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| 1 | Identification of Graves’ophthalmology by laser-induced breakdown spectroscopy combined with machine learning method显示文摘Diagnosis of the Graves’ophthalmology remains a significant challenge.We identified between Graves’ophthalmology tissues and healthy controls by using laser-induced breakdown spectroscopy(LIBS)combined with machine learning method.In this work,the paraffin-embedded samples of the Graves’ophthalmology were prepared for LIBS spectra acquisition.The metallic elements(Na,K,Al,Ca),non-metallic element(O)and molecular bands((C-N),(C-O))were selected for diagnosing Graves’ophthalmology.The selected spectral lines were inputted into the supervised classification methods including linear discriminant analysis(LDA),support vector machine(SVM),k-nearest neighbor(ANN),and generalized regression neural network(GRNN),respectively.The results showed that the predicted accuracy rates of LDA,SVM,ANN,GRNN were 76.33%,96.28%,96.56%,and 96.33%,respectively.The sensitivity of four models were 75.89%,93.78%,96.78%,and 96.67%,respectively.The specificity of four models were 76.78%,98.78%,96.33%,and 96.00%,respectively.This demonstrated that LIBS assisted with a nonlinear model can be used to identify Graves’ophthalmopathy with a higher rate of accuracy.The ANN had the best performance by comparing the three nonlinear models.Therefore,LIBS combined with machine learning method can be an effective way to discriminate Graves’ophthalmology. | Jingjing LI Feng CHEN Guangqian HUANG Siyu ZHANG Weiliang WANG Yun TANG Yanwu CHU Jian YAO Lianbo GUO Fagang JIANG | 2021 | Frontiers of Optoelectronics2021，14，3： | 3 |
| 2 | Rationale for the use of multifunctional drugs as neuroprotective agents for glaucoma显示文摘Glaucoma, the leading cause globally of irreversible blindness, is a neurodegenerative disease characterized by progressive retinal ganglion cell death. To date, no drug has been shown to prevent the retinal ganglion cell loss associated with glaucoma. Multiple mechanisms lead to ganglion cell death in glaucoma, suggesting that a neuroprotectant that has a single mode of action, like memantine, would have a limited positive effect at slowing down ganglion cell death. Conversely, simultaneously targeting several factors may be the best therapeutic approach to improve outcomes. Multifunctional drugs are fast gaining acceptance as a strategy for the treatment of complex disor-ders of the central nervous system, such as Parkinson's disease, Alzheimer's disease and other progressive neurodegenerative diseases. In this paper, we review the current literature on multi-functional drugs and propose a rationale for the use of multifunctional drugs in glaucomatous optic neuropathy. | Jiahua Fang Fagang Jiang Jingbo Li Yanhua Zhu | 2012 | Neural Regeneration Research2012，7，4： | 3 |
| 3 | Secretions from hypochlorous acid-treated tumor cells delivered in a melittin hydrogel potentiate cancer immunotherapy显示文摘Autologous tumor cells and cell-derived secretions(CDS)can induce antitumor immune responses.The conditions in which cells are cultured and treated impact CDS,and cellular insults alter their composition and function.In this study,we generated CDS from tumor cells exposed to normal culture conditions,hypoxia,cisplatin,radiotherapy,photodynamic therapy,or hypochlorous acid(HOCl).In vitro HOCl-CDS showed the strongest stimulatory effects on dendritic cells and macrophages compared to CDS generated by hypoxia,cisplatin,radiotherapy or photodynamic therapy.To improve HOCl-CDS activity at the tumor site,we loaded HOCl-CDS into a melittin-encapsulated hydrogel scaffold.When injected intratumorally,the HOCl-CDS hydrogel promoted tumor cell death,cytotoxic T lymphocyte infiltration,and tumor-associated macrophage reprogramming towards an M1 phenotype.The hydrogel inhibited tumor growth and prolonged the survival of mice bearing B16-F10 melanoma.Furthermore,hydrogel-delivered HOCl-CDS augmented the antitumor effects of immune checkpoint blockade.These results underscore the importance of the CDS generation method and delivery approach for improving cancer immunotherapy. | Yuhan Zhou Ting Ye Chengzhi Ye Chao Wan Siyue Yuan Yushuai Liu Tianyu Li Fagang Jiang Jonathan F.Lovell Honglin Jin Jing Chen | 2022 | Bioactive Materials2022，7，3： | 0 |
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