Smartphone‐based rapid and visual pathological diagnosis of glioma using perovskite probes
Dongdong Wu,
Jimei Chi,
Junzhen Fan,
Lijun Cheng,
Xuning Wang,
Xu Yang,
Meng Zhang,
Zewei Lian,
Zengqi Huang,
Huadong Wang,
Hongfei Xie,
Sisi Chen,
Qi Pan,
Zeying Zhang,
Bingda Chen,
Guochen Sun,
Bainan Xu,
Meng Su,
Yanlin Song
Affiliations
Dongdong Wu
Department of Neurosurgery, The First Medical Centre Chinese PLA General Hospital Beijing Beijing the People's Republic of China
Jimei Chi
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Junzhen Fan
Department of Pathology, Third Medical Center Chinese PLA General Hospital Beijing the People's Republic of China
Lijun Cheng
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Xuning Wang
Department of General Surgery The Air Force Hospital of Northern Theater PLA Shenyang the People's Republic of China
Xu Yang
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Meng Zhang
Department of Neurosurgery, The First Medical Centre Chinese PLA General Hospital Beijing Beijing the People's Republic of China
Zewei Lian
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Zengqi Huang
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Huadong Wang
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Hongfei Xie
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Sisi Chen
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Qi Pan
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Zeying Zhang
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Bingda Chen
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Guochen Sun
Department of Neurosurgery, The First Medical Centre Chinese PLA General Hospital Beijing Beijing the People's Republic of China
Bainan Xu
Department of Neurosurgery, The First Medical Centre Chinese PLA General Hospital Beijing Beijing the People's Republic of China
Meng Su
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Yanlin Song
Key Laboratory of Green Printing, CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry, Chinese Academy of Sciences (ICCAS), Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS) Beijing the People's Republic of China
Abstract Histopathology plays a great role in diagnosing various diseases, which is considered as a golden standard for tumor identification. The tissue constituents must be stained by visible labels for microscopic analysis by medical experts. However, this process is time‐consuming, labor‐intensive, and expensive, which requires rapid pathological approaches for diagnosis in the operating room. Here, we present an easy‐to‐process and high‐performance perovskite biological probes for rapid and visual pathological diagnosis of glioma. Perovskite quantum dots can be encapsulated by the copolymer into nanocrystals (PNCs) with a diameter of 100 nm, which is modified with chlorotoxin to achieve the specific recognition of glioma. Benefiting from the super photoluminescence quantum yield (above 93%) of EVA@PNCs aqueous solution, the glioma can be clearly imaged and captured via a smartphone under the excitation of a handheld UV lamp. To demonstrate the visualization and efficiency of PNC probes, different malignant grades of brain tumor sections can be distinguished in no more than 5 min. This strategy provides a general auxiliary diagnosis platform for achieving the histopathology analysis near the operating bed, which is currently not feasible with standard histochemical staining methods.