Results 211 to 220 of about 5,789,434 (312)

TRPML1 agonist ML‐SA5 attenuates pulmonary fibroblast activation by suppressing mTOR and restoring autophagic flux

FEBS Open Bio, EarlyView.
TGF‐β1 stimulation downregulates lysosomal channel TRPML1 in pulmonary fibroblasts. The TRPML1 agonist ML‐SA5 suppressed fibroblast‐to‐myofibroblast activation and collagen production. Mechanistically, ML‐SA5 inhibited mTOR phosphorylation, restored autophagic flux, and its effects were enhanced by rapamycin (mTOR inhibitor) and reversed by MHY1485 ...
Jiatong Yao, Xiaoting Kang, Lulu Meng, Shaoxuan Zhang, Qiujie Li, Jinyu Zhou, Mengyue Xue, Chu Li, Hua Zhu, Pengzhou Hang, Jing Zhao   +10 more
wiley   +1 more source

Standardized quantitative imaging of extracellular polymeric substance in chronic wounds: Prognostic comparison of wound blotting and bacterial fluorescence imaging. [PDF]

Biofilm
Wu YF, Tung YC, Sheu SY, Cheng NC, Cheng CM.   +4 more
europepmc   +1 more source

Ultrafast visual detection of Streptococcus suis via HtpsC‐targeted LAMP–CRISPR–Cas12a coupled with lateral flow immunochromatography

FEBS Open Bio, EarlyView.
A rapid visual test combines DNA amplification, CRISPR–based target verification, and a lateral flow strip to detect Streptococcus suis. The assay gives results in about 45 min, reduces false‐positive interpretation, and does not require fluorescence equipment.
Liu‐xin Li, Miao Xin, Xiao‐wen Cui, Shi‐yin Yu, Fei Meng, Min Cao, Xiao‐hui Xiong, Yi‐chen Lu   +7 more
wiley   +1 more source

Dactolisib outperforms Rapamycin in potentiating apoptosis induced by XPO1, Bcl‐2 and Mcl‐1 blockade in preclinical glioblastoma models

FEBS Open Bio, EarlyView.
The PAM pathway and its impact on cellular metabolism. Color‐coded key symbols represent Rapamycin (R, orange, targeting mTOR) and Dactolisib (D, green, targeting PI3K/mTOR), indicating their sites of action. Created with BioRenders.com. Glioblastoma resists therapy through interconnected survival programs.
Kai Zhao, Leonie Meyer, Madita Braun, Katharina Otte, Celine Bitter, Maite Pawlik, Hartmann Raifer, Frederik Helmprobst, Axel Pagenstecher, Hans Urban, Michael C. Burger, Michael W. Ronellenfitsch, Joachim P. Steinbach, Jarmila Jedelská, Shamim Bagheri, Behrooz H. Yousefi, Pietro Di Fazio, Markus Luster, Andreas H. Mahnken, Andreas Neubauer, Andreas Burchert, Christopher Nimsky, Jörg W. Bartsch, Tillmann Rusch   +23 more
wiley   +1 more source

Relative CT Number as a Quantitative Imaging Biomarker for Differentiating Sinonasal Polyp, Inverted Papilloma, and Squamous Cell Carcinoma: A Preliminary Retrospective Study. [PDF]

Tomography
Öztürk Taşkıran T, Akyüz S, Tuzcu G.   +2 more
europepmc   +1 more source

Design and evaluation of FEBS Education and Training Academy module – Integrating generative artificial intelligence into life‐science education

FEBS Open Bio, EarlyView.
Life‐science educators from 14 countries redesigned their own course materials with generative AI in a three‐session, pedagogy‐first FEBS Education and Training Academy workshop built on PICRAT. Among 12 matched respondents, four more reported high confidence in each of five practical domains, and 10 of 13 reported implementing at least one idea ...
Zvonimir Mlinarić, Ali Burak Özkaya
wiley   +1 more source

Magneto-optical microscopy platform for quantitative imaging of hemozoin in blood for malaria diagnosis. [PDF]

Biomed Opt Express
Kinyua DM, Kotar J, Cicuta P.
europepmc   +1 more source

Chronobiology of Cancer: How Aging Fuels Oncogenesis at the Molecular Level

Aging and Cancer, EarlyView.
This graphical abstract illustrates the key biological pathways linking aging with cancer development and progression. In the upper left, cumulative exposure to ultraviolet radiation, toxins, and reactive oxygen species (ROS) causes DNA damage and genomic instability, whereas age‐related decline in repair mechanisms, such as ATM/ATR, BER, and NER ...
Anu Singh, Aroonima Misra, Sufian Zaheer
wiley   +1 more source

Bibliometric Analysis of Whole-Body MRI from 2015 to 2025 Across Clinical Applications, Quantitative Imaging, and Artificial Intelligence. [PDF]

J Imaging
Lee J, Lee C, Cyphers ED, Bonzell C, Kim S, Repajic M, Assadsangabi R, Clifford TG, Duddalwar V, Beutler BD.   +9 more
europepmc   +1 more source

Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec, Elif Everest, Melih Tutuncu, Ugur Bilge, Sabahattin Saip, Ugur Uygunoglu, Aksel Siva   +6 more
wiley   +1 more source