NAD(P)H:quinone oxidoreductase 1 (NQO1) is overexpressed in a broad range of human tumors but remains difficult to study. Herein, we report a novel two-photon fluorescent probe with NIR emission for NQO1 detection. The probe demonstrated superior analytical performance with a large Stokes shift and deep tissue penetration.
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http://dx.doi.org/10.1039/d2cc01654k | DOI Listing |
Am J Pathol
December 2024
Department of Computer Science, Faculty of Engineering Sciences, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Understanding the tumor hypoxic microenvironment is crucial for grasping tumor biology, clinical progression, and treatment responses. This study presents a novel application of AI in computational histopathology to evaluate hypoxia in breast cancer. Weakly Supervised Deep Learning (WSDL) models can accurately detect morphological changes associated with hypoxia in routine Hematoxylin and Eosin (H&E) whole slide images (WSI).
View Article and Find Full Text PDFACS Nano
December 2024
School of Biomedical Sciences and Engineering, Guangzhou International Campus, South China University of Technology, Guangzhou 511442, P. R. China.
Chemotherapy is the primary treatment option for pancreatic cancer, although nanocarrier-based drug delivery systems often struggle with multiple physiological barriers, limiting their therapeutic efficacy. Here, we developed a pH/reactive oxygen species (ROS) dual-sensitive self-adaptive nanocarrier (DAT) encapsulating camptothecin (CPT), an analog of the pancreatic chemotherapeutic drug irinotecan (CPT-11), to enhance chemotherapy outcomes in orthotopic pancreatic cancer by addressing multiple physiological barriers. The nanocarrier features a peripherally positively charged arginine (Arg) residue on DAT and is masked with an acid-labile 2,3-dimethylmaleic anhydride (DA) to improve circulation time.
View Article and Find Full Text PDFBMC Infect Dis
December 2024
Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zürich, Zurich, 8097, Switzerland.
Introduction: The ability to detect pathogenic bacteria before the onsets of severe respiratory symptoms and to differentiate bacterial infection allows to improve patient-tailored treatment leading to a significant reduction in illness severity, comorbidity as well as antibiotic resistance. As such, this study refines the application of the non-invasive Secondary Electrospray Ionization-High Resolution Mass Spectrometry (SESI-HRMS) methodology for real-time and early detection of human respiratory bacterial pathogens in the respiratory tract of a mouse infection model.
Methods: A real-time analysis of changes in volatile metabolites excreted by mice undergoing a lung infection by Staphylococcus aureus or Streptococcus pneumoniae were evaluated using a SESI-HRMS instrument.
BMC Genomics
December 2024
School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, 333403, China.
Background: The subcellular localization of mRNA plays a crucial role in gene expression regulation and various cellular processes. However, existing wet lab techniques like RNA-FISH are usually time-consuming, labor-intensive, and limited to specific tissue types. Researchers have developed several computational methods to predict mRNA subcellular localization to address this.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Orthopedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Ossification of the ligamentum flavum (OLF) is the main causative factor of spinal stenosis, but how to accurately and efficiently identify the ossification region is a clinical pain point and an urgent problem to be solved. Currently, we can only rely on the doctor's subjective experience for identification, with low efficiency and large error. In this study, a deep learning method is introduced for the first time into the diagnosis of ligamentum flavum ossificans, we proposed a lightweight, automatic and efficient method for identifying ossified regions, called CDUNeXt.
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