Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Purpose: Neuroendocrine prostate cancer (NEPC) represents a particularly aggressive subtype of prostate cancer with a challenging prognosis. The purpose of this investigation is to craft and confirm the reliability of nomograms that can accurately forecast the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) rates for individuals afflicted with NEPC. Materials and Methods: Data pertaining to patients diagnosed with NEPC within the timeframe of 2010 to 2020 was meticulously gathered and examined from the Surveillance, Epidemiology, and End Results Program (SEER). To predict OS and CSS, we devised and authenticated two distinct nomograms, utilizing predictive variables pinpointed through both univariate and multivariate Cox regression analyses. Results: The study encompassed 393 of NEPC patients, who were systematically divided into training and validation cohorts at a 2:1 ratio. Key prognostic factors were isolated, verified, and integrated into the respective nomograms for OS and CSS. The performance metrics, denoted by C-indices, stood at 0.730, 0.735 for the training set, and 0.784, 0.756 for the validation set. The precision and clinical relevance of the nomograms were further corroborated by the analysis of receiver operating characteristic curves, calibration plots, and decision curve analyses. Conclusions The constructed nomograms have demonstrated impressive efficacy in forecasting the 1-, 3-, and 5-year OS and rates for patients with NEPC. Implementing these predictive tools in clinical settings is anticipated to considerably enhance the care and treatment planning for individuals diagnosed with this aggressive form of prostate cancer, thus providing tailored and more precise prognostic assessments.

Objective To investigate the factors influencing the efficacy of intravesical Bacille Calmette-Guérin(BCG)instillation after transurethral resection of bladder tumor(TURBT)in patients with intermediate-and high-risk non-muscle invasive bladder cancer(NMIBC),and to construct a prediction model for recurrence after BCG treatment.Methods A retrospective cohort study was conducted on the subjected patients diagnosed with intermediate-and high-risk NMIBC undergoing TURBT followed by standard BCG instillation.The 110 patients treated in Department of Urology of Army Medical Center of PLA from January 2018 to December 2023 were assigned into a training set,while the 52 patients treated at Department of Urology of General Hospital of Central Theater Command from January 2015 to December 2020 were into an external validation set.A total of 17 variables were included and analyzed.Univariate and multivariate Cox regression analyses were performed to identify factors associated with recurrence after BCG instillation,and nomograms were plotted to predict 1-year,3-year,and 5-year recurrence-free survival(RFS).Calibration curve,decision curve analysis(DCA),and receiver operating characteristic(ROC)curve analysis were conducted for internal and external validation to evaluate the predictive performance and clinical utility of the model.Results In the training set,26 patients(23.64%)experienced recurrence during the follow-up period,with a median RFS of 32.00(18.00～50.50)months.Univariate Cox regression analysis suggested that platelet count,eosinophil to lymphocyte ratio(ELR),neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),systemic immune inflammation(SII)index,and neutrophil-monocyte to lymphocyte ratio(NMLR),pathological T1 stage(pT1)tumor and hemoglobin,albumin,lymphocyte,and platelet(HALP)score were potential factors influencing recurrence after BCG instillation.Multivariate Cox regression analysis identified high HALP score(HR=0.185,95%CI:0.046～0.736,P=0.017)as an independent protective factor,while high ELR(HR=3.599,95%CI:1.505～8.608,P=0.004)and pT1 stage(HR=3.240,95%CI:1.191～8.818,P=0.021)were independent risk factors for recurrence.Based on this,a nomogram prediction model was constructed.The calibration curves demonstrated good agreement between predicted and actual 1-,3-,and 5-year recurrence risks.Decision curve analysis indicated clinical utility across a wide threshold probability range.In the training set,the model showed strong predictive performance for 1-(AUC=0.842),3-(AUC=0.847),and 5-year(AUC=0.887)recurrence risks,which was further validated in the external cohort.Conclusion Higher HALP score prior to BCG instillation therapy is a protective factor against tumor recurrence,while higher ELR and pT1 stage are risk factors.Our nomogram prediction model based on HALP score,ELR and pathological T stage,can identify individuals at high risk of recurrence after BCG instillation therapy.

Objective To investigate risk factors for residual lesions after initial transurethral resection of bladder tumors(TURBT)and risk factors for tumor recurrence after second TURBT in patients with non-muscle-invasive bladder cancer(NMIBC)in order to provide reference for clinical management.Methods A case-control study design was adopted to include 120 NMIBC patients who underwent initial TURBT and then second surgery within 2～8 weeks in our department from January 2017 to January 2025.Based on the presence of residual lesions after the initial TURBT or not,the patients were divided into a residual lesion group(n=34)and a non-residual lesion group(n=86).Chi-square test and multivariate logistic regression analysis were performed to identify potential risk factors for residual lesions following the initial TURBT.Univariate and multivariate Cox regression models were used to analyze potential risk factors for tumor recurrence after the second TURBT.Results The residual lesion rate after initial TURBT was 28.33％.Chi-square test analysis revealed that tumor stage T1(Chi-square=5.756,P=0.016)and broad tumor base(Chi-square=4.331,P=0.037)were factors influencing residual lesions after initial TURBT.Multivariate logistic regression analysis identified tumor stage T1(OR=3.047,95％CI:1.128～8.226,P=0.028)as an independent risk factor for residual lesions after initial TURBT.The tumor recurrence rate after second TURBT was 17.5％.Multivariate Cox regression analysis identified tumor stage T1(OR=4.258,95％CI:1.248～14.532,P=0.021),intravesical chemotherapy instillation after second TURBT(OR=3.539,95％CI:1.284～9.752,P=0.015),history of urinary system tumors(OR=3.002,95％CI:1.145～7.873,P=0.025)and high platelet-to-lymphocyte(PLR)ratio(OR=2.798,95％CI:1.115～7.023,P=0.028)as independent risk factors for tumor recurrence after second TURBT.Conclusion Tumor stage T1 and broad tumor base are risk factors for residual lesions after initial TURBT,while tumor stage T1,intravesical chemotherapy instillation after second TURBT,history of urinary system tumors and high PLR ratio are risk factors for tumor recurrence after second TURBT.Comprehensive analysis on above 4 indicators can effectively assess the risk of tumor recurrence in NMIBC patients following second TURBT,and timely early medical intervention is beneficial for improving patient outcomes.

Objective The study aimed to construct and validate a predictive model for pulmonary nodules(PN)nature based on clinicopa-thological features,imaging,and serum biomarkers,so as to provide scientificdecision-making for early diagnosis and treatment of lung cancer.Methods A retrospective was performed on 816 PN patients with definited pathological diagnosis who received surgical resection analysisor lung biopsy in the Department of Thoracic Surgery and Oncology of Shenzhen Traditional Chinese Medicine Hospital from January 2019 to February 2023.Among them,113 cases that did not meet the inclusion criteria were excluded,and the remaining 703 cases were included in the study.The study based on the clinicopathologic features(age,gender,smoking history,smoking cessation history and family history of cancer),chest imaging(maximum diameter of nodule,location of lesion,clear border,Lobulation,spiculation,vascular convergence sign,vacuole,calcification,air bronchial sign,emphysema,nodule type and pleural indentation,nodule number)and serum carcinoembryonic antigen(CEA),cytokeratin 19 fragment(CYFRA21-1),squamous cell carcinoma antigen(SCCA)in patients with PN.These cases were randomly divided into a modeling group(n=552,237 benign,315 malignant)and a validation group(n=151,85 benign,66 malignant).First,univariate analysis was performed to screen for statistically significant predictors of nodules nature.Then,multivariate regression analysis was performed to screen for independent predictors of nodules nature.Finally,the prediction model of PN nature was constructed by logistic regression analysis.Subsequently,the validation group data were entered into the proposed model and Mayo clinic(Mayo)model,veterans affairs(VA)model,Brock University(Brock)model,Peking University(PKU)model and Guangzhou Medical University(GZMU)model,respectively.PN malignancy probability was calculated.The receiver operating characteristic(ROC)curves were plotted.The diagnostic efficiency of each model was compared according to the area under the curve(AUC).Results There were statistically significant variables including age,family history of cancer,maximum nodule diameter,nodule type,upper lobe of lung,calcification,vascular convergence sign,lobulation,clear border,spiculation,and serum CEA,SCCA,CYFRA21-1 using univariate analysis.Multiple regression analysis showed that age,CEA,clear border,CYFRA21-1,SCCA,upper lobe of lung,maximum nodule diameter,family history of cancer,spiculation and nodule type were independent predictors of PN nature.The prediction model equation constructed in this study is as follows:f(x)= ex/(1+ex),X=(-6.318 8+0.020 8×Age+0.527 4×CEA-0.928 4×clear border+0.294 6×Cyfra21-1+0.294×maximum nodule diameter+1.220 1×family history of cancer +0.573 2×upper lobe of lung +0.064 8×SCCA +1.461 5×Spiculation +1.497 6×nodule type).The AUC(0.799 vs 0.659,0.650)of the proposed model was significantly higher compared with Mayo model and VA model,and there were statistically significant differences(Z=3.029,2.638,P=0.003,0.008).However,compared with Brock model,PKU model and GZMU model,the differences of AUC(0.799 vs 0.762,0.773,0.769)were not statistically significant(Z=1.063,0.686,0.757,P=0.288,0.493,0.449).Conclusion The prediction model for PN nature established in this study is accurate and reliable,which can help clinics with early diagnosis and early intervention,and this prediction model deserves to be popularized.

BACKGROUND:Low to moderate intensity aerobic exercise can help protect knee cartilage.Long-chain non-coding RNAs are crucial for gene regulation.Among them,HOTAIR can activate numerous transcriptional co-repressors to repress the activation of certain genes. OBJECTIVE:To detect the expression levels of HOX transcript antisense RNA(HOTAIR)and other related factors in chondrocytes of high fat-fed mice and after low to moderate intensity exercise intervention,and to investigate their role in cartilage injury and sports rehabilitation. METHODS:Thirty C57BL/6 male mice were randomly divided into control group(normal feeding),high fat feeding group and high fat feeding plus treadmill exercise group,with 10 mice in each group.The mice in the high fat feeding plus treadmill exercise group were subjected to an 8-week low to middle intensity treadmill exercise,and the mice in the other two groups were caged.During this period,body mass was weighed every week on Sunday.After the 8-week exercise,both lower extremities of mice were taken,and the knee joint was scanned using Micro CT to make a 3D femoral condyle image to obtain relevant parameters.Hematoxylin-eosin and safranin O-fast green staining of the knee joint were performed for Mankin and Osteoarthritis Research Society International(OARSI)scoring.RT-PCR was performed to detect the mRNA levels of cartilage metabolic indicators and lipid metabolism indicators,including type II collagen,matrix metalloproteinase 13,interleukin 1,low-density lipoprotein receptor-related protein 5,HOTAIR and its downstream factor lysine specific demethylase 1. RESULTS AND CONCLUSION:The body mass of high fat-fed mice were higher than that of the control group(P<0.01),and the body mass of the high fat feeding plus treadmill exercise group was lower than that of the high fat feeding group(P<0.05).The connectivity density of high fat-fed mice was higher than that of the control group(P<0.01).Mankin and OARSI scores of the high fat feeding were higher than those of the control group(P<0.01)and high fat feeding plus treadmill exercise group(P<0.05).The mRNA level of type II collagen was higher in the control group than the high fat feeding plus treadmill exercise group(P<0.05)and high fat feeding group(P<0.01)as well as higher in the high fat feeding plus treadmill exercise group than the high fat feeding group(P<0.01).The mRNA levels of matrix metalloproteinase 13,interleukin 1,low-density lipoprotein receptor-related protein 5,HOTAIR and lysine specific demethylase 1 were higher in the high fat feed group than the control group and high fat feeding plus treadmill exercise group(P<0.01).To conclude,high fat feeding can increase the bone substance of the femoral condyle,lead to knee cartilage wear,and cause chondrocyte metabolism disorder.HOTAIR is highly expressed in this process.An 8-week low to middle intensity treadmill exercise can reduce body mass,alleviate knee cartilage wear,improve chondrocyte function and down-regulate HOTAIR expression in mice.

Objective To observe the role of dried tangerine peel in Yigong Powder improves iron metabolism and promotes red blood cell generation in anemia of chronic disease (ACD).Methods With a two-by-two factorial design,the Yigong Powder was divided into dried tangerine peel and Chenpi absent Decoction. According to the random number table method,32 zymosan-induced generalized inflammation (ZIGI) mice were randomly divided into the model group,the dried tangerine peel group,the Chenpi absent Decoction group,and the Yigong Powder group. The dried tangerine peel group,Chenpi absent Decoction group and the Yigong Powder group were given dried tangerine peel(3.083 g/kg),Chenpi absent Decoction(12.33g/kg),and Yigong Powder(15.413g/kg)by gavage to the corresponding group of mice. The model group was given an equal amount of physiological saline by gavage,and treated continuously for 7 days. After the completion of administration,the body weight of each group of mice was recorded. The hemoglobin content of each group of mice was detected using a fully automatic cell counter,the serum iron content was detected using colorimetry,the serum ferritin content was detected using enzyme-linked immunosorbent assay (ELISA),and the spleen index was calculated. The liver tissue inflammatory factors interleukin-1β (IL-1β),interleukin-6 (IL-6),tumor necrosis factor-α (TNF-α),interferon-γ (IFN-γ),interleukin-4 (IL-4),and interleukin-10 (IL-10) levels were detected using Luminex method. The mRNA expressions of liver tissue hepcidin gene (HAMP) and membrane iron transporter ( Fpn) were detected using real-time fluorescence PCR method. Results Dried tangerine peel and Chenpi absent Decoction both showed interactive effects in regulating hemoglobin,serum iron,serum ferritin content,improving spleen index,and regulating the mRNA expressions of HAMP,Fpn,as well as IL-1β and IFN-γ (P<0.05). Compared with the model group,dried tangerine peel significantly increased hemoglobin,serum iron content,and Fpn mRNA expression in ZIGI model mice,while decreasing ferritin content,spleen index,HAMP mRNA expression,and the levels of IL-1β,IL-6,TNF-α,and IFN-γ (P<0.05). Chenpi absent Decoction significantly increased serum iron content and Fpn mRNA expression in ZIGI model mice,while reducing spleen index,ferritin content,HAMP mRNA expression,and the levels of IL-1β and IFN-γ、IL-4 (P<0.05). Conclusion The effects of dried tangerine peel on inflammatory factors (IL-6 and TNF-α) and Fpn may play a key role in the improvement effects of Yigong Powder on ACD and iron metabolism.