS spectrum, the so – called X-ray Absorption Near Edge Structure (XANES), can typically provide the following information on the photoexcited atom: - Oxidation state and coordination environment. - Speciation of transition metal compounds. - Conduction band DOS projected on the excited atomic species (PDOS). Analysis of XANES spectra is greatly aided by simulations; in the most common scheme the multiple scattering framework is used with the muffin tin approximation for the scattering potential and the spectral simulation is based on a hypothetical, reference structure. This approach has the advantage of requiring relatively little computing power but in many cases the assumed structure is quite different from the actual system measured and the muffin tin approximation is not adequate for low symmetry structures or highly directional bonds. It is therefore very interesting and justified to develop alternative methods. In one approach, the spectral simulation is based on atomic coordinates obtained from a DFT (Density Functional Theory) optimized structure. In another approach, which is the object of this thesis, the XANES spectrum is calculated directly based on an ab – initio DFT calculation of the atomic and electronic structure. This method takes full advantage of the real many-electron final wavefunction that can be computed with DFT algorithms that include a core-hole in the absorbing atom to compute the final cross section. To calculate the many-electron final wavefunction the Projector Augmented Wave method (PAW) is used. In this scheme, the absorption cross section is written in function of several contributions as the many-electrons function of the finale state; it is calculated starting from pseudo-wavefunction and performing a reconstruction of the real-wavefunction by using a transform operator which contains some parameters, called partial waves and projector waves. The aim of my thesis is to apply and test the PAW methodology to the calculation of the XANES cross section. I have focused on iron and silicon structures and on some biological molecules target (myoglobin and cytochrome c). Finally other inorganic and biological systems could be taken into account for future applications of this methodology, which could become an important improvement with respect to the multiscattering approach.
Resumo:
Conventional inorganic materials for x-ray radiation sensors suffer from several drawbacks, including their inability to cover large curved areas, me- chanical sti ffness, lack of tissue-equivalence and toxicity. Semiconducting organic polymers represent an alternative and have been employed as di- rect photoconversion material in organic diodes. In contrast to inorganic detector materials, polymers allow low-cost and large area fabrication by sol- vent based methods. In addition their processing is compliant with fexible low-temperature substrates. Flexible and large-area detectors are needed for dosimetry in medical radiotherapy and security applications. The objective of my thesis is to achieve optimized organic polymer diodes for fexible, di- rect x-ray detectors. To this end polymer diodes based on two different semi- conducting polymers, polyvinylcarbazole (PVK) and poly(9,9-dioctyluorene) (PFO) have been fabricated. The diodes show state-of-the-art rectifying be- haviour and hole transport mobilities comparable to reference materials. In order to improve the X-ray stopping power, high-Z nanoparticle Bi2O3 or WO3 where added to realize a polymer-nanoparticle composite with opti- mized properities. X-ray detector characterization resulted in sensitivties of up to 14 uC/Gy/cm2 for PVK when diodes were operated in reverse. Addition of nanoparticles could further improve the performance and a maximum sensitivy of 19 uC/Gy/cm2 was obtained for the PFO diodes. Compared to the pure PFO diode this corresponds to a five-fold increase and thus highlights the potentiality of nanoparticles for polymer detector design. In- terestingly the pure polymer diodes showed an order of magnitude increase in sensitivity when operated in forward regime. The increase was attributed to a different detection mechanism based on the modulation of the diodes conductivity.
Resumo:
This work describes the synthesis of a propargylcarbamate-functionalized isophthalate ligand and its use in the solvothermal preparation of a new copper(II)-based metal organic framework named [Cu(1,3-YBDC)]ˑxH2O (also abbreviated as Cu-MOF. The characterization of this compound was performed using several complementary techniques such as infrared (ATR-FTIR) and Raman spectroscopy, X-ray powder diffraction spectroscopy (PXRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), atomic absorption spectroscopy (AAS) as well as thermal and surface area measurements. Synchrotron X-ray diffraction analysis revealed that this MOF contains a complex network of 5-substituted isophthalate anions bound to Cu(II) centers, arranged in pairs within paddlewheel (or “Chinese lantern”) structure with a short Cu…Cu distance of 2.633 Å. Quite unexpectedly, the apical atom in the paddlewheel structure belongs to the carbamate carbonyl oxygen atom. Such extra coordination by the propargylcarbamate groups drastically reduces the MOF porosity, a feature that was also confirmed by BET measurements. Indeed, its surface area was determined to be low (14.5 ± 0.8 m2/g) as its total pore volume (46 mm3/g). Successively the Cu-MOF was treated with HAuCl4 with the aim of studying the ability of the propargylcarbamate functionality to capture the Au(III) ion and reduce it to Au(0) to give gold nanoparticles (AuNPs). The overall amount of gold retained by the Cu-MOF/Au was determined by AAS while the amount of gold and its oxidation state on the surface of the MOF was studied by XPS. A glassy carbon (GC) electrode was drop-casted with a Cu-MOF suspension to electrochemically characterize the material through cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The performance of the modified electrodes towards nitrite oxidation was tested by CV and chronoamperometry.
Resumo:
The aim of this thesis is to demonstrate that 3D-printing technologies can be considered significantly attractive in the production of microwave devices and in the antenna design, with the intention of making them lightweight, cheaper, and easily integrable for the production of wireless, battery-free, and wearable devices for vital signals monitoring. In this work, a new 3D-printable, low-cost resin material, the Flexible80A, is proposed as RF substrate in the implementation of a rectifying antenna (rectenna) operating at 2.45 GHz for wireless power transfer. A careful and accurate electromagnetic characterization of the abovementioned material, revealing it to be a very lossy substrate, has paved the way for the investigation of innovative transmission line and antenna layouts, as well as etching techniques, possible thanks to the design freedom enabled by 3D-printing technologies with the aim of improving the wave propagation performance within lossy materials. This analysis is crucial in the design process of a patch antenna, meant to be successively connected to the rectifier. In fact, many different patch antenna layouts are explored varying the antenna dimensions, the substrate etchings shape and position, the feeding line technology, and the operating frequency. Before dealing with the rectification stage of the rectenna design, the hot and long-discussed topic of the equivalent receiving antenna circuit representation is addressed, providing an overview of the interpretation of different authors about the issue, and the position that has been adopted in this thesis. Furthermore, two rectenna designs are proposed and simulated with the aim of minimizing the dielectric losses. Finally, a prototype of a rectenna with the antenna conjugate matched to the rectifier, operating at 2.45 GHz, has been fabricated with adhesive copper on a substrate sample of Flexible80A and measured, in order to validate the simulated results.
Resumo:
This study presents an evaluation on compressive strength of metakaolin-based geopolymers synthetized by using different activators, KOH and NaOH. The influence of NaOH/KOH concentration ratio together with curing temperature and time were investigated to find the best results from the compressive strength tests of metakaolin-based geopolymers, synthesized with a commercial metakaolin. Aggregates of small grain size referred as fillers, were added to reduce brittleness, and minimize the pore size and shrinkage of the final mixture creating a stronger network. In this work, silt recovered from industrial processes of wash water used for aggregates production was used as a filler in the production of KOH-based geopolymers, examining the possible influence on the mechanical strength of the final product. The curing temperatures chosen for the synthesis were 85°C, 60°C and 40°C. The samples were tested after 7 days and 28 days, according to the UNI EN 1015-11:2019 applied on Ca-based cements, analyzing the differences in mechanical strength comparing samples with similar and different compositions. The study presented in total 72 synthetized geopolymer specimens that were analyzed with unconfined compression test (UCT). The characterization of the starting materials metakaolin and silt was carried out using X- ray diffraction analysis (XRD). Whereas, the formed geopolymers were analyzed using X- ray diffraction (XRD), and scanning electron microscopy (SEM) with energy dispersive X- ray spectroscopy (EDS).
Resumo:
In order to estimate depth through supervised deep learning-based stereo methods, it is necessary to have access to precise ground truth depth data. While the gathering of precise labels is commonly tackled by deploying depth sensors, this is not always a viable solution. For instance, in many applications in the biomedical domain, the choice of sensors capable of sensing depth at small distances with high precision on difficult surfaces (that present non-Lambertian properties) is very limited. It is therefore necessary to find alternative techniques to gather ground truth data without having to rely on external sensors. In this thesis, two different approaches have been tested to produce supervision data for biomedical images. The first aims to obtain input stereo image pairs and disparities through simulation in a virtual environment, while the second relies on a non-learned disparity estimation algorithm in order to produce noisy disparities, which are then filtered by means of hand-crafted confidence measures to create noisy labels for a subset of pixels. Among the two, the second approach, which is referred in literature as proxy-labeling, has shown the best results and has even outperformed the non-learned disparity estimation algorithm used for supervision.
Resumo:
Nowadays the idea of injecting world or domain-specific structured knowledge into pre-trained language models (PLMs) is becoming an increasingly popular approach for solving problems such as biases, hallucinations, huge architectural sizes, and explainability lack—critical for real-world natural language processing applications in sensitive fields like bioinformatics. One recent work that has garnered much attention in Neuro-symbolic AI is QA-GNN, an end-to-end model for multiple-choice open-domain question answering (MCOQA) tasks via interpretable text-graph reasoning. Unlike previous publications, QA-GNN mutually informs PLMs and graph neural networks (GNNs) on top of relevant facts retrieved from knowledge graphs (KGs). However, taking a more holistic view, existing PLM+KG contributions mainly consider commonsense benchmarks and ignore or shallowly analyze performances on biomedical datasets. This thesis start from a propose of a deep investigation of QA-GNN for biomedicine, comparing existing or brand-new PLMs, KGs, edge-aware GNNs, preprocessing techniques, and initialization strategies. By combining the insights emerged in DISI's research, we introduce Bio-QA-GNN that include a KG. Working with this part has led to an improvement in state-of-the-art of MCOQA model on biomedical/clinical text, largely outperforming the original one (+3.63\% accuracy on MedQA). Our findings also contribute to a better understanding of the explanation degree allowed by joint text-graph reasoning architectures and their effectiveness on different medical subjects and reasoning types. Codes, models, datasets, and demos to reproduce the results are freely available at: \url{https://github.com/disi-unibo-nlp/bio-qagnn}.