Chronic lung allograft dysfunction (CLAD) is a common complication after lung transplantation, which severely impairs the long-term survival of patients. At present, effective therapeutic approaches remain lacking. Dysregulation of the lung microbiome acts as a pathogenic factor for a variety of pulmonary diseases. Accumulating studies have demonstrated that the compositional characteristics of the lung microbiome after lung transplantation are closely associated with CLAD. Therefore, this article reviews the definition of CLAD, characteristics of the lung microbiome, the influence of the lung microbiome on the occurrence and progression of CLAD, the potential mechanisms underlying the lung microbiome in the pathogenesis of CLAD, and microbiome-based intervention strategies for CLAD. It aims to provide novel insights for the prevention and treatment of CLAD following lung transplantation and further improve the prognosis of lung transplant recipients.

Objective:To explore the relationship between obesity indicators and DNA methylation clocks acceleration,and to analyze their temporal sequence.Methods:Data were obtained from two sur-veys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry.Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip.DNA methylation clocks/acceleration metrics(GrimAA,PCGrimAA and Dunedin-PACE)were calculated using the DNA methylation online tool(https://dnamage.genetics.ucla.edu/)or R code provided by researchers.Obesity indicators included weight,body mass index(BMI),waist circumference,waist-hip ratio,and waist-height ratio.A total of 1 070 twin individuals were included in the cross-sectional analysis,comprising 378 monozygotic(MZ)twin pairs and 155 dizygotic(DZ)twin pairs for within-pair analysis.Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks,as well as their acceleration measures.The longitudinal analysis included 314 twin individuals,comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analy-sis.Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators.All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.Results:In the cross-sectional analysis population,monozygotic twins accounted for 71.0％,males for 68.0％,and the mean chronological age was(49.9±12.1)years.In the longitudinal analysis population,monozygotic twins accounted for 60.5％,males for 60.8％,with a mean baseline chronological age of(50.4±10.2)years and a mean follow-up duration of(4.6±0.6)years.Except for the waist-to-hip ratio,which was significantly higher at follow-up com-pared with baseline,no statistically significant differences were observed in the means of other obesity in-dicators between baseline and follow-up.Correlation analysis revealed that weight,BMI,waist circumfe-rence,waist-hip ratio(WHR),and waist-height ratio(WHtR)were positively correlated with Dunedin-PACE in all the twins,with WHtR showing the strongest association(β=0.21,95％CI:0.11 to 0.31).Weight and BMI were negatively associated with GrimAA(β=-0.03,95％CI:-0.05 to-0.01;β=-0.07,95％CI:-0.12 to-0.02),while weight was negatively associated with PCGrim-AA(β=-0.02,95％CI:-0.03 to 0.00).However,within-twin-pair analyses showed no statistically significant correlations.Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up,while elevated baseline weight,BMI,and waist circumference might increase PCGrimAA.Higher baseline WHR was associated with increased DunedinPACE at follow-up.Conclusion:Obesity indicators correlate with DNA methylation clock acceleration metrics.Baseline obesity may influence changes in certain DNA methylation clock indicators over time,suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging.However,these associations may be confounded by shared genetic or environmental factors among the twins.

Objective To explore the risk factors for healthcare-associated infection(HAI)in lung transplant re-cipients(LTRs),and construct a predictive nomogram model.Methods Clinical data of patients who underwent lung transplant in Wuxi People's Hospital from January 2019 to December 2023 were analyzed retrospectively.The patients were divided into a training set(n=506)and a validation set(n=218).Independent risk factors were screened through LASSO regression,and multivariate logistic regression was included to construct a nomogram pre-diction model.The discrimination,calibration,and clinical applicability of the model were evaluated using receiver operating characteristic(ROC)curves,Hosmer-Lemeshow goodness-of-fit,and decision curves.Results Among the 506 LTRs,201 developed HAIs,with an incidence of 39.72％.The major infection site was lower respiratory tract,and the major pathogen were Gram-negative bacilli(Acinetobacter baumannii).Older age,use of extracorpo-real membrane oxygenation(ECMO),double-lung transplant,surgery duration＞3 hours,long duration of contin-uous fever,frequent abnormal blood routine examination,and long duration of combined use of antimicrobial agents were identified as independent risk factors for HAI after lung transplant.The ROC curve analysis results showed that the areas under the curve(AUCs)of the training set and the validation set were 0.74(95％CI:0.70-0.78)and 0.71(95％CI:0.64-0.78),respectively.The Hosmer-Lemeshow test results showed that there was no sta-tistically significant difference between the predictive and actual probability of HAI(P＞0.05).The clinical decision curve results indicated that the model had clinical benefits at a threshold probability value of 7％-71％.Conclusion The nomogram prediction model constructed in this study can effectively evaluate the risk of postoperative infection in LTRs.The model is stable and has high clinical application value,providing scientific reference for postoperative infection prevention and control.

Objective:To investigate the incidence, risk factors, and outcomes of falls among the elderly community population in Beijing.Methods:A cross-sectional survey was conducted using stratified multistage random sampling to select urban and rural residents aged 65 years and older in Beijing. Mortality data was collected after the baseline survey for 5 years. The incidence of falls was weighted based on the composition ratios of age and gender from the 2010 Nation-wide Population Census of Beijing. A logistic regression model was used to analyze the impacts of demographic sociology of common chronic diseases on fall occurrence. The Cox proportional hazards regression model was used to analyze the fall and 5-year survival association.Results:A total of 2 968 participants completed the questionnaire, at cross-sectional survey, with an average age of (73.2±6.0) years, and 1 581 (53.8%) participants were female. Three hundred and sixty-one individuals experienced a fall within the past year. Among those who fell, 64 (17.7%) fell twice, and 95 (26.6%) fell three or more times. Of them, 14.4% (52) had post-fall fractures, with the wrist, knee, and hip being the most common fracture sites, accounting for 25.0%, 17.3%, and 15.4%, respectively. The weighted fall incidence was 12.4% (95% CI: 11.2%-13.5%). Aging, being female, and living in rural areas were more likely to fall. Logistic regression analysis showed that after adjusting for age, gender, and urban-rural status, the risk of falls for those living alone ( OR=1.48, 95% CI: 1.08-2.04) or living with children/grandchildren ( OR=1.51, 95% CI: 1.15-1.97) were significantly higher than those living with their spouse. In addition, the risk of falls was elevated significantly among the elderly with hypertension, diabetes, stroke, dementia, depression status, urinary incontinence, arthritis, insomnia, vision, and hearing loss, dependence on activities of daily living (ADL), general and poor self-rated health (SRH). The Cox proportional hazard regression model revealed that the 5-year risk of death increased by 65% ( HR=1.65, 95% CI: 1.29-2.11) for those who experienced a fall, which increased with fall frequency. This elevated risk persisted after adjusting for chronic conditions, ADL, and SRH. Conclusions:Ageing, female, living in rural regions, having common chronic diseases, dependence on ADL, general and poor SRH, living alone or living with children/grandchildren were associated with the elevated fall risk. The occurrence of fall was seasonal. The most common short-term adverse consequence after a fall was fractures, while the long-term effect was an increased risk of death.

Lung transplantation is an effective treatment for various end-stage lung diseases. Optimizing perioperative fluid management can reduce the incidence of postoperative pulmonary edema and improve the prognosis of lung transplant recipients. Excessive fluid administration may lead to pulmonary edema, ischemia-reperfusion injury of the transplant lung, and increased cardiac burden, which can induce heart failure. On the other hand, overly strict fluid restriction may lead to hypovolemia, affecting tissue perfusion and causing organ dysfunction. Therefore, precise regulation of fluid balance is crucial for the postoperative recovery of lung transplant recipients. This article reviews the physiological characteristics of lung transplant recipients, types of infused fluids, fluid therapy regimens, and hemodynamic monitoring, aiming to elucidate the particularities of perioperative fluid management in lung transplantation and provide new ideas and directions for individualized fluid management.

Objective To analyze the characteristics of postoperative hospital-acquired infections and drug sensitivity in lung transplant recipients over the past 5 years in a single center. Methods A total of 724 lung transplant recipients at Wuxi People's Hospital from January 2019 to December 2023 were selected. Based on the principles of hospital-acquired infection diagnosis, a retrospective analysis was conducted on the hospital infection situation and infection sites of lung transplant recipients, and an analysis of the distribution of hospital-acquired infection pathogens and their antimicrobial susceptibility test status was performed. Results Among the 724 lung transplant recipients, 275 cases of hospital-acquired infection occurred, with an infection rate of 38.0%. The case-time infection rate decreased from 54.2% in 2019 to 22.8% in 2023, showing a downward trend year by year (Z=30.98, P<0.001). The main infection site was the lower respiratory tract, accounting for 73.6%. The pathogens were mainly Gram-negative bacteria, with the top four being Acinetobacter baumannii (37.1%), Pseudomonas aeruginosa (17.3%), Klebsiella pneumoniae (13.7%), and Stenotrophomonas maltophilia (13.4%), with imipenem resistance rates of 89%, 53%, 58% and 100%, respectively. Gram-positive bacteria were mainly Staphylococcus aureus (3.6%), with a methicillin resistance rate of 67%. Conclusions Over the past 5 years, the hospital-acquired infections in lung transplant recipients have shown a downward trend, mainly involving lower respiratory tract infections, with the main pathogens being Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae, all of which have high resistance rates to imipenem.

Objective To explore the risk factors for healthcare-associated infection(HAI)in lung transplant re-cipients(LTRs),and construct a predictive nomogram model.Methods Clinical data of patients who underwent lung transplant in Wuxi People's Hospital from January 2019 to December 2023 were analyzed retrospectively.The patients were divided into a training set(n=506)and a validation set(n=218).Independent risk factors were screened through LASSO regression,and multivariate logistic regression was included to construct a nomogram pre-diction model.The discrimination,calibration,and clinical applicability of the model were evaluated using receiver operating characteristic(ROC)curves,Hosmer-Lemeshow goodness-of-fit,and decision curves.Results Among the 506 LTRs,201 developed HAIs,with an incidence of 39.72％.The major infection site was lower respiratory tract,and the major pathogen were Gram-negative bacilli(Acinetobacter baumannii).Older age,use of extracorpo-real membrane oxygenation(ECMO),double-lung transplant,surgery duration＞3 hours,long duration of contin-uous fever,frequent abnormal blood routine examination,and long duration of combined use of antimicrobial agents were identified as independent risk factors for HAI after lung transplant.The ROC curve analysis results showed that the areas under the curve(AUCs)of the training set and the validation set were 0.74(95％CI:0.70-0.78)and 0.71(95％CI:0.64-0.78),respectively.The Hosmer-Lemeshow test results showed that there was no sta-tistically significant difference between the predictive and actual probability of HAI(P＞0.05).The clinical decision curve results indicated that the model had clinical benefits at a threshold probability value of 7％-71％.Conclusion The nomogram prediction model constructed in this study can effectively evaluate the risk of postoperative infection in LTRs.The model is stable and has high clinical application value,providing scientific reference for postoperative infection prevention and control.

Lung transplantation is the only effective treatment for end-stage lung disease. Acute kidney injury is a common complication after lung transplantation, which is related to the occurrence of chronic kidney disease and increased postoperative fatality. The factors and mechanisms affecting the occurrence of acute kidney injury are very complex. Clinically, it has been found that various risk factors during the perioperative period of lung transplantation may lead to the occurrence of acute kidney injury, including preoperative, intraoperative and postoperative factors. Early diagnosis of acute kidney injury after lung transplantation and timely intervention are of great significance to improving patient prognosis. Therefore, this article reviews the definition of acute kidney injury, non-invasive assessment, risk factors, prognosis, and clinical management of acute kidney injury after lung transplantation, aiming to provide a reference for the diagnosis and treatment of acute kidney injury after lung transplantation in clinical practice and to improve the survival rate of lung transplant recipients.

Arthritis, encompassing osteoarthritis (OA), rheumatoid arthritis (RA), and gouty arthritis (GA), is a prevalent inflammatory disease that significantly impacts quality of life. Natural products (NPs), derived from animals, plants, marine organisms, and microorganisms, have demonstrated beneficial effects in arthritis treatment both domestically and internationally. These natural compounds offer advantages in drug discovery due to their skeletal diversity, structural complexity, and multi-effect, multi-target, and low-toxicity properties compared to conventional small-molecule medicines. However, unclear mechanisms have hindered the development and clinical application of NPs. This review summarizes recent experimental studies from the past decade on natural medicine for arthritis treatment, emphasizing key NPs with therapeutic effects on OA, RA, and GA. It examines the effects and molecular mechanisms of NPs acting on different cells to treat arthritis. Furthermore, this review provides insights into the future prospects of NP research in this field, which is crucial for advancing NP-based arthritis treatments.
Humans ; Biological Products/therapeutic use* ; Animals ; Arthritis, Rheumatoid/drug therapy* ; Arthritis, Gouty/drug therapy* ; Arthritis/drug therapy* ; Osteoarthritis/drug therapy*

Lung transplantation is the ultimate therapeutic option for end-stage pulmonary diseases such as interstitial pneumonia, chronic obstructive pulmonary disease and pneumoconiosis. Currently, the shortage of allogeneic lung donors significantly limits the opportunity for end-stage lung disease patients to receive lung transplantation. In recent years, with the rapid development of biomedical engineering technologies, especially the major breakthroughs in genetic modification and cloning, xenogeneic lung transplantation has shown important potential for clinical translation. Among them, genetically modified pigs have become the most promising xenogeneic lung source due to the close similarity of organ size and physiological characteristics to humans, and the ability to perform targeted gene knockouts (such as α-Gal antigen knockout) to reduce the occurrence of hyperacute rejection. This article focuses on the research progress of porcine xenogeneic lung transplantation, systematically reviews the latest achievements and challenges in animal experiments and human trials, and introduces the technical experience accumulated by Shenzhen Third People's Hospital in the porcine-to-monkey xenogeneic lung transplantation model, in the hope of providing practical references for future research in this field.