http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Jiachen Shi (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Jiachen Shi,Qiuling Ma,Wenting Su,Congyan Liu,Huangqin Zhang,Yuping Liu,Xiaoqi Li,Xi Jiang,Chang Ge,Fei Kong,Yan Chen,Ding Qu 한국생체재료학회 2023 생체재료학회지 Vol.27 No.00
Background Conventional dissolving microneedles (DMNs) face significant challenges in anti-melanoma therapy due to the lack of active thrust to achieve efficient transdermal drug delivery and intra-tumoral penetration. Methods In this study, the effervescent cannabidiol solid dispersion-doped dissolving microneedles (Ef/CBD-SD@ DMNs) composed of the combined effervescent components (CaCO3 & NaHCO3) and CBD-based solid dispersion (CBD-SD) were facilely fabricated by the “one-step micro-molding” method for boosted transdermal and tumoral delivery of cannabidiol (CBD). Results Upon pressing into the skin, Ef/CBD-SD@DMNs rapidly produce CO2 bubbles through proton elimination, significantly enhancing the skin permeation and tumoral penetration of CBD. Once reaching the tumors, Ef/CBD-SD@ DMNs can activate transient receptor potential vanilloid 1 (TRPV1) to increase Ca2+ influx and inhibit the downstream NFATc1-ATF3 signal to induce cell apoptosis. Additionally, Ef/CBD-SD@DMNs raise intra-tumoral pH environment to trigger the engineering of the tumor microenvironment (TME), including the M1 polarization of tumor-associated macrophages (TAMs) and increase of T cells infiltration. The introduction of Ca2+ can not only amplify the effervescent effect but also provide sufficient Ca2+ with CBD to potentiate the anti-melanoma efficacy. Such a “one stone, two birds” strategy combines the advantages of effervescent effects on transdermal delivery and TME regulation, creating favorable therapeutic conditions for CBD to obtain stronger inhibition of melanoma growth in vitro and in vivo. Conclusions This study holds promising potential in the transdermal delivery of CBD for melanoma therapy and offers a facile tool for transdermal therapies of skin tumors.
-
Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6
Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.
KCI
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
