Production Of Electrochemical Immunosensor For Detection Of Saccharomyces Cerevisiae

Saccharomyces cerevisiae is a common eukaryotic microorganism that is widely used as a mass-producing strain in food production processes such as beer,white wine and bread,as well as a probiotic for the prevention and treatment of intestinal diseases such as abdominal pain and diarrhea,due to its short growth cycle and high reproductive capacity.Saccharomyces cerevisiae is usually considered to be beneficial,however,in recent decades,infections caused by ingestion of saccharomyces cerevisiae have been few and far between,especially in the elderly,children and immunocompromised populations,and some patients have developed unexplained lung infections,sepsis,vaginitis and other diseases.Traditional cell culture-based detection methods for invasive saccharomyces cerevisiae infections are time-consuming and costly,and there may be problems such as failure of the test due to contamination of the sample sent for testing.Therefore,rapid and accurate detection of saccharomyces cerevisiae has become crucial for early prevention of invasive saccharomyces cerevisiae infections and is also important for the diagnosis and treatment of related diseases.Therefore,this thesis proposes a saccharomyces cerevisiae detection method based on electrochemical immunosensor to achieve rapid and accurate detection of saccharomyces cerevisiae.This thesis focuses on three aspects of the research work as follows:(1)The working electrode of the electrochemical immunosensor was designed and constructed.Firstly,the electrode(GO-Au NPs/ITO)substrate for the immunosensor was prepared by modifying graphene oxide(GO)and gold nanoparticles(Au NPs)onto the surface of indium tin oxide(ITO)glass electrode using cyclic voltammetry electrodeposition technique;secondly,the voltammetric properties of different electrodeposition processes were investigated by electrodeposition curve analysis;Finally,the effects of different composite volume ratios,cycle times and reaction area sizes on the preparation effect were investigated to achieve the optimization of the electrode substrate performance.(2)Constructing electrochemical immunosensors and performing performance tests.First,on the basis of the GO-Au NPs/ITO electrode fabricated in the previous step,three substances,3-mercaptopropionic acid(3-MPA),1-ethyl-(3-dimethylaminopropyl)carbonyldimethylamine(EDC)and N-hydroxysuccinimide(NHS),were selected to modify saccharomyces cerevisiae antibodies onto the electrode by using the principle of covalent coupling,and the effect of each chemical modification on ITO during the preparation of the immunosensor was analyzed.Secondly,the prepared electrochemical immunosensor was used for the testing of different concentrations of saccharomyces cerevisiae,and the results showed that the logarithmic value of saccharomyces cerevisiae concentration and the peak current showed good linear characteristics in a certain concentration range;finally,the interference experiment by adding red blood cells verified the Finally,the specificity of the immunosensor was verified by adding red blood cells.(3)Prediction of saccharomyces cerevisiae detection concentrations using traditional regression prediction models and BP neural networks.The experimentally obtained data supporting the relationship between saccharomyces cerevisiae concentration and detection response signal are limited and cannot reflect the detection concentration at non-measurement points more accurately.Therefore,in this chapter,the data processing methods such as regression prediction and BP neural network were used to predict the detection data by the obtained detection data.Based on the oxidation peak currents of saccharomyces cerevisiae at different concentrations obtained from the constructed electrochemical immunosensor,regression prediction of cell concentrations and sampling currents was performed by using univariate linear regression,quadratic polynomial regression,cubic polynomial regression,exponential regression and BP neural network,respectively,and the prediction results of several methods were compared and analyzed to select the prediction method with high detection accuracy for invasive saccharomyces cerevisiae infection detection This paper provides technical guidance for the detection of invasive saccharomyces cerevisiae infection.In summary,this thesis investigated a technique based on electrochemical immunosensor to achieve the detection of invasive saccharomyces cerevisiae,using graphene oxide and gold nanoparticles to construct the sensing region,immobilizing antibodies on the electrode surface by covalent coupling,and predicting saccharomyces cerevisiae concentration by BP neural network method to achieve rapid and accurate detection of saccharomyces cerevisiae cells,which provides a technical guide for invasive saccharomyces cerevisiae cell infection disease detection.