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Akademický článek

Novel protein-truncating variant in the APOB gene may protect from coronary artery disease and adverse cardiovascular events

Autor: Gabriele Mango, Nicola Osti, Silvia Udali, Anna Vareschi, Giovanni Malerba, Alejandro Giorgetti, Francesca Pizzolo, Simonetta Friso, Domenico Girelli, Oliviero Olivieri, Annalisa Castagna, Nicola Martinelli

Publikováno v: Atherosclerosis Plus, Vol 49, Iss , Pp 42-46 (2022)

Background and aims: Genetic testing is still rarely used for the diagnosis of dyslipidemia, even though gene variants determining plasma lipids levels are not uncommon. Methods: Starting from a a pilot-analysis of targeted Next Generation Sequencing

Externí odkaz: https://doaj.org/article/1dc939bde54d463eb67694b264f9cbf7

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Akademický článek

Crosstalk between Bone and Muscles during Physical Activity

Autor: Luca Dalle Carbonare, Arianna Minoia, Sharazed Zouari, Francesca Cristiana Piritore, Anna Vareschi, Maria Grazia Romanelli, Maria Teresa Valenti

Publikováno v: Cells, Vol 12, Iss 16, p 2088 (2023)

Bone–muscle crosstalk is enabled thanks to the integration of different molecular signals, and it is essential for maintaining the homeostasis of skeletal and muscle tissue. Both the skeletal system and the muscular system perform endocrine activit

Externí odkaz: https://doaj.org/article/792385988b434c54b88d892fe9741e43

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Akademický článek

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Noisy Laplace deconvolution with error in the operator

Autor: Vareschi, Thomas

We adress the problem of Laplace deconvolution with random noise in a regression framework. The time set is not considered to be fixed, but grows with the number of observation points. Moreover, the convolution kernel is unknown, and accessible only

Externí odkaz: http://arxiv.org/abs/1303.7437

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Application of second generation wavelets to blind spherical deconvolution

Autor: Vareschi, Thomas

We adress the problem of spherical deconvolution in a non parametric statistical framework, where both the signal and the operator kernel are subject to error measurements. After a preliminary treatment of the kernel, we apply a thresholding procedur

Externí odkaz: http://arxiv.org/abs/1301.3289

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Blockwise SVD with error in the operator and application to blind deconvolution

Autor: Delattre, S., Hoffmann, M., Picard, D., Vareschi, T.

We consider linear inverse problems in a nonparametric statistical framework. Both the signal and the operator are unknown and subject to error measurements. We establish minimax rates of convergence under squared error loss when the operator admits

Externí odkaz: http://arxiv.org/abs/1204.2964

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