Three pairs of homochiral Ag(Ⅰ)enantiomers formulated as[Ag_(2)(L_(R))(pa)]_(n)/[Ag_(2)(Ls)(pa)]_(n)(R1/S1,H_(2)pa=phthalic acid),[Ag_(2)(L_(R))(tda)]_(n)·H_(2)O/[Ag_(2)(Ls)(tda)]_(n)·H_(2)O(R2/S2,H_(2)tda=...Three pairs of homochiral Ag(Ⅰ)enantiomers formulated as[Ag_(2)(L_(R))(pa)]_(n)/[Ag_(2)(Ls)(pa)]_(n)(R1/S1,H_(2)pa=phthalic acid),[Ag_(2)(L_(R))(tda)]_(n)·H_(2)O/[Ag_(2)(Ls)(tda)]_(n)·H_(2)O(R2/S2,H_(2)tda=3,4-thiophene dicarboxylic acid),and[Ag_(4)(L_(R))_(2)(3-npa)_(2)]_(n)/[Ag_(4)(Ls)_(2)(3-npa)2]_(n)(R3/S3,3-H_(2)npa=3-nitrophthalic acid)were prepared by using different dicarboxylic acid coligands via the reactions of AgNO_(3)with enantiopure monobidentate N-donor heterocyclic ligands named(+)/(−)-4,5-pinenepyridyl-2-pyrazine(LS/L_(R)),respectively.Ⅰnvestigations on the nonlinear optical(NLO)response suggest R1/S1 and R2/S2 enantiomers present very strong third-harmonic generation(THG)responses,and the lowest THG intensities of R1/S1 and R2/S2 are 244 and 142 times that ofα-SiO_(2),respectively.However,R3/S3 enantiomers only exhibit mild second-harmonic generation(SHG)response(0.36×KDP).A comparative study on the molecular structures of these Ag(Ⅰ)enantiomeric pairs reveals that both the symmetry and degree ofπ-conjugation of the dicarboxylate ligands are mainly responsible for their different NLO responses.Our research result not only provides a feasible method of constructing coordination polymers(CPs)with strong THG response but also points out an effective strategy for switching NLO behaviors from THG to SHG response.展开更多
This study aimed to investigate the performance of^(18)F-DCFPyL positron emission tomography/computerized tomography(PET/CT)models for predicting benign-vs-malignancy,high pathological grade(Gleason score>7),and cl...This study aimed to investigate the performance of^(18)F-DCFPyL positron emission tomography/computerized tomography(PET/CT)models for predicting benign-vs-malignancy,high pathological grade(Gleason score>7),and clinical D'Amico classifcation with machine learning.The study included 138 patients with treatment-naïve prostate cancer presenting positive^(18)F-DCFPyL scans.The primary lesions were delineated on PET images,followed by the extraction of tumor-to-backgroundbased general and higher-order textural features by applying fve diferent binning approaches.Three layer-machine learning approaches were used to identify relevant in vivo features and patient characteristics and their relative weights for predicting high-risk malignant disease.The weighted features were integrated and implemented to establish individual predictive models for malignancy(Mm),high path-risk lesions(by Gleason score)(Mgs),and high clinical risk disease(by amico)(Mamico).The established models were validated in a Monte Carlo cross-validation scheme.In patients with all primary prostate cancer,the highest areas under the curve for our models were calculated.The performance of established models as revealed by the Monte Carlo cross-validation presenting as the area under the receiver operator characteristic curve(AUC):0.97 for Mm,AUC:0.73 for Mgs,AUC:0.82 for Mamico.Our study demonstrated the clinical potential of^(18)F-DCFPyL PET/CT radiomics in distinguishing malignant from benign prostate tumors,and high-risk tumors,without biopsy sampling.And in vivo^(18)F-DCFPyL PET/CT can be considered a noninvasive tool for virtual biopsy for personalized treatment management.展开更多
基金the National Natural Science Foundation of China(No.21701150 and 21371156)the school doctorial foundation of Zhengzhou University of Light Industry(No.2016BSJJ028)Zhongyuan Science and Technology Innovation Leading Talents(214200510017).
文摘Three pairs of homochiral Ag(Ⅰ)enantiomers formulated as[Ag_(2)(L_(R))(pa)]_(n)/[Ag_(2)(Ls)(pa)]_(n)(R1/S1,H_(2)pa=phthalic acid),[Ag_(2)(L_(R))(tda)]_(n)·H_(2)O/[Ag_(2)(Ls)(tda)]_(n)·H_(2)O(R2/S2,H_(2)tda=3,4-thiophene dicarboxylic acid),and[Ag_(4)(L_(R))_(2)(3-npa)_(2)]_(n)/[Ag_(4)(Ls)_(2)(3-npa)2]_(n)(R3/S3,3-H_(2)npa=3-nitrophthalic acid)were prepared by using different dicarboxylic acid coligands via the reactions of AgNO_(3)with enantiopure monobidentate N-donor heterocyclic ligands named(+)/(−)-4,5-pinenepyridyl-2-pyrazine(LS/L_(R)),respectively.Ⅰnvestigations on the nonlinear optical(NLO)response suggest R1/S1 and R2/S2 enantiomers present very strong third-harmonic generation(THG)responses,and the lowest THG intensities of R1/S1 and R2/S2 are 244 and 142 times that ofα-SiO_(2),respectively.However,R3/S3 enantiomers only exhibit mild second-harmonic generation(SHG)response(0.36×KDP).A comparative study on the molecular structures of these Ag(Ⅰ)enantiomeric pairs reveals that both the symmetry and degree ofπ-conjugation of the dicarboxylate ligands are mainly responsible for their different NLO responses.Our research result not only provides a feasible method of constructing coordination polymers(CPs)with strong THG response but also points out an effective strategy for switching NLO behaviors from THG to SHG response.
文摘This study aimed to investigate the performance of^(18)F-DCFPyL positron emission tomography/computerized tomography(PET/CT)models for predicting benign-vs-malignancy,high pathological grade(Gleason score>7),and clinical D'Amico classifcation with machine learning.The study included 138 patients with treatment-naïve prostate cancer presenting positive^(18)F-DCFPyL scans.The primary lesions were delineated on PET images,followed by the extraction of tumor-to-backgroundbased general and higher-order textural features by applying fve diferent binning approaches.Three layer-machine learning approaches were used to identify relevant in vivo features and patient characteristics and their relative weights for predicting high-risk malignant disease.The weighted features were integrated and implemented to establish individual predictive models for malignancy(Mm),high path-risk lesions(by Gleason score)(Mgs),and high clinical risk disease(by amico)(Mamico).The established models were validated in a Monte Carlo cross-validation scheme.In patients with all primary prostate cancer,the highest areas under the curve for our models were calculated.The performance of established models as revealed by the Monte Carlo cross-validation presenting as the area under the receiver operator characteristic curve(AUC):0.97 for Mm,AUC:0.73 for Mgs,AUC:0.82 for Mamico.Our study demonstrated the clinical potential of^(18)F-DCFPyL PET/CT radiomics in distinguishing malignant from benign prostate tumors,and high-risk tumors,without biopsy sampling.And in vivo^(18)F-DCFPyL PET/CT can be considered a noninvasive tool for virtual biopsy for personalized treatment management.
