Analysis of the effects of serotonin/histamine manipulation in skin cells on mental wellbeing

在过去的几十年里，人们进行了广泛的研究，以探讨血清素、组胺水平与精神疾病之间的关系。这些神经递质已被证明与抑郁症、精神分裂症和自闭症有关[4]。最近的研究表明，抑郁症患者的血清素（5-HT）水平与正常水平相比有所下降[4]。类似地，组胺受体阻断与抗抑郁作用相关[2]。此外，研究发现，抑郁症患者的组胺水平更高[3]。治疗这种疾病的方法之一是使用选择性5-羟色胺再摄取抑制剂（SSRI），它会影响大脑中情感信息的处理方式[4]。研究者得出结论，这种药物治疗是有效的;然而，需要进一步分析，以了解SSRI浓度和心理健康之间更清晰的关系[5]。对焦虑症药物治疗的回顾表明，对此类疾病的指导治疗存在局限性[6]。此外，SSRI药物有副作用，可能会损害患者的生活质量[7]。因此，确定达到最佳结果所需的5-羟色胺刺激的确切量是至关重要的，因为缺乏测量中枢神经系统中神经递质的可用手段。这为5-羟色胺测量技术的进一步发展提供了动力。最有前途的技术之一是使用碳纤维微电极的快速扫描循环伏安法（FSCV）[8]。虽然它已经被广泛研究，但这种方法面临的一些挑战包括电极的快速降解，由于电极形状而难以进行测量，以及无法测量人脑中的血清素。FSCV已被用于测量小鼠血清素水平，但缺乏使用人体试验的研究[9，10，14]。这是因为由于该过程的侵入性，很难对人脑进行测量。同样，尽管FSCV提供了对神经递质水平及其浓度变化的见解，但由此产生的数据分析是耗时的。神经网络的应用是一种很有前途的方法来分析这样的数据在真实的时间，它也提供了洞察神经元的兴奋性。有限的研究已经进行了调查神经网络的神经递质数据的可用性。一项研究使用深度神经网络检测多巴胺释放，准确率达到98.13%[11]。然而，其局限性在于，在应用神经网络之前，对图像进行了大量处理。由于大量的预处理，很难将模型推广到原始数据。然而，机器学习模型已广泛用于其他医疗问题[12，13].有一个明确的动机，调查血清素浓度对心理健康的影响，以填补目前的研究和理解的问题的空白。博士的主要假设是，有两个-皮肤或毛细胞中的血清素水平与中枢神经系统中的水平之间存在联系。因此，通过控制皮肤和头发中神经递质的浓度，可以改变大脑中的浓度，从而改善心理健康。博士的主要目标是：1.使用碳基微电极FSCV测量皮肤细胞中的血清素和组胺水平。2.使用分析工具，如神经网络，分析结果数据。3.开发一种方法来操纵皮肤细胞中的血清素水平，无论是机械还是化学。4.确定一种刺激方法，产生最佳数量的神经递质，改善心理健康。

n the past few decades, extensive research has beenconducted to investigate the relationshipsbetween serotonin, histaminelevelsand psychiatric disorders. Theseneurotransmittershavebeen shown be implicatedindepression, schizophrenia andautism [4]. Recent research showsthat serotonin (5-HT) levels in patients suffering from depression are decreased compared to normal levels [4]. Similarly, histamine receptor blocking has been associated with antidepressant effect[2]. Moreover, the researchfound that histamine levels were higher in patients with depression[3]. One of the treatment methods forsuchdisorders is the administration of Selective Serotonin Reuptake Inhibitors (SSRI), which influences how emotional information is processed in the brain [4]. Studieshaveconcluded that such medication is working; however, there is a need for further analysis to understand a clearerrelationshipbetween SSRI concentration and mental wellbeing [5].The review of pharmacological treatment of anxiety disorders showed that there are limitations on guided treatments of such disorders[6]. Additionally, SSRI drugs have side effects which can impair the quality of life for patients[7]. It isthereforecrucialto determine theexactamount of serotonin stimulation needed to achieve optimalresults as the available means of measuringthe neurotransmitter in the central nervous system are lacking.This providesmotivation forfurtherdevelopment of serotonin measurement techniques. One of the most promising techniques is Fast-Scan Cyclic Voltammetry (FSCV) using carbon fibre microelectrodes[8]. While it has been widely studied, some of the challenges presentedby this method includefast degradation of electrodes, difficulty to produce measurements due to the shape of the electrodes,as well astheinability to measure serotonin inthehuman brain. FSCV has been used to measure serotonin levels in mice but there is lack of research usinghuman trails[9, 10, 14].Thisis because it is difficultto make measurements on human brain dueto invasivenessof the procedure.Similarly, while FSCV provides insightsintoneurotransmitter levels and changesin theirconcentrations, the resulting data analysis is time consuming. The application of Neural Networks is a promising method to analyse suchdata in real time and it also provides insight into the excitability of neurons. Limited research has been carried out toinvestigatethe usability of neural networks for neurotransmitter data. One studylooked at dopamine release detection using deep neural networksandachieved 98.13% accuracy[11]. However, the limitation is thatthe images wereheavilyprocessed before applying the neural network. Due to the heavy pre-processing, it would be difficult to generalise the model to raw data.Nevertheless, machine learning models have been widely used in other medical problems [12, 13].There is a clear motivation to investigate serotonin concentration effects on mental wellbeing to fillthe gaps in currentresearch and understanding of theproblem.Themain hypothesis for the PhD is that there is a two-way connection between serotonin levels in skin or hair cells and the levels inthecentral nervous systems. Therefore, it is possible by manipulating the concentration of neurotransmitters in skin and hair,to change the concentration in the brain andconsequentlyimprove mental wellbeing. The main objectives of the PhD would be to:1.Measure serotonin and histamine levels in the skin cells using FSCV with carbon-based microelectrodes.2.Use analytical tools,such as neural networks,to analyse theresultingdata.3.Develop a method to manipulate serotonin levels in skin cells either mechanically or chemically.4.Determine a stimulation method which produces optimal amounts of neurotransmittersand improves mental wellbeing.