NanoBioAI: Utilizing Python to Investigate Magnetocaloric Effects in Magnetotactic Bacteria and Optimized Conditions for Thermotherapy

Year : 2024 | Volume : 11 | Issue : 02 | Page : 122 131
    By

    Prashant D. Sawant,

  1. Director, Ai-Discovery Consultancy, Melbourne, Australia

Abstract

The study presented in the research work represents a multidisciplinary approach, integrating biology, nanotechnology, and artificial intelligence. It specifically highlights the use of python computational power to investigate magnetocaloric effect (MCE) in magnetotactic bacteria (MTB), a phenomenon yet to be fully understood, characterized by reversible heating and cooling effects induced by magnetic fields. MTB are unique in that they contain embedded magnetic nanoparticles ranging from 10–100 nm in diameters. These nanoparticles provide geomagnetic responsiveness and exhibit medicinal properties such as safety, non-toxicity, superior contrasts for diagnosis, and overall biocompatibility. These characteristics make MTB a promising candidate for medical applications. The python code developed as part of this study was used to examine the heat generation by MTB under magnetic fields. The goal was to optimize the heating cycles and magnetic flux for potential effective tumor eradication. The python code was able to optimize the conditions to achieve a temperature of 40°C under two scenarios: (i) the minimum magnetic flux density would be 25 μT with 20 cycles, and (ii) the minimum number of cycles at 65 μT magnetic flux density would be 3 cycles. This computational model can be further modified considering experimental factors to optimize dosing and therapy for clinical trials and treatments. This approach enhances the safety and efficacy of MTB-based thermotherapy theoretically and has the potential to reduce the cost of animal and clinical trials. Thus, the study underscores the significant role of python in advancing the field of MTB-based thermotherapy.

Keywords: MTB-based thermotherapy, nanotechnology, python code, clinical trials, magnetotactic bacteria

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Prashant D. Sawant. NanoBioAI: Utilizing Python to Investigate Magnetocaloric Effects in Magnetotactic Bacteria and Optimized Conditions for Thermotherapy. Journal of Artificial Intelligence Research & Advances. 2024; 11(02):122-131.
How to cite this URL:
Prashant D. Sawant. NanoBioAI: Utilizing Python to Investigate Magnetocaloric Effects in Magnetotactic Bacteria and Optimized Conditions for Thermotherapy. Journal of Artificial Intelligence Research & Advances. 2024; 11(02):122-131. Available from: https://journals.stmjournals.com/joaira/article=2024/view=155869


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Regular Issue Subscription Review Article
Volume 11
Issue 02
Received 15/04/2024
Accepted 01/06/2024
Published 10/07/2024
342

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