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Elucidating the microscopic and computational techniques to study the structure and pathology of SARS-CoVs.

ABSTRACT: Severe Acute Respiratory Syndrome Coronaviruses (SARS-CoVs), causative of major outbreaks in the past two decades, has claimed many lives all over the world. The virus effectively spreads through saliva aerosols or nasal discharge from an infected person. Currently, no specific vaccines or treatments exist for coronavirus; however, several attempts are being made to develop possible treatments. Hence, it is important to study the viral structure and life cycle to understand its functionality, activity, and infectious nature. Further, such studies can aid in the development of vaccinations against this virus. Microscopy plays an important role in examining the structure and topology of the virus as well as pathogenesis in infected host cells. This review deals with different microscopy techniques including electron microscopy, atomic force microscopy, fluorescence microscopy as well as computational methods to elucidate various prospects of this life-threatening virus.

SUBMITTER: Kaniyala Melanthota S

PROVIDER: S-EPMC7436590 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Elucidating the microscopic and computational techniques to study the structure and pathology of SARS-CoVs.

Kaniyala Melanthota Sindhoora S Banik Soumyabrata S Chakraborty Ishita I Pallen Sparsha S Gopal Dharshini D Chakrabarti Shweta S Mazumder Nirmal N

Microscopy research and technique 20200807 12

Severe Acute Respiratory Syndrome Coronaviruses (SARS-CoVs), causative of major outbreaks in the past two decades, has claimed many lives all over the world. The virus effectively spreads through saliva aerosols or nasal discharge from an infected person. Currently, no specific vaccines or treatments exist for coronavirus; however, several attempts are being made to develop possible treatments. Hence, it is important to study the viral structure and life cycle to understand its functionality, ac ...[more]

PMID: 32770582

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Project description:The inverse problem of electrocardiography is usually analyzed during stationary rhythms. However, the performance of the regularization methods under fibrillatory conditions has not been fully studied. In this work, we assessed different regularization techniques during atrial fibrillation (AF) for estimating four target parameters, namely, epicardial potentials, dominant frequency (DF), phase maps, and singularity point (SP) location. We use a realistic mathematical model of atria and torso anatomy with three different electrical activity patterns (i.e., sinus rhythm, simple AF, and complex AF). Body surface potentials (BSP) were simulated using Boundary Element Method and corrupted with white Gaussian noise of different powers. Noisy BSPs were used to obtain the epicardial potentials on the atrial surface, using 14 different regularization techniques. DF, phase maps, and SP location were computed from estimated epicardial potentials. Inverse solutions were evaluated using a set of performance metrics adapted to each clinical target. For the case of SP location, an assessment methodology based on the spatial mass function of the SP location, and four spatial error metrics was proposed. The role of the regularization parameter for Tikhonov-based methods, and the effect of noise level and imperfections in the knowledge of the transfer matrix were also addressed. Results showed that the Bayes maximum-a-posteriori method clearly outperforms the rest of the techniques but requires a priori information about the epicardial potentials. Among the purely non-invasive techniques, Tikhonov-based methods performed as well as more complex techniques in realistic fibrillatory conditions, with a slight gain between 0.02 and 0.2 in terms of the correlation coefficient. Also, the use of a constant regularization parameter may be advisable since the performance was similar to that obtained with a variable parameter (indeed there was no difference for the zero-order Tikhonov method in complex fibrillatory conditions). Regarding the different targets, DF and SP location estimation were more robust with respect to pattern complexity and noise, and most algorithms provided a reasonable estimation of these parameters, even when the epicardial potentials estimation was inaccurate. Finally, the proposed evaluation procedure and metrics represent a suitable framework for techniques benchmarking and provide useful insights for the clinical practice.

Dataset Information

Elucidating the microscopic and computational techniques to study the structure and pathology of SARS-CoVs.

Publications

Elucidating the microscopic and computational techniques to study the structure and pathology of SARS-CoVs.

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