Brain neural network, development, microbiome, microbial toxins and COVID-19

Ali Samrezaee, Maryam Doustmehraban, Naimeh Ghadimi, Sedigheh Bahador, Arash Barghi, Erfan Ghanbarzadeh, Amir Rigi, Mojtaba Hedayati Ch, Atiyeh Kimiaeifar


Although almost 2 years have passed since the beginning of the coronavirus disease 2019 (COVID-19) pandemic in the world, there is still a threat to the health of people at risk and patients. Specialists in various sciences conduct various researches in order to eliminate or reduce the problems caused by this disease. Neural network science plays a vital role in this regard. It is important to note the key points of neuro-microbial involvement in the diagnosis and management of COVID-19 therapy by physicians and patients whose nervous systems are challenged. The relationship between COVID-19, microbiome and the profile of microbial toxins in the body is one of the factors that can directly or indirectly play a key role in the body's resistance to Covid-19 and changes in the neural network of the brain. In this article, we introduce the relationship and behavioral and mood problems that can result from neuronal changes. In linking the components of this network, artificial intelligence (AI), machine learning (ML) and data mining (DM) can be important strategies to assist health providers to choose best decision based on patient’s history. 


COVID-19; Brain; Neural network; Microbial toxins; Machine learning

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Stawicki SP, Jeanmonod R, Miller AC, Paladino L, Gaieski DF, Yaffee AQ, et al. The 2019-2020 Novel Coronavirus (Severe Acute Respiratory Syndrome Coronavirus 2) Pandemic: A Joint American College of Academic International Medicine-World Academic Council of Emergency Medicine Multidisciplinary COVID-19 Working Group Consensus Paper. J Glob Infect Dis. 2020; 12(2):47-93.

Malik YS, Kumar N, Sircar S, Kaushik R, Bhat S, Dhama K, et al. Coronavirus Disease Pandemic (COVID-19): Challenges and a Global Perspective. Pathogens. 2020; 9(7):519.

Woods JA, Hutchinson NT, Powers SK, Roberts WO, Gomez-Cabrera MC, Radak Z, et al. The COVID-19 pandemic and physical activity. Sports Med Health Sci. 2020; 2(2):55-64.

Khanizadeh A-M, Ejlali M, Karimzadeh F. The Effect of SARS-COV-2 Viruses on the Function of Different Organs, Especially the Nervous System. Neurosci J Shefaye Khatam. 2020; 8(3):111-21.

Sheppard O, Coleman MP, Durrant CS. Lipopolysaccharide-induced neuroinflammation induces presynaptic disruption through a direct action on brain tissue involving microglia-derived interleukin 1 beta. J Neuroinflammation. 2019; 16(1):106.

Iadecola C, Anrather J, Kamel H. Effects of COVID-19 on the Nervous System. Cell. 2020; 183(1):16-27.e1.

Wu Y, Xu X, Chen Z, Duan J, Hashimoto K, Yang L, et al. Nervous system involvement after infection with COVID-19 and other coronaviruses. Brain Behav Immun. 2020; 87:18-22.

Desforges M, Le Coupanec A, Dubeau P, Bourgouin A, Lajoie L, Dubé M, et al. Human Coronaviruses and Other Respiratory Viruses: Underestimated Opportunistic Pathogens of the Central Nervous System? Viruses. 2019; 12(1):14.

Herrera-Rincon C, Paré JF, Martyniuk CJ, Jannetty SK, Harrison C, Fischer A, et al. An in vivo brain-bacteria interface: the developing brain as a key regulator of innate immunity. NPJ Regen Med. 2020; 5:2.

Babakhani S, Hosseini F. Gut Microbiota: An Effective Factor in the Human Brain and Behavior. Neurosci J Shefaye Khatam. 2019; 7(1):106-18.

Johnson KV. Gut microbiome composition and diversity are related to human personality traits. Hum Microb J. 2020; 15.

Mohajeri MH, La Fata G, Steinert RE, Weber P. Relationship between the gut microbiome and brain function. Nutr Rev. 2018; 76(7):481-96.

Smith LK, Wissel EF. Microbes and the Mind: How Bacteria Shape Affect, Neurological Processes, Cognition, Social Relationships, Development, and Pathology. Perspect Psychol Sci. 2019; 14(3):397-418.

Ghasemi-Varnamkhasti M, Mohtasebi SS, Siadat M, Balasubramanian S. Meat quality assessment by electronic nose (machine olfaction technology). Sensors (Basel). 2009; 9(8):6058-83.

Tseng C-Y. Effects of Atypical Neurotoxins on the Developing Fetal Brain. Medical Toxicology: IntechOpen; 2019.

Child NSCotD. Early exposure to toxic substances damages brain architecture: Harvard University, Center on the Developing Child; 2006.

Ma Q, Xing C, Long W, Wang HY, Liu Q, Wang RF. Impact of microbiota on central nervous system and neurological diseases: the gut-brain axis. J Neuroinflammation. 2019; 16(1):53.

Smythies LE, Smythies JR. Microbiota, the immune system, black moods and the brain-melancholia updated. Front Hum Neurosci. 2014; 8:720.

Whitton PS. Inflammation as a causative factor in the aetiology of Parkinson's disease. Br J Pharmacol. 2007; 150(8):963-76.

Martins NRB, Angelica A, Chakravarthy K, Svidinenko Y, Boehm FJ, Opris I, et al. Human Brain/Cloud Interface. Front Neurosci. 2019; 13:112.

Morris G, Fernandes BS, Puri BK, Walker AJ, Carvalho AF, Berk M. Leaky brain in neurological and psychiatric disorders: Drivers and consequences. Aust N Z J Psychiatry. 2018; 52(10):924-48.

Maguire M, Maguire G. Gut dysbiosis, leaky gut, and intestinal epithelial proliferation in neurological disorders: towards the development of a new therapeutic using amino acids, prebiotics, probiotics, and postbiotics. Rev Neurosci. 2019; 30(2):179-201.

Tantillo E, Colistra A, Vannini E, Cerri C, Pancrazi L, Baroncelli L, et al. Bacterial Toxins and Targeted Brain Therapy: New Insights from Cytotoxic Necrotizing Factor 1 (CNF1). Int J Mol Sci. 2018; 19(6):1632.

Popoff MR, Poulain B. Bacterial toxins and the nervous system: neurotoxins and multipotential toxins interacting with neuronal cells. Toxins (Basel). 2010; 2(4):683-737.

Farthing MJ. Enterotoxins and the enteric nervous system--a fatal attraction. Int J Med Microbiol. 2000; 290(4-5):491-6.

Kouanda B, Sattar Z, Geraghty P. Periodontal Diseases: Major Exacerbators of Pulmonary Diseases? Pulm Med. 2021; 2021:4712406.

Luz CF, Vollmer M, Decruyenaere J, Nijsten MW, Glasner C, Sinha B. Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies. Clin Microbiol Infect. 2020; 26(10):1291-9.

Alzubi J, Nayyar A, Kumar A, editors. Machine learning from theory to algorithms: an overview. J Phys Conf Ser; 2018: IOP Publishing.

Patel L, Shukla T, Huang X, Ussery DW, Wang S. Machine Learning Methods in Drug Discovery. Molecules. 2020; 25(22):5277.

Strieth-Kalthoff F, Sandfort F, Segler MHS, Glorius F. Machine learning the ropes: principles, applications and directions in synthetic chemistry. Chem Soc Rev. 2020; 49(17):6154-68.

Mahon CR, Lehman DC, Manuselis G. Textbook of diagnostic microbiology-e-book: Elsevier Health Sciences; 2018.

Myszczynska MA, Ojamies PN, Lacoste AMB, Neil D, Saffari A, Mead R, et al. Applications of machine learning to diagnosis and treatment of neurodegenerative diseases. Nat Rev Neurol. 2020; 16(8):440-56.

Christakis NA. Death foretold: prophecy and prognosis in medical care: University of Chicago Press; 2001.

Ji S, Yang M, Yu K. 3D convolutional neural networks for human action recognition. IEEE Trans Pattern Anal Mach Intell. 2013; 35(1):221-31.

ten Bosch L, Ernestus M, Boves L. Analyzing Reaction Time Sequences from Human Participants in Auditory Experiments Proceedings of Interspeech 2018: The 19th Annual Conference of the International Speech Communication Association, pages 971-9752018.

Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Georgiou P, Lescure FX, et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect. 2020; 26(5):584-95.



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