4 resultados para Cell imaging

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Newly designed 2,1,3-benzothiadiazole-containing fluorescent probes with four excited state intramolecular proton transfer (ESIPT) sites were successfully tested in live cell-imaging assays using a confluent monolayer of human stem-cells (tissue). All tested dyes were compared with the commercially available DAPI and gave far better results. (c) 2010 Elsevier Ltd. All rights reserved.

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The perforated whole-cell configuration of the patch-clamp technique was applied to functionally identified beta-cells in intact mouse pancreatic islets to study the extent of cell coupling between adjacent beta-cells. Using a combination of current- and voltage-clamp recordings, the total gap junctional conductance between beta-cells in an islet was estimated to be 1.22 nS. The analysis of the current waveforms in a voltage-clamped cell ( due to the. ring of an action potential in a neighbouring cell) suggested that the gap junctional conductance between a pair of beta-cells was 0.17 nS. Subthreshold voltage-clamp depolarization (to -55 mV) gave rise to a slow capacitive current indicative of coupling between beta-cells, but not in non-beta-cells, with a time constant of 13.5 ms and a total charge movement of 0.2 pC. Our data suggest that a superficial beta-cell in an islet is in electrical contact with six to seven other beta-cells. No evidence for dye coupling was obtained when cells were dialysed with Lucifer yellow even when electrical coupling was apparent. The correction of the measured resting conductance for the contribution of the gap junctional conductance indicated that the whole-cell K(ATP) channel conductance (G(K,ATP)) falls from approximately 2.5 nS in the absence of glucose to 0.1 nS at 15 mM glucose with an estimated IC(50) of approximately 4 mM. Theoretical considerations indicate that the coupling between beta-cells within the islet is sufficient to allow propagation of [Ca(2+)](i) waves to spread with a speed of approximately 80 mu m s(-1), similar to that observed experimentally in confocal [Ca(2+)](i) imaging.

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Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.

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We use two-photon polymerization to fabricate 3D scaffolds with precise control over pore size and shape for studying cell migration in 3D. These scaffolds allow movement of cells in all directions. The fabrication, imaging, and quantitative analysis method developed here can be used to do systematic cell studies in 3D.