BACKGROUND:Alzheimer's disease has been associated with sarcopenia,but a causal relationship has not been established.Exploring the causal relationship between the two most common disability-burdening diseases in the aging population-Alzheimer's disease and sarcopenia-and their potential mediating factors holds certain implications for further alleviating the healthcare costs and socioeconomic burden for older adults in China.OBJECTIVE:To explore the potential causal relationship between Alzheimer's disease and sarcopenia in the general population using a Mendelian randomization study and to explore the role of body mass index in this context.METHODS:Two-sample Mendelian randomization analysis based on published genome-wide association studies(GWAS)were used to infer causality,and univariate Mendelian randomization and mediation analyses were used in the study design.Through the Integrative Epidemiology Unit(IEU)database,ieu-b-2 was selected as the Alzheimer's disease dataset(sample size:63 926),ieu-b-4816 as the body mass index dataset(99 998),ebi-a-GCST90000027 as the appendicular lean mass dataset(244 730),ukb-b-7478 as the left hand grip strength dataset(461 026),ukb-b-10215 as the right hand grip strength dataset(461 089)and ukb-b-4711 as the walking pace dataset(459 915).Inverse-variance weighting was used as the primary analysis method,and the results were validated by pleiotropy and heterogeneity analysis.The Steiger Directionality Test was performed to validate the reasonableness of the causal direction.RESULTS AND CONCLUSION:(1)The Mendelian randomization analyses provided evidence that Alzheimer's disease predicted the risk of appendicular lean mass[odds ratio(OR)=1.009;95％confidence interval(Cl),1.001-1.017;P=0.023),and walking pace(OR=1.010;95％Cl,1.003-1.017;P=0.008).No correlation with hand grip strength was observed.(2)Alzheimer's disease was negatively correlated with body mass index(OR=0.893;95％Cl,0.811-0.984;P=0.022);body mass index was positively correlated with appendicular lean mass(OR=1.084;95％Cl,1.031-1.141;P=0.002)and negatively correlated with walking pace(OR=0.975;95％Cl,0.969-0.980;P＜0.001).(3)Mediation analyses showed that the causal relationship between Alzheimer's disease and appendicular lean mass and walking pace was partially mediated by body mass index,with the proportion of mediations being 50.25％and 32.11％,respectively.(4)The results of this study suggest that based on large-scale population studies,genetic prediction of Alzheimer's disease is a potential risk factor for sarcopenia,in which body mass index plays an important mediating role.This suggests that in clinical practice,attention should be paid to the muscle condition of patients with Alzheimer's disease,and weight management should be implemented,as maintaining a body mass index within the normal high range may have a preventive effect on the occurrence of sarcopenia in patients with Alzheimer's disease.However,further research is needed to verify the applicability of this conclusion to other ethnic groups.This study utilized an international public database for analysis,providing a reference for research on the correlation between Alzheimer's disease and sarcopenia in the Chinese population.It also highlights the significant mediating role of body mass index,offering insights for further prevention and treatment of sarcopenia among Chinese individuals.

BACKGROUND:Alzheimer's disease has been associated with sarcopenia,but a causal relationship has not been established.Exploring the causal relationship between the two most common disability-burdening diseases in the aging population-Alzheimer's disease and sarcopenia-and their potential mediating factors holds certain implications for further alleviating the healthcare costs and socioeconomic burden for older adults in China.OBJECTIVE:To explore the potential causal relationship between Alzheimer's disease and sarcopenia in the general population using a Mendelian randomization study and to explore the role of body mass index in this context.METHODS:Two-sample Mendelian randomization analysis based on published genome-wide association studies(GWAS)were used to infer causality,and univariate Mendelian randomization and mediation analyses were used in the study design.Through the Integrative Epidemiology Unit(IEU)database,ieu-b-2 was selected as the Alzheimer's disease dataset(sample size:63 926),ieu-b-4816 as the body mass index dataset(99 998),ebi-a-GCST90000027 as the appendicular lean mass dataset(244 730),ukb-b-7478 as the left hand grip strength dataset(461 026),ukb-b-10215 as the right hand grip strength dataset(461 089)and ukb-b-4711 as the walking pace dataset(459 915).Inverse-variance weighting was used as the primary analysis method,and the results were validated by pleiotropy and heterogeneity analysis.The Steiger Directionality Test was performed to validate the reasonableness of the causal direction.RESULTS AND CONCLUSION:(1)The Mendelian randomization analyses provided evidence that Alzheimer's disease predicted the risk of appendicular lean mass[odds ratio(OR)=1.009;95％confidence interval(Cl),1.001-1.017;P=0.023),and walking pace(OR=1.010;95％Cl,1.003-1.017;P=0.008).No correlation with hand grip strength was observed.(2)Alzheimer's disease was negatively correlated with body mass index(OR=0.893;95％Cl,0.811-0.984;P=0.022);body mass index was positively correlated with appendicular lean mass(OR=1.084;95％Cl,1.031-1.141;P=0.002)and negatively correlated with walking pace(OR=0.975;95％Cl,0.969-0.980;P＜0.001).(3)Mediation analyses showed that the causal relationship between Alzheimer's disease and appendicular lean mass and walking pace was partially mediated by body mass index,with the proportion of mediations being 50.25％and 32.11％,respectively.(4)The results of this study suggest that based on large-scale population studies,genetic prediction of Alzheimer's disease is a potential risk factor for sarcopenia,in which body mass index plays an important mediating role.This suggests that in clinical practice,attention should be paid to the muscle condition of patients with Alzheimer's disease,and weight management should be implemented,as maintaining a body mass index within the normal high range may have a preventive effect on the occurrence of sarcopenia in patients with Alzheimer's disease.However,further research is needed to verify the applicability of this conclusion to other ethnic groups.This study utilized an international public database for analysis,providing a reference for research on the correlation between Alzheimer's disease and sarcopenia in the Chinese population.It also highlights the significant mediating role of body mass index,offering insights for further prevention and treatment of sarcopenia among Chinese individuals.

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

A nodule in the right middle lobe of the lung was treated by a combination of cone-beam CT,three-dimensional registration for fusion imaging,and electromagnetic navigation bronchoscopy-guided thermal ablation.The procedure lasted for 90 min,with no significant bleeding observed under the bronchoscope.The total radiation dose during the operation was 384 mGy.The patient recovered well postoperatively,with only a small amount of blood in the sputum and no pneumothorax or other complications.A follow-up chest CT on the first day post operation showed that the ablation area completely covered the lesion,and the patient was discharged successfully.
Humans ; Bronchoscopy/methods* ; Catheter Ablation/methods* ; Cone-Beam Computed Tomography ; Electromagnetic Phenomena ; Imaging, Three-Dimensional ; Lung Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed

On the basis of that the fluorescence wavelength of copper nanoclusters(CuNCs)could cover the entire visible region,multicolor fluorescent CuNCs/starch composites were prepared and applied in fingermark development.With L-glutathione as the reducing agent and protective ligand,blue emissive and orange emissive CuNCs solutions were obtained in alkaline solutions at 90℃and 25℃,respectively.With the aggregation-induced emission effect induced by ethanol as a poor solvent,the fluorescence of orange emissive CuNCs with a higher intensity was achieved in an ethanol-water solution.With ascorbic acid as the reducing agent and 3-mercaptopropionic acid as the protective agent,green emissive CuNCs solution was prepared in an acid solution.Particle morphologies,chemical compositions and optical properties of these three CuNCs above were investigated using physical characterization and spectroscopic analysis,indicating that well-dispersed CuNCs had excellent photoluminescent properties.These CuNCs solutions were combined with starch to form composite powders by simply drying.The influences of the type of CuNCs and the ratio of CuNCs to starch on the emission wavelength and fluorescence intensity of the products were studied.The obtained CuNCs/starch composites could emit blue,green and orange fluorescence under 365 nm ultraviolet light,respectively,which were suitable for fingermark development.Minutiae and partial level-3 features of latent fingermarks could be effectively developed.High-quality fluorescence fingermark images would be captured using appropriate optical filters to eliminate background interference of various substrates.

Di-(2-ethylhexyl)phthalate(DEHP)is an environmental pollutant commonly found in plastic products and has toxic effects on female reproductive system.DEHP can interfere with the synthesis of progesterone,testosterone and estradiol through female hypothalamic-pituitary-ovarian axis,aggravate insulin resistance and obesity by affecting glucose and lipid metabolism,and cause ovarian damage through inducing oxidative stress,excessive autophagy and pyroptosis of oocyte or granulosa cells.It can also alter epigenetic genes relating to follicular development and prevent follicles from mature.These factors are closely contribute to the pathogenesis of polycystic ovary syndrome.We systematically summarizes the mechanism of DEHP interfering with ovarian function and inducing polycystic ovary syndrome,in order to provide help for the prevention and treatment of female reproductive injury from environmental pollutant.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.