Results 171 to 180 of about 26,884,443 (275)

Somatostatin receptor 4 (SSTR4) is a tumor suppressor in cutaneous and head & neck squamous cell carcinomas

Molecular Oncology, EarlyView.
This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi, Tuan Khang Huynh, Adway Kadam, Zahra Kardan, Yue Yan, Amina Jamal Laham, Sampath Kumar Loganathan   +6 more
wiley   +1 more source

Three-Dimensional Data Acquisition Methods and Their Use in River Levee Topographic Survey. [PDF]

Sensors (Basel)
Kaneto J, Nishiyama S, Yoshida K.
europepmc   +1 more source

Castration‐resistant prostate cancer cells are addicted to the high activity of cyclin‐dependent kinase 2

Molecular Oncology, EarlyView.
We show that emergence of castration‐resistant prostate (CRPC) is associated with significant upregulation of cyclins that positively regulate cyclin‐dependent kinase 2 (CDK2) and concomitant downregulation of CDK4 cyclins. This renders CRPC cells dependent on the high activity of CDK2, and CDK2 inhibitors synergistically sensitize CRPC cells to both ...
Joyeeta Chatterjee, Alessia Marin, Shivani Yalala, Harri M. Itkonen   +3 more
wiley   +1 more source

A Review of Source-Term Estimation for Continuous Methane Monitoring: From Data Acquisition to Modeling and Estimation. [PDF]

ACS Omega
Xie Z, Tang J, Li R, Tian G, Ma R.
europepmc   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

MLDAAPP: machine learning data acquisition for assessing population phenotypes. [PDF]

G3 (Bethesda)
Gabidulin AR, Rudman SM.
europepmc   +1 more source

Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy

Molecular Oncology, EarlyView.
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen, Zhi Zhao, Henrik Horndalsveen, Maria Moksnes Bjaanæs, Bjørn Henning Grønberg, Tarje Halvorsen, Tesfaye Madebo, Marianne Aanerud, Jussi Koivunen, Kersti Oselin, Saulius Cicenas, Nina Helbekkmo, Jarkko Ahvonen, Maria Silvoniemi, Tine Norman Alver, Tonje Dalen, Åsa Kristina Öjlert, Saima Jamil Farooqi, Åslaug Helland, Vilde Drageset Haakensen   +19 more
wiley   +1 more source

Semi-Supervised Seven-Segment LED Display Recognition with an Integrated Data-Acquisition Framework. [PDF]

Sensors (Basel)
Xiang X, Zhu C, Ou Z, Zhang Q, Zheng S, Chen Z.   +5 more
europepmc   +1 more source

NAPRT loss promotes lung tumor initiation and growth through AKT signaling independently of NAD+ biosynthesis

Molecular Oncology, EarlyView.
Loss of NAPRT promotes lung tumor initiation and growth through a noncanonical mechanism, independent of its role in NAD+ biosynthesis. Mechanistically, NAPRT depletion activates the mTORC2‐driven AKT/β‐catenin signaling axis to enhance clonogenic and invasive phenotypes. Furthermore, lung‐specific Naprt deletion significantly increases tumor burden in
Myung Joon Oh, Ji Yun Jang, Yoon Jeon, Gi‐Cheon Kim, Hwanho Lee, Jooyoung Lee, Ju‐Hwa Kim, Hakhyun Kim, Minjee Kim, Ho‐Keun Kwon, Ho Lee, Hyun Seok Kim   +11 more
wiley   +1 more source

Unsupervised Transformer Learning for Rapid and High-Quality MRI Data Acquisition. [PDF]

Health Data Sci
Sui Y, Afacan O, Jaimes C, Gholipour A, Warfield SK.   +4 more
europepmc   +1 more source