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Combinatorial functionomics identifies HDAC6-dependent molecular vulnerability of radioresistant head and neck cancer.
Exp Hematol Oncol
January 2025
Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
Background: Radiotherapy is the primary treatment modality for most head and neck cancers (HNCs). Despite the addition of chemotherapy to radiotherapy to enhance its tumoricidal effects, almost a third of HNC patients suffer from locoregional relapses. Salvage therapy options for such recurrences are limited and often suboptimal, partly owing to divergent tumor and microenvironmental factors underpinning radioresistance.
View Article and Find Full Text PDFN6-methyladenosine RNA modification regulates the transcription of SLC7A11 through KDM6B and GATA3 to modulate ferroptosis.
J Biomed Sci
January 2025
Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, State Key Laboratory of Anti-Infective Drug Discovery and Development, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, 510006, China.
Background: Recent studies indicate that N6-methyladenosine (mA) RNA modification may regulate ferroptosis in cancer cells, while its molecular mechanisms require further investigation.
Methods: Liquid Chromatography-Tandem Mass Spectrometry (HPLC/MS/MS) was used to detect changes in mA levels in cells. Transmission electron microscopy and flow cytometry were used to detect mitochondrial reactive oxygen species (ROS).
Lysosome-targeted dual-locked NIR fluorescent probe for visualization of HS and viscosity in drug-induced liver injury and tumor models.
Anal Chim Acta
February 2025
Department of Radiology, Changhai Hospital, Naval Medical University, Changhai Road 168, Shanghai 200433, China. Electronic address:
Background: Lysosomes, as an indispensable subcellular organelle have numerous physiological functions closely associated with HS and viscosity, and accurate assessment of HS/viscosity fluctuations in lysosomes is essential for gaining a comprehensive understanding of lysosome-related physiological activities and pathological processes. The previous single-response fluorescent probes for either HS or viscosity alone have the potential to generate "false positive" signals in a complex biological environment. In contrast, dual-locked probes can simultaneously respond to multiple targets simultaneously, which could effectively eliminate this defect.
View Article and Find Full Text PDFEGFP/RFP-based FRET sensors for botulinum neurotoxin A biological activity detection and methodological validation.
Anal Chim Acta
February 2025
Joint Drug Development and Innovation Centre for Neurological Disorders of Lanzhou University-China National Biotec Group-Lanzhou Biotechnology Development Co., School of Pharmacy, Lanzhou University, Lanzhou, Gansu, 730000, PR China; MOE Frontiers Science Center for Rare Isotopes, Lanzhou University, Lanzhou, Gansu, 730000, PR China. Electronic address:
Background: Botulinum neurotoxin type A (BoNT/A) is the most potent and prevalent neurotoxin known to cause botulism, and is also widely used in medical and cosmetic applications. The detection of BoNT/A is of great significance for botulism diagnosis and drug potency determination. Currently, the mouse bioassay (MBA) has long been the gold standard method but has disadvantages of ethical concerns, long testing duration, and high costs.
View Article and Find Full Text PDFEnd-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.
Open Heart
January 2025
Department of Molecular and Clinical Medicine, University of Gothenburg Institute of Medicine, Gothenburg, Sweden.
Purpose: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ECG-gated coronary CT angiography (CCTA) scans.
Methods: From a database of 6293 CCTA scans, we used pre-existing curved multiplanar reformations (CMR) images of the LAD, RCA and LCX arteries to create end-to-end deep-learning models for the detection of moderate or severe stenoses. We preprocessed the images by exploiting domain knowledge and employed a transfer learning approach using EfficientNet, ResNet, DenseNet and Inception-ResNet, with a class-weighted strategy optimised through cross-validation.
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