OBJECTIVE To analyze the characteristics and influencing factors of disposal behavior of expired medicines among Chinese residents across regional divisions， and to provide references for regional classification management and precise policy implementation regarding expired medicines. METHODS A stratified random sampling method was employed to conduct a questionnaire survey among residents across sample provinces and cities， utilizing a combination of online and offline approaches. Binary Logistic regression analysis was used to systematically explore the regional （eastern， central and western regions） and urban-rural disparities in the recycling of expired medicines among Chinese residents， identify the core driving factors influencing standardized disposal behaviors， and propose corresponding recommendations. RESULTS A total of 2 200 ques tionnaires were collected， with 2 159 deemed valid， yielding an effective response rate of 98.1%. The surveyed residents commonly stored medicines at home （67.7%）， yet the rate of regular medicine clearance was low （only 57.7%）. Nearly half of the residents （49.7%） had expired medicines in their households， with improper disposal of expired medicines remaining the predominant behavior. Insufficient convenience in recycling was identified as the primary reason for improper disposal of expired medicines （50.1%）. Statistically significant differences were observed between residents in the eastern， central and western regions， as well as between urban and rural residents， in terms of household medicine storage rates and the prevalence of expired medicine possession （ P ＜0.05）. However， no statistically significant difference was found in the standardized disposal rates across regional divisions （ P ＞0.05）. Furthermore， the residents demonstrated a higher level of awareness regarding the health hazards of expired medicines compared to their awareness of environmental hazards， with 46.0% and 32.1% indicating they were “relatively familiar” and “very familiar”， respectively. The participation rate in standardized recycling was only 37.6%. Among non-participating residents， the three primary barriers were “recycling points being too far away” （46.6%）， “unawareness of recycling channels” （46.1%） and “lack of incentives” （48.1%）. The surveyed residents showed relatively high trust in pharmaceutical regulatory authorities and on-site recycling personnel， with “high trust” accounting for 31.2% and 34.7%， respectively. Binary Logistic regression analysis results indicated that the awareness of environmental hazards and the accessibility of recycling points were the core driving factors for proper disposal. CONCLUSIONS Significant issues exist in the recycling of expired medicines among Chinese residents， characterized by “improper behavior， cognitive bias， and unbalanced system”. It is recommended to construct a tiered recycling network focusing on “quality improvement in the eastern region， expansion in the central region， and basic coverage in the western region”， implement targeted educational campaigns and differentiated incentive policies. Moreover， the specific needs of groups such as the elderly should be addressed to achieve spatial equalization and service optimization of the recycling system.

Objective:To explore the value of the deep learning model based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI in preoperatively predicting vessels completely encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).Methods:This study adopted a case-control design to retrospectively analyze 420 patients with HCC confirmed by postoperative pathology who underwent Gd-EOB-DTPA enhanced MRI between June 2016 and March 2023. A total of 420 patients were divided into a training set ( n=305) from the First Affiliated Hospital of Soochow University and an external validation set ( n=115) from Affiliated Nantong Hospital 3 of Nantong University. Based on postoperative pathological findings, patients were stratified into VETC-positive and VETC-negative groups. The training set comprised 161 VETC-positive cases and 144 VETC-negative cases, while the external validation set included 55 VETC-positive cases and 60 VETC-negative cases. Tumor regions of interest in arterial, portal venous, and hepatobiliary phases were manually delineated using ITK-SNAP software. Pre-trained Vgg19, Densenet121, and Vision Transformer (ViT) models were employed for transfer learning, extracting deep learning features from each image. Feature data were processed using FAE software, and 12 logistic regression models (arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase models) were constructed to select the optimal deep learning model. Independent predictors in clinical characteristics were identified through univariate and multivariate logistic analyses to establish a clinical model for predicting VETC pattern. Subsequently, a clinical-deep learning fusion model was developed by integrating these clinical predictors with the optimal deep learning features. Model performance in predicting VETC-positive HCC was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results:In the external validation set, the area under the curve (AUC) of the Vgg19 model in the arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase, respectively were 0.799,0.756,0.789,0.821, which were higher than those of Densenet121 (AUC: 0.544,0.581,0.544,0.583) and ViT (AUC: 0.740,0.752,0.785,0.767) model. The three-phase combined Vgg19 model achieved the highest AUC of 0.821 (95% CI 0.746-0.897). Multivariate logistic regression identified alpha-fetoprotein level ( OR=1.826,95% CI 1.069-3.120, P=0.028) and tumor diameter ( OR=1.329,95% CI 1.206-1.466, P<0.001) as independent predictors of VETC-positive HCC, forming the clinical model with an AUC of 0.789 (95% CI 0.703-0.859). The clinical-deep learning fusion model further achieved the AUC of 0.825 (95% CI 0.749-0.900). Calibration curves confirmed high concordance between predicted and actual probabilities for the three-phase Vgg19 model, while DCA revealed greater net clinical benefit for the combined Vgg19 and fusion models compared with the clinical model alone. Conclusions:The deep learning model based on Gd-EOB-DTPA enhanced MRI can be used to predict VETC of HCC preoperatively, among which the three-phase combined Vgg19 model and the clinical-deep learning model provide high predictive value.

Objective To analyze the changes in serum levels of Krüppel-like transcription factors(KLF11)and long non-coding RNA small nucleolar RNA host gene 12(lncRNA SNHG12)in patients with intracranial aneurysm(IA),and their predictive value for prognosis.Methods A retrospective analysis was performed on 132 IA patients(IA group)who underwent interventional embolization for IA rupture and bleeding from February 2019 to February 2023,and 60 healthy people who underwent outpatient physical examination during the same period were selected as the control group.Serum levels of KLF11 was detected by enzyme-linked immunosorbent assay(ELISA),the level of lncRNA SNHG12 was detected by real-time fluorescence quantitative PCR(qRT-PCR).According to the modified Rankin scale(MRS)score,IA patients were divided into a good prognosis group(n=98,MRS score 0～2)and poor prognosis group(n=34,MRS score 3～6).Pearson correlation analysis was used to analyze the correlation between serum KLF11,lncRNA SNHG12 and cerebral hemodynamic parameters.Logistic regression analysis was used to analyze the factors affecting the prognosis of IA patients.The receiver operating characteristic curve was used to analyze the prognostic value of serum KLF11 and lncRNA SNHG12 in IA patients.Results The serum KLF11(47.12±6.58ng/L)and lncRNA SNHG12(1.89±0.36)in the IA group were lower than those in the control group(113.89±19.35ng/L,3.24±0.58),and the differences were statistically significant(t=19.695,35.476,all P<0.05).The levels of serum KLF11 and lncRNA SNHG12 in IA group were positively correlated with cerebral blood flow,cerebral blood volume and mean transit time(rKLF11=0.722,0.627,0.752;rlncRNA SNHG12=0.630,0.714,0.766,all P<0.05),and negatively correlated with intracranial pressure(r=-0.658,-0.599,all P<0.05).The proportion of CT Fisher grade 3～4 in IA patients in the poor prognosis group was higher than that in the good prognosis group,and the postoperative complication rate was higher than that in the good prognosis group,the serum KLF11(35.98±6.11 ng/L)and lncRNA SNHG12(1.12±0.30)levels were lower than those in the good prognosis group(50.98±6.90ng/L,2.16±0.39),and the differences were statistically significant(t=4.630～14.151,all P<0.05).CT Fisher grade 3～4,postoperative complications were risk factors for poor prognosis of IA patients(Wald χ2=8.403,12.049,all P<0.001),serum KLF11,lncRNA SNHG12 were protective factors(Wald χ2=5.550,7.904,all P<0.001).The AUC(95%CI)for predicting the prognosis of IA patients with the combination of serum KLF11 and lncRNA SNHG12 was 0.921(0.889～0.942),which was higher than the single detection of serum KLF11 and lncRNA SNHG12 at 0.848(0.805～0.886)and 0.810(0.767～0.852),and the differences were statistically significant(Z=5.886,4.367,all P<0.001).Conclusion The levels of serum KLF11 and lncRNA SNHG12 in IA patients are decreased,which are related to cerebral hemodynamic parameters.The combined detection has a high evaluation value for the prognosis of IA patients.

Objective To analyze the changes in serum levels of Krüppel-like transcription factors(KLF11)and long non-coding RNA small nucleolar RNA host gene 12(lncRNA SNHG12)in patients with intracranial aneurysm(IA),and their predictive value for prognosis.Methods A retrospective analysis was performed on 132 IA patients(IA group)who underwent interventional embolization for IA rupture and bleeding from February 2019 to February 2023,and 60 healthy people who underwent outpatient physical examination during the same period were selected as the control group.Serum levels of KLF11 was detected by enzyme-linked immunosorbent assay(ELISA),the level of lncRNA SNHG12 was detected by real-time fluorescence quantitative PCR(qRT-PCR).According to the modified Rankin scale(MRS)score,IA patients were divided into a good prognosis group(n=98,MRS score 0～2)and poor prognosis group(n=34,MRS score 3～6).Pearson correlation analysis was used to analyze the correlation between serum KLF11,lncRNA SNHG12 and cerebral hemodynamic parameters.Logistic regression analysis was used to analyze the factors affecting the prognosis of IA patients.The receiver operating characteristic curve was used to analyze the prognostic value of serum KLF11 and lncRNA SNHG12 in IA patients.Results The serum KLF11(47.12±6.58ng/L)and lncRNA SNHG12(1.89±0.36)in the IA group were lower than those in the control group(113.89±19.35ng/L,3.24±0.58),and the differences were statistically significant(t=19.695,35.476,all P<0.05).The levels of serum KLF11 and lncRNA SNHG12 in IA group were positively correlated with cerebral blood flow,cerebral blood volume and mean transit time(rKLF11=0.722,0.627,0.752;rlncRNA SNHG12=0.630,0.714,0.766,all P<0.05),and negatively correlated with intracranial pressure(r=-0.658,-0.599,all P<0.05).The proportion of CT Fisher grade 3～4 in IA patients in the poor prognosis group was higher than that in the good prognosis group,and the postoperative complication rate was higher than that in the good prognosis group,the serum KLF11(35.98±6.11 ng/L)and lncRNA SNHG12(1.12±0.30)levels were lower than those in the good prognosis group(50.98±6.90ng/L,2.16±0.39),and the differences were statistically significant(t=4.630～14.151,all P<0.05).CT Fisher grade 3～4,postoperative complications were risk factors for poor prognosis of IA patients(Wald χ2=8.403,12.049,all P<0.001),serum KLF11,lncRNA SNHG12 were protective factors(Wald χ2=5.550,7.904,all P<0.001).The AUC(95%CI)for predicting the prognosis of IA patients with the combination of serum KLF11 and lncRNA SNHG12 was 0.921(0.889～0.942),which was higher than the single detection of serum KLF11 and lncRNA SNHG12 at 0.848(0.805～0.886)and 0.810(0.767～0.852),and the differences were statistically significant(Z=5.886,4.367,all P<0.001).Conclusion The levels of serum KLF11 and lncRNA SNHG12 in IA patients are decreased,which are related to cerebral hemodynamic parameters.The combined detection has a high evaluation value for the prognosis of IA patients.

Pulmonary endometriosis (PEM) is a rare disease with diverse clinical manifestations, most commonly presenting as hemoptysis, while patients presenting solely with pulmonary nodules are less common. Here, we report three female patients (aged 32, 19, and 46 years, respectively). One patient sought medical attention due to hemoptysis during menstruation, while the other two had no obvious symptoms and were found to have pulmonary nodules during routine physical examinations. Two patients had a history of cesarean section, and one had a history of miscarriage. Pathologically, one patient of PEM showed extensive hemorrhage in the alveolar spaces, with fragmented endometrial glandular epithelium observed within the hemorrhagic foci. The other two patients exhibited proliferative endometrial glands and stroma, surrounded by old hemorrhage. Immunohistochemistry revealed that the endometrial glands and stroma in all three patients were positive for estrogen receptor, progesterone receptor, and vimentin, with CD10 positivity in the endometrial stroma. All three patients were definitively diagnosed as PEM by pathology and underwent thoracoscopic pulmonary wedge resection. Follow-up periods were 18, 31, and 49 months, respectively, with no recurrence observed in any of the patients.

In order to further promote the standardization of the integrated traditional Chinese and western medicine treatment of atopic dermatitis(AD),the team of Professor Chen Dacan,who is honored as the Qihuang Scholar,developed the Clinical Practice Guidelines for Integrated Traditional Chinese and Western Medicine in Atopic Dermatitis(hereinafter referred to as Guidelines for AD).This paper detailed the process of development of Guidelines for AD,and analyzed the characteristics of Guidelines for AD,as well as the difficulties and countermeasures encountered during such a time.The development of Guidelines for AD follows the methodology of international guidelines for clinical trial.Experts specializing in various disciplines,such as traditional Chinese medicine,western medicine,integrated traditional Chinese and western medicine,and methodology,composed an expert group and a working group.On the basis of systematic literature research,the clinic experiences of frontline experts were well-summarized,and the draft of Guidelines for AD was formed after several meetings and discussions.In the process of developing Guidelines for AD,quite a number of problems were encountered,and the project team found the corresponding countermeasures after analyzing these problems.The countermeasures became the characteristics of Guidelines for AD:the integration of traditional Chinese medicine therapies and western medicine therapies,and the evaluation of the evidence of integrated traditional Chinese and western medicine solved the problem of traditional Chinese and western medicine diagnosis and treatment of AD lacking standardization;the adequately combination of the evidence with the experience of clinical practice solved the problems of the low overall level and the insufficiency of traditional Chinese medicine evidence for AD;the establishment of management goals and strategies for AD after taking the advantages of both traditional Chinese medicine and western medicine into account was in line with the international treatment and management concepts;the formulation of individualized traditional Chinese and western medicine therapy based on the integration of traditional Chinese medicine therapy and western medicine therapy met the clinical needs of patients with different characteristics of AD.The development process of Guidelines for AD and the analysis of problems and countermeasures during such a time will provide reference and reflection for the subsequent establishment of clinical guidelines for the integrated traditional Chinese and western medicine in other diseases.

To identify factors associated with the recurrence of polymyalgia rheumatica(PMR) within one year.

Objective:To explore the value of the deep learning model based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI in preoperatively predicting vessels completely encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC).Methods:This study adopted a case-control design to retrospectively analyze 420 patients with HCC confirmed by postoperative pathology who underwent Gd-EOB-DTPA enhanced MRI between June 2016 and March 2023. A total of 420 patients were divided into a training set ( n=305) from the First Affiliated Hospital of Soochow University and an external validation set ( n=115) from Affiliated Nantong Hospital 3 of Nantong University. Based on postoperative pathological findings, patients were stratified into VETC-positive and VETC-negative groups. The training set comprised 161 VETC-positive cases and 144 VETC-negative cases, while the external validation set included 55 VETC-positive cases and 60 VETC-negative cases. Tumor regions of interest in arterial, portal venous, and hepatobiliary phases were manually delineated using ITK-SNAP software. Pre-trained Vgg19, Densenet121, and Vision Transformer (ViT) models were employed for transfer learning, extracting deep learning features from each image. Feature data were processed using FAE software, and 12 logistic regression models (arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase models) were constructed to select the optimal deep learning model. Independent predictors in clinical characteristics were identified through univariate and multivariate logistic analyses to establish a clinical model for predicting VETC pattern. Subsequently, a clinical-deep learning fusion model was developed by integrating these clinical predictors with the optimal deep learning features. Model performance in predicting VETC-positive HCC was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Results:In the external validation set, the area under the curve (AUC) of the Vgg19 model in the arterial phase, portal venous phase, hepatobiliary phase, and combined three-phase, respectively were 0.799,0.756,0.789,0.821, which were higher than those of Densenet121 (AUC: 0.544,0.581,0.544,0.583) and ViT (AUC: 0.740,0.752,0.785,0.767) model. The three-phase combined Vgg19 model achieved the highest AUC of 0.821 (95% CI 0.746-0.897). Multivariate logistic regression identified alpha-fetoprotein level ( OR=1.826,95% CI 1.069-3.120, P=0.028) and tumor diameter ( OR=1.329,95% CI 1.206-1.466, P<0.001) as independent predictors of VETC-positive HCC, forming the clinical model with an AUC of 0.789 (95% CI 0.703-0.859). The clinical-deep learning fusion model further achieved the AUC of 0.825 (95% CI 0.749-0.900). Calibration curves confirmed high concordance between predicted and actual probabilities for the three-phase Vgg19 model, while DCA revealed greater net clinical benefit for the combined Vgg19 and fusion models compared with the clinical model alone. Conclusions:The deep learning model based on Gd-EOB-DTPA enhanced MRI can be used to predict VETC of HCC preoperatively, among which the three-phase combined Vgg19 model and the clinical-deep learning model provide high predictive value.

Objective:To construct a chain mediating model based on two mediating variables of positive psychological capital and general self-efficacy, so as to explore the impact mechanism of social support on posttraumatic growth in thyroid cancer patients.Methods:From March to December 2023, convenience sampling was used to select 270 postoperative patients with thyroid cancer from the Chinese People's Liberation Army General Hospital as participants. The patients were surveyed using the General Information Questionnaire, Post Traumatic Growth Inventory, Social Support Rating Scale, Positive Psychological Questionnaire, and General Self-efficacy Scale. Spearman correlation was used to analyze the correlation between social support, positive psychological capital, general self-efficacy, and posttraumatic growth in thyroid cancer patients. SPSS PROCESS program was used to test for the chain mediating effect.Results:A total of 270 questionnaires were distributed, and 257 questionnaires were collected. After excluding questionnaires with missing items exceeding 10% and regular responses, 246 valid questionnaires were collected, with a valid response rate of 91.11% (246/270). Spearman correlation showed that there was positive correlations between social support, positive psychological capital, general self-efficacy, and posttraumatic growth in patients ( P<0.01). Mediating effect analysis showed that social support directly and positively predicted posttraumatic growth in thyroid cancer [ β=0.403, 95% CI (0.258, 0.547) ], and also affected patients' posttraumatic growth through three indirect pathways, namely social support → positive psychological capital → posttraumatic growth, with an effect value of 0.083 [95% CI (0.002, 0.173) ], accounting for 13.63% of the total effect, and social support → general self-efficacy → posttraumatic growth, with an effect value of 0.099 [95% CI (0.040, 0.166) ], accounting for 16.26% of the total effect, and social support → positive psychological capital → general self-efficacy → posttraumatic growth, with an effect value of 0.025 [95% CI (0.005, 0.051) ], accounting for 4.11% of the total effect. The total indirect effect accounted for 33.83% of the total effect. Conclusions:Social support can not only directly affect the post-traumatic growth of thyroid cancer patients, but also indirectly affect post-traumatic growth through the mediating effect of positive psychological capital and general self-efficacy.

Objective:To further investigate the safety and efficacy of Belimumab in the treatment of patients with systemic lupus erythematosus (SLE).Methods:All SLE patients treated with Belimumab from May 1, 2020 to February 1, 2022 in Peking Union Medical College Hospital were retrospectively collected and analyzed. The clinical manifestations, the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2000) score, and laboratory test such as levels of anti-dsDNA antibody, the medication before and after Belimumab treatment, adverse events were collected. Normally distributed data were tested using the t-test, otherwise the Wilcoxon paired signed rank test was used. Results:A total of 81 patients were enrolled in this study. The use of belimumab could significantly decrease the SLEDAI-2000 score [10.00(7.75, 12.00) vs. 4.00(3.75, 6.00), Z=-5.38, P<0.001], ESR of SLE patients [19.50(12.75, 32.25) mm/1 h vs. 14.00(7.75, 20.25) mm/1 h, Z=-3.71, P=0.003], anti-dsDNA titer detected by CLIFT [300.00 (117.00, 864.00) vs. 183.00(100.00, 471.00), Z=-4.15, P=0.001], meanwhile, increase the complement C3 [0.78 (0.62, 0.97)g/L vs. 0.69 (0.55, 0.84)g/L, Z=-4.68, P<0.001], and the complement C4 [0.12 (0.08, 0.19)g/L vs. 0.10 (0.05, 0.14)g/L, Z=-4.78, P<0.001]. We also observed that with the use of Belimumab, the dosage of Glucocorticoids decreased significantly, which were [10.00(7.50, 22.50) mg vs. 7.50(5.00, 10.00) mg, Z=-4.90, P<0.001]. In addition, the antibody of IgG, IgA and IgM decreased significantly. Only one patient stopped the administration of Belimumab due to the low level of immunoglobulin. Conclusion:Belimumab can alleviate disease activity of patients with SLE and help in safely tapering the daily dose of glucocorticoid with good safety.