Area of research
Genetics · Public Health, Environmental and Occupational Health
Research interest
Research topics from publications: Isotope labelling – paired homologous double neutral loss scan-mass spectrometry for profiling of metabolites with a carboxyl group; Analysis of the Relevance of the Ultrasonographic Features of Papillary Thyroid Carcinoma and Cervical Lymph Node Metastasis on Conventional and Contrast-Enhanced Ultrasonography; Enhanced bone regeneration by low-intensity pulsed ultrasound and lipid microbubbles on PLGA/TCP 3D-printed scaffolds; Multi-modal ultrasound multistage classification of PTC cervical lymph node metastasis via DualSwinThyroid; Correlation and Performance of three Ultrasound Techniques to Stage HepaticSteatosis in Nonalcoholic Fatty Liver Disease; Radiomics Combined with ACR TI-RADS for Thyroid Nodules: Diagnostic Performance, Unnecessary Biopsy Rate, and Nomogram Construction; Construction and validation of a predictive model for lymph node metastasis in patients with papillary thyroid carcinoma; Multi-channel deep learning radiomics model based on contrast-enhanced CT for predicting postoperative prognosis in laryngeal carcinoma; Interplatform Agreement Between Liver Steatosis Analysis and Ultrasound-Guided Attenuation Parameter in the Evaluation of Hepatic Steatosis; Dual-channel deep learning captures intratumoural heterogeneity on CECT for preoperative risk stratification of thymic epithelial tumors. Representative work: We developed a novel method for non-targeted screening of metabolites by high performance liquid chromatography-mass spectrometry with paired homologous double neutral loss scan mode after in vitro isotope labelling (IL-HPLC-PHDNL-MS). As a proof of concept, we investigated the carboxylic acid metabolite profiling in plant samples by the IL-HPLC-PHDNL-MS method. To this end, N,N-dimethylaminobutylamine (DMBA) and d(4)-N,N-dimethylaminobutylamine (d(4)-DMBA) were synthesized and utilized to label carboxylic acids. Our results show the MS response of carboxylic acids was enhanced by 20- to 40-fold after labelling. As for the IL-HPLC-PHDNL-MS analysis, DMBA and d(4)-DMBA labelled samples were m Background Preoperative prediction of lymph node metastases has a major impact on prognosis and recurrence for patients with papillary thyroid carcinoma (PTC). Thyroid ultrasonography is the preferred inspection to guide the appropriate diagnostic procedure. Purpose To investigate the relationship between PTC
Construction and validation of a predictive model for lymph node metastasis in patients with papillary thyroid carcinoma
Multi-channel deep learning radiomics model based on contrast-enhanced CT for predicting postoperative prognosis in laryngeal carcinoma
Interplatform Agreement Between Liver Steatosis Analysis and Ultrasound-Guided Attenuation Parameter in the Evaluation of Hepatic Steatosis
Dual-channel deep learning captures intratumoural heterogeneity on CECT for preoperative risk stratification of thymic epithelial tumors
Multi-modal ultrasound multistage classification of PTC cervical lymph node metastasis via DualSwinThyroid
Correlation and Performance of three Ultrasound Techniques to Stage HepaticSteatosis in Nonalcoholic Fatty Liver Disease
Radiomics Combined with ACR TI-RADS for Thyroid Nodules: Diagnostic Performance, Unnecessary Biopsy Rate, and Nomogram Construction
Enhanced bone regeneration by low-intensity pulsed ultrasound and lipid microbubbles on PLGA/TCP 3D-printed scaffolds
Analysis of the Relevance of the Ultrasonographic Features of Papillary Thyroid Carcinoma and Cervical Lymph Node Metastasis on Conventional and Contrast-Enhanced Ultrasonography
Isotope labelling – paired homologous double neutral loss scan-mass spectrometry for profiling of metabolites with a carboxyl group