In: Archives of Gynecology and Obstetrics, 2015, vol. 291, no. 6, p. 1387-1394
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In: Targeted Oncology, 2015, vol. 10, no. 2, p. 297-301
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In: World Journal of Surgery, 2015, vol. 39, no. 7, p. 1767-1772
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In: Breast Cancer Research and Treatment, 2015, vol. 150, no. 2, p. 363-371
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In: Hormone Molecular Biology and Clinical Investigation, 2017, vol. 32, no. 2, p. -
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In: Hormone Molecular Biology and Clinical Investigation, 2017, vol. 32, no. 1, p. -
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In: Breast Cancer Research and Treatment, ///-
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In: Molecular Oncology, 2020, vol. 14, no. 12, p. 3198–3210
Breast cancer metastasis is a complex process that depends not only on intrinsic characteristics of metastatic stem cells, but also on the particular microenvironment that supports their growth and modulates the plasticity of the system. In search for microenvironmental factors supporting cancer stem cell (CSC) growth and tumour progression to metastasis, we here investigated the role of the...
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In: Dalton Transactions, 2018, vol. 47, no. 48, p. 17221–17232
Herein we report the synthesis of a new biomaterial designed for targeted delivery of poorly water-soluble inorganic anticancer drugs, with a focus on colorectal cancer. Diatomaceous earth microparticles derived from marine microalgae were coated with vitamin B12 (cyanocobalamin) as a tumor targeting agent and loaded with the well- known anticancer agents cisplatin, 5-fluorouracil (5-FU), and...
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In: Frontiers in Genetics, 2020, vol. 11, p. -
Classification of histopathological images of cancer is challenging even for well- trained professionals, due to the fine-grained variability of the disease. Deep Convolutional Neural Networks (CNNs) showed great potential for classification of a number of the highly variable fine-grained objects. In this study, we introduce a Bilinear Convolutional Neural Networks (BCNNs) based deep learning...
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