Background And Objective: A microspectrofluorometric analysis on "ex vivo" samples from normal tissue and adenocarcinoma of the human colon has been performed to characterize the histological, biochemical, and biophysical bases of the autofluorescence.
Study Design/materials And Methods: Differences between normal and tumor tissues are found that concern both the intensity distribution and spectral shape of the autofluorescence emission. The different pattern of the fluorescence intensity can be related to the histological organization of the tissue, and involves mainly the arrangement of the submucosa, the most fluorescent layer.
Results: The most evident differences in the spectral shape found in the 480-580 nm range involve the stromal compartment, seem to be due to the presence of different fluorochromes, and are possibly related to the host response to the tumor.
Conclusion: The nature and the extent of the autofluorescence modification between normal and tumor tissue in sections explain at least partly the evidence of the "in vivo" analysis and highlight the importance of excitation for full exploitation of the potentials of autofluorescence in diagnosis.
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http://dx.doi.org/10.1002/lsm.1900160107 | DOI Listing |
J Proteome Res
January 2025
European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, U.K.
The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse.
View Article and Find Full Text PDFFront Microbiol
December 2024
College of Life Sciences, Zaozhuang University, Zaozhuang, China.
Introduction: The conjugative transfer of antibiotic resistance genes (ARGs) mediated by plasmids occurred in different intestinal segments of mice was explored.
Methods: The location of ARG donor bacteria and ARGs was investigated by qPCR, flow cytometry, and small animal imaging. The resistant microbiota was analyzed by gene amplification sequencing.
Sci Rep
January 2025
School of Chemistry, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.
In this work, we synthesize a quinoline-based heptamethine cyanine, QuCy7, with sulfonate groups to enhance water solubility. This dye demonstrates exceptional near-infrared absorption beyond 750 nm, accompanied by photothermal properties but low photostability. Encapsulating QyCy7 with polyethylene glycol to form nanopolymer, QuCy7@mPEG NPs, addresses the issue of its photoinstability.
View Article and Find Full Text PDFBMJ Open
January 2025
National Institute of Health and Care Research (NIHR) Birmingham Biomedical Research Centre (BRC) Center for Liver and Gastrointestinal Research, University of Birmingham, Birmingham, England, UK
Introduction: Primary sclerosing cholangitis (PSC) is the classical hepatobiliary manifestation of inflammatory bowel disease (IBD). The strong association between gut and liver inflammation has driven several pathogenic hypotheses to which the intestinal microbiome is proposed to contribute. Pilot studies of faecal microbiota transplantation (FMT) in PSC and IBD are demonstrated to be safe and associated with increased gut bacterial diversity.
View Article and Find Full Text PDFBMJ Open Gastroenterol
January 2025
Histopathology, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.
Objective: Artificial intelligence (AI) tools for histological diagnosis offer great potential to healthcare, yet failure to understand their clinical context is delaying adoption. IGUANA (Interpretable Gland-Graphs using a Neural Aggregator) is an AI algorithm that can effectively classify colonic biopsies into normal versus abnormal categories, designed to automatically report normal cases. We performed a retrospective pathological and clinical review of the errors made by IGUANA.
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