1.A prediction model for mild cognitive impairment risk among the elderly
MA Zongkang ; LIU Xinglang ; LI Huihui ; HE Guowei ; YAN Ping ; ZHANG Chuanrong ; MA Xuan ; CHE Yajie ; YU Shan ; CHEN Fenghui
Journal of Preventive Medicine 2026;38(2):124-129
Objective:
To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening.
Methods :
From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA).
Results:
A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764.
Conclusion
The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.
2.A preliminary study of mechanosensitive channels Piezo 1 and Piezo 2 promoting neurogenic bladder fibrosis in young rats
Lei LYU ; Yanping ZHANG ; Qi LI ; Junkui WANG ; Shuai YANG ; Zhaokai ZHOU ; Shuai LI ; Yibo WEN ; Yakai LIU ; Guowei SI ; Xingchen LIU ; Jianguo WEN
Journal of Modern Urology 2025;30(4):343-349
Objective: To explore the changes of mechanosensitive channels Piezos (Piezo 1 and Piezo 2) in neurogenic bladder (NB) of young rats and their effects,so as to provide reference for clinical search of new therapeutic targets. Methods: A total of 30 female young SD rats were divided into 5 groups based on random number table method:sham operation group (sham),2-week nerve transection group (NB-2W),6-week nerve transection group (NB-6W),2-week nerve transection + Piezos inhibitor group (NB-P-2W) and 6-week nerve transection + Piezos inhibitor group (NB-P-6W),with 6 rats in each group.The NB models were constructed by transecting the L6 and S1 spinal nerves of young rats.The NB-2W and NB-6W groups were not intervened after modeling,while the NB-P-2W and NB-P-6W groups were intraperitoneally injected with Piezos inhibitor GsMTx4 (10 mg/kg) every 2 days after modeling.Bladder cystometry and ultrasound were performed after 2 and 6 weeks of transection.The expressions of Piezos and fibrosis-related indexes (Collagen Ⅰ and α-smooth muscle actin) were detected in bladder tissues. Results: The results of bladder cystometry showed that the basal bladder pressure in NB-2W group was significantly increased,while it was slightly decreased but was still higher in NB-6W group than in the sham group (P<0.05).Basal bladder pressure was lower in NB-P-2W group than in NB-2W group,but was higher than that in the sham group; basal bladder pressure was lower in NB-P-6W group than in NB-6W group,but higher than that in the sham group (P<0.05).Compared with the sham group,the NB-2W and NB-6W groups had firstly increased and then decreased maximum cystometric capacity (MCC) (P<0.05).Compared with NB-2W group,NB-P-2W group had lower bladder leakage point pressure (BLPP),but higher MCC and bladder compliance (BC) (P<0.05).Compared with NB-6W group,NB-P-6W group had significantly lower BLPP but higher MCC and BC (P<0.05).HE and MASSON staining and ultrasound results showed that,with the extension of nerve transection time,bladder fibrosis gradually worsened,the bladder wall became rough and thickened,calculi were visible inside,and hydronephrosis gradually appeared; the degree of fibrosis in NB-P-2W and NB-P-6W groups was less than that in NB-2W and NB-6W groups,and no hydronephrosis was observed in the upper urinary tract.In addition,Western blotting and immunohistochemical results showed that NB-2W and NB-6W groups had significantly higher relative expression levels of Piezos,Collagen Ⅰ and α-SMA than the sham group (P<0.01),while NB-P-2W and NB-P-6W groups had lower relative expression levels of Piezos,Collagen Ⅰ and α-SMA than NB-2W and NB-6W groups (P<0.01). Conclusion: The increased expressions of mechanosensitive channels Piezos in NB young rats may be involved in the progression of bladder fibrosis,but its mechanism needs further study.
3.Influencing factors of overactive bladder in college freshmen and the impacts on anxiety,quality of life,and social interaction
Guowei SI ; Ce GAO ; Sida SHAO ; Feng SI ; Yakai LIU ; Songyang WANG ; Maochuan FAN ; Huiqing ZHANG ; Qifeng DOU ; Jianguo WEN
Journal of Modern Urology 2025;30(6):513-519
Objective: To investigate the influencing factors of overactive bladder (OAB) in college freshmen and the impacts of OAB on their mental health, quality of life and social interaction. Methods: An epidemiological questionnaire survey was conducted in an anonymous manner on the prevalence of OAB among 5300 freshmen aged 17 to 22 years enrolled in the 2023—2024 academic year in Xinxiang Medical University and Sanquan College of Xinxiang Medical University.The questionnaire included questions on basic information, history of urinary tract infection, constipation, smoking, history of alcohol consumption, history of coffee/strong tea drinking, history of carbonated beverage drinking, redundant prepuce, phimosis, holding urine, chronic insomnia, self-rating anxiety scale (SAS), quality of life score (QoL), and social avoidance and distress scale (SADS).The influencing factors of OAB were analyzed with multivariate logistic regression analysis.The subjects were grouped according to whether they had OAB, and the differences in SAS, QoL and SADS between the OAB group and non-OAB group were compared.The impacts of OAB on the anxiety level, quality of life, and social interaction were analyzed with multiple linear regression analysis. Results: The overall prevalence rate of OAB was 4.9% (244/5018).Multivariate logistic regression analysis showed that the history of urinary tract infection (OR=0.177), constipation (OR=0.636), smoking (OR=0.582), alcohol consumption (OR=0.685), coffee/strong tea drinking (OR=0.387), carbonated beverage drinking (OR=0.631), redundant prepuce (OR=0.673), phimosis (OR=0.311), urine holding (OR=0.593), and chronic insomnia (OR=0.256) were influencing factors for the occurrence of OAB (P<0.05).The OAB group had higher SAS score [(41.18±6.54) vs. (38.61±6.36)], QoL score [(3.65±1.20) vs. (2.79±0.95)], social avoidance score [(6.25±1.86) vs. (5.86±1.51)], social distress score [(6.27±1.59) vs. (5.97±1.32)], and total SADS score [(12.51±2.35) vs. (11.84±2.01)] than the non-OAB group (P<0.05).The results of multiple linear regression analysis showed that OAB could independently affect the scores of QoL, SAS, and SADS.The OAB group had higher scores of QoL, SAS, and SADS compared with the non-OAB group (P<0.001). Conclusion: History of urinary tract infection, constipation, smoking, alcohol consumption, coffee/strong tea drinking, carbonated beverage drinking, redundant prepuce, phimosis, urine holding, and chronic insomnia are influencing factors for the occurrence of OAB in male college students.Moreover, OAB has negative impacts on their mental health, quality of life, and social interaction.
4.The clinical value of artificial intelligence quantitative parameters in distinguishing pathological grades of stage Ⅰ invasive pulmonary adenocarcinoma
Yun LIANG ; Mengmeng REN ; Delong HUANG ; Jingyan DIAO ; Xuri MU ; Guowei ZHANG ; Shuliang LIU ; Xiuqu FEI ; Dongmei DI ; Ning XIE
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(05):598-607
Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.
5.Study on artificial intelligence-based ultrasound diagnosis and auxiliary decision-making for ovarian tumors
Chunli QIU ; Yanlin CHEN ; Yuanji ZHANG ; Haotian LIN ; Xiaoyi PAN ; Siying LIANG ; Xiang CONG ; Xin LIU ; Zhen MA ; Cai ZANG ; Xin YANG ; Dong NI ; Guowei TAO
Chinese Journal of Ultrasonography 2025;34(7):608-615
Objective:To apply artificial intelligence(AI)in classifying ovarian tumors on ultrasound images,and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures,i.e.,Alexnet,Densenet121,and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors,while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently,the benign and malignant results of the model's predictions were disclosed to each sonographer,and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941,sensitivity of 0.936,and specificity of 0.944 on the internal test dataset,and maintained robust performance on the external test dataset with accuracy of 0.891,sensitivity of 0.880,and specificity of 0.907. Compared to junior sonographers,the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors(0.880 vs. 0.723,0.602;all P<0.05). No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1( P=0.05). With assistance from the optimal model,junior sonographers achieved significant improvements in both sensitivity and specificity(sensitivity:0.723 vs. 0.843,0.602 vs. 0.819;specificity:0.778 vs. 0.833,0.685 vs. 0.741;all P<0.05). Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance,the diagnostic performance of junior sonographers is significantly improved.
6.Optimization of Processing Technology of Curculigo orchioides Gaertn.by Box-Behnken Response Surface Method Combined with Analytic Hierarchy Process
Guowei XU ; Wei WANG ; Sihan LIU ; Yidan HONG ; Liqiang ZHANG ; Chengguo JU
Chinese Journal of Information on Traditional Chinese Medicine 2025;32(1):134-139
Objective To optimize the processing technology of Curculigo orchioides Gaertn.Methods On the basis of single factor experiment,the ratio of material to liquid,frying temperature and frying time were taken as the influencing factors,and the comprehensive scores of appearance traits,curculigoside,orcinol glucoside and orcinol gentiobioside were taken as the evaluation indexes.The optimal processing technology was optimized by Box-Behnken response surface method combined with analytic hierarchy process,and the process verification was carried out.Results The optimal process was as follows:the raw C.orchioides pieces were mixed with the same amount of Evodia rutaecarpa juice,placed in a closed container,moistened until the juice was completely absorbed,stir-fried at 130 ℃ for 6 min,taken out and dried at 60 ℃.For each 100 kg of Curculigo,10 kg of Evodia rutaecarpa was used.Evodia rutaecarpa juice preparation method:10 kg of Evodia rutaecarpa was soaked in 12 times the amount of water for 60 min,decocted for 50 min,extracted for 3 times,combined with the filtrate,and concentrated to 100 kg to obtain Evodia rutaecarpa juice.Conclusion The optimal processing technology of Curculigo orchioides Gaertn.is stable and feasible.
7.Construction and Validation of A Prognostic Model for Lung Adenocarcinoma Based on Ferroptosis-related Genes.
Zhanrui ZHANG ; Wenhao ZHAO ; Zixuan HU ; Chen DING ; Hua HUANG ; Guowei LIANG ; Hongyu LIU ; Jun CHEN
Chinese Journal of Lung Cancer 2025;28(1):22-32
BACKGROUND:
Ferroptosis-related genes play a crucial role in regulating intracellular iron homeostasis and lipid peroxidation, and they are involved in the regulation of tumor growth and drug resistance. The expression of ferroptosis-related genes in tumor tissues can be used to predict patients' future survival times, aiding doctors and patients in anticipating disease progression. Based on the sequencing data of lung adenocarcinoma (LUAD) patients from The Cancer Genome Atlas (TCGA) database, this study identified genes involved in the regulation of ferroptosis, constructed a prognostic model, and evaluated the predictive performance of the model.
METHODS:
A total of 1467 ferroptosis-related genes were obtained from the GeneCards database. Gene expression profiles and clinical data from 541 LUAD patients were collected from the TCGA database. The expression data of all ferroptosis-related genes were extracted, and differentially expressed genes were identified using R software. Survival analysis was performed on these genes to screen for those with prognostic value. Subsequently, a prognostic risk scoring model for ferroptosis-related genes was constructed using LASSO regression model. Each LUAD patient sample was scored, and the patients were divided into high-risk and low-risk groups based on the median score. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated. Kaplan-Meier survival curves were generated to assess model performance, followed by validation in an external dataset. Finally, univariate and multivariate Cox regression analyses were conducted to evaluate the independent prognostic value and clinical relevance of the model.
RESULTS:
Through survival analysis, 121 ferroptosis-related genes associated with prognosis were initially identified. Based on this, a LUAD prognostic risk scoring model was constructed using 12 ferroptosis-related genes (ALG3, C1QTNF6, CCT6A, GLS2, KRT6A, LDHA, NUPR1, OGFRP1, PCSK9, TRIM6, IGF2BP1 and MIR31HG). The results indicated that patients in the high-risk group had significantly shorter survival time than those in the low-risk group (P<0.001), and the model demonstrated good predictive performance in both the training set (1-yr AUC=0.721) and the external validation set (1-yr AUC=0.768). Risk scores were significantly associated with the prognosis of LUAD patients in both univariate and multivariate Cox regression analyses (P<0.001), suggesting that this score is an important prognostic factor for LUAD patients.
CONCLUSIONS
This study successfully established a LUAD risk scoring model composed of 12 ferroptosis-related genes. In the future, this model is expected to be used in conjunction with the tumor-node-metastasis (TNM) staging system for prognostic predictions in LUAD patients.
Humans
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Ferroptosis/genetics*
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Prognosis
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Adenocarcinoma of Lung/pathology*
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Lung Neoplasms/pathology*
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Male
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Female
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Gene Expression Regulation, Neoplastic
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Middle Aged
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ROC Curve
8.Application of prostate health index and prostate health index density in the detection of intermediate-to high-risk prostate cancer
Chenchen CHEN ; Yinghao ZHOU ; Yaozong XU ; Yibo MENG ; Guowei SHI ; Jun ZHANG ; Wandong YU
Journal of Modern Urology 2025;30(8):642-647,700
Objective To evaluate the diagnostic value of prostate health index(PHI)and prostate health index density(PHID)in identifying intermediate-to high-risk prostate cancer(PCa).Methods Clinical data of 160 treatment-na?ve patients with highly suspected PCa,who underwent initial prostate biopsy in our hospital during Jul.2022 and Feb.2024,were retrospectively analyzed.Data included age,body mass index(BMI),prostate volume(PV),total prostate-specific antigen(tPSA),free PSA(fPSA),[-2]proPSA(p2PSA),PHI and PHID.Biopsy-positive results were stratified according to the EAU D'Amico risk criteria.Receiver operating characteristic(ROC)curve and multivariate logistic regression analysis were employed to assess the diagnostic performance of PHI and PHID in predicting PCa and identifying intermediate-to high-risk PCa.Results There were statistically significant differences in tPSA,p2PSA,PHI and PHID between the negative and positive groups,as well as among the low-,medium-and high-risk groups(P<0.01).Both PHI and PHID demonstrated good diagnostic performance in predicting PCa(AUC=0.820 8 and 0.875 7,respectively;all P<0.001),and in identifying intermediate-to high-risk PCa(AUC=0.838 0 and 0.878 3,respectively;all P<0.001).Compared to the baseline model,the incorporation of PHI and PHID individually into the multivariate model significantly improved the screening performance for PCa(AUC=0.910 and 0.898,respectively;all P<0.001).Conclusion PHI and PHID exhibit high diagnostic efficacy in screening PCa,particularly in identifying intermediate-to high-risk disease.
9.Investigation and evaluation for the popularization and demonstration of domestically innovative medical devices in Liaoning province
Shengyuan HAO ; Jinyi ZHANG ; Li LIU ; Huihui YU ; Qing TONG ; Guowei PAN ; Wei SUN
China Medical Equipment 2025;22(3):102-107
Objective:To investigate and assess the situation of popularization and promotion of domestically innovative medical devices in Liaoning Province,so as to provide a basis for promoting the allocation policy of domestically innovation medical devices.Methods:Self-made questionnaire and on-site filling survey were conducted to implement investigation and analysis for the allocation situation of newly medical equipment of 188 medical institutions in 9 demonstration regions of the Project on Regional Application and Demonstration of Innovative Medical Equipment in Liaoning Province from 2015 to 2020.The allocation data of medical equipment between before(from 2015 to 2017)and after the demonstration projects were implemented(from 2018 to 2020)were compared.The occupancy rate of domestically medical devices(referred as"occupancy ratio of domestic device")was used as an evaluation indicator to assess the status of equipment allocation and application before and after the projects of application and demonstration were implemented in the region of innovative equipment for diagnosis and treatment.Results:In the 9 demonstrational regions of Liaoning province,the number of newly added domestic medical devices during the period from 2018 to 2020 increased from 1,608 units between 2015 and 2017 to 1,703 units.The occupancy ratio of newly added domestic devices increased from 72.7%to 84.9%.The occupancy ratio of domestic devices of newly added key equipment increased from 63.0%to 83.4%,and the growth rate reached 20.4%.In different districts and different grades of medical institution,the increase and application of domestically medical devices appeared difference.Conclusion:The occupancy rate of newly added domestically medical devices in 9 demonstration regions in Liaoning province has generally increased.However,there are still imbalances between different regions and different grades of medical institutions.The manufacturers of domestically medical devices still need strengthen brand building and marketing promotion,so as to further enhance market competitiveness of domestically medical devices.
10.The effect of left colic artery preservation on low anterior resection syndrome in patients of rectal cancer
Junling ZHANG ; Shuo FENG ; Tao WU ; Changyou WANG ; Guowei CHEN ; Yong JIANG ; Lie SUN ; Tao LIU ; Jingui WANG ; Weidong DOU ; Yingchao WU ; Xin WANG
Chinese Journal of General Surgery 2025;40(2):88-93
Objective:To investigate the effect of left colonic artery (LCA) preservation on rectal cancer patients' short-term postoperative anal function and quality of life.Methods:Two-hundred ninty-two patients with rectal cancer at the Department of Gastrointestinal Surgery of Peking University First Hospital between Jan 2022 and Dec 2023 were enrolled . The patients were divided into two groups according to whether the LCA was preserved during surgery or not. The LARS scale and EORTC QLQ-CR29 quality of life questionnaire were used to assess postoperative anal function and quality of life.Results:There were no significant differences between the two groups in terms of the amount of surgical blood loss and the number of lymph node dissections in the root No. 253 group and the time to postoperative voiding (all P>0.05). However, the LARS scores at 1 and 3 months postoperatively were significantly lower in the preserved LCA group than in the LCA nonpreserved group, especially for gas incontinence, loose stool leakage, and number of bowel movements (all P<0.05). The EORTC QLQ-CR29 scores showed that the LCA preserved group recovered significantly better than the non-preserved group in terms of postoperative voiding dysfunction ( P=0.007), urinary incontinence ( P=0.006), mucus discharge ( P=0.009), and fecal incontinence symptoms ( P<0.001). Male sexual dysfunction recovery was quicker in the preserved LCA group ( P=0.043), but there was no significant difference between the two groups at 3 months postoperatively( P>0.05). Conclusion:Preservation of the left colonic artery in low anterior resection of rectal cancer helps to reduce the incidence of postoperative low anterior resection syndrome, improve genitourinary symptoms, and improve patients' quality of life.


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