There exists a broad range of techniques that can be used to classify and count white blood cells in a point-of-care (POC) three-part leukocyte differential test. Improvements in lenses, light sources, and cameras for image-based POC systems have renewed interest in acridine orange (AO) as a contrast agent, whereby subpopulations of leukocytes can be differentiated by colorimetric analysis of AO fluorescence emission. We evaluated the effect on test accuracy using different AO staining and postprocessing methods in the context of an image-based POC colorimetric cell classification scheme. Thirty blood specimens were measured for percent cell counts using our POC system and a conventional hematology analyzer for comparison. Controlling the AO concentration used during whole-blood staining, the incubation time with AO, and the colorimetric ratios among the three population of leukocytes yielded a percent deviation of 0.706%, ? 1.534 % , and ? 0.645 % for the lymphocytes, monocytes, and granulocytes, respectively. Overall, we demonstrated that a redshift in AO fluorescence was observed at elevated AO concentrations, which lead to reproducible inaccuracy of cell counts. This study demonstrates there is a need for a strict control of the AO staining and postprocessing methods to improve test accuracy in these POC systems.
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http://dx.doi.org/10.1117/1.JBO.22.3.035001 | DOI Listing |
Sci Adv
January 2025
Department of Biophysics, Institute of Quantum Biophysics, Sungkyunkwan University, Suwon 16419, Republic of Korea.
Optical resolution photoacoustic imaging of uneven samples without z-scanning is transformative for the fast analysis and diagnosis of diseases. However, current approaches to elongate the depth of field (DOF) typically imply cumbersome postprocessing procedures, bulky optical element ensembles, or substantial excitation beam side lobes. Metasurface technology allows for the phase modulation of light and the miniaturization of imaging systems to wavelength-size thickness.
View Article and Find Full Text PDFAm J Orthod Dentofacial Orthop
January 2025
School of Materials Science and Innovation, Faculty of Science, Mahidol University, Nakhon Pathom, Thailand. Electronic address:
Introduction: This study investigated the physical, mechanical, and optical properties of 3-dimensional (3D) printing resins compared with thermoplastic materials to evaluate their suitability for the fabrication of orthodontic clear retainers.
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PeerJ Comput Sci
October 2024
Department of Pathology, University Malaya Medical Center, Kuala Lumpur, Malaysia.
The human epidermal growth factor receptor 2 (HER2) gene is a critical biomarker for determining amplification status and targeting clinical therapies in breast cancer treatment. This study introduces a computer-aided method that automatically measures and scores HER2 gene status from invasive tissue regions of breast cancer using whole slide images (WSI) through silver hybridization (SISH) staining. Image processing and deep learning techniques are employed to isolate untruncated and non-overlapping single nuclei from cancer regions.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
February 2025
Innovation Center for Enzyme Catalysis and Drug Synthesis, School of Pharmacy and Pharmaceutical Sciences, Xiamen Medical College, Xiamen 361023, PR China. Electronic address:
Hypoxia will accelerate tumors metastasis and deterioration, thereby limiting the effects of chemotherapy or radiotherapy. Thus, developing efficient techniques for detecting hypoxia in tumor cells is extremely important for cancer diagnosis and therapy. In this work, we reported a dicyanoisophorone-based probe (DCI-Azo) that specifically switched on its near infrared emission with hypoxia up-regulated azo-reductase (AzoR).
View Article and Find Full Text PDFLab Invest
November 2024
Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Bioinformatics, UT Southwestern Medical Center, Dallas, Texas; Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas. Electronic address:
Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment. Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E)-stained images, there remains a need for effective whole-cell segmentation methods. This study aimed to develop a deep learning-based pipeline to automatically segment cells in H&E-stained tissues, thereby advancing the capabilities of pathological image analysis.
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