BACKGROUND:Osteoporotic fracture is the most serious complication of osteoporosis.Previous studies have demonstrated that gut microbiota has a regulatory effect on skeletal tissue and that gut microbiota has an important relationship with osteoporotic fracture,but the causal relationship between the two is unclear. OBJECTIVE:To explore the causal relationship between gut microbiota and osteoporotic fractures using Mendelian randomization method. METHODS:The genome-wide association study(GWAS)datasets of gut microbiota and osteoporotic fracture were obtained from the IEU Open GWAS database and the Finnish database R9,respectively.Using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,Mendelian randomization analyses with random-effects inverse variance weighted,MR-Egger regression,weighted median,simple model,and weighted model methods were performed to assess whether there is a causal relationship between gut microbiota and osteoporotic fracture.Sensitivity analyses were performed to test the reliability and robustness of the results.Reverse Mendelian randomization analyses were performed to further validate the causal relationship identified in the forward Mendelian randomization analyses. RESULTS AND CONCLUSION:The results of this Mendelian randomization analysis indicated a causal relationship between gut microbiota and osteoporotic fracture.Elevated abundance of Actinomycetales[odds ratio(OR)=1.562,95%confidence interval(CI):1.027-2.375,P=0.037),Actinomycetaceae(OR=1.561,95%CI:1.027-2.374,P=0.037),Actinomyces(OR=1.544,95%CI:1.130-2.110,P=0.006),Butyricicoccus(OR=1.781,95%CI:1.194-2.657,P=0.005),Coprococcus 2(OR=1.550,95%CI:1.068-2.251,P=0.021),Family ⅩⅢ UCG-001(OR=1.473,95%CI:1.001-2.168,P=0.049),Methanobrevibacter(OR=1.274,95%CI:1.001-1.621,P=0.049),and Roseburia(OR=1.429,95%CI:1.015-2.013,P=0.041)would increase the risk of osteoporotic fractures in patients.Elevated abundance of Bacteroidia(OR=0.660,95%CI:0.455-0.959,P=0.029),Bacteroidales(OR=0.660,95%CI:0.455-0.959,P=0.029),Christensenellacea(OR=0.725,95%CI:0.529-0.995,P=0.047),Ruminococcaceae(OR=0.643,95%CI:0.443-0.933,P=0.020),Enterorhabdus(OR=0.558,95%CI:0.395-0.788,P=0.001),Eubacterium rectale group(OR=0.631,95%CI:0.435-0.916,P=0.016),Lachnospiraceae UCG008(OR=0.738,95%CI:0.546-0.998,P=0.048),and Ruminiclostridium 9(OR=0.492,95%CI:0.324-0.746,P=0.001)would reduce the risk of osteoporotic fractures in patients.We identified 16 gut microbiota associated with osteoporotic fracture by the Mendelian randomization method.That is,using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,eight gut microbiota showed positive causal associations with osteoporotic fracture and another eight gut microbiota showed negative causal associations with osteoporotic fracture.The results of this study not only identify new biomarkers for the early prediction of osteoporotic fracture and potential therapeutic targets in clinical practice,but also provide an experimental basis and theoretical basis for the study of improving the occurrence and prognosis of osteoporotic fracture through gut microbiota in bone tissue engineering.

Objective: To explore the factors affecting language development delay among children aged <3 years, so as to provide a basis for the prevention and early intervention of children's language development problems. Methods: Eighty-one children aged <3 years with language development delay who visited the children's language development clinic of Shaoxing Maternal and Child Health Hospital from January to December 2024 as the case group. Meanwhile, 118 children who underwent routine physical examinations at the children's health clinic during the same period, had normal language development were randomly selected as the control group. Data on children's basic information, parenting environment, and screen exposure were collected through questionnaire surveys. Language development delay was assessed using the Early Language Milestone Scale and the Gesell Developmental Diagnosis Scale. The factors for language development delay were analyzed using a multivariable logistic regression model. Results: The case group comprised 81 children, including 56 boys (69.14%) and 25 girls (30.86%), with a mean age of (23.14±4.84) months. The control group consisted of 118 children, including 81 boys (68.64%) and 37 girls (31.36%), with a mean age of (23.81±4.60) months. Multivariable logistic regression analysis showed that daily parental companionship time of ≥2 hours (OR=0.121, 95%CI: 0.040-0.367), attending childcare institutions (OR=0.103, 95%CI: 0.030-0.352), the average daily screen exposure time <1 hour (OR=0.614, 95%CI: 0.400-0.942), interactive parental accompaniment during screen exposure (OR=0.350, 95%CI: 0.157-0.779), and restricting screen exposure time (OR=0.162, 95%CI: 0.056-0.470) were associated with a lower risk of language development delay among children aged <3 years. Conclusion Daily paternal companionship of 2 hours or more, attending childcare institutions, daily screen exposure time of less than 1 hour, interactive parental companionship during screen time, and limiting screen exposure time can reduce the risk of language developmental delay among children aged under 3 years.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

Objective To investigate the ameliorative effects and potential mechanism of Lithocarpus litseifoliu on renal function and inflammation in mice with hyperuricemic nephropathy(HN).Methods The HN model was established by the combined administration of adenine and potassium oxyzate.The mice were randomly divided into normal control group,model control group,benzbromarone group,and high,medium and low dose groups of Lithocarpus litseifoliu.Different drugs were given to the mice,and their body mass was recorded once a week.The levels of uric acid(UA),creatinine(Cr),urine protein(UP),blood urea nitrogen(BUN)and urine urea nitrogen(UUN)as well as the levels of tumor necrosis factor α(TNF-α)and interleukin 6(IL-6)in serum or urine of each group were collected and measured on the 21st day.Hematoxylin-eosin(HE)staining was performed to observe kidney tissue injury in mice;real-time PCR(RT-PCR)was performed to determine ATP-binding cassette subfamily G member 2(ABCG2),urate transporter protein(URAT1),glucose transporter protein 9(GLUT9),and cytosolic factor NF-κB p50(κB p50)in kidney tissues.Results Compared with the normal control group,the body mass of mice in the model control group was significantly lower after the second weeks of modeling(P＜0.05),and the levels of UA,Cr,UP,BUN,UUN,TNF-α,IL-6 contents and GLUT9 mRNA and κB p50 mRNA expression contents of kidney tissues were significantly higher(P＜0.01,P＜0.05).Compared with the model control group,the levels of Cr,UP,BUN and UUN contents and renal tissue nuclear cytokine κB p50 mRNA expression were significantly lower in the high,medium and low dose groups of Lithocarpus litseifoliu(P＜0.01,P＜0.05).The UA levels were significantly lower in the high dose group of Lithocarpus litseifoliu(P＜0.05),and renal ABCG2 mRNA expression was significantly higher in the medium dose group(P＜0.01).The renal URAT1 mRNA expression was significantly decreased in the low dose group(P＜0.01).Conclusion Lithocarpus litseifoliu has shown ameliorative effects on HN mice,and the mechanism may be related to the modulation of renal uric acid transporters,improvement of renal function and anti-inflammation effects.

Circadian disruption is being increasingly recognized as a critical factor in the development and progression of Parkinson’s disease (PD). This review aims to provide an in-depth overview of the relationship between circadian disruption and PD by exploring the molecular, cellular, and behavioral aspects of this interaction. This review will include a comprehensive understanding of how the clock gene system and transcription–translation feedback loops function and how they are diminished in PD. The article also discusses the role of clock genes in the regulation of circadian rhythms, as well as the impact of clock gene dysregulation on mitochondrial function, oxidative stress, and neuroinflammation, including the microbiota-gut-brain axis, which have all been proposed as being crucial mechanisms in the pathophysiology of PD. Finally, this review highlights potential therapeutic strategies targeting the clock gene system and circadian rhythm for the treatment of PD.

Objectives: Bipolar hemiarthroplasty is commonly performed to treat displaced femoral neck fractures in osteo porotic patients. This study aimed to assess the occurrence and outcomes of unplanned return visits to the emergency department (ED) within 90 days following bipolar hemiarthroplasty for displaced femoral neck fractures. Methods: The clinical data of 1322 consecutive patients who underwent bipolar hemiarthroplasty for osteoporotic femoral neck fractures at a tertiary medical center were analyzed. Data from the patients’ electronic medical records, including demographic information, comorbidities, and operative details, were collected. The risk factors and mortality rates were analyzed. Results: Within 90 days after surgery, 19.9% of patients returned to the ED. Surgery-related reasons accounted for 20.2% of the patient’s returns. Older age, a high Charlson comorbidity index score, chronic kidney disease, and a history of cancer were identified as significant risk factors for unplanned ED visits. Patients with uncemented implants had a significantly greater risk of returning to the ED due to periprosthetic fractures than did those with cemented implants (P = 0.04). Patients who returned to the ED within 90 days had an almost fivefold greater 1-year mortality rate (15.2% vs 3.1%, P < 0.001) and a greater overall mortality rate (26.2% vs 10.5%, P < 0.001). Conclusions This study highlights the importance of identifying risk factors for unplanned ED visits after bipolar hemiarthroplasty, which may contribute to a better prognosis. Consideration should be given to the use of cemented implants for hemiarthroplasty, as uncemented implants are associated with a greater risk of peri prosthetic fractures.