10.1234/mjee.v5i1.403

Nitric Oxide Diffusion Attributes in Biological And Artificial Environments: A Computational Study

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Published in Issue 2024-02-25

How to Cite

Suárez Araujo, C. P., Fernández López, P., & García Báez, P. (2024). Nitric Oxide Diffusion Attributes in Biological And Artificial Environments: A Computational Study. Majlesi Journal of Electrical Engineering, 5(2). https://doi.org/10.1234/mjee.v5i1.403

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Abstract

This paper presents a computational study on the dynamic of nitric oxide (NO) in both the biological and artificial environments, by means the analysis of important nitric oxide diffusion attributes, which are defined in this work. We apply the compartmental model of NO diffusion as a formal tool, using a computational neuroscience point of view. The main objective is the analyses of the emergence and dynamic of complex structures, essentially diffusion neighbourhood (DNB), in environments with volume transmission (VT). The study is performed by the observation of the NO diffusion attributes, the NO directionality (NOD), the average influence (AI) and the center of DNB (CDNB). We present a study of the influences and dependences with respect to associated features to the NO synthesis-diffusion process, and to the different environments where it spreads (non-isotropy and non-homogeneity). The paper is structured into three sets of experiences which cover the aforementioned aspects: influence of the NO synthesis process, isolated and multiple processes, influence of distance to the element where NO is synthesized, and influence of features of the diffusion environment. The developments have been performed in mono bi-and three-dimensional environments, with endothelial cell features. The study contributes the needed formalism to management the dynamic of NO in artificial an biological environments also to quantify the information representation capacity that a type of NO diffusion-based signaling presents and their implications in many other underlying neural mechanisms, such as neural recruitment, synchronization of computations between neurons and in the brain activity in general.䏿°§åæ°®æ´æ£å±¬æ§çç©å人工ç°å¢ï¼è¨ç®ç ç©¶å¡éæå·´æ¯èäºé·æ¯é¿åéï¼å·´åç¾·è²»ç¾å德毷æ´ä½©æ¯ï¼å¸ç¹é西奧·å è¥¿äº·è²è²æè¦æ¬æå°ä¸æ°§åæ°®ï¼NOï¼ççç©å人é ç°å¢çåæçè¨ç®ç ç©¶ï¼ç±è£ç½®çéè¦ç䏿°§åæ°®æ´æ£å±¬æ§ï¼éæ¯å¨æ­¤å·¥ä½ä¸­å®ç¾©çåæãæåä¸æç¨æ´æ£çæ¿å®¤æ¨¡åä½çºä¸åæ­£å¼çå·¥å·ï¼ä½¿ç¨è¦åè¨ç®ç¥ç¶ç§å­¸é»ãå¶ä¸»è¦ç®çæ¯å¨åºç¾çåæååæè¤éççµæ§ï¼åºæ¬ä¸æ¯æ´æ£éè¿ï¼DNBï¼èé«ç©å³è¼¸ï¼VTï¼ç°å¢ã該ç ç©¶æ¯ç±NOæ´æ£å±¬æ§ï¼NOçæ¹åæ§ï¼NODï¼çè§å¯é²è¡çï¼å¹³åå½±é¿ï¼AIï¼åDNBï¼CDNBï¼ç中å¿ãæåç®åçå½±é¿åä¾è³´éä¿çç ç©¶ï¼ç¸å°æ¼ç¸éåè½çNOåææ´æ£éç¨ï¼ä¸¦å¨é£è£¡å®å³æ­ï¼éåååæ§åéå廿§ï¼å¨ä¸åçç°å¢ãæ¬æççµæ§åçºä¸çµç¶é©æ¶µèä¸è¿°å¹¾åæ¹é¢ï¼NOåæéç¨ä¸­çå½±é¿åï¼å­¤ç«åå¤é²ç¨ï¼å°NOåæåç´ è·é¢çå½±é¿ï¼æ´æ£ç°å¢çç¹å¾µçå½±é¿ãçç¼å±å·²ç¶å¨å®éååä¸ç¶­ç°å¢ä¸­è¢«å·è¡æï¼èå§ç®ç´°èçç¹å¾µã該ç ç©¶æå©æ¼æéçå½¢å¼ä¸»ç¾©ç®¡çNOçåæäººå·¥ççç©ç°å¢ä¹éåä¿¡æ¯ç表示è½åï¼ä¸åé¡åæ²æåºæ¼æ´æ£ä¿¡è禮ç©å許å¤å¶ä»æ½å¨çç¥ç¶æ©å¶å½±é¿ï¼å¦ç¥ç¶æèï¼åæ­¥çç¥ç¶åä¹éï¼ä¸¦ä¸å¨ä¸è¬çå¤§è¦æ´»åçè¨ç®ã

Keywords

  • Artificial Neural Networks,
  • Cellular Signalling,
  • Nitric oxide,
  • Volume Transmission. Diffusion Neighbourhood