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Phase analysis simulating the Takeda method to obtain a 3D profile of SARS-CoV-2 cells

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Abstract

In this work, we propose a morphologic analysis by means of the construction of 3D models of the SARS-CoV-2 VP (viral particles) with algorithms in Python and Matlab based on the processing of frames. To this aim, we simulate the Takeda method to induce periodicity and apply the Fourier transform to obtain the phase of objects under analysis. To this aim, we analyze several research works focused on infected tissues by SARS-CoV-2 virus culture cells, highlighting the obtained medical images of the virus from microscopy and tomography. We optimize the results by performing image processing (segmentation and periodic noise removal) in order to obtain an accurate ROI (Region of Interest) segmentation containing only information on SARS-CoV-2 cells. We apply our algorithm to these images (3D tomographic medical images) to simulate the Takeda method (which also filters the image), considering the periodicity induced by us in the image to carry out a phase unwrapping process. Finally, we use the image phase to focus on the body, center (RNA, Protein M-N), and spikes (Protein S) of the SARS-CoV-2 cells to identify them as characteristic elements of the SARS-CoV-2 virion morphology to build a 3D model based only in the metadata of clinical studies on cell cultures. The latter results in the construction of a mathematical, physical, biological, and numerical model of the SARS-CoV-2 virion, a tool with volumes, or 3D non-speculative or animated models, based only on medical images (3D tomography) in clinical tests, faithful to the virus.

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Data availability

The datasets generated during and/or analyzed during the current study are available in the Github repository.

Notes

  1. We include all the algorithms in our proposal in the Github repository

  2. We recall the two Matlab algorithms Results.m and FrameMask.m included in Github repository.

  3. The Python code 2DFrame\(\_\)Fit is included in Github repository.

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Acknowledgements

The authors thank CONACYT (Consejo Nacional de Ciencia y Tecnologia, México) and the Benemerita Universidad Autonoma de Puebla (BUAP) for the support given during this research work. Special thanks to Dra. Lilia Cedillo Ramírez, Dr. Ygnacio Martínez Laguna and Dr. Jorge Antonio Yáñez Santos for their collaboration and comments. We also thank the technical staff of the Biomolecular Detection Centre at BUAP: M.C. Jose Sergio Tepanecatl Xihuitl, M.C. Elda Carreon Moreno, M. C. Cristina Lara Ochoa, and David Zenteno Diaz for their support.

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Author notes

  1. B. Cuevas-Otahola, J. J. Oliveros-Oliveros, M. M. Morín-Castillo: These authors contributed equally to this work.

Authors and Affiliations

  1. Mathematics Department, Facultad de Ciencias Físico Matemáticas at Benemérita Universidad Autónoma de Puebla (FCFM-BUAP), San Claudio Av. Cd Universitaria, Puebla, 72572, Puebla, México

    Jesús Arriaga-Hernández & José J. Oliveros-Oliveros

  2. Mathematics Department, Facultad de Ciencias de la Electrónica at Benemérita Universidad Autónoma de Puebla (FCE-BUAP), San Claudio Av. Cd Universitaria, Puebla, 72572, Puebla, México

    Bolivia Cuevas-Otahola & María M. Morín-Castillo

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  1. Jesús Arriaga-Hernández
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  2. Bolivia Cuevas-Otahola
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  3. José J. Oliveros-Oliveros
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Correspondence to Bolivia Cuevas-Otahola.

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Arriaga-Hernández, J., Cuevas-Otahola, B., Oliveros-Oliveros, J.J. et al. Phase analysis simulating the Takeda method to obtain a 3D profile of SARS-CoV-2 cells. Pattern Anal Applic 27, 16 (2024). https://doi.org/10.1007/s10044-024-01225-8

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