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| 1 | Effective nanotherapeutic approach for metastatic breast cancer treatment by supplemental oxygenation and imaging-guided phototherapy显示文摘Metastasis remains the primary cause for mortality of breast cancer.Despite advances in current therapeutic agents,patients with metastatic breast cancer still have poor prognoses.Tumor hypoxia,a key microenvironment factor,is emerging as an attractive target to prevent metastasis and is also involved with resistance to phototherapy.Here,we show an effective nanotherapeutic approach based on manganese dioxide-coated polydopamine nanocarriers to trigger robust anti-tumor and anti-metastasis responses against metastatic breast cancer by supplemental oxygenation and multimodal imaging-guided phototherapies.In cancer cells,the produced oxygen by the developed nanoplatform decreases the expression of hypoxia-inducible factors 1 a to inhibit tumor metastasis,and enhances the efficacy of photodynamic therapy.This nanotherapeutic approach enables the combined photodynamic/photothermal treatments with great inhibition on cell migration and invasion in vitro.Moreover,the nanotherapeutics effectively suppresses primary tumor progress and inhibits lung metastasis in v ivo in a breast cancer mouse model with satisfying biosafety.This study suggests that the tumor hypoxia-targeting nanotherapeutics have great potential for preventing and treating metastatic cancers. | Jialing Hu Fuan Wang Feng Liu Wentong Sun Qunying Jiang Yahua Liu Yun Zhao Xiaoqing Liu | 2020 | Nano Research2020，13，4： | 1 |
| 2 | Laparoscopic Treatment for Choledochal Cysts with Stenosis of the Com- mon Hepatic Duct 显示文摘 | Jian Wang Wentong Zhang Daqing Sun | 2012 | The Jourl of American College of Surgeons2012，214，6： | 1 |
| 3 | A CONTROLLED STUDY OF THERAPEUTIC EFFECTS OF COMPUTER-CONTROLLED ELECTRIC ACUPUNCTURE TREATMENT ON REFRACTORY SCHIZOPHRENIA显示文摘Out of 100 cases of intractable schizophrenia,57 cases were in the group ofComputer-Controlled Electric Acupuncture (CCEA) and 43 in the control group.The therapeutic re-sults showed that clinically CCEA had a remarkably effective rate of 40. 35% on refractoryschizophrenia,which had much better curative effects than those in the control group.Through dy-namic evaluation of brief psychiatric rating scale (BPRS),negative symptom scale (SANS) and posi-tive symptom scale (SAPS) for both groups before,during and after treatment,the results indicatedthat in CCEA group the scores of BPRS,SANS and SAPS after treatment were much less than thosebefore treatment,which were remarkably different from those in the control group (P<0.01).Lab-oratory examination of thyroxin and androgen of patients in both groups before and after treatmentfound a significant result. | Zhang Ben Meng Surong Yu Jiang Quan Changgeng Li Wentong Sun Hexiang Zhang Baoting Shi Qiuying Kailuan Psychiatric Hospital,Tangshan 063001,ChinaWang Jianjun Kailuan Hospital,Tangshan 063001,China | 1993 | World Journal of Acupuncture-Moxibustion1993，3，4： | 1 |
| 4 | Auto-CSC:A Transfer Learning Based Automatic Cell Segmentation and Count Framework显示文摘Cell segmentation and counting play a very important role in the medical field.The diagnosis of many diseases relies heavily on the kind and number of cells in the blood.convolution neural network achieves encouraging results on image segmentation.However,this data-driven method requires a large number of annotations and can be a time-consuming and expensive process,prone to human error.In this paper,we present a novel frame to segment and count cells without too many manually annotated cell images.Before training.we generated the cell image labels on single-kind cell images using traditional algorithms.These images were then used to form the train set with the label.Different train sets composed of different kinds of cell images are presented to the segmentation model to update its parameters.Finally,the pretrained U-Net model is transferred to segment the mixed cell images using a small dataset of manually labeled mixed cell images.To better evaluate the efectiveness of the proposed method,we design and train a new automatic cell segmentation and count framework.The test results and analyses show that the segmentation and count performance of the framework trained by the proposed method equal the model trained by large amounts of annotated mixed cell images. | Guangdong Zhan Wentong Wang Hongyan Sun Yaxin Hou Lin Feng | 2022 | Cyborg and Bionic Systems2022，，1： | 0 |
| 5 | Temporal-spatial Generation of Astrocytes in the Developing Diencephalon显示文摘tAstrocytes are the largest glial population in the mammalian brain.However,we have a minimal understanding of astrocyte development,especially fate specification in different regions of the brain.Through lineage tracing of the progenitors of the third ventricle(3V)wall via in-utero electroporation in the embryonic mouse brain,we show the fate specification and migration pattern of astrocytes derived from radial glia along the 3V wall.Unexpectedly,radial glia located in different regions along the 3V wall of the diencephalon produce distinct cell types:radial glia in the upper region produce astrocytes and those in the lower region produce neurons in the diencephalon.With genetic fate mapping analysis,we reveal that the first population of astrocytes appears along the zona incerta in the diencephalon.Astrogenesis occurs at an early time point in the dorsal region relative to that in the ventral region of the developing diencephalon.With transcriptomic analysis of the region-specific 3V wall and lateral ventricle(LV)wall,we identified cohorts of differentially-expressed genes in the dorsal 3V wall compared to the ventral 3V wall and LV wall that may regulate astrogenesis in the dorsal diencephalon.Together,these results demonstrate that the generation of astrocytes shows a spatiotemporal pattern in the developing mouse diencephalon. | Wentong Hong Pifang Gong Xinjie Pan Zhonggan Ren Yitong Liu Guibo Qi Jun-Liszt Li Wenzhi Sun Woo-Ping Ge Chun-Li Zhang Shumin Duan Song Qin | 2024 | Neuroscience Bulletin2024，40，1： | 0 |
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