Objective To explore clinical value of the expression levels of cell surface transmembrane glycoprotein molecule 44(CD44)mRNA,cell surface transmembrane glycoprotein molecule 24(CD24)mRNA,and protein in the placenta of severe preeclampsia(SPE)patients.Methods The SPE patients who were delivered by cesarean section in the Second People's Hospital of Liaocheng from June 2019 to June 2022 were further divided into 45 patients in early onset SPE group(gestational age≤34 weeks)and 55 patients in late onset SPE group(gestational age＞34 weeks)according to the different gestational age.The control group consisted of 100 normal cases in the same period.The expression of CD44 and CD24 in placenta of SPE patients was detected by fluorescent quantitative PCR and immunohistochemistry,Pearson method was used to analyze the difference of their expression levels and their correlation with the clinical characteristics of SPE disease,and multivariate logistic regression was used to analyze the influencing factors of SPE.Results Compared with the control group,the expression levels of CD44 mRNA(0.55±0.12 vs 1.02±0.33)and CD24 mRNA(0.68±0.19 vs 1.05±0.11)in SPE placental tissues decreased significantly,the differences were statistically significant(t=13.385,16.853,P＜0.05).The immunohistochemical staining results showed that CD44 and CD24 were mostly negative or weakly positive in the SPE group placental tissue,while they were mostly positive in the control group,the positive rates of CD44 and CD24 in the SPE placental tissue were lower than those in the control group,and the differences were statistically significant(χ2=9.696,14.346,P＜0.05).Compared to the early onset SPE group,the expression levels of CD44(0.65±0.17 vs 0.42±0.11)and CD24(0.77±0.23 vs 0.58±0.13)mRNA in placental tissue of late onset SPE were higher,and the differences were statistically significant(t=7.830,4.932,P＜0.05).Compared with the control group,the BMI,systolic blood pressure,diastolic blood pressure,urinary protein,Cr,LDH and BUN were significantly increased in SPE group(t=5.360～30.241,all P＜0.05).In SPE group,the gestational age was earlier,the MPV and ALB were lower,the newborn's birth length was shorter,and the body weight than control group,the differences were statistically great(t=3.232～11.109,all P＜0.05).The expression of CD44 and CD24 in SPE placenta was positively correlated(r=0.698,P＜0.05),the expression of CD44 in SPE placenta was positively correlated with CD24,gestational week of delivery,MPV and neonatal birth length(r=0.611,0.639,0.612,0.465,all P＜0.05),and was negatively correlated with systolic blood pressure,urinary protein and LDH(r=-0.604,-0.569,-0.593,all P＜0.05).The expression of CD24 was positively correlated with gestational age,MPV and newborn birth length(r=0.605,0.584,0.640,all P＜0.05),and was negatively correlated with systolic blood pressure,urinary protein and LDH(r=-0.637,-0.593,-0.561,all P＜0.05).The results of logistic regression analysis showed that MPV(95％CI:1.429～4.350),urinary protein(95％CI:1.529～2.709),and LDH(95％CI:1.425～3.932)were all independent risk factors for SPE(all P＜0.05).High levels of CD44(95％CI:0.561～0.940)and CD24(95％CI:0.495～0.814)were independent protective factors for SPE(P＜0.05).Conclusion The low expression levels of CD44 and CD24 in placenta of SPE patients are independent protective factors of SPE,which can provide direction for the follow-up treatment of SPE.

Objective To construct the theoretical framework of rehabilitation big data based on International Classification of Func-tioning,Disability and Health(ICF). Methods Drawing upon international rehabilitation policy documents,such as the World Health Organization's Rehabili-tation in health systems;Rehabilitation in health systems:guide for action;Rehabilitation indicator menu:a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation(FRAME);Template for Rehabilita-tion Information Collection(TRIC):a tool accompanying the Systematic Assessment of Rehabilitation Situation(STARS);and Framework and Standards for Country Health Information Systems;this study examined the com-position and function of rehabilitation big data.The content structure of the rehabilitation big data domain was an-alyzed using the World Health Organization Family of International Classifications(WHO-FICs).Furthermore,the generation patterns of rehabilitation big data was constructed drawing on the Health Metrics Network and big data hierarchical classification. Results Within the six primary elements of the health service system,the information system element was particularly significant,encompassing a substantial branch known as rehabilitation big data.There were three components of rehabilitation big data:health condition,health-related factors and health services.The content framework for this data was derived from the WHO-FICs framework,which covered three dimensions:health and function,dis-ease and function,and disease,function and intervention.A comprehensive model for generating and applying re-habilitation big data in rehabilitation services was developed in line with the requirements for constructing big da-ta architectures.The sources of this data included population censuses,social registration information,population surveys,resources,services and personal records.The result chain of rehabilitation big data encompassed five major processes:input,process,output,outcome and impact.The processing and utilization of this data involved collection,storage,management,analysis and application. Conclusion A theoretical framework for rehabilitation big data has been constructed based on the ICF theory.