{"title":"金黄色葡萄球菌与食源性病原菌的生物膜形成、粘附作用:牛蒡草作用的数学模型","authors":"G. Uba, M. A. Ginsau, K. M. Aujara","doi":"10.54987/jobimb.v8i2.540","DOIUrl":null,"url":null,"abstract":"Biofilm formation is a process by which microorganisms irreversibly bind to and grow on a surface and create extracellular polymers that promote the formation of attachments and matrixes, resulting in a change in the organisms' phenotype in terms of growth rate and transcription of genes. A. philippense is a fern with many curative properties that is medicinally treasured. Predictive mathematical modeling approach was used to study adhesion of S. aureus with biofilm. Out of the eight different primary model, modified Gompertz best fit the effect of the plant extract on the biofilm formation and adhesion with S. aureus with the least value for RMSE, AICc and the uppermost value for adjusted R2. The parameters obtained from the modified Gompertz when compared with control and chloramphenicol were ymax 0.980 (95% C.I. 0.889 to 1.070) and 0.637 (95% C.I. 0.604 to 0.670), umax 0.185 (95% C.I. 0.120 to 0.250) and 0.183 (95% C.I. 0.141 to 0.225), lag (h) 0.180 (95% C.I. -0.764 to 1.124) and 3.343 (95% C.I. 2.933 to 3.753) respectively. A strong model to use to fit sigmoidal growth or formation curves tends to be the modified Gompertz equation. The benefit of using this function is that a constant formation rate is not assumed by the Gompertz equation. Instead, it is a model that can be used to model rates of formation (of biofilm) that change over time. \nKeywords","PeriodicalId":15132,"journal":{"name":"Journal of Biochemistry, Microbiology and Biotechnology","volume":"57 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Biofilm Formation, Adhesion with Staphylococcus aureus Against Food Borne Pathogen: A Mathematical Modeling on the Effects of Adiantum phillippense\",\"authors\":\"G. Uba, M. A. Ginsau, K. M. Aujara\",\"doi\":\"10.54987/jobimb.v8i2.540\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Biofilm formation is a process by which microorganisms irreversibly bind to and grow on a surface and create extracellular polymers that promote the formation of attachments and matrixes, resulting in a change in the organisms' phenotype in terms of growth rate and transcription of genes. A. philippense is a fern with many curative properties that is medicinally treasured. Predictive mathematical modeling approach was used to study adhesion of S. aureus with biofilm. Out of the eight different primary model, modified Gompertz best fit the effect of the plant extract on the biofilm formation and adhesion with S. aureus with the least value for RMSE, AICc and the uppermost value for adjusted R2. The parameters obtained from the modified Gompertz when compared with control and chloramphenicol were ymax 0.980 (95% C.I. 0.889 to 1.070) and 0.637 (95% C.I. 0.604 to 0.670), umax 0.185 (95% C.I. 0.120 to 0.250) and 0.183 (95% C.I. 0.141 to 0.225), lag (h) 0.180 (95% C.I. -0.764 to 1.124) and 3.343 (95% C.I. 2.933 to 3.753) respectively. A strong model to use to fit sigmoidal growth or formation curves tends to be the modified Gompertz equation. The benefit of using this function is that a constant formation rate is not assumed by the Gompertz equation. Instead, it is a model that can be used to model rates of formation (of biofilm) that change over time. \\nKeywords\",\"PeriodicalId\":15132,\"journal\":{\"name\":\"Journal of Biochemistry, Microbiology and Biotechnology\",\"volume\":\"57 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biochemistry, Microbiology and Biotechnology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54987/jobimb.v8i2.540\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biochemistry, Microbiology and Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54987/jobimb.v8i2.540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biofilm Formation, Adhesion with Staphylococcus aureus Against Food Borne Pathogen: A Mathematical Modeling on the Effects of Adiantum phillippense
Biofilm formation is a process by which microorganisms irreversibly bind to and grow on a surface and create extracellular polymers that promote the formation of attachments and matrixes, resulting in a change in the organisms' phenotype in terms of growth rate and transcription of genes. A. philippense is a fern with many curative properties that is medicinally treasured. Predictive mathematical modeling approach was used to study adhesion of S. aureus with biofilm. Out of the eight different primary model, modified Gompertz best fit the effect of the plant extract on the biofilm formation and adhesion with S. aureus with the least value for RMSE, AICc and the uppermost value for adjusted R2. The parameters obtained from the modified Gompertz when compared with control and chloramphenicol were ymax 0.980 (95% C.I. 0.889 to 1.070) and 0.637 (95% C.I. 0.604 to 0.670), umax 0.185 (95% C.I. 0.120 to 0.250) and 0.183 (95% C.I. 0.141 to 0.225), lag (h) 0.180 (95% C.I. -0.764 to 1.124) and 3.343 (95% C.I. 2.933 to 3.753) respectively. A strong model to use to fit sigmoidal growth or formation curves tends to be the modified Gompertz equation. The benefit of using this function is that a constant formation rate is not assumed by the Gompertz equation. Instead, it is a model that can be used to model rates of formation (of biofilm) that change over time.
Keywords