Xiaojing He

Notable Publications:

Liu ML, Li Y, Zhao ML, Zhuo Y, He XJ. Y-shaped DNA nanostructures assembled-spherical nucleic acids as target converters to activate CRISPR-Cas12a enabling sensitive ECL biosensing. Biosens Bioelectron. 2022;214:114512. doi: 10.1016/j.bios.2022.114512.

Li Y, Liu ML, Liang WB, Zhuo Y, He XJ. Spherical nucleic acid enzyme programmed network to accelerate CRISPR assays for electrochemiluminescence biosensing applications. Biosens Bioelectron. 2023;238:115589. doi: 10.1016/j.bios.2023.115589.

Qiu Y, Liu YF, Shu X, Qiao XF, Ai GY, He XJ. Peritumoral radiomics strategy based on ensemble learning for the prediction of Gleason grade group of prostate cancer. Acad Radiol. 2023;30 Suppl 1:S1-S13. doi: 10.1016/j.acra.2023.06.011.

Qiao X, Gu X, Liu Y, Shu X, Ai G, Qian S, Liu L, He X, Zhang J. MRI radiomics-based machine learning models for Ki67 expression and Gleason grade group prediction in prostate cancer. Cancers. 2023;15(18):4536. doi: 10.3390/cancers15184536.

Liu ML, He XJ, Li Y, Zhao ML, Zhuo Y. A convenient and economical strategy for multiple-target electrochemiluminescence detection using peroxydisulfate solution. Talanta. 2023;251:123788. doi: 10.1016/j.talanta.2023.123788.

Liu YF, Shu X, Qiao XF, Ai GY, Liu L, Liao J, Qian S, He XJ. Radiomics-based machine learning models for predicting P504s/P63 immunohistochemical expression: A noninvasive diagnostic tool for prostate cancer. Front Oncol. 2022;12:911426. doi: 10.3389/fonc.2022.911426.

Shu X, Liu Y, Qiao X, Ai G, Liu L, Liao J, Deng Z, He XJ. Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification. Br J Radiol. 2022;20220238. doi: 10.1259/bjr.20220238.

He X, Xiong H, Zhang H, Liu X, Zhou J, Guo D. Value of MRI texture analysis for predicting new Gleason grade group. Br J Radiol. 2021;94(1121):20210005. doi: 10.1259/bjr.20210005.

Xiong H, He X, Guo D. Value of MRI texture analysis for predicting high-grade prostate cancer. Clin Imaging. 2021;72:168-174. doi: 10.1016/j.clinimag.2021.06.024.

Jiang W, Fang H, Liu F, Zhou X, Zhao H, He X, Guo D. PEG-coated and Gd-loaded fluorescent silica nanoparticles for targeted prostate cancer magnetic resonance imaging and fluorescence imaging. Int J Nanomedicine. 2019;14:5611-5622. doi: 10.2147/IJN.S207408.

Zhang H, He X, Yu J, Song W, Liu X, Liu Y, Zhou J, Guo D. Preoperative MRI features and clinical laboratory indicators for predicting the early therapeutic response of hepatocellular carcinoma to transcatheter arterial chemoembolization combined with high-intensity focused ultrasound treatment. Br J Radiol. 2019;92(1099):20190073. doi: 10.1259/bjr.20190073.

Jiang W, He X, Fang H, Zhou X, Ran H, Guo D. Novel gadopentetic acid-doped silica nanoparticles conjugated with YPSMA-1 targeting prostate cancer for MR imaging: an in vitro study. Biochem Biophys Res Commun. 2018;499:202-208. doi: 10.1016/j.bbrc.2018.03.184.

Zhou X, He X, Guo D, Jiang W, Zheng J. New MRI nano-contrast agent: Synthesis, characterization and MRI study of gadopentetic acid-doped mesoporous silica nanoparticles. J Clin Radiol. 2017;36(4):577-581. [Article in Chinese]

He X, Guo D, Jiang W, Zhou X, Liu X, Zhou J, Liu Y. Evaluation of the value of PI-RADS V2 in improving the diagnostic efficacy of prostate cancer imaging. J Third Mil Med Univ. 2017;39(18):1841-1847. [Article in Chinese]

He X, Jiang W, Zhou X, Peng L, Yu Y, Zhuo Y. Development of a cadmium telluride quantum dot-based electroluminescent immunosensor for myocardial troponin detection using metal-organic framework materials. Chem Sensors. 2017;37(1):60-65. [Article in Chinese]

He X, Zhong Y, Jiang W, Ma S, Zhao J, Zhuo Y. Construction of an electroluminescent sensor for microRNA detection using a target-triggered rolling circle amplification strategy. Chem Sensors. 2017;37(1):40-45. [Article in Chinese] Projects as PI:

"Targeted Mesoporous Silica Nanoballs MR Imaging for Prostate Cancer," National Natural Science Foundation Youth Fund, 81401382, 2015.01-2017.12, National level, concluded, Principal Investigator.

"Study on Multi-parameter MRI for Early Diagnosis, Active Surveillance, and Treatment Follow-up of Prostate Cancer," Chongqing Municipal Health and Family Planning Commission Medical Science Research Program, 2016MSXM024, 2016.09-2018.08, Departmental level, concluded, Principal Investigator.

"Radiomics Combined with Machine Learning for Early Diagnosis of Prostate Cancer - A Multicenter Study in the Medical Union Model," Chongqing Municipal Science and Health Joint Medical Science Research Project (Young and Middle-aged High-end Talent Project), 2019GDRC011, 2019.09-2022.08, Provincial and Ministerial level, ongoing, Principal Investigator.

"Construction of an ECL Immunosensor and MR-targeted Imaging Integrated Precision Diagnosis Strategy for Prostate Cancer," Chongqing Natural Science Foundation General Project (Basic and Frontier Exploration), cstc2019jcyj-msxmX0073, 2019.11-2022.10, Provincial and Ministerial level, ongoing, Principal Investigator.