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Akademický článek

Class Effect Unveiled: PPARγ Agonists and MEK Inhibitors in Cancer Cell Differentiation

Autor: Rakefet Ben-Yishay, Opher Globus, Nora Balint-Lahat, Sheli Arbili-Yarhi, Neta Bar-Hai, Vered Bar, Sara Aharon, Anna Kosenko, Adi Zundelevich, Raanan Berger, Dana Ishay-Ronen

Publikováno v: Cells, Vol 13, Iss 17, p 1506 (2024)

Epithelial-to-mesenchymal transition (EMT) plays a major role in breast cancer progression and the development of drug resistance. We have previously demonstrated a trans-differentiation therapeutic approach targeting invasive dedifferentiated cancer

Externí odkaz: https://doaj.org/article/c330496992df471197afa20b6a4dc4ea

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Akademický článek

A clinical evaluation of an ex vivo organ culture system to predict patient response to cancer therapy

Publikováno v: Frontiers in Medicine, Vol 10 (2023)

IntroductionEx vivo organ cultures (EVOC) were recently optimized to sustain cancer tissue for 5 days with its complete microenvironment. We examined the ability of an EVOC platform to predict patient response to cancer therapy.MethodsA multicenter,

Externí odkaz: https://doaj.org/article/9e606d0806d6437093649828fdd409d0

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Akademický článek

Estimation of postpartum depression risk from electronic health records using machine learning

Autor: Guy Amit, Irena Girshovitz, Karni Marcus, Yiye Zhang, Jyotishman Pathak, Vered Bar, Pinchas Akiva

Publikováno v: BMC Pregnancy and Childbirth, Vol 21, Iss 1, Pp 1-10 (2021)

Abstract Background Postpartum depression is a widespread disorder, adversely affecting the well-being of mothers and their newborns. We aim to utilize machine learning for predicting risk of postpartum depression (PPD) using primary care electronic

Externí odkaz: https://doaj.org/article/ce74080516194763b2897a7220f37a38

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Akademický článek

Comparing Intraperitoneal and Intravenous Personalized ErbB2CAR-T for the Treatment of Epithelial Ovarian Cancer

Autor: Naamit Deshet-Unger, Galit Horn, Moran Rawet-Slobodkin, Tova Waks, Ido Laskov, Nadav Michaan, Yael Raz, Vered Bar, Adi Zundelevich, Sara Aharon, Lubov Turovsky, Giuseppe Mallel, Seth Salpeter, Guy Neev, Kenneth Samuel Hollander, Ben-Zion Katz, Dan Grisaru, Anat Globerson Levin

Publikováno v: Biomedicines, Vol 10, Iss 9, p 2216 (2022)

High-grade serous ovarian carcinoma (HGSOC) is the most common type of epithelial ovarian cancer. The majority of cases are diagnosed at advanced stages, when intraperitoneal (IP) spread has already occurred. Despite significant surgical and chemothe

Externí odkaz: https://doaj.org/article/16dbc1696e5e4daea159f67c152a7d9b

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AMFPMC -- An improved method of detecting multiple types of drug-drug interactions using only known drug-drug interactions

Autor: Vered, Bar, Shtar, Guy, Rokach, Lior, Shapira, Bracha

Adverse drug interactions are largely preventable causes of medical accidents, which frequently result in physician and emergency room encounters. The detection of drug interactions in a lab, prior to a drug's use in medical practice, is essential, h

Externí odkaz: http://arxiv.org/abs/2302.03355

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Adaptive Causal Network Coding with Feedback for Multipath Multi-hop Communications

Autor: Cohen, Alejandro, Thiran, Guillaume, Bracha, Vered Bar, Médard, Muriel

We propose a novel multipath multi-hop adaptive and causal random linear network coding (AC-RLNC) algorithm with forward error correction. This algorithm generalizes our joint optimization coding solution for point-to-point communication with delayed

Externí odkaz: http://arxiv.org/abs/1910.13290

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Adaptive Causal Network Coding with Feedback

Autor: Cohen, Alejandro, Malak, Derya, Bracha, Vered Bar, Medard, Muriel

We propose a novel adaptive and causal random linear network coding (AC-RLNC) algorithm with forward error correction (FEC) for a point-to-point communication channel with delayed feedback. AC-RLNC is adaptive to the channel condition, that the algor

Externí odkaz: http://arxiv.org/abs/1905.02870

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