Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Maria Irene Pastena"'
Autor:
Annarita Fanizzi, Domenico Pomarico, Alessandro Rizzo, Samantha Bove, Maria Colomba Comes, Vittorio Didonna, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Maria Irene Pastena, Nicole Petruzzellis, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Vito Lorusso, Raffaella Massafra
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract For endocrine-positive Her2 negative breast cancer patients at an early stage, the benefit of adding chemotherapy to adjuvant endocrine therapy is not still confirmed. Several genomic tests are available on the market but are very expensive.
Externí odkaz:
https://doaj.org/article/b56ee393ea0943caa915c1041b0d325d
Autor:
Samantha Bove, Maria Colomba Comes, Vito Lorusso, Cristian Cristofaro, Vittorio Didonna, Gianluca Gatta, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Maria Irene Pastena, Nicole Petruzzellis, Domenico Pomarico, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Annarita Fanizzi, Raffaella Massafra
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract In breast cancer patients, an accurate detection of the axillary lymph node metastasis status is essential for reducing distant metastasis occurrence probabilities. In case of patients resulted negative at both clinical and instrumental exam
Externí odkaz:
https://doaj.org/article/21667fa02e724bf7860830faad46bc80
Autor:
Raffaella Massafra, Annarita Fanizzi, Nicola Amoroso, Samantha Bove, Maria Colomba Comes, Domenico Pomarico, Vittorio Didonna, Sergio Diotaiuti, Luisa Galati, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Angela Lombardi, Annalisa Nardone, Maria Irene Pastena, Cosmo Maurizio Ressa, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Angelo Virgilio Paradiso, Roberto Bellotti, Vito Lorusso
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
IntroductionRecently, accurate machine learning and deep learning approaches have been dedicated to the investigation of breast cancer invasive disease events (IDEs), such as recurrence, contralateral and second cancers. However, such approaches are
Externí odkaz:
https://doaj.org/article/6a6b097c0dac4ec68f7e132a2023c0ef
Autor:
Laura Schirosi, Concetta Saponaro, Francesco Giotta, Ondina Popescu, Maria Irene Pastena, Emanuela Scarpi, Anita Mangia
Publikováno v:
Translational Oncology, Vol 13, Iss 2, Pp 186-192 (2020)
BACKGROUND: Breast cancer (BC) is a heterogeneous disease, and patients with apparently similar clinicopathological characteristics in clinical practice show different outcome. This study evaluated in primary BCs and in the subgroup of the triple-neg
Externí odkaz:
https://doaj.org/article/8c670eb8dd754614859c734bd9b9f8eb
Autor:
Concetta Saponaro, Emanuela Scarpi, Margherita Sonnessa, Antonella Cioffi, Francesca Buccino, Francesco Giotta, Maria Irene Pastena, Francesco Alfredo Zito, Anita Mangia
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
Inflammasome complexes play a pivotal role in different cancer types. NOD-like receptor protein 3 (NLRP3) inflammasome is one of the most well-studied inflammasomes. Activation of the NLRP3 inflammasome induces abnormal secretion of soluble cytokines
Externí odkaz:
https://doaj.org/article/be8e5b059b7a4fb2ac3de55b5ca89664
Autor:
Raffaella Massafra, Maria Colomba Comes, Samantha Bove, Vittorio Didonna, Gianluca Gatta, Francesco Giotta, Annarita Fanizzi, Daniele La Forgia, Agnese Latorre, Maria Irene Pastena, Domenico Pomarico, Lucia Rinaldi, Pasquale Tamborra, Alfredo Zito, Vito Lorusso, Angelo Virgilio Paradiso
Publikováno v:
Journal of Personalized Medicine, Vol 12, Iss 6, p 953 (2022)
To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as potential earlier indicators of pathological Complete Response (pCR) in breast canc
Externí odkaz:
https://doaj.org/article/99a5334425e44139a146573bc0a98b99
Autor:
Concetta Saponaro, Alessandro Vagheggini, Emanuela Scarpi, Matteo Centonze, Ivana Catacchio, Ondina Popescu, Maria Irene Pastena, Francesco Giotta, Nicola Silvestris, Anita Mangia
Publikováno v:
Journal of Experimental & Clinical Cancer Research, Vol 37, Iss 1, Pp 1-16 (2018)
Abstract Background Tumor microenvironment (TME) includes many factors such as tumor associated inflammatory cells, vessels, and lymphocytes, as well as different signaling molecules and extracellular matrix components. These aspects can be de-regula
Externí odkaz:
https://doaj.org/article/b46680c76e6f4ffe9323be2ac050cf99
Autor:
Domenico Pomarico, Annarita Fanizzi, Nicola Amoroso, Roberto Bellotti, Albino Biafora, Samantha Bove, Vittorio Didonna, Daniele La Forgia, Maria Irene Pastena, Pasquale Tamborra, Alfredo Zito, Vito Lorusso, Raffaella Massafra
Publikováno v:
Mathematics, Vol 9, Iss 4, p 410 (2021)
Learning tasks are implemented via mappings of the sampled data set, including both the classical and the quantum framework. Biomedical data characterizing complex diseases such as cancer typically require an algorithmic support for clinical decision
Externí odkaz:
https://doaj.org/article/e44bfdfcd0e340f4ad748e2fdf47d053
Autor:
Annarita Fanizzi, Domenico Pomarico, Angelo Paradiso, Samantha Bove, Sergio Diotaiuti, Vittorio Didonna, Francesco Giotta, Daniele La Forgia, Agnese Latorre, Maria Irene Pastena, Pasquale Tamborra, Alfredo Zito, Vito Lorusso, Raffaella Massafra
Publikováno v:
Cancers, Vol 13, Iss 2, p 352 (2021)
In the absence of lymph node abnormalities detectable on clinical examination or imaging, the guidelines provide for the dissection of the first axillary draining lymph nodes during surgery. It is not always possible to arrive at surgery without diag
Externí odkaz:
https://doaj.org/article/630cea344153483e82e56707db469157
Autor:
Daniele La Forgia, Annarita Fanizzi, Francesco Campobasso, Roberto Bellotti, Vittorio Didonna, Vito Lorusso, Marco Moschetta, Raffaella Massafra, Pasquale Tamborra, Sabina Tangaro, Michele Telegrafo, Maria Irene Pastena, Alfredo Zito
Publikováno v:
Diagnostics, Vol 10, Iss 9, p 708 (2020)
Contrast-Enhanced Spectral Mammography (CESM) is a recently introduced mammographic method with characteristics particularly suitable for breast cancer radiomic analysis. This work aims to evaluate radiomic features for predicting histological outcom
Externí odkaz:
https://doaj.org/article/177585aa7bb54938a6fd6c5a1c63bca0