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1.
J Org Chem ; 85(5): 3576-3586, 2020 Mar 06.
Artigo em Inglês | MEDLINE | ID: mdl-31984747

RESUMO

A copper-catalyzed decarboxylative cycloaddition of propiolic acids, azides, and arylboronic acids is described. The present reaction provides an efficient and convenient method for the synthesis of various fully substituted 1,2,3-triazoles from readily available starting materials. A possible mechanism is proposed.

2.
Org Lett ; 21(7): 2227-2230, 2019 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-30868884

RESUMO

A novel copper-catalyzed decarboxylative oxyalkylation of alkynyl carboxylic acids with ketones and alkylnitriles via direct C(sp3)-H bond functionalization to construct new C-C bonds and C-O double bonds was developed. This transformation is featured by wide functional group compatibility and the use of readily available reagents, thus affording a general approach to γ-diketones and γ-ketonitriles. A possible mechanism is proposed.

3.
Org Lett ; 21(2): 444-447, 2019 01 18.
Artigo em Inglês | MEDLINE | ID: mdl-30588816

RESUMO

A novel radical [2 + 2 + 1] cyclization of ortho-cyanoarylacrylamides with dual α-C-H bonds in alkyl nitriles has been developed. The reaction provides new facile and straightforward access to cyano-substituted pyrrolo[3,2- c]quinolines, which are important nitrogen-containing polyheterocycles. A possible mechanism for the transformation is proposed.

4.
Conf Proc IEEE Eng Med Biol Soc ; 2019: 2801-2804, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31946475

RESUMO

Botulinum toxin injection is a highly efficacious treatment for masseter muscle hypertrophy, while manual injection point localization based on experience can be non-quantitative, subjective and therefore suboptimal and even side-effect risky. To address this important while challenging task, in this paper we present a methodology of automatic ideal point localization for botulinum toxin injection based on automatic segmentation, measurement and quantitative analysis. Specifically, we first present a novel three-dimensional (3D) fully convolutional neural network for fully automatic mandible and masseter regions of interest (RoI) localization and segmentation from head computed tomography (CT) images. Given the segmentation results, the ideal injection points on the face are located using ray casting based automatic thickness measurement. We conducted experiments on an internal dataset consisting of head CT images acquired from 53 patients to evaluate the segmentation performance and localization reliability. The results demonstrate that the segmentation framework outperforms the state-of-the-art method by a significant margin, and the localization system provides intuitive, interactive user interface and reliable injection point decisions.

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