Objective: To investigate the association between sleep duration and depressive symptoms in children and adolescents, so as to provide scientific evidence for promoting mental health and preventing depression among relevant populations. Methods: A total of 2 192 children and adolescents aged 10-17 years with complete data from the 2018 China Family Panel Studies Database were included. Eight item Center for Epidemiologic Studies Depressive Scale(CES-D8) was used to assess participants depressive levels, and sleep duration was assessed via questionnaire. Multivariate Logistic regression model was used to analyze the association between different sleep duration categories and depressive symptom occurrence among children and adolescents. A restricted cubic spline(RCS) model analyzed the dose response relationship between sleep duration and the risk of depressive symptoms occurrence and segmented Logistic regression models to identify dose response effects. Results: Among the surveyed children and adolescents, 524(23.91%) exhibited depressive symptoms. Compared to those with sufficient sleep, children aged 10-12 years had a higher risk of depressive symptoms on average per day( OR =1.66, 95% CI =1.19-2.33) and during weekdays( OR =1.76, 95% CI =1.26-2.46), as well as in adolescents aged 13-17 years on a daily basis( OR =1.40，95% CI =1.06-1.85) and during weekdays( OR = 1.48，95% CI =1.12-1.95), and excessive sleep in adolescents on rest days was also significantly associated with higher risk of depressive symptoms( OR =1.65，95% CI =1.11-2.43)(all P <0.05). RCS analysis results indicate that children s sleep duration exhibits a linear negative correlation with the risk of depressive symptoms(all P nonlinear >0.05), while adolescents sleep duration showed a U shaped association with depressive symptoms(all P nonlinear <0.05) on a daily basis, during weekdays and weekends, with potential threshold effects at 10.00, 9.88, and 9.60 hours, respectively. Conclusions Sleep duration among children and adolescents is associated with depressive symptoms, with notable age related differeneces. It is recommended to develop targeted age specific interventions to reduce the risk of depressive symptoms in children and adolescents.

Calcineurin inhibitor（CNI） is potent immunosuppressive agents and serve as cornerstone therapies in the treatment of organ transplantation and autoimmune diseases， with cyclosporine A and tacrolimus being the representative drugs. Long-term use of CNI can lead to drug-induced hyperglycemia， severely affecting patients’ prognosis. The pathogenesis involves multilevel pathological alterations： at the pancreatic β-cell level， CNI directly damage β-cell by inducing calcium overload， oxidative stress， and mitochondrial dysfunction， suppressing the expression of key insulin synthesis factors and promoting apoptosis； in peripheral tissues， CNI interfere with insulin receptor substrate phosphorylation and inhibit the phosphatidylinositol 3 kinase/protein kinase B signaling pathway， resulting in decreased glucose uptake and insulin resistance； additionally， CNI can also induce β-cell injury by suppressing the secretion and receptor signal transduction of glucagon-like peptide-1， as well as by activating the nuclear factor kappa B pathway to promote inflammatory responses. Clinical studies demonstrate that the incidence of CNI-associated hyperglycemia is closely related to drug type， dosage， and individual patient factors. For high-risk patients， dose adjustment of CNI， switching to agents with lower metabolic toxicity when necessary， and selection of appropriate glucose-lowering regimens based on glycemic levels are recommended. Future research should further elucidate the molecular mechanisms of CNI metabolic toxicity and optimize individualized pharmacotherapy strategies to improve long-term patient outcomes.

Objective To understand the status of body image disturbance and its influencing factors in patients with ankylosing spondylitis (AS), so as to provide a scientific basis for the clinical management of AS. Methods A total of 353 AS patients admitted from January 2022 to December 2024 were selected as research subjects. Chinese version of Body Image Disturbance Questionnaire (BIDQ) was used to investigate the body image disturbance in AS patients. Single factor analysis was performed by t test and analysis of variance, and multiple factors were analyzed by multivariate linear regression. Results The total score of BIDQ in 342 AS patients was (25.01±4.22). Multivariate linear regression analysis results showed that self-paid medical expense, nighttime VAS score and negative emotion PANAS score could positively predict body image disturbance in AS patients (standardized regression coefficient=0.413, 0.413, 0.460, P<0.05), and PSSS score, positive emotion PANAS score and exercise management CDSSM score could negatively predict body image disturbance (standardized regression coefficient=-0.245, -0.134, -0.247, P<0.05). Conclusion The body image disturbance in AS patients is worthy of clinical attention. Nighttime pain, negative emotion and self-paid medical treatment can increase the risk of body image disturbance. Positive emotion, social support and high self-management level of exercise behavior can reduce the formation of body image disturbance, which can provide new ideas for clinical management of AS patients.

Objective To explore the correlation between osteocalcin (OCN) and visceral fat area (VFA) in overweight/obese population. Methods The data of 297 overweight/obese people who underwent health examinations in Health Management Department of Second Affiliated Hospital of Xi'an Jiaotong University from August 2021 to August 2024 were analyzed. According to the VFA value measured by InBody, the subjects were divided into an excessive group (VFA ≥100 cm²) and a normal group (VFA<100 cm2). The baseline data, glucose metabolism indicators, lipid metabolism indicators and OCN were compared between the two groups. Binary logistic regression analysis was used to analyze the independent risk factors affecting visceral fat deposition in overweight/obese people. Results According to the VFA value, there were 193 cases (64.98%) in the excessive group and 104 cases (35.02%) in the normal group. There were no statistical differences in gender, age and comorbidities between the two groups (P>0.05). The BMI, FPG, HbA1c, TC, TG, and LDL-C in the excessive group were higher than those in the normal group, while the HDL-C and OCN were lower than those in the normal group (P<0.05). Binary logistic regression analysis revealed that BMI, FPG, HbA1c, TC, TG and LDL-C were independent risk factors for visceral fat deposition in overweight/obese people, while HDL-C and OCN were protective factors (P<0.05). Conclusion Visceral fat deposition in overweight/obese people is closely related to OCN content, and is affected by abnormal glucolipid metabolism, which provides new ideas for the prevention and treatment of obesity-related diseases.

Objective: To evaluate the accuracy of body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR) in screening true obesity among children, so as to provide a scientific basis for precise screening and early prevention and control of childhood obesity. Methods: A total of 1 322 children aged 10-15 years old were surveyed by the Huantai Children Cardiovascular Health Cohort in 2021. Fat mass percentage (FMP) and fat mass index (FMI) were measured by bioelectrical impedance analysis, with FMP or FMI values at or above the age and sex-specific 70th percentiles as the criteria for defining true obesity. BMI, WC and WHtR were used to define general obesity and central obesity. The accuracy of these measures in screening for true obesity was evaluated by calculating the missed diagnosis rate, misdiagnosis rate, area under the curve(AUC) for receiver operating characteristic and Kappa coefficient. Results: Boys had higher BMI [(21.79±4.56) kg/m 2], WC [(76.41±12.53) cm] and WHtR (0.47±0.07) than girls [(20.83±4.13) kg/m 2, (70.69±10.06) cm, (0.45±0.06)] ( t =4.02, 9.19, 6.63), while boys had lower FMP [(18.29±8.35)%] and FMI [(4.35±2.79) kg/m 2] than girls [(24.87±6.51)%, (5.44±2.53) kg/m 2] ( t =-16.10,-7.42) ( P <0.01). Using FMP as a reference standard, the diagnosis error rates of screening for true obesity based on BMI, WC and WHtR were 12.24%, 2.11% and 2.11%, respectively; the diagnosis error rates were 10.88%, 27.28% and 24.33%; the AUC values were 0.88, 0.85 and 0.87; the Kappa coefficients were 0.67, 0.48 and 0.52. Using FMI as a reference standard, rates of BMI, WC and WHtR screening for true obesity were 14.20%, 1.23% and 2.78%; the diagnosis error rates were 4.81%, 20.84% and 18.14 %; the AUC values were 0.90, 0.89 and 0.90; the Kappa coefficients were 0.81, 0.64 and 0.67. Conclusions BMI has a higher diagnosis error rate in screening for true obesity in children, while WC and WHtR have higher diagnosis error rates. It is recommended to promote body fat assessment in clinical practice, so as to achieve more accurate prevention and control of chronic diseases.

Objective: To examine the association of joint effect of overweight and obesity with dyslipidemia on left ventricular hypertrophy (LVH) in children, so as to provide scientific evidence for the prevention of early cardiovascular damage in children. Methods: Data were obtained from the second followup crosssectional survey of Huantai Childhood Cardiovascular Health Cohort study in 2021, comprising 1 047 children aged 10-15 years with complete information. Based on overweight and obesity status and dyslipidemia status, all participants were divided into four groups:normal weight with normal lipid levels, normal weight with dyslipidemia, overweight and obesity with normal lipid levels, and overweight and obesity with dyslipidemia. Left ventricular mass index (LVMI) levels and prevalence of LVH across four groups were compared. Multivariate Logistic regression model was used to examine the association of joint effect of overweight and obesity with dyslipidemia on LVH in children. Results: There were significant differences in LVMI levels [(28.66±7.10, 29.63±4.71,31.49±5.86,32.65±4.80)g/m2.7] and prevalence of LVH (4.28%, 12.50%, 22.74%, 31.30%) across four groups (F/χ2=50.76, 90.92, P<0.05). After adjustment for confounding variables such as gender,age,screen time,sleep duration,fruit and vegetable intake,carbonated beverage consumption,physical activity and elevated blood pressure, compared to children with both normal weight and normal lipid levels, the risk of LVH in children with dyslipidemia alone increased (OR=3.27, 95%CI=1.57-6.82，P<0.05). Children with overweight and obesity alone also had a significantly increased risk of LVH (OR=6.33, 95%CI=3.76-10.66), and the highest risk was observed in those with both overweight and obesity with dyslipidemia (OR=9.66, 95%CI=5.35-17.43) (P<0.05). Conclusions The joint effect of overweight and obesity with dyslipidemia is positively correlated with LVH in children. To prevent LVH in children, both overweight and obesity with dyslipidemia should be paid attention to.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Objective To understand the sleep status in patients with Parkinson's disease (PD), and to explore its relationship with dyskinesia and negative emotions. Methods A total of 308 patients with PD who met the inclusion and exclusion criteria in the hospital from September 2022 to May 2024 were selected as the research subjects. The scores of sleep status [Pittsburgh Sleep Quality Index (PSQI)], dyskinesia [Simplified Fugl-Meyer Motor Assessment (FMA)] and negative emotions [Beck Anxiety Inventory (BAI), Beck Depression Inventory-II (BDI-II)] were analyzed, and the PSQI score was compared among patients with different demographic characteristics. Pearson correlation analysis was performed to analyze the correlation of sleep with dyskinesia and negative emotions in patients with PD. Results The total score of PSQI scale was (6.16±0.97) points in 308 PD patients, of which 208 cases (67.53%) were complicated with sleep disorders. The proportions of female, 61-75 years old, technical secondary school or below, disease course of 4 years and above, Hoehn-Yahr stage IV and unmarried status in the sleep disorder group were higher than those in the non-sleep disorder group (P<0.05). Compared with the non-sleep disorder group, the FMA score in the sleep disorder group was lower (P<0.05) while the BAI score and BDI-II score were higher (P<0.05). Pearson correlation analysis revealed that PSQI was negatively correlated with FMA (r=-0.489, P<0.05), and was positively correlated with BAI and BDI-II (r=0.476, 0.502, P<0.05). Conclusion The incidence rate of sleep disorders in PD patients is high. PSQI is negatively correlated with FMA, and is positively correlated with BAI and BDI-II.

Objective: To investigate the relationship between serum alanine transaminase (ALT) and carotid intima media thickness (cIMT) in adolescents, providing evidence for early prevention and control strategies for cardiovascular structural abnormalities in adolescents. Methods: Data were obtained from the third follow up survey (from October to November 2023) of the "Huantai Children Cardiovascular Health Cohort", including 1 153 healthy adolescents with complete information. Analysis of variance (ANOVA) was used to compare cIMT across different ALT level groups, and multiple linear regression was employed to analyze the relationship between serum ALT levels and cIMT. Results: Significant differences in cIMT were observed among Q 1, Q 2, and Q 3 ALT level groups [(0.56±0.04) (0.57±0.04) (0.59±0.04)mm, respectively; F=3.61, P <0.01]. After adjusting for covariates, multiple linear regression revealed a positive correlation between ALT levels and cIMT ( β=0.18, P <0.01). Gender subgroup analysis showed similar results in males ( β=0.19, P <0.01), but no statistically significant association was found in females ( β=0.07, P = 0.54). Conclusions Elevated serum ALT levels are associated with an increased risk of vascular structural damage in adolescents, especially in boys. Early detection and control of abnormal serum ALT levels can help to reduce early vascular structural damage and further reduce the risk of adverse cardiovascular events.