Laparoscopic subtotal cholecystectomy (LSC) has been a safe and viable alternative to conversion to laparotomy in cases of severe cholecystitis. The objective of this study is to determine the utility of intraoperative choledochoscopy in LSC for the exploration of the gallbladder, cyst duct, and subsequent stone clearance of the cystic duct in cases of severe cholecystitis. A total of 72 patients diagnosed with severe cholecystitis received choledochoscopy-assisted laparoscopic subtotal cholecystectomy (CALSC). A choledochoscopy was performed to explore the gallbladder cavity and/or cystic duct, and to extract stones using a range of techniques. The clinical records, including the operative records and outcomes, were subjected to analysis. No LSC was converted to open surgery, and no bile duct or vascular injuries were sustained. All stones within the cystic duct were removed by a combination of techniques, including high-frequency needle knife electrotomy, basket, and electrohydraulic lithotripsy. A follow-up examination revealed the absence of residual bile duct stones, with the exception of one common bile duct stone, which was extracted via endoscopic retrograde cholangiopancreatography. In certain special cases, CALSC may prove to be an efficacious treatment for the management of severe cholecystitis. This technique allows for optimal comprehension of the situation within the gallbladder cavity and cystic duct, facilitating the removal of stones from the cystic duct and reducing the residue of the non-functional gallbladder remnant.

Objective: To investigate the association of sleep and circadian rhythm disruption indicators (including chronotype, sleep duration, and social jetlag) with co-occurring depressive and anxiety symptoms among primary and secondary school students, so as to provide a reference for promoting their mental health. Methods: In October 2023, a total of 15 944 primary and secondary school students were recruited from Nanjing, using a stratified cluster random sampling method. The Morning and Evening Questionnaire-5, Center for Epidemiological Studies Depression, and Generalized Anxiety Disorder-7 were used for the survey. Chi-square test was employed for intergroup comparisons, and Logistic regression model was applied to analyze the independent and joint effects of sleep related factors on comorbid symptoms of depressive and anxiety among primary and middle school students. Results: The prevalence of co-occurring depressive and anxiety symptoms among primary and secondary school students in Nanjing was 16.9%. After adjusting for covariates, Logistic regression analysis revealed significant independent associations between evening chronotype ( OR=6.55, 95%CI =5.59-7.68), insufficient sleep duration ( OR=3.05, 95%CI =2.60-3.59), and social jetlag ≥2 h ( OR= 2.09 , 95%CI =1.85-2.37) with comorbid symptoms of depressive and anxiety among students (all P <0.05). Concurrent of evening chronotype and insufficient sleep ( OR=7.54, 95%CI =3.55-16.01), as well as evening chronotype and social jetlag ≥2 h ( OR=4.18, 95%CI =3.01-5.81), were associated with an increased risk of co-occurring depressive and anxiety symptoms (both P < 0.05 ). In the female and high school student subgroups, the combination of evening chronotype and insufficient sleep or social jetlag ≥2 h showed stronger joint effects on co-occurring depressive and anxiety symptoms [ OR (95% CI )=8.46(3.25-22.04) and 15.90(3.66-69.08); 7.87(4.90-12.65) and 4.85(3.10-7.59), respectively; all P <0.05]. Conclusions Evening chronotype, insufficient sleep, and social jetlag≥2 h may serve as risk factors for comorbid symptoms of depressive and anxiety in school aged populations. Paying attention to the coexistence of multiple sleep related risk factors may help mitigate the occurrence of emotional disorders in this demographic.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

Congenital heart disease (CHD) is a congenital malformation resulting from abnormal embryonic development of the heart and great vessels, accounting for approximately 25% of all congenital malformations. Children with CHD are often complicated by short stature. Although surgical treatment can improve their growth and development to a certain extent, some children still experience growth retardation after surgery. Recombinant human growth hormone (rhGH) is the main drug for treating short stature, but its efficacy and safety in the treatment of patients with concomitant CHD warrant further investigation. This article reports six cases of children with CHD and short stature who were treated with rhGH. Through a literature review, we summarize and discuss the therapeutic efficacy, follow-up experiences, and adverse reactions of rhGH treatment, aiming to provide references for clinicians in applying rhGH to treat patients with CHD and short stature.

Objective:To evaluate the clinical outcomes of a large-diameter autograft of 8-strand semitendinosus/gracilis (8S-ST/G) in reconstruction of anterior cruciate ligament (ACL).Methods:A retrospective analysis was conducted of the 56 patients with primary ACL injury who had been treated by the 8S-ST/G autograft technique at Sports Medicine Service, Beijing Jishuitan Hospital, Capital Medical University between January 2019 and January 2022. The cohort included 42 males and 14 females, with an age of (28.3±7.3) years and a body mass index of (24.4±3.3) kg/m 2. There were 28 left and 28 right knees involved. The preoperative posterior tibial slope measured 14.8°±2.8°. The diameter of 8S-ST/G autograft was (9.3±0.7) mm. The postoperative outcomes documented were knee stability (assessed via KT-1000 arthrometer side-to-side difference, Lachman test, and pivot-shift test), graft maturity, graft roof impingement, and complications. Results:The patients were followed up for (2.4±0.3) years postoperatively. The side-to-side difference decreased significantly from preoperative 6.0 (5.0, 8.0) mm to postoperative 2.0 (0.0, 3.0) mm ( P<0.001). The positive rate of high-grade pivot shift (2+, 3+) reduced significantly from 50.0% (28/56) preoperatively to 3.6% (2/56) postoperatively ( P<0.001). The ACL graft signal grades revealed by the MRI at the final follow-up were grade Ⅰ in 45 cases, grade Ⅱ in 7 cases, and grade Ⅲ in 4 cases. After the 15 patients with their preoperative MRI from other hospitals (showing ACL graft signal of grade I in all) were excluded, the anterior subluxation of lateral compartment (ASLC) and anterior subluxation of medial compartment (ASMC) in the other 41 patients at the final follow-up [(4.8±3.1) mm and 3.0 (2.0, 4.9) mm, respectively] showed no significant differences from the preoperative values [(5.9±3.2) mm and 3.9 (0.0, 6.3) mm, respectively] ( P>0.05). However, in the 30 patients with well-preserved ACL graft signal (grade I), both ASLC and ASMC at the final follow-up [(3.9±2.5) mm and 3.0 (1.5, 4.7) mm] showed significant improvements compared to the preoperative values [(5.5±3.1) mm and 5.1 (2.7, 6.2) mm] ( P<0.05). At the final follow-up, 19.6% (11/56) of the patients showed ACL graft laxity; graft failure occurred in 8.9% (5/56) of the patients, one of whom underwent revision surgery. Second-look arthroscopy revealed concomitant cartilage injuries in 12.5% (7/56) of the patients, cyclops lesions in 3.6% (2/56), and ACL graft impingement in 7.1% (4/56). Conclusion:In the treatment of patients with ACL injury, the 8S-ST/G autograft configuration can significantly improve the stability of the knee joint and graft maturity, but it can not effectively correct the ASLC and ASMC for a subset of patients.

Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective:To investigate the characteristics of Internet addiction(IA)in adolescents with depression and explore its relationship with impulsivity and aggressive personality traits.Methods:A total of 71 adolescent patients with depressive disorders were recruited from the Child Psychiatry Outpatient Clinic of Peking University Sixth Hospital between April 2021 and November 2022 (15 males, 56 females; median age 14 [13, 15] years) as the depressive disorder group. Additionally, 83 healthy adolescents (27 males, 56 females; median age 14 [13, 17] years) were recruited as the control group during the same period. Internet addiction was assed using the Chinese version of Young′s Internet Addiction Test (YIAT), with a total score≥50 indicating internet addiction. Impulsivity was evaluated using the Barratt Impulsiveness Scale-11(BIS-11), and aggression was measured with the Buss-Perry Aggression Questionnaire(BPAQ). Differences in internet addiction, impulsivity, and aggression between the depression group and the control group were analyzed. Pearson correlation analysis was used to explore the correlation between internet addiction and impulsivity, aggression. Hierarchical linear regression models were used to analyze the factors influencing internet addiction, and a parallel mediation model was used to examine the mediating effect of impulsivity and aggressive personality traits in the relationship between depressive disorders and internet addiction.Results:The prevalence of IA was significantly higher in adolescents with depression than the healthy control group [57.75%(41/71) vs 31.33%(26/83); χ 2=10.87, P<0.001]. Adolescents with depressive disorders also exhibited higher impulsivity (65.5±9.2 vs 57.0±9.2, t=-5.72, P<0.001) and aggression (56.3±16.0 vs 42.4±15.1, t=-5.13, P<0.001) compared to the control group. Internet addiction was positively correlated with aggression ( r=0.47, P<0.01) and impulsivity ( r=0.57, P<0.01). Hierarchical regression analysis with the YIAT total score as the dependent variable revealed that impulsivity ( β=0.48, P<0.001) and aggression ( β=0.24, P<0.001) significantly predicted internet addiction. Mediation analysis indicated that depressive disorders indirectly indirectly influenced internet addiction through parallel paths of impulsivity and aggression, with a total indirect effect of 0.543 (95% CI: 0.362-0.761). Conversely, internect addiction influenced depressive disorders through reverse parallel pathway of impulsivity and aggression with a total indirect effect of 0.038 (95% CI: 0.021-0.067). Direct effects were not significant in either direction. Conclusion:Adolescents with depressive disorders exhibit more internet addiction. Impulsivity and aggressive personality traits play bidirectional mediating roles in the relationship between depressive disorders and internet addiction.

AIM: To explore the efficacy of 0.05% cyclosporine A combined with olopatadine eye drops in treating allergic conjunctivitis-related dry eye disease.METHODS: A total of 63 patients(63 eyes)with allergic conjunctivitis-related dry eye disease in the People's Hospital of Guangxi Zhuang Autonomous Region from August 2022 to April 2023 were enrolled and randomly divided into control group(n=33)and observation group(n=30). The patients of the control group were administrated with 0.1% olopatadine eye drops and 0.3% sodium hyaluronate eye drops, while the observation group was administrated with 0.1% olopatadine eye drops and 0.05% cyclosporine A eye drops. The ocular surface disease index(OSDI), total ocular symptom score(TOSS), conjunctival congestion score, conjunctival papillae and follicle score, Schirmer I test(SⅠt), tear meniscus height(TMH), meibomian gland secretion ability and property score, meibomian gland loss area score, corneal fluorescein staining(CFS), tear film break-up time(BUT), noninvasive first tear film break-up time(NIBUTf), noninvasive average tear film break-up time(NIBUTav)before and after treatment and the drug safety during the treatment period of both groups of patients were evaluated.RESULTS: After treatment, OSDI, TOSS, conjunctival congestion score, conjunctival papillae and follicle score, SⅠt, TMH, meibomian gland secretion ability score and property score, CFS, BUT, NIBUTf, and NIBUTav of the observation group showed improvements compared with those before treatment(all P<0.017). Among these, OSDI, TOSS, conjunctival congestion score, conjunctival papillae and follicle score, BUT, NIBUTf, and NIBUTav demonstrated significant improvement compared with the control group(all P<0.05). There was no statistically significant difference in meibomian gland loss area score between the two groups before and after treatment(P>0.05). During the treatment period, there were no local or systemic adverse reactions.CONCLUSION: The combined use of 0.05% cyclosporine A and olopatadine eye drops can significantly improve ocular discomfort symptoms of patients with dry eye disease associated with allergic conjunctivitis, such as red eyes, itchy eyes and foreign body sensation, promote tear film stability and have high safety.

Objective:To compare the diagnostic value of semi-quantitative parameters of fluorine 18-labelled prostate-specific membrane antigen( 18F-PSMA)positron emission tomography /computed tomography(PET/CT)and the Prostate-specific Membrane Antigen Reporting and Data System(PSMA-RADS)score for identifying benign and malignant oligo-PSMA-avid bone lesions(1-5 lesions)in elderly patients with prostate cancer. Methods:A retrospective analysis was conducted on 157 prostate cancer patients who underwent 18F-PSMA PET/CT examinations at Beijing Hospital from October 2022 to August 2024.According to the inclusion and exclusion criteria, a total of 63 patients were selected.All patients underwent 18F-PSMA PET/CT examination for the purpose of initial staging or detecting lesions with biochemical recurrence.PSMA-avid bone lesions were evaluated using the PSMA-RADS version 2.0 scoring system and the semi-quantitative parameters were measured on PSMA PET/CT images.According to the comprehensive diagnostic criteria, PSMA-avid bone lesions were divided into metastatic group and non-metastatic group.The differences in PSMA-RADS scores, semi-quantitative parameters, bone density abnormalities, and lesion distribution were compared between the two groups.Multivariate logistic regression analysis was performed to determine the factors related to the bone metastasis in prostate cancer.By plotting the receiver operating characteristic(ROC)curves and calculating the area under the curve(AUC), factors with better diagnostic performance were evaluated and screened, and the optimal diagnostic threshold for each factor in diagnosing bone metastasis was determined. Results:There were a total of 129 PSMA-avid bone lesions for 63 patients(aged 60-84 years, median age 69 years), including 35 lesions(27.1%)in the metastatic group and 94 lesions(72.9%)in the non-metastatic group.The differences between metastatic group and non-metastatic group in PSMA-RADS scores[5(4, 5) vs.3(3, 3)], maximum standardized uptake value(SUV max)[12.6(7.0, 18.4) vs.4.7(3.5, 5.9)], lesion SUV max/mediastinal blood pool SUV max ratio(lesion-to-blood pool ratio, LBR)[5.4(3.0, 8.3) vs.1.7(1.4, 2.2)], lesion SUV max/liver SUV max ratio(lesion-to-liver ratio, LLR)[2.6(1.6, 4.1) vs.0.8(0.7, 1.1)], PSMA receptor expressing tumor volume(PSMA-TV)[0.6(0.3, 1.0) vs.1.0(0.7, 1.5)], total lesion of PSMA(TL-PSMA)[4.4(2.4, 7.0) vs.2.4(1.7, 3.9)], proportion of changes in osteogenic bone density[77.1%(27/35) vs.2.1%(2/94)], proportion of lesions located in the ribs[14.3%(5/35) vs.46.8%(44/94)], and proportion of lesions located in the pelvis[54.3%(19/35) vs.20.2%(19/94)]were all statistically significant(all P<0.05). Multivariate logistic regression analysis indicated that none of the variables with statistically significant differences between groups above were independent risk factors for osseous metastasis in prostate cancer(all P>0.05). Among them, The PSMA-RADS score, LLR, LBR, and SUV max all had good diagnostic efficacy for osseous metastasis, with 0.995(95% CI: 0.987-1.000), 0.923(95% CI: 0.869-0.977), 0.898(95% CI: 0.828-0.967), and 0.890(95% CI: 0.820-0.961), respectively.The cut-off values for diagnosing osseous metastasis were 4 score for PSMA-RADS score, 0.934 for LLR, 1.990 for LBR, and 5.47 for SUV max, respectively.According to Delong's test, there were statistically significant differences in AUC between PSMA-RADS score and 18F-PSMA PET/CT semi-quantitative parameters(LLR, LBR, and SUV max)( Z-values were 2.677, 2.776, and 2.929, respectively, and P-values were 0.007, 0.006, and 0.003, respectively). Conclusions:The PSMA-RADS score(Version 2.0)and 18F-PSMA PET/CT semi-quantitative parameters(LLR, LBR, and SUV max)both have good diagnostic value in differentiating benign and malignant PSMA-avid bone lesions in elderly patients with prostate cancer, among which the PSMA-RADS score has the best diagnostic efficacy.