Results 151 to 160 of about 6,504,273 (325)

Patient‐specific pharmacogenomics demonstrates xCT as predictive therapeutic target in colon cancer with possible implications in tumor connectivity

Molecular Oncology, EarlyView.
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker, Keren Zohar, Martin Böttcher, Thomas Wartmann, Henry Freudenstein, Maximilian Doelling, Mihailo Andric, Wenjie Shi, Or Kakhlon, Katrin Hippe, Beatrix Jahnke, Dimitrios Mougiakakos, Franziska Baenke, Daniel Stange, Roland S. Croner, Michal Linial, Ulf D. Kahlert   +16 more
wiley   +1 more source

Sixth blind test of organic crystal-structure prediction methods [PDF]

, 2014
Colin R. Groom, Anthony M. Reilly
openalex   +1 more source

Predictors of response and rational combinations for the novel MCL‐1 inhibitor MIK665 in acute myeloid leukemia

Molecular Oncology, EarlyView.
This study characterizes the responses of primary acute myeloid leukemia (AML) patient samples to the MCL‐1 inhibitor MIK665. The results revealed that monocytic differentiation is associated with MIK665 sensitivity. Conversely, elevated ABCB1 expression is a potential biomarker of resistance to the treatment, which can be overcome by the combination ...
Joseph Saad, Rhiannon Newman, Elmira Khabusheva, Sofia Aakko, Eric Durand, Mahesh Tambe, Heikki Kuusanmäki, Alun Parsons, Juho J. Miettinen, Komal Kumar Javarappa, Ezgi June Olgac, Nemo Ikonen, Mika Kontro, Kimmo Porkka, Heiko Maacke, Janghee Woo, Ensar Halilovic, Caroline A. Heckman   +17 more
wiley   +1 more source

Enhanced cardiovascular disease prediction through self-improved Aquila optimized feature selection in quantum neural network & LSTM model [PDF]

Aman Darolia, Rajender Singh Chhillar, Musaed Alhussein, Surjeet Dalal, Khursheed Aurangzeb, Umesh Kumar Lilhore   +5 more
openalex   +1 more source

Research on Power Quality Prediction Based on BiLSTM Optimized by Bayesian Algorithm [PDF]

, 2022
Wenhui Zhang, Baohua Wang, Dafei Wang, Jiacheng Yu, Chi Zhang   +4 more
openalex   +1 more source

Aggressive prostate cancer is associated with pericyte dysfunction

Molecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero, Ane Martinez‐Larrinaga, Joaquim Grego‐Bessa, Saioa Garcia‐Longarte, Hielke van Splunder, Ianire Astobiza, Amaia Ercilla, Laura Bozal‐Basterra, Isabel Mendizabal, Pilar Villacampa, Arkaitz Carracedo, Mariona Graupera   +11 more
wiley   +1 more source

Tumor and germline testing with next generation sequencing in epithelial ovarian cancer: a prospective paired comparison using an 18‐gene panel

Molecular Oncology, EarlyView.
Genetic testing in epithelial ovarian cancer includes both germline and tumor‐testing. This approach often duplicates resources. The current prospective study assessed the feasibility of tumor‐first multigene testing by comparing tumor tissue with germline testing of peripheral blood using an 18‐gene NGS panel in 106 patients.
Elisabeth Spenard, Cristina Mitric, Melanie Care, Tracy L. Stockley, Raymond H. Kim, Jeanna McCuaig, Blaise Clarke, Laura Ranich, Clare Sheen, Sarah E. Ferguson, Liat Hogen, Taymaa May, Marcus Q. Bernardini   +12 more
wiley   +1 more source

Prediction of apartment prices per unit in Daegu-Gyeongbuk areas by spatial regression models [PDF]

, 2015
Woo Jung Lee, Cheolyong Park
openalex   +1 more source

The neural crest‐associated gene ERRFI1 is involved in melanoma progression and resistance toward targeted therapy

Molecular Oncology, EarlyView.
ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang, Qian Sun, Daniel Novak, Lei Zhu, Juliane Poelchen, Tamara Steinfass, Yiman Wang, Viktor Umansky, Jochen Utikal   +8 more
wiley   +1 more source

A Deep Learning Framework for Flash-Flood-Runoff Prediction: Integrating CNN-RNN with Neural Ordinary Differential Equations (ODEs) [PDF]

Khaula Alkaabi, Uzma Sarfraz, Saif Bin Hdhaiba   +2 more
openalex   +1 more source