Fractals refer to structures whose component parts exhibit similarity to the whole in certain aspects. The retinal microvascular system, as the only terminal microvasculature that can be directly observed in vivo, possesses a tree-like branching morphology that conforms to the characteristics of fractals. Fractal dimension(FD)is a numerical value that describes the density and complexity of the overall retinal vascular network, complementing the limitations of vessel density alone in characterizing vascular structural features. In recent years, the widespread application of optical coherence tomography angiography(OCTA)has enabled the visualization of blood flow across various retinal capillary layers, thereby extending the concept of fractal analysis to the retinal microvasculature. FD has been demonstrated to serve as a novel potential biomarker for ophthalmic conditions, including diabetic retinopathy, glaucoma, age-related macular degeneration, high myopia, and retinal vein occlusion, providing valuable metrics for the early diagnosis of these diseases. This review provides a comprehensive summary of the definition, calculation methods, influencing factors, and recent research developments regarding FD in various ophthalmic disorders.

Objective To investigate the drivers,stakeholders,core tasks,and differentiated development models of digital transformation in Chinese hospitals,develop a hospital digital transformation model,and propose advancement pathways.Methods Leveraging ROCCIPI theory,socio-technical systems theory,and social network theory,a multiple case study approach was employed to analyze four representative Chinese hospitals,examining the driving factors,social network relationship,and core tasks of digital transformation.Results Hospital digital transformation is a complex process driven by regulations,opportunities,and capabilities,requiring efficient collaboration among stakeholders focused on patient services,clinical operations,hospital management,and security.It identified three development models-ecology-oriented,regional integration,and grassroots enhancement—based on the distinct characteristics of the hospitals.A theoretical model for digital transformation in four Chinese hospitals was developed,along with proposed pathways and strategies.Conclusion It presents a digital transformation model and advancement pathways for hospitals through multiple case analyses,addressing the limited perspectives of existing research and providing a reference for practice.

Objective To analyze the influencing factors of the success of clinical pregnancy in secondary infertility patients undergoing in vitro fertilization-embryo transfer(IVF-ET)and construct a nomogram prediction model.Methods A retrospective analysis was conducted on the clinical data of 235 patients with secondary infertility who underwent IVF-ET at Urumqi Maternal and Child Health Hospital from January 2020 to December 2023.They were divided into successful pregnancy group(n=109)and failed pregnancy group(n=1 26)based on whether clinical pregnancy was successful.The general information,ovulation induction data and embryo data of two groups of patients were compared.Multivariate Logistic regression analysis was used to screen out statistically significant indicators,and based on this,a nomogram prediction model was constructed.The receiver operating characteristic curve,calibration curve and decision analysis curve were drawn to verify the discrimination,accuracy and clinical practicability of the model.Results The results of multivariate Logistic regression analysis showed that the female's age,overweight and obesity were all risk factors for clinical pregnancy failure,while anti-Müllerian hormone(AMH)and the total amount of gonadotropins(Gn)were protective factor for clinical pregnancy outcomes.On this basis,a nomogram prediction model was successfully constructed,which has a medium degree of discrimination,good accuracy and clinical practicability.Conclusion For secondary infertility patients undergoing IVF-ET,the female's age,overweight and obesity,AMH,and the total amount of Gn have certain influences on clinical pregnancy.The clinical pregnancy outcome can be predicted through the constructed nomogram prediction model.

Objective:To explore the applicability of modified comprehensive interventions in the treatment of non-severe dry eye syndrome in military pilots.Methods:A total of 88 military pilots with non-severe dry eye syndrome admitted to the Special Service Department of the 988th Hospital of the Joint Logistic Support Force between December 2021 and December 2023 were divided into an intervention group and a control group using the random number table method, with 44 cases in each. The intervention group received modified comprehensive interventions, while the control group underwent conventional treatment. The Ocular Surface Disease Index (OSDI), break-up time, tear meniscus height, changes in meibomian gland function, and levels of satisfaction of military pilots were compared between the 2 groups. The correlations between the OSDI, break-up time, tear meniscus height and levels of satisfaction were analyzed.Results:Before treatment, there was no significant difference in the OSDI between the 2 groups ( P>0.05). After 4 weeks of treatment, the changes in the OSDI of military pilots were smaller in the intervention group than in the control group ( t=3.21, P=0.002). After 2 and 4 weeks of treatment, the break-up time (both P<0.001) and tear meniscus height ( P<0.001, =0.012) of pilots in the intervention group exceeded those of the control group. In both groups, the break-up time (all P<0.001) and tear meniscus height (all P<0.001) kept increasing after treatment. After 4 weeks of treatment, there were significant differences in the distribution of meibomian gland function between the 2 groups ( Z=-2.55, -2.41, -2.29, P=0.011, 0.016, 0.022). Clinical care, procedure flow, and health education scored higher in the intervention group than in the control group during the survey on levels of satisfaction with the treatment ( t=6.55, 6.77, 3.63, all P≤0.001). The OSDI was negatively correlated with clinical care, procedure flow and health education ( r=-0.286, -0.275, -0.363, P=0.007, 0.010, 0.001) while the break-up time was positively correlated with clinical care and procedure flow ( r=0.248, 0.278, P=0.020, 0.009). Conclusions:The implementation of modified comprehensive intervention measures for dry eye syndrome in military pilots can effectively improve clinical symptoms and leave military pilots more satisfied.

Organoids,as a three-dimensional structural model that has been rapidly developed and widely concerned in recent years,enable the key functions and microenvironment of internal organs to be simulated in the real world,and closely reflect the physiological and pathological characteristics of the natural occurrence and metastasis of tumors,providing a new platform for disease modeling,drug research and precision medicine.This paper briefly summarizes the limitations and development prospects of organoid models,analyzes the current construction and development of organoid models of lung cancer and its applicability compared with traditional models under the holistic concept of traditional Chinese medicine and the basic theory of syndrome differentiation and treatment,and discusses the application of organoid technology in the basic research of lung cancer treatment.The advantages in screening anti-tumor Chinese medicine and drug resistance research and precision medicine provide new ideas for realizing innovative breakthroughs in traditional Chinese medicine research combined with modern science and technology.

Objective:To explore the correlation between serum soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and cognitive impairment in patients with cerebral small vessel disease (CSVD), and the role of deep medullary vein (DMV) score in this process.Methods:A total of 140 patients with CSVD admitted to the Department of Neurology, the First Affiliated Hospital of Henan Medical University from December 2022 to August 2024 were selected as the research objects. The basic data statistics, head magnetic resonance imaging examination, cognitive function assessment, serum sTREM2 detection and DMV score were performed. All data were analyzed by SPSS 29.0 software and GraphPad Prism 10.0 software packages. Logistic regression model was used to explore the influencing factors of cognitive impairment. Structural equation model was used to analyze the mediating effect of DMV score on the association between serum sTREM2 and cognitive impairment. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of serum sTREM2 level and DMV score for cognitive impairment in CSVD patients.Results:Serum sTREM2 level ( B=0.017, OR=1.017, 95% CI=1.003-1.031), DMV score ( B=0.375, OR=1.455, 95% CI=1.175-1.802) and years of education ( B=-0.248, OR=0.780, 95% CI=0.635-0.958) were risk factors for cognitive impairment (all P<0.05). sTREM2 not only directly affected cognitive function, but also indirectly affected cognitive function through DMV score. The direct effect (effect size=-0.022) and mediating effect (effect size=-0.007) accounted for 75.9% and 24.1% of the total effect (effect size=-0.029), respectively. The areas under the ROC curve of serum sTREM2 level, DMV score, and their combination for predicting cognitive impairment in CSVD patients were 0.880, 0.891, and 0.910, respectively (all P<0.001). Conclusion:Serum sTREM2 not only directly affects the cognitive function of patients with cerebral small vessel disease, but also indirectly affects cognitive function through DMV score. The combination of serum sTREM2 levels and DMV score has high predictive value for the risk of CSVD-related cognitive impairment.

Objective:To explore the correlation between serum soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and cognitive impairment in patients with cerebral small vessel disease (CSVD), and the role of deep medullary vein (DMV) score in this process.Methods:A total of 140 patients with CSVD admitted to the Department of Neurology, the First Affiliated Hospital of Henan Medical University from December 2022 to August 2024 were selected as the research objects. The basic data statistics, head magnetic resonance imaging examination, cognitive function assessment, serum sTREM2 detection and DMV score were performed. All data were analyzed by SPSS 29.0 software and GraphPad Prism 10.0 software packages. Logistic regression model was used to explore the influencing factors of cognitive impairment. Structural equation model was used to analyze the mediating effect of DMV score on the association between serum sTREM2 and cognitive impairment. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of serum sTREM2 level and DMV score for cognitive impairment in CSVD patients.Results:Serum sTREM2 level ( B=0.017, OR=1.017, 95% CI=1.003-1.031), DMV score ( B=0.375, OR=1.455, 95% CI=1.175-1.802) and years of education ( B=-0.248, OR=0.780, 95% CI=0.635-0.958) were risk factors for cognitive impairment (all P<0.05). sTREM2 not only directly affected cognitive function, but also indirectly affected cognitive function through DMV score. The direct effect (effect size=-0.022) and mediating effect (effect size=-0.007) accounted for 75.9% and 24.1% of the total effect (effect size=-0.029), respectively. The areas under the ROC curve of serum sTREM2 level, DMV score, and their combination for predicting cognitive impairment in CSVD patients were 0.880, 0.891, and 0.910, respectively (all P<0.001). Conclusion:Serum sTREM2 not only directly affects the cognitive function of patients with cerebral small vessel disease, but also indirectly affects cognitive function through DMV score. The combination of serum sTREM2 levels and DMV score has high predictive value for the risk of CSVD-related cognitive impairment.

Organoids,as a three-dimensional structural model that has been rapidly developed and widely concerned in recent years,enable the key functions and microenvironment of internal organs to be simulated in the real world,and closely reflect the physiological and pathological characteristics of the natural occurrence and metastasis of tumors,providing a new platform for disease modeling,drug research and precision medicine.This paper briefly summarizes the limitations and development prospects of organoid models,analyzes the current construction and development of organoid models of lung cancer and its applicability compared with traditional models under the holistic concept of traditional Chinese medicine and the basic theory of syndrome differentiation and treatment,and discusses the application of organoid technology in the basic research of lung cancer treatment.The advantages in screening anti-tumor Chinese medicine and drug resistance research and precision medicine provide new ideas for realizing innovative breakthroughs in traditional Chinese medicine research combined with modern science and technology.

Objective To analyze the influencing factors of the success of clinical pregnancy in secondary infertility patients undergoing in vitro fertilization-embryo transfer(IVF-ET)and construct a nomogram prediction model.Methods A retrospective analysis was conducted on the clinical data of 235 patients with secondary infertility who underwent IVF-ET at Urumqi Maternal and Child Health Hospital from January 2020 to December 2023.They were divided into successful pregnancy group(n=109)and failed pregnancy group(n=1 26)based on whether clinical pregnancy was successful.The general information,ovulation induction data and embryo data of two groups of patients were compared.Multivariate Logistic regression analysis was used to screen out statistically significant indicators,and based on this,a nomogram prediction model was constructed.The receiver operating characteristic curve,calibration curve and decision analysis curve were drawn to verify the discrimination,accuracy and clinical practicability of the model.Results The results of multivariate Logistic regression analysis showed that the female's age,overweight and obesity were all risk factors for clinical pregnancy failure,while anti-Müllerian hormone(AMH)and the total amount of gonadotropins(Gn)were protective factor for clinical pregnancy outcomes.On this basis,a nomogram prediction model was successfully constructed,which has a medium degree of discrimination,good accuracy and clinical practicability.Conclusion For secondary infertility patients undergoing IVF-ET,the female's age,overweight and obesity,AMH,and the total amount of Gn have certain influences on clinical pregnancy.The clinical pregnancy outcome can be predicted through the constructed nomogram prediction model.

Objective To investigate the drivers,stakeholders,core tasks,and differentiated development models of digital transformation in Chinese hospitals,develop a hospital digital transformation model,and propose advancement pathways.Methods Leveraging ROCCIPI theory,socio-technical systems theory,and social network theory,a multiple case study approach was employed to analyze four representative Chinese hospitals,examining the driving factors,social network relationship,and core tasks of digital transformation.Results Hospital digital transformation is a complex process driven by regulations,opportunities,and capabilities,requiring efficient collaboration among stakeholders focused on patient services,clinical operations,hospital management,and security.It identified three development models-ecology-oriented,regional integration,and grassroots enhancement—based on the distinct characteristics of the hospitals.A theoretical model for digital transformation in four Chinese hospitals was developed,along with proposed pathways and strategies.Conclusion It presents a digital transformation model and advancement pathways for hospitals through multiple case analyses,addressing the limited perspectives of existing research and providing a reference for practice.