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dc.contributor.authorda Silva, Fernanda Aparecida Borges
dc.contributor.authorFlorindo, João Batista
dc.contributor.authorde Mattos, Amilcar Castro
dc.contributor.authorCosta, Fernando Ferreira
dc.contributor.authorLorand-Metze, Irene
dc.contributor.authorMetze, Konradin
dc.date.accessioned2025-05-13T17:36:57Z
dc.date.available2025-05-13T17:36:57Z
dc.date.issued2024
dc.identifier.urihttp://repositorio.sis.puc-campinas.edu.br/xmlui/handle/123456789/17946
dc.description.abstractIn recent studies, it has been shown that fluorescence lifetime imaging (FLIM) may reveal intracellular structural details in unstained cytological preparations that are not revealed by standard staining procedures. The aim of our investigation was to examine whether FLIM images could reveal areas suggestive of polymerization in red blood cells (RBCs) of sickle cell disease (SCD) patients. We examined label-free blood films using auto-fluorescence FLIM images of 45 SCD patients and compared the results with those of 27 control persons without hematological disease. All control RBCs revealed homogeneous cytoplasm without any foci. Rounded non-sickled RBCs in SCD showed between zero and three small intensively fluorescent dots with higher lifetime values. In sickled RBCs, we found additionally larger irregularly shaped intensively fluorescent areas with increased FLIM values. These areas were interpreted as equivalent to polymerized hemoglobin. The rounded, non-sickled RBCs of SCD patients with homogeneous cytoplasm were not different from those of the erythrocytes of control patients in light microscopy. Yet, variables from the local binary pattern-transformed matrix of the FLIM values per pixel showed significant differences between non-sickled RBCs and those of control cells. In a linear discriminant analysis, using local binary pattern-transformed texture features (mean and entropy) of the erythrocyte cytoplasm of normal appearing cells, the final model could distinguish between SCD patients and control persons with an accuracy of 84.7% of the patients. When the classification was based on the examination of a single rounded erythrocyte, an accuracy of 68.5% was achieved. Employing the Linear Discriminant Analysis classifier method for machine learning, the accuracy was 68.1%. We believe that our study shows that FLIM is able to disclose the topography of the intracellular polymerization process of hemoglobin in sickle cell disease and that the images are compatible with the theory of the two-step nucleation. Furthermore, we think that the presented technique may be an interesting tool for the investigation of therapeutic inhibition of polymerization.
dc.language.isoInglês
dc.publisherMDPI AGpt_BR
dc.rightsAcesso abertopt_BR
dc.subjectFluorescence lifetime imaging
dc.subjectAuto-fluorescence
dc.subjectHemoglobin
dc.subjectPolymerization
dc.subjectMachine learning
dc.titleAccompanying hemoglobin polymerization in red blood cells in patients with sickle cell disease using fluorescence lifetime imagingpt_BR
dc.typeArtigopt_BR
dc.contributor.institutionPontifícia Universidade Católica de Campinas (PUC-Campinas)pt_BR
dc.identifier.doihttps://doi.org/10.3390/ijms252212290pt_BR


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