The number of patients with eye diseases in China is enormous,and the negative effects of these conditions,such as impaired visual function,psychological burdens,and restricted social participation,are becoming increasingly severe.Due to the limited and unevenly distributed ophthalmic resources,and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency,there is an urgent need for more sensitive and efficient modalities.With the rapid advancement of artificial intelligence technology,ophthalmic diagnosis has entered a new stage of intelligent transformation.Facial photos,as a noninvasive and convenient medium,show unique advantages in eye disease diagnosis.Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia,strabismus,ptosis,and thyroid eye disease,showing promising results.This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs,with a focus on recapitulating relevant research findings both domestically and internationally in recent years.It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos,analyzes the current technical bottlenecks and challenges in application,proposes corresponding countermeasures,and discusses future development directions,aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.

The number of patients with eye diseases in China is enormous,and the negative effects of these conditions,such as impaired visual function,psychological burdens,and restricted social participation,are becoming increasingly severe.Due to the limited and unevenly distributed ophthalmic resources,and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency,there is an urgent need for more sensitive and efficient modalities.With the rapid advancement of artificial intelligence technology,ophthalmic diagnosis has entered a new stage of intelligent transformation.Facial photos,as a noninvasive and convenient medium,show unique advantages in eye disease diagnosis.Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia,strabismus,ptosis,and thyroid eye disease,showing promising results.This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs,with a focus on recapitulating relevant research findings both domestically and internationally in recent years.It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos,analyzes the current technical bottlenecks and challenges in application,proposes corresponding countermeasures,and discusses future development directions,aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.

Objective To explore the regulatory effect of STING pathway on the immunity related to regulatory T cells(Treg)in glioma mice.Methods Glioma models were constructed based on ectopic GL261 implantation of cell lines established from ectopic brain implantation in mice.After successful modeling,the mice were randomly divided into control group,SN-011 group and MSA-2 group.STING was inhibited by intracranial injection of SN-011(10 mg/ml)in group SN-011,and promoted by intracranial injection of MSA-2(50 mg/ml)in group MSA-2.The effects of STING on tumor volume,mass and immune factors IFN-β and IL-10 were compared.The infiltrated Treg cells in tumor tissues were observed by immunohistochemical staining with FOXP3,and the expression of STING and IRF3 proteins were detected.Results Compared with the control group,the tumor volume,tumor mass,IL-10 level and Treg invasion ratioin SN-011 group were increased(P<0.05),while the protein levels of IFN-β,STING and IRF3 were decreased(P<0.05);Compared with the control group,the tumor volume,tumor mass,IL-10 level and Treg invasion ratio in the MSA-2 group were decreased(P<0.05),while IFN-β,STING and IRF3 protein levels were increased(P<0.05).Compared with SN-011 group,tumor volume,mass,IL-10 level and Treg invasion ratio in MSA-2 group were decreased(P<0.05),while IFN-β,STING and IRF3 protein levels were increased(P<0.05).Conclusion STING pathway promotes the progression of brain glioma by promoting Treg infiltration and inducing immune escape.

Objective To explore the regulatory effect of STING pathway on the immunity related to regulatory T cells(Treg)in glioma mice.Methods Glioma models were constructed based on ectopic GL261 implantation of cell lines established from ectopic brain implantation in mice.After successful modeling,the mice were randomly divided into control group,SN-011 group and MSA-2 group.STING was inhibited by intracranial injection of SN-011(10 mg/ml)in group SN-011,and promoted by intracranial injection of MSA-2(50 mg/ml)in group MSA-2.The effects of STING on tumor volume,mass and immune factors IFN-β and IL-10 were compared.The infiltrated Treg cells in tumor tissues were observed by immunohistochemical staining with FOXP3,and the expression of STING and IRF3 proteins were detected.Results Compared with the control group,the tumor volume,tumor mass,IL-10 level and Treg invasion ratioin SN-011 group were increased(P<0.05),while the protein levels of IFN-β,STING and IRF3 were decreased(P<0.05);Compared with the control group,the tumor volume,tumor mass,IL-10 level and Treg invasion ratio in the MSA-2 group were decreased(P<0.05),while IFN-β,STING and IRF3 protein levels were increased(P<0.05).Compared with SN-011 group,tumor volume,mass,IL-10 level and Treg invasion ratio in MSA-2 group were decreased(P<0.05),while IFN-β,STING and IRF3 protein levels were increased(P<0.05).Conclusion STING pathway promotes the progression of brain glioma by promoting Treg infiltration and inducing immune escape.

The goal of this paper is to solve the problems of large volume, slow dynamic response and poor intelligent controllability of traditional gait rehabilitation training equipment by using the characteristic that the shear yield strength of magnetorheological fluid changes with the applied magnetic field strength. Based on the extended Bingham model, the main structural parameters of the magnetorheological fluid damper and its output force were simulated and optimized by using scientific computing software, and the three-dimensional modeling of the damper was carried out after the size was determined. On this basis and according to the design and use requirements of the damper, the finite element analysis software was used for force analysis, strength check and topology optimization of the main force components. Finally, a micro magnetorheological fluid damper suitable for wearable rehabilitation training system was designed, which has reference value for the design of lightweight, portable and intelligent rehabilitation training equipment.
Computer Simulation ; Software ; Wearable Electronic Devices

Objective To establish an easy, rapid and sensitive method for determination of micro 2,4-dinitrotoluene in waste water. Methods Based on the fact that micro 2,4-dinitrotoluene could inhibit the discoloring oxidation reaction of methylene blue by KIO4 in the HC1 solution, micro 2,4-dinitrotoluene was determined using kinetic spectrophotometric method. Results A new kinetic spectrophotometric method for determination of micro 2,4-dinitrotoluene was established. The linear range of the method was 0.20?10~(-5)-1.8?10~(-5) mg/L, the detection limit was 1.7xlO'7 mg/L. When the method was applied to the determination of the 2,4-dinitrotoluene in waste water, its recovery rates in standard addition method were 95.6%-99.1% and the RSDs were 1.5%-2.6%. Conclusion The method was easier to operate and more rapid, which was suitable for the determination of micro 2,4-dinitrtoluene in wastewater.