RESUMO
The enantioselective construction of C-CF2R (R: alkyl or fluoroalkyl) bonds has attracted the attention of synthetic chemists because of the importance of chiral fluorinated compounds in life and materials sciences. Catalytic asymmetric fluoroalkylation has mainly been realized under organocatalysis and Lewis acid catalysis, with substrates limited to carbonyl compounds. Few examples using transition-metal catalysis exist, owing to side reactions including decomposition and isomerization of fluoroalkylating reagents. Herein we report umpolung asymmetric difluoroallylation of hydrazones with 3-bromo-3,3-difluoropropene (BDFP) under palladium catalysis. Difluoroallylation products having quaternary chiral carbon centers are afforded in good yields with high α/γ- and enantioselectivities. The usefulness of the reaction products is demonstrated and an inner-sphere mechanism of the reaction is proposed. The use of chiral N-heterocyclic carbene as ligand is the key for the selectivities as well as the productivity of the reaction.
RESUMO
BACKGROUND: Accurate estimation of the recurrence of pancreatic neuroendocrine tumors help with prognosis, guide follow-up, and avoid futile treatments. PURPOSE: To investigate whether MRI features could preoperatively estimate the recurrence of pancreatic neuroendocrine tumors (PNETs) and to refine a novel prognostic model through developing a nomogram incorporating various MRI features. STUDY TYPE: Retrospective. POPULATION: In all, 81 patients with clinicopathologically confirmed nonmetastatic PNETs. FIELD STRENGTH/SEQUENCES: 1.5 T MR, including T1 -weighted, T2 -weighted, and diffusion-weighted imaging sequences. ASSESSMENT: Qualitative and quantitative MRI features of PNET were assessed by three experienced radiologists. STATISTICAL TESTS: Uni- and multivariable analyses for recurrence-free survival (RFS) were evaluated using a Cox proportional hazards model. The MRI-based nomogram was then designed based on multivariable logistic analysis in our study and the performance of the nomogram was validated according to C-index, calibration, and decision curve analyses. RESULTS: MRI features, including tumor size (hazard ratio [HR]: 14.131; P = 0.034), enhancement pattern (HR: 21.821, P = 0.032), and the apparent diffusion coefficient (ADC) values (HR: 0.055, P = 0.038) were significant independent predictors of RFS at multivariable analysis. The performance of the nomogram incorporating various MRI features (with a C-index of 0.910) was improved compared with that based on tumor size, enhancement pattern, and ADC alone (with C-index values of 0.672, 0.851, and 0.809, respectively). The calibration curve of the nomogram exhibited perfect consistency between estimation and observation at 0.5, 1, and 2 years after surgery. The decision curve showed that a nomogram incorporating three features had more favorable clinical predictive usefulness than any single feature. DATA CONCLUSION: MRI features can be considered effective recurrence predictors for PNETs after surgery. The preliminary nomogram incorporating various MRI features could assess the risk of recurrence in PNETs and may be used to optimize individual treatment strategies. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:397-409.
