1.Protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on a yorkshire model of brain injury after traumatic blood loss.
Xiang-Yu SONG ; Yang-Hui DONG ; Zhi-Bo JIA ; Lei-Jia CHEN ; Meng-Yi CUI ; Yan-Jun GUAN ; Bo-Yao YANG ; Si-Ce WANG ; Sheng-Feng CHEN ; Peng-Kai LI ; Heng CHEN ; Hao-Chen ZUO ; Zhan-Cheng YANG ; Wen-Jing XU ; Ya-Qun ZHAO ; Jiang PENG
Chinese Journal of Traumatology 2025;28(6):469-476
PURPOSE:
To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss.
METHODS:
This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA+, K+, and Ca2+ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance.
RESULTS:
The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA+ and K+ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca2+ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group.
CONCLUSIONS
Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals
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Perfusion/methods*
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Disease Models, Animal
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Brain Injuries/etiology*
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Swine
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Male
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Hypothermia, Induced/methods*
2.Association between maximal urethral length preservation and postoperative continence after robot-assisted radical prostatectomy: a meta-analysis and systematic review.
Tian-Yu XIONG ; Zhan-Liang LIU ; Hao-Yu WU ; Yun-Peng FAN ; Yi-Nong NIU
Asian Journal of Andrology 2025;27(2):225-230
Urinary incontinence is a common complication following robot-assisted radical prostatectomy (RARP). Urethral length has been identified as a factor affecting postoperative continence recovery. In this meta-analysis, we examined the association between use of the maximal urethral length preservation (MULP) technique and postoperative urinary continence in patients undergoing RARP. We conducted a comprehensive search of PubMed, Web of Science, Embase, and the Cochrane Library up to December 31, 2023. The quality of the literature was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis was performed to synthesize data and calculate the odds ratio (OR) from eligible studies on continence and MULP. Six studies involving 1869 patients met the eligibility criteria. MULP was positively associated with both early continence (1 month after RARP; Z = 3.62, P = 0.003, OR = 3.10, 95% confidence interval [CI]: 1.68-5.73) and late continence (12 months after RARP; Z = 2.34, P = 0.019, OR = 2.10, 95% CI: 1.13-3.90). Oncological outcomes indicated that MULP did not increase the overall positive surgical margin rate or the positive surgical margin status at the prostate apex (both P > 0.05). In conclusion, the use of the MULP technique in RARP significantly improved both early and late postoperative continence outcomes without compromising oncological outcomes.
Humans
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Prostatectomy/adverse effects*
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Robotic Surgical Procedures/methods*
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Male
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Urethra/surgery*
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Urinary Incontinence/prevention & control*
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Postoperative Complications/etiology*
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Prostatic Neoplasms/surgery*
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Organ Sparing Treatments/methods*
3.Chain mediating role of family care and emotional management between social support and anxiety in primary school students.
Zhan-Wen LI ; Jian-Hui WEI ; Ke-Bin CHEN ; Xiao-Rui RUAN ; Yu-Ting WEN ; Cheng-Lu ZHOU ; Jia-Peng TANG ; Ting-Ting WANG ; Ya-Qing TAN ; Jia-Bi QIN
Chinese Journal of Contemporary Pediatrics 2025;27(10):1176-1184
OBJECTIVES:
To investigate the chain mediating role of family care and emotional management in the relationship between social support and anxiety among rural primary school students.
METHODS:
A questionnaire survey was conducted among students in grades 4 to 6 from four counties in Hunan Province. Data were collected using the Social Support Rating Scale, Family Care Index Scale, Emotional Intelligence Scale, and Generalized Anxiety Disorder -7. Logistic regression analysis was used to explore the influencing factors of anxiety symptoms. Mediation analysis was conducted to assess the chain mediating effects of family care and emotional management between social support and anxiety.
RESULTS:
A total of 4 141 questionnaires were distributed, with 3 874 valid responses (effective response rate: 93.55%). The prevalence rate of anxiety symptoms among these students was 9.32% (95%CI: 8.40%-10.23%). Significant differences were observed in the prevalence rates of anxiety symptoms among groups with different levels of social support, family functioning, and emotional management ability (P<0.05). The total indirect effect of social support on anxiety symptoms via family care and emotional management was significant (β=-0.137, 95%CI: -0.167 to -0.109), and the direct effect of social support on anxiety symptoms remained significant (P<0.05). Family care and emotional management served as significant chain mediators in the relationship between social support and anxiety symptoms (β=-0.025,95%CI:-0.032 to -0.018), accounting for 14.5% of the total effect.
CONCLUSIONS
Social support can directly affect anxiety symptoms among rural primary school students and can also indirectly influence anxiety symptoms through the chain mediating effects of family care and emotional management. These findings provide scientific evidence for the prevention of anxiety in primary school students from multiple perspectives.
Humans
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Female
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Male
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Social Support
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Anxiety/etiology*
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Child
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Students/psychology*
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Emotions
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Logistic Models
4.The Sequential Mediating Roles of Body Pain and Self-Reported Health Status in the Relationship between Sleep Duration and Life Satisfaction.
Jia Feng LI ; Xue Wei FU ; Dan YANG ; Ye WANG ; Ting CHEN ; Yang PENG ; Feng Hao YANG ; Yu Chen ZHAN ; Yu WANG ; Xiang Dong TANG
Biomedical and Environmental Sciences 2025;38(1):47-55
OBJECTIVE:
This study examines the sequential mediating roles of body pain and self-reported health in the association between sleep duration and self-reported life satisfaction among elderly Chinese adults.
METHODS:
Data from the fifth wave of the China Health and Retirement Longitudinal Survey (CHARLS) were used to analyse the relationships between sleep duration and body pain, self-reported health, and life satisfaction through logistic regression and Restricted Cubic Spline (RCS) analyses. The sequential mediation effects of body pain and self-reported health status were examined via chain mediation analysis.
RESULTS:
Logistic regression analysis showed that sleeping fewer than 6 hours or 6-7 hours was linked to higher risks of body pain, poor health, and dissatisfaction with life compared to sleeping 7-8 hours (all P < 0.05). Additionally, those sleeping more than 9 hours also had increased risks of poor health and dissatisfaction with life compared to those sleeping 7-8 hours (all P < 0.05). Chain mediation analysis showed that body pain and self-reported health status sequentially mediated 46.15% of the association between sleep duration and life satisfaction.
CONCLUSION
Body pain and self-reported health may shape the relationship between sleep duration and life satisfaction in elderly Chinese adults.
Humans
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Male
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Female
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Aged
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Personal Satisfaction
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Sleep
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Health Status
;
Self Report
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China
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Middle Aged
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Longitudinal Studies
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Pain/psychology*
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Sleep Duration
5.Development of a prediction model for incidence of diabetic foot in patients with type 2 diabetes and its application based on a local health data platform
Yexian YU ; Meng ZHANG ; Xiaowei CHEN ; Lijia LIU ; Pei LI ; Houyu ZHAO ; Yexiang SUN ; Hongyu SUN ; Yumei SUN ; Xueyang LIU ; Hongbo LIN ; Peng SHEN ; Siyan ZHAN ; Feng SUN
Chinese Journal of Epidemiology 2024;45(7):997-1006
Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.
6.Development and application of a prediction model for incidence of diabetic retinopathy in newly diagnosed type 2 diabetic patients based on regional health data platform
Xiaowei CHEN ; Lijia LIU ; Yexian YU ; Meng ZHANG ; Pei LI ; Houyu ZHAO ; Yexiang SUN ; Hongyu SUN ; Yumei SUN ; Xueyang LIU ; Hongbo LIN ; Peng SHEN ; Siyan ZHAN ; Feng SUN
Chinese Journal of Epidemiology 2024;45(9):1283-1290
Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.
7.Development of a prediction model for the incidence of type 2 diabetic kidney disease and its application based on a regional health data platform
Lijia LIU ; Xiaowei CHEN ; Yexian YU ; Meng ZHANG ; Pei LI ; Houyu ZHAO ; Yexiang SUN ; Hongyu SUN ; Yumei SUN ; Xueyang LIU ; Hongbo LIN ; Peng SHEN ; Siyan ZHAN ; Feng SUN
Chinese Journal of Epidemiology 2024;45(10):1426-1432
Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.
8.Urine Metabolites Changes in Acute Myocardial Infarction Rats via Metabolomic Analysis
Nian-Nian CHEN ; Jiao-Fang YU ; Peng WU ; Li LUO ; Ya-Qin BAI ; Li-Kai WANG ; Xiao-Qian LI ; Zhan-Peng LI ; Cai-Rong GAO ; Xiang-Jie GUO
Journal of Forensic Medicine 2024;40(3):227-236
Objective To screen biomarkers for forensic identification of acute myocardial infarction (AMI) by non-targeted metabolomic studies on changes of urine metabolites in rats with AMI.Methods The rat models of the sham surgery group,AMI group and hyperlipidemia+acute myocardial infarction (HAMI) group were established.Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the changes of urine metabolic spectrometry in AMI rats.Principal compo-nent analysis,partial least squares-discriminant analysis,and orthogonal partial least squares-discriminant analysis were used to screen differential metabolites.The MetaboAnalyst database was used to analyze the metabolic pathway enrichment and access the predictive ability of differential metabolites.Results A total of 40 and 61 differential metabolites associated with AMI and HAMI were screened,respec-tively.Among them,22 metabolites were common in both rat models.These small metabolites were mainly concentrated in the niacin and nicotinamide metabolic pathways.Within the 95% confidence in-terval,the area under the curve (AUC) values of receiver operator characteristic curve for N8-acetyl-spermidine,3-methylhistamine,and thymine were greater than 0.95.Conclusion N8-acetylspermidine,3-methylhistamine,and thymine can be used as potential biomarkers for AMI diagnosis,and abnormal metabolism in niacin and nicotinamide may be the main causes of AMI.This study can provide reference for the mechanism and causes of AMI identification.
9.Recent advances in drug screening methods of SARS-CoV-2 spike protein
Li-de HU ; Chuan-feng LIU ; Ping LI ; Guan-yu DONG ; Xin-yong LIU ; Peng ZHAN
Acta Pharmaceutica Sinica 2024;59(2):298-312
The pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious impact on global public health and the economy. SARS-CoV-2 infiltrates host cells
10.Two cases of neonatal Legionella pneumonia
Yin-Zhi LIU ; Rong ZHANG ; Jing-Jing XIE ; Qiong GUO ; Cai-Xia ZHAN ; Meng-Yu CHEN ; Jun-Shuai LI ; Xiao-Ming PENG
Chinese Journal of Contemporary Pediatrics 2024;26(9):986-988
Patient 1,a 12-day-old female infant,presented with fever,cough,dyspnea,and elevated infection markers,requiring respiratory support.Metagenomic next-generation sequencing(mNGS)of blood and bronchoalveolar lavage fluid revealed Legionella pneumophila(LP),leading to diagnoses of LP pneumonia and LP sepsis.The patient was treated with erythromycin for 15 days and azithromycin for 5 days,resulting in recovery and discharge.Patient 2,an 11-day-old female infant,presented with dyspnea,fever,elevated infection markers,and multiple organ dysfunction,requiring mechanical ventilation.mNGS of blood and cerebrospinal fluid indicated LP,leading to diagnoses of LP pneumonia,LP sepsis,and LP intracranial infection.The patient was treated with erythromycin for 19 days and was discharged after recovery.Neonatal LP pneumonia lacks specific clinical symptoms,and azithromycin is the preferred antimicrobial agent.The use of mNGS can provide early and definitive diagnosis for severe neonatal pneumonia of unknown origin.

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