摘要
Ensuring the timely and precise monitoring of severe liver diseases is crucial for guiding effective therapies and significantly extending overall quality of life.However,this remains a worldwide challenge,given the high incidence rate and the presence of strong confounding clinical symptoms.Herein,we applied a convenient and high-yield method to prepare the magnetic mesoporous carbon(MMC-Fe),guided by a composite of resol and triblock copolymer.With the combination of MMC-Fe,high-throughput mass spectrometry,and a simple machine learning algorithm,we extracted N-glycan profiles from various serum samples,including healthy controls,liver cirrhosis,and liver cancer,and from which we screened specific N-glycans.Specifically,the selected N-glycans demonstrate exceptional performance with area under the curve(AUC)values ranging from 0.948 to 0.993 for the detection of liver diseases,including alpha fetoprotein(AFP)-negative liver cancer.Among them,five N-glycans holds potential in monitoring distinctions between liver cirrhosis and AFP-negative liver cancer(AUC values of 0.827–0.842).This study is expected to promote the glycan-based precise monitoring of diseases,not limited to liver disease.
基金
supported by National Key R&D Program of China(No.2018YFA0507501)
the National Natural Science Foundation of China(Nos.22074019,21425518,22004017)
Shanghai Sailing Program(No.20YF1405300)。
