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1.
Phys Med Biol ; 69(11)2024 May 21.
Artigo em Inglês | MEDLINE | ID: mdl-38657639

RESUMO

Optimizing complex imaging procedures within Computed Tomography, considering both dose and image quality, presents significant challenges amidst rapid technological advancements and the adoption of machine learning (ML) methods. A crucial metric in this context is the Difference-Detailed Curve, which relies on human observer studies. However, these studies are labor-intensive and prone to both inter- and intra-observer variability. To tackle these issues, a ML-based model observer utilizing the U-Net architecture and a Bayesian methodology is proposed. In order to train a model observer unaffected by the spatial arrangement of low-contrast objects, the image preprocessing incorporates a Gaussian Process-based noise model. Additionally, gradient-weighted class activation mapping is utilized to gain insights into the model observer's decision-making process. By training on data from a diverse group of observers, well-calibrated probabilistic predictions that quantify observer variability are achieved. Leveraging the principles of Beta regression, the Bayesian methodology is used to derive a model observer performance metric, effectively gauging the model observer's strength in terms of an 'effective number of observers'. Ultimately, this framework enables to predict the DDC distribution by applying thresholds to the inferred probabilities (Part of this work has been presented at: Stocker D, Sommer C, Gueng S, Stäuble J, Özden I, Griessinger J, Weyland M S, Lutters G, Scheidegger S (2023). Probabilistic U-Net Model Observer for the DDC Method in CT Scan Protocol Optimization. The 56th SSRMP Annual Meeting 2023, November 30. - December 1., 2023, Luzern, Switzerland).


Assuntos
Processamento de Imagem Assistida por Computador , Tomografia Computadorizada por Raios X , Processamento de Imagem Assistida por Computador/métodos , Humanos , Teorema de Bayes , Aprendizado de Máquina , Variações Dependentes do Observador
2.
Cell Signal ; 42: 176-183, 2018 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-29074139

RESUMO

Focal adhesion kinase (FAK) integrates signaling from integrins, growth factor receptors and mechanical stress to control cell adhesion, motility, survival and proliferation. Here, we developed a single-component, photo-activatable FAK, termed optoFAK, by using blue light-induced oligomerization of cryptochrome 2 (CRY2) to activate FAK-CRY2 fusion proteins. OptoFAK functions uncoupled from physiological stimuli and activates downstream signaling rapidly and reversibly upon blue light exposure. OptoFAK stimulates SRC creating a positive feedback loop on FAK activation, facilitating phosphorylation of paxillin and p130Cas in adherent cells. In detached cells or in mechanically stressed adherent cells, optoFAK is autophosphorylated upon exposure to blue light, however, downstream signaling is hampered indicating that the accessibility to these substrates is disturbed. OptoFAK may prove to be a useful tool to study the biological function of FAK in growth factor and integrin signaling, tension-mediated focal adhesion maturation or anoikis and could additionally serve as test system for kinase inhibitors.


Assuntos
Criptocromos/metabolismo , Retroalimentação Fisiológica , Quinase 1 de Adesão Focal/metabolismo , Optogenética/métodos , Transdução de Sinais , Adesão Celular , Proteína Substrato Associada a Crk/genética , Proteína Substrato Associada a Crk/metabolismo , Criptocromos/genética , Quinase 1 de Adesão Focal/genética , Regulação da Expressão Gênica , Células HEK293 , Células HeLa , Humanos , Luz , Paxilina/genética , Paxilina/metabolismo , Fosforilação , Plasmídeos/química , Plasmídeos/metabolismo , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/metabolismo , Estresse Mecânico , Transfecção
3.
Eur J Intern Med ; 13(1): 57-64, 2002 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-11836084

RESUMO

Background: In patients with ischemic heart disease (IHD), secondary preventive drug therapy improves overall prognosis. Therefore, this study evaluated cardiovascular drug utilization in patients suffering from IHD, identified factors influencing drug utilization, and determined the prevalence of shortfalls of antithrombotic, beta-blocker, and lipid-lowering drug use. Methods: This study is based on data recorded prospectively between 1996 and 1998 in two Swiss teaching hospitals for the SAS/CHDM pharmacoepidemiologic database project. Drug utilization was evaluated in all 987 monitored medical inpatients with IHD. Results: At discharge, only 64% of patients with IHD received platelet aggregation inhibitors, 42% beta-blockers, and 26% lipid-lowering drugs. Secondary preventive drugs were more frequently administered to patients with acute myocardial infarction and less frequently in the elderly. After including other co-factors, no gender difference could be detected. Shortfalls of antithrombotic therapy occurred in 6.5--8.3% of patients and shortfalls in beta-blocker use in 9.9--23.3%. Only about half of all patients with IHD and elevated cholesterol received lipid-lowering drugs. Conclusions: Drugs for secondary prevention are prescribed to the majority of patients with IHD. However, their use could be further increased, especially in the elderly and in patients with IHD who are admitted to the hospital for reasons other than acute myocardial infarction. Lipid-lowering drugs should also be prescribed more often for patients with hypercholesterolemia.

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