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Activation and Expansion of Human T-Cells Using Microfluidic Devices
(MDPI AG, 2025-04-25)
PEÑAHERRERA PAZMIÑO, ANA BELÉN
;
Gustavo Rosero
;
Dario Ruarte
;
Julia Pinter
;
Vizuete, Karla
Treatment of cancer patients with autologous T-cells expressing a chimeric antigen receptor (CAR) is one of the most promising therapeutic modalities for hematological malignancy treatment. For this treatment, primary T-cell expansion is needed. Microfluidic technologies can be used to better understand T-cell activation and proliferation. Microfluidics have had a meaningful impact in the way experimental biology and biomedical research are approached in general. Furthermore, microfluidic technology allows the generation of large amounts of data and enables the use of image processing for analysis. However, one of the major technical hurdles involved in growing suspension cells under microfluidic conditions is their immobilization, to avoid washing them out of the microfluidic chip during medium renewal. In this work, we use a multilevel microfluidic chip to successfully capture and immobilize suspension cells. Jurkat cells and T-cells are isolated through traps to microscopically track their development and proliferation after activation over a period of 8 days. The T-cell area of four independent microchannels was compared and there is no statistically significant difference between them (ANOVA p-value = 0.976). These multilevel microfluidic chips provide a new method of studying T-cell activation.
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AQSA—Algorithm for Automatic Quantification of Spheres Derived from Cancer Cells in Microfluidic Devices
(MDPI AG, 2024-11-20)
PEÑAHERRERA PAZMIÑO, ANA BELÉN
;
Ramiro Fernando Isa-Jara
;
Elsa Hincapié-Arias
;
Silvia Gómez
;
Denise Belgorosky
Sphere formation assay is an accepted cancer stem cell (CSC) enrichment method. CSCs play a crucial role in chemoresistance and cancer recurrence. Therefore, CSC growth is studied in plates and microdevices to develop prediction chemotherapy assays in cancer. As counting spheres cultured in devices is laborious, time-consuming, and operator-dependent, a computational program called the Automatic Quantification of Spheres Algorithm (ASQA) that detects, identifies, counts, and measures spheres automatically was developed. The algorithm and manual counts were compared, and there was no statistically significant difference (p = 0.167). The performance of the AQSA is better when the input image has a uniform background, whereas, with a nonuniform background, artifacts can be interpreted as spheres according to image characteristics. The areas of spheres derived from LN229 cells and CSCs from primary cultures were measured. For images with one sphere, area measurements obtained with the AQSA and SpheroidJ were compared, and there was no statistically significant difference between them (p = 0.173). Notably, the AQSA detects more than one sphere, compared to other approaches available in the literature, and computes the sphere area automatically, which enables the observation of treatment response in the sphere derived from the human glioblastoma LN229 cell line. In addition, the algorithm identifies spheres with numbers to identify each one over time. The AQSA analyzes many images in 0.3 s per image with a low computational cost, enabling laboratories from developing countries to perform sphere counts and area measurements without needing a powerful computer. Consequently, it can be a useful tool for automated CSC quantification from cancer cell lines, and it can be adjusted to quantify CSCs from primary culture cells. CSC-derived sphere detection is highly relevant as it avoids expensive treatments and unnecessary toxicity.

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