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Desenvolvimento de sondas multimodais baseadas em pontos quânticos para aplicações biomédicasCABRAL FILHO, Paulo Euzébio 15 July 2016 (has links)
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Previous issue date: 2016-07-15 / CAPES / Os pontos quânticos ou quantum dots (QDs) são nanocristais fluorescentes de
semicondutores com propriedades ópticas únicas, tendo como principais vantagens: (1)
alta resistência à fotodegradação, possibilitando o acompanhamento de eventos
biológicos em tempo real e, (2) superfície ativa, permitindo a conjugação a
biomoléculas que vão propiciar especificidade às marcações, além de possibilitar
também sua ligação a outras nanopartículas. Com isso, é possível quantificar uma
variedade de biomoléculas em células e tecidos e desenvolver nanossondas bimodais
(magnético-fluorescentes) baseadas em QDs. O desenvolvimento de nanopartículas
bimodais pode aliar as vantagens das técnicas baseadas em fluorescência com as de
imagem por ressonância magnética (IRM). Entretanto, a obtenção de sondas bimodais é
ainda um desafio, pois durante a conjugação devem ser mantidas as propriedades
fluorescentes e magnéticas das nanopartículas, e com isso ainda há poucos trabalhos que
façam aplicações em sistemas biológicos. O objetivo desta tese se caracteriza pelo
desenvolvimento de sondas com propriedades multimodais baseadas em QDs de
Telureto de Cádmio (CdTe) associadas a nanopartículas magnéticas de óxido de ferro
como marcadores sítio-específicos em células cancerígenas. Inicialmente os QDs foram
conjugados covalentemente à transferrina (Tf) [QDs-Tf] para a quantificação específica
de seus receptores (TfRs) em células HeLa e em duas linhagens de glioblastoma (U87 e
DBTRG). Através de ensaios de saturação do TfR, foi possível inferir sobre a taxa de
renovação deste receptor nessas células. Os resultados mostraram que as células HeLa e
as DBTRG possuem uma maior quantidade do TfR quando comparadas às U87. As
DBTRG apresentaram maior taxa de renovação do TfR, quando comparadas aos outros
dois tipos, demonstrando que os conjugados QDs-Tf são potenciais ferramentas para o
estudo da biologia celular do câncer. Posteriormente, nanossondas bimodais (QDsMNPs),
baseadas em QDs associados a nanopartículas magnéticas de óxido de ferro,
foram obtidas por conjugação covalente. De acordo com as caracterizações, QDs-MNPs
mantiveram suas propriedades ópticas e magnéticas e apresentaram-se como potenciais
sondas inespecíficas para fluorescência e para aquisição de imagens por RM ponderadas
em T2 (tempo de relaxação nuclear transversal). A conjugação prévia dos QDs a Tf,
além de fornecer informações sobre a biologia do câncer, auxiliou também na
padronização da marcação específica do TfR em células cancerígenas e no
estabelecimento de protocolos de conjugação das sondas bimodais a Tf. Por fim, as
QDs-MNPs foram conjugadas covalentemente a Tf e essa nova sonda multimodal
[(QDs-MNPs)-Tf] reconheceu especificamente os TfR em células HeLa. As
caracterizações indicaram que o sistema multimodal não apresentou alteração
significativa nas propriedades ópticas e exibiu uma maior relaxividade transversal (r2),
se mostrando igualmente potencial sonda para análise por fluorescência e IRM
ponderada em T2. Neste trabalho foram obtidas nanossondas promissoras para serem
aplicadas na compreensão da biologia celular do câncer, além de auxiliar em métodos
diagnósticos e terapêuticos para essa doença. / Quantum dots (QDs) are fluorescent semiconductor nanocrystals with unique optical
properties, which have as major advantages: (1) the high resistance to photobleaching,
making possible to monitor biological events in real-time and, (2) active surface,
allowing the conjugation not only with biomolecules for specific labeling, but also to
other nanoparticles. Thus, it would be possible to quantify a variety of biomolecules in
cells and tissues, as well as to develop bimodal nanoprobes (fluorescent-magnetic)
[BNPs] based on QDs. The development of BNPs can help to combine the advantages
of the fluorescence with the resonance magnetic imaging techniques. However, the
preparation of bimodal probes can still be considered a challenge, since the fluorescent
and magnetic nanoparticles’ properties need to be preserved after conjugation.
Therefore, there are still few works applying BNPs in biological studies. The aim of this
thesis was to develop nanoprobes, with multimodal properties, based on cadmium
telluride (CdTe) QDs conjugated with iron oxide magnetic nanoparticles (MNPs), for
site-specific labeling in cancer cells. For this, initially, QDs were covalently coupling to
transferrin (Tf) [QDs-Tf] and used to quantify the transferrin receptor (TfRs) in HeLa
cells as well as in two glioblastoma lines (U87 and DBTRG). Furthermore, by a TfR
saturation assay, it was possible to study the recycling rate of this receptor in cells
studied. The results showed that HeLa and DBTRG cells present a higher amount of
TfRs when compared to U87. DBTGR showed a higher TfR recycling rate, when
compared to the other two lineages, demonstrating that QDs-Tf conjugates are potential
tools to study the cancer cell biology. BNPs, based on the conjugation of QDs with
MNPs (QDs-MNPs), were obtained by covalent coupling. According to
characterizations, the BNPs remained with their optical and magnetic properties
preserved and showed to be potential unspecific probes for fluorescence analysis and for
T2-weighted magnetic resonance imaging (MRI) acquisition. The conjugation of QDs to
Tf, performed previously, was a valuable step not only to provide us information about
the biology of cancer cells, but also for the standardization of TfR specific labeling and
the establishment of protocol to conjugate the BNPs with Tf. Therefore, QDs-MNPs
were also covalently coupling to Tf and this new multimodal nanotool [(QDs-MNPs)Tf]
was also able to recognize specifically TfRs in HeLa cells. The multimodal
nanosystems presented their fluorescent properties practically unchanged and also
exhibited a higher transversal relaxivity (r2), when compared to bare BNPs, showing
likewise potential to be used for fluorescence and T2-weighted MRI analyses. In this
work, it was developed promising nanoprobes, able to be applied for the cancer cell
biology comprehension, and with potential for helping in the improvement of diagnostic
and therapeutic methods for this disease.
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Training large multimodal language models with ethical valuesRoger, Alexis 10 1900 (has links)
The rapid expansion of artificial intelligence (AI) in modern society, exemplified by systems like ChatGPT and Stable Diffusion, has given rise to significant ethical considerations. These systems, increasingly prevalent in diverse sectors such as mental health treatment, as in Koko, and art creation, necessitate a careful examination of their alignment with human values. This thesis addresses the pressing need for ethical evaluation of multimodal AI systems - those capable of processing and responding to both text and image inputs.
Our research is twofold: initially, we focus on developing a multimodal ethical database through interactive human feedback. Participants assess various examples, determining their ethical appropriateness. This process culminates in a dataset that serves as a foundation for the subsequent phase - designing and testing algorithms capable of autonomously evaluating the morality of AI responses. We explore the effectiveness of two models in this context: a RoBERTa-large classifier and a multilayer perceptron classifier.
Furthermore, this thesis highlights significant limitations in the existing multimodal AI systems studied. We propose alternative models, offering a comparative analysis mainly in terms of performance. This comprehensive study not only contributes to the field of AI alignment but also proposes methodologies for enhancing the moral framework within which these influential technologies operate. / L'expansion rapide de l'intelligence artificielle (IA) dans la société moderne, illustrée par des systèmes tels que ChatGPT et Stable Diffusion, a suscité d'importantes considérations éthiques. Ces systèmes, de plus en plus présents dans divers secteurs tels que le traitement de la santé mentale, avec Koko, et la création artistique, nécessitent un examen attentif de leur alignement avec les valeurs humaines. Ce mémoire aborde le besoin pressant d'une évaluation éthique des systèmes d'IA multimodaux - capables de traiter et de répondre à la fois aux entrées textuelles et visuelles.
Notre recherche est double : initialement, nous nous concentrons sur le développement d'une base de données éthiques multimodales par le biais de retours interactifs d'utilisateurs. Les participants évaluent divers exemples pour déterminer leur éthique. Ce processus aboutit à un ensemble de données qui sert de fondement à la phase suivante - la conception et le test d'algorithmes capables d'évaluer de manière autonome la moralité des réponses de l'IA. Nous explorons l'efficacité de deux modèles dans ce contexte : un classificateur RoBERTa-large et un perceptron multicouche.
De plus, ce mémoire met en évidence des limitations significatives dans les systèmes d'IA multimodaux existants étudiés. Nous proposons des modèles alternatifs, offrant une analyse comparative en termes de performance. Cette étude complète contribue non seulement au domaine de l'alignement de l'IA, mais propose également des méthodologies pour améliorer le cadre moral dans lequel ces technologies influentes opèrent.
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