Liquid-liquid phase separation is an important process in which intracellular biomolecules condense to form membraneless organelles,playing a significant role in cell signaling and gene expression regulation.Studies have shown that liquid-liquid phase separation may be involved in the occurrence and development of atherosclerosis and has po-tential applications in the diagnosis and treatment of the disease.This article introduces the concept and mechanism of liquid-liquid phase separation,delves into the relationship between liquid-liquid phase separation and atherosclerosis,sum-marizes the progress of liquid-liquid phase separation in atherosclerosis research,and looks forward to its application pros-pects.

Liquid-liquid phase separation is an important process in which intracellular biomolecules condense to form membraneless organelles,playing a significant role in cell signaling and gene expression regulation.Studies have shown that liquid-liquid phase separation may be involved in the occurrence and development of atherosclerosis and has po-tential applications in the diagnosis and treatment of the disease.This article introduces the concept and mechanism of liquid-liquid phase separation,delves into the relationship between liquid-liquid phase separation and atherosclerosis,sum-marizes the progress of liquid-liquid phase separation in atherosclerosis research,and looks forward to its application pros-pects.

Objective To explore the effect of exposure to noise of 3.0T magnetic resonance imaging(MRI)on children's cochlear function.Methods We prospectively recruited 72 children who underwent cranial MRI examination at our hospital from May to November 2018;3M earplugs and sponge mats were used for hearing protection during MRI scanning.Noise level(dBA)of each MRI sequence was detected with a nonmagnetic microphone and a sound level meter.Distortion product otoacoustic emissions(DPOAE)test at 2-7 kHz was performed 24 hours before and 30 minutes after the MRI examination.Paired t-test or Wilcoxon signed-rank test was used to analyze differences in DPOAE amplitude before and after the MRI examination.Results The average noise level of MRI measured in the study was(107.7±3.92)dBA.Compared with that before the MRI examination,the DPOAE amplitude(dB)changed little after the MRI examination;the range of amplitude differences in each age group was as follows:left ear(-0.24-1.10)and right ear(-0.24-0.74)in the 0-1 year-old group;left ear(-0.07-0.59)and right ear(-0.57-0.75)in the 2-5 year-old group;left ear(-0.36-0.44)and right ear(-0.30-0.57)in the 6-12 year-old group.No statistically significant difference was found(correction P＞0.05).Conclusion No potential impact of 3.0T MRI noise on children's cochlear function was observed under routine hearing protection.

【Objective】 To estimate the prevalence, associated factors and patterns of multimorbidity of non-communicable diseases among adults in Shaanxi Province so as to provide evidence for the prevention and control of non-communicable diseases. 【Methods】 We used the data of adults aged 18 years and older collected in the baseline survey of Shaanxi Project in the Regional Ethnic Cohort Study in Northwest China. Multinomial logistic regression was used to explore the associated factors for multimorbidity. Exploratory factor analysis was used to extract patterns of multimorbidity. 【Results】 The prevalence of multimorbidity was 10.7% among the 44 442 participants. Age increase, being males, urban residence, and being overweight or obesity were positively associated with multimorbidity. Compared with women, men had a higher risk of multimorbidity. The OR and 95% CI was 1.25 (1.12-1.39). The risk of multimorbidity increased with age among adults. Compared with participants aged 18.0-34.9 years, the ORs and 95% CIs of those aged 35.0-44.9, 45.0-54.9, 55.0-64.9, and ≥65.0 years were 4.73 (3.47-6.46), 15.61 (11.60-21.00), 41.39 (30.76-55.70) and 90.04 (66.58-121.77), respectively. The primary multimorbidity patterns among adults in Shaanxi were cardiovascular-metabolic multimorbidity (5.4%), viscero-articular multimorbidity (1.0%), and respiratory multimorbidity (0.3%). 【Conclusion】 More than one in ten adults in Shaanxi Province had multimorbidity, and the predominant pattern of multimorbidity was cardiovascular-metabolic multimorbidity. The prevention and control of non-communicable diseases should be reinforced in middle-aged and older people, males, people living in the urban, and overweight or obese people. More attention should be paid to the prevention and control of cardiovascular-metabolic diseases.

【Objective】 To evaluate the dietary quality with the dietary balance index (DBI_16) and the association between dietary quality and bone mass among middle-aged and elderly people in Gansu Province so as to provide evidence for improving dietary quality and bone health status of Gansu population. 【Methods】 Based on the information of the type and quantity of food intake and the bone mass of middle-aged and elderly people aged 35 years and above collected by the Gansu Project in the Regional Ethnic Cohort Study in Northwest China, DBI_16 was used to evaluate the intake level of cereals, vegetables, fruits, milk, beans, fish and shrimp, eggs and other foods, and the degree of inadequate, excessive and unbalanced dietary intake of the participants. Multiple linear regression was used to evaluate the associations of three component indexes of DBI_16, high bound score (DBI_HBS), low bound score (DBI_LBS), diet quality distance (DBI_DQD), and seven single indexes of DBI_16 with bone mass. 【Results】 Analyses of the dietary and bone mass data of 11,840 participants showed that 44.8% of participants consumed excessive amounts of cereals compared to the dietary recommendation. 96.3%, 90.6%, 90.1%, 71.9%, 95.1% and 60.3% of participants’ intake of vegetables, fruits, milk, soybeans, fish and shrimp, and eggs, respectively, were inadequate. 47.7% participants consumed less than 10 types of food. 2.3% participants’ DBI_LBS levels were appropriate. 54.7% participants’ DBI_HBS levels were appropriate. Only 1.2% participants’ DBI_DQD reached a balanced level. The bone mass level in the study population was (2.5±0.6) kg [(2.8±0.5) kg for men and (2.3±0.5) kg for women]. After adjusting for sociodemographic characteristics, lifestyle, total dietary energy intake and body mass index, DBI_LBS and DBI_DQD were negatively associated with bone mass [β and 95% CI was -0.002 01 (-0.003 62--0.000 40) and -0.001 76 (-0.003 09--0.000 43), respectively]. 【Conclusion】 Dietary intake imbalance is common among middle-aged and elderly people in Gansu Province, and the more severe the dietary intake imbalance, the lower the bone mass level.

【Objective】 To explore the dynamic change of depression in diabetic patients so as to provide evidence for early detection and warning of psychological problems in diabetic patients. 【Methods】 Based on the data from the China Health and Retirement Longitudinal Study （CHARLS）， the propensity score matching method was used to eliminate confounding factors in the study. The linear growth model， the nonlinear quadratic growth model， and the growth model without defined curve type were fitted respectively. According to the fitting indices of the models， the optimal solution of the growth function was determined to explore the changes of depression development in the diabetic patients. 【Results】 A total of 5 711 cases （5 380 cases in the non-diabetic group and 331 cases in the diabetic group） were included in the study. After propensity score matching， 1 621 cases （1 291 cases in the non-diabetic group and 330 cases in the diabetic group） were included and all confounding factors were balanced between the two groups. By fitting three growth curve models with latent variables， the results showed that the model without defined curve type was better than the other two models. The mean depression score for initial status in the non-diabetic and diabetic groups was 9.640 and 10.097， respectively， with significant inter-individual differences. During the follow-up period， the depression status of both groups showed a trend of decrease first and then increase， but the depression score was always lower in the non-diabetic group than in the diabetic group. At the same time， there was no individual difference in the rate of change between the two groups， and there was no statistical difference between the initial depression score and the subsequent slope of change. 【Conclusion】 Exploring the change track of depression status over time in diabetic patients， understanding the individual psychological change trend and further explaining the differences between individuals are of great significance for intervention on psychological status at different stages.

【Objective】 To compare the ability of body mass index （BMI）， body fat percentage （BFP）， waist circumference （WC）， waist-to-height ratio （WHtR）， visceral fat index （VFI） and the combinations of two kinds of obesity indices to predict the risk of hypertension. 【Methods】 Data collected in the baseline survey of “Gansu Province’s Urban and Rural Natural Population Cohort Establishment and Tumor Follow-up Study” were analyzed. Area under the curve （AUC） of ROC curve with covariates was used to analyze and compare the effects of individual obesity evaluation index and the combination of two kinds of obesity indices in predicting the risk of hypertension. 【Results】 Analyses of data of 20，079 adults showed that the AUC of BMI， WC， WHtR， BFP and VFI was 0.636， 0.604， 0.615， 0.614 and 0.619， respectively. AUC of the combination of BMI and WC （0.643） was higher than that of BMI （0.636）； however， the change rate of AUC was only 1.09%. AUC of the combinations of WC， WHtR and VFI， the three central obesity evaluation indices， and BFP， a general obesity evaluation index， were lower than that of BMI. The optimal cutoff value for BMI was 24.2 kg/m². 【Conclusion】 The effect of BMI in predicting the risk of hypertension is better than that of BFP， WC， WHtR and VFI. The effects of the combinations of the two kinds of obesity evaluation indices are not better than that of BMI. To prevent and control hypertension， adults should keep their BMI under overweight.

Objective:Data being missed is an unavoidable problem in cohort studies. This paper compares the imputation effect of eight common missing data imputation methods involved in cutting longitudinal data through simulation study to provide a valuable reference for the treatment of missing data in longitudinal studies.Methods:The simulation study is based on R language software and generates missing longitudinal data by the Monte Carlo method. By comparing the average absolute deviation, average relative deviation, and TypeⅠerror from the regression analysis of different imputation methods, the imputation effect of varying imputation methods on missing longitudinal data and the influence on subsequent multivariate analysis are evaluated.Results:The mean imputation, k nearest neighbor (KNN), regression imputation, and random forest all have a similar imputation effect, which is also steady. However, the hot deck is inferior to the above imputation methods. K-means clustering and expectation maximization (EM) algorithm are among the worst and unstable. Mean imputation, EM algorithm, random forest, KNN, and regression imputation can control TypeⅠerror. Still, multiple imputations, hot deck, and K-means clustering cannot effectively manage the TypeⅠerror.Conclusions:For missing data in longitudinal studies, mean imputation, KNN, regression imputation, and random forest can be used as better imputation methods under the mechanism of missing at random. When the missing ratio is not too large, multiple imputations and hot deck can also perform well, but K-means clustering and EM algorithm are not recommended.

【Objective】 To compare the performance of five commonly used variable selection methods in high-dimensional biomedical data variable screening so as to explore the effects of sample size and association among candidate variables on screening results and provide evidence for the development of variable selection strategy in high-dimensional biomedical data analysis. 【Methods】 Variable selection algorithms were implemented based on R-programming language. Monte Carlo method was used to simulate high-dimensional biomedical data under different conditions to evaluate and compare the performance of different variable selection methods. Variable selection performance was evaluated based on the true positive rate and true negative rate in screening. 【Results】 For specified high-dimensional data, the variable selection performance was improved for all the methods when sample size was increased, and the association between candidate variables did affect variable screening results. Simulation results indicated that the elastic network algorithm yielded the best screening performance, LASSO algorithm took the second place, and ridge algorithm did not work at all. 【Conclusion】 Elastic network algorithm is an ideal variable screening method for high-dimensional data variable screening.