Results 271 to 280 of about 1,853,445 (346)

Who is Seeking Traditional Chinese Medicine (TCM) for Cancer? Insights from a Large Cohort in a Rehabilitation Clinic. [PDF]

Patient Prefer Adherence
Zhang Y, Dai Y, Kang D, Yu Q, Zhou X, Tian X, Chen Q, Chen Y, Liu F, Shi Q.   +9 more
europepmc   +1 more source

Adaptaquin is selectively toxic to glioma stem cells through disruption of iron and cholesterol metabolism

Molecular Oncology, EarlyView.
Adaptaquin selectively kills glioma stem cells while sparing differentiated brain cells. Transcriptomic and proteomic analyses show Adaptaquin disrupts iron and cholesterol homeostasis, with iron chelation amplifying cytotoxicity via cholesterol depletion, mitochondrial dysfunction, and elevated reactive oxygen species.
Adrien M. Vaquié, Davod R. Shah, Eliane E. S. Brechbühl, Michael McNicholas, Zhaoyang Xu, John H. Stockley, Laura Morcom, Diana Gold Diaz, Gemma C. Girdler, Rachel V. Seear, Gabriel Balmus, Rajiv R. Ratan, Harry Bulstrode, James A. Nathan, Manav Pathania, Kevin M. Brindle, David H. Rowitch   +16 more
wiley   +1 more source

Large-scale web-based survey on eating behaviour in the Japanese general population using a dietary behaviour questionnaire. [PDF]

Diabetes Obes Metab
Fujii K, Fujishima Y, Kimura Y, Hara T, Nagao H, Obata Y, Fukuda S, Nagai N, Kakuma T, Nishizawa H, Shimomura I.   +10 more
europepmc   +1 more source

The Economics of Constitution-Making [PDF]

, 1982
Watson, William G.
core   +1 more source

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

The First State Constitutions

, 1893
William C. Morey
openalex   +2 more sources

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

Implementation of the WHO Pandemic Agreement. [PDF]

Bull World Health Organ
Jon W.
europepmc   +1 more source

Characterizing epithelial‐mesenchymal transition‐linked heterogeneity in breast cancer circulating tumor cells at a single‐cell level

Molecular Oncology, EarlyView.
In over 50% of non‐metastatic breast cancer patients, circulating tumor cells (CTCs) along the whole epithelial‐mesenchymal transition spectrum are detected. Total CTC number and individual phenotypes relate to aggressive disease characteristics, including lymph node involvement and higher tumor proliferation. At the single‐cell level, mesenchymal CTCs
Justyna Topa, Julia Richert, Tomasz Stokowy, Alicja Staśczak, Mariusz Szajewski, Maciej Ciesielski, Petra M. Grešner, Bartłomiej Tomasik, Łukasz Arcimowicz, Agnieszka Stankiewicz, Grażyna Suchodolska, Elżbieta Senkus, Wiesław Kruszewski, Anna J. Żaczek, Aleksandra Markiewicz   +14 more
wiley   +1 more source

A Synergistic Framework for Hardness Prediction and Design of High-Entropy Alloys Based on Deep Learning and Intelligent Optimization Algorithms. [PDF]

ACS Omega
Wang K, Zhou X, Liu C, Li X.
europepmc   +1 more source