Te Wang , Rui Wang , Junsheng Zeng , Wei Zhao , Yan Liu , Hui Xiao
{"title":"基于SIX3OS1、miR-511-3p和RBP4联合构建脑卒中前期认知障碍预测模型","authors":"Te Wang , Rui Wang , Junsheng Zeng , Wei Zhao , Yan Liu , Hui Xiao","doi":"10.1016/j.neuroscience.2025.05.020","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>The incidence of stroke is increasing year by year. Post-stroke cognitive impairment (PSCI) is one of the most serious complications of stroke, which lacks effective early prediction tools.</div></div><div><h3>Methods</h3><div>A total of 147 S patients and 80 healthy individuals were enrolled, with corresponding clinical data and serum samples collected. The expression of SIX3OS1, miR-511-3p and retinol binding protein 4 (RBP4) were detected by reverse transcription-quantitative PCR (RT-qPCR). These data were then used to build a logistic regression model, and receiver operating characteristic (ROC) curves were drawn to evaluate the clinical value of SIX3OS1, miR-511-3p and RBP4.</div></div><div><h3>Results</h3><div>Our study found that SIX3OS1, miR-511-3p and RBP4 abnormally expressed in stroke and the area under the curve (AUC) of the combined detection of these was 0.965. Additionally, ROC curve showed that the AUC of SIX3OS1, miR-511-3p and RBP4 combined was 0.955 for the prediction of PSCI. Based on SIX3OS1 (X1), miR-511-3p (X2) and RBP4 (X3), we developed multivariate logistic regression predictive model, <em>p</em> = 1/ [1 + e (7.190–5.400X1 + 11.109X2–3.585X3)].</div></div><div><h3>Conclusion</h3><div>Serum SIX3OS1, miR-511-3p and RBP4 are candidate diagnostic biomarker in stroke and PSCI patients, which achieve good diagnostic performance when used in combination with other factors, and may have the potential to be novel therapeutic targets for PSCI.</div></div>","PeriodicalId":19142,"journal":{"name":"Neuroscience","volume":"579 ","pages":"Pages 47-53"},"PeriodicalIF":2.9000,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel predictive model constructed based on the combination of SIX3OS1, miR-511-3p and RBP4 for stroke-prost cognitive impairment\",\"authors\":\"Te Wang , Rui Wang , Junsheng Zeng , Wei Zhao , Yan Liu , Hui Xiao\",\"doi\":\"10.1016/j.neuroscience.2025.05.020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>The incidence of stroke is increasing year by year. Post-stroke cognitive impairment (PSCI) is one of the most serious complications of stroke, which lacks effective early prediction tools.</div></div><div><h3>Methods</h3><div>A total of 147 S patients and 80 healthy individuals were enrolled, with corresponding clinical data and serum samples collected. The expression of SIX3OS1, miR-511-3p and retinol binding protein 4 (RBP4) were detected by reverse transcription-quantitative PCR (RT-qPCR). These data were then used to build a logistic regression model, and receiver operating characteristic (ROC) curves were drawn to evaluate the clinical value of SIX3OS1, miR-511-3p and RBP4.</div></div><div><h3>Results</h3><div>Our study found that SIX3OS1, miR-511-3p and RBP4 abnormally expressed in stroke and the area under the curve (AUC) of the combined detection of these was 0.965. Additionally, ROC curve showed that the AUC of SIX3OS1, miR-511-3p and RBP4 combined was 0.955 for the prediction of PSCI. Based on SIX3OS1 (X1), miR-511-3p (X2) and RBP4 (X3), we developed multivariate logistic regression predictive model, <em>p</em> = 1/ [1 + e (7.190–5.400X1 + 11.109X2–3.585X3)].</div></div><div><h3>Conclusion</h3><div>Serum SIX3OS1, miR-511-3p and RBP4 are candidate diagnostic biomarker in stroke and PSCI patients, which achieve good diagnostic performance when used in combination with other factors, and may have the potential to be novel therapeutic targets for PSCI.</div></div>\",\"PeriodicalId\":19142,\"journal\":{\"name\":\"Neuroscience\",\"volume\":\"579 \",\"pages\":\"Pages 47-53\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0306452225003720\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306452225003720","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
A novel predictive model constructed based on the combination of SIX3OS1, miR-511-3p and RBP4 for stroke-prost cognitive impairment
Background
The incidence of stroke is increasing year by year. Post-stroke cognitive impairment (PSCI) is one of the most serious complications of stroke, which lacks effective early prediction tools.
Methods
A total of 147 S patients and 80 healthy individuals were enrolled, with corresponding clinical data and serum samples collected. The expression of SIX3OS1, miR-511-3p and retinol binding protein 4 (RBP4) were detected by reverse transcription-quantitative PCR (RT-qPCR). These data were then used to build a logistic regression model, and receiver operating characteristic (ROC) curves were drawn to evaluate the clinical value of SIX3OS1, miR-511-3p and RBP4.
Results
Our study found that SIX3OS1, miR-511-3p and RBP4 abnormally expressed in stroke and the area under the curve (AUC) of the combined detection of these was 0.965. Additionally, ROC curve showed that the AUC of SIX3OS1, miR-511-3p and RBP4 combined was 0.955 for the prediction of PSCI. Based on SIX3OS1 (X1), miR-511-3p (X2) and RBP4 (X3), we developed multivariate logistic regression predictive model, p = 1/ [1 + e (7.190–5.400X1 + 11.109X2–3.585X3)].
Conclusion
Serum SIX3OS1, miR-511-3p and RBP4 are candidate diagnostic biomarker in stroke and PSCI patients, which achieve good diagnostic performance when used in combination with other factors, and may have the potential to be novel therapeutic targets for PSCI.
期刊介绍:
Neuroscience publishes papers describing the results of original research on any aspect of the scientific study of the nervous system. Any paper, however short, will be considered for publication provided that it reports significant, new and carefully confirmed findings with full experimental details.