Objective:To analyze the epidemic characteristics of reported tuberculosis incidence in Kashgar from 2015 to 2022, and use the seasonal autoregressive integrated moving average (SARIMA) model to predict the incidence, providing references for the local control of pulmonary tuberculosis.Methods:The reported incidence data of tuberculosis in the Kashgar area of Xinjiang from January 2015 to August 2023 were collected through the"Infectious Disease Monitoring System", a subsystem of the "Chinese Disease Prevention and Control Information System". The epidemic characteristics of reported incidence in this area from 2015 to 2022 were analyzed. Two SARIMA models of monthly reported incidence number and rate were established. The prediction performance of the two models was evaluated using the reported incidence data of tuberculosis from January 2023 to August 2023. The χ2 test was used to analyze population characteristics, and the Cochran-Armitage trend test was used to analyze annual incidence. Results:From 2015 to 2022, 133 972 cases of pulmonary tuberculosis were reported in Kashgar, with a yearly reported incidence rate of 383.64/100 000, showing a rising trend ( TCA=77.03, P<0.001) and then a declining trend ( TCA=176.16, P<0.001). The proportion of pathogenic positive pulmonary tuberculosis had increased yearly ( TCA=132.66, P<0.001). The reported onset time was concentrated from January to June each year, with a peak in April. Yengisar County, Zepu County and Yopurga County had the highest reported incidence rate in Kashgar. The sex ratio of men to women was 1.03∶1, and the reported incidence rate of men was higher than that of women ( χ2=27.04, P<0.001). The reported incidence rate of the group aged 60 years and older was the highest. The patient′s occupation was mainly farmers (84.99%). The average relative errors of the SARIMA ( 1, 1, 2) ( 0, 1, 1) 12 model and SARIMA ( 0, 1, 1)( 0, 1, 1) 12 model in predicting the reported monthly incidence number and rate were 11.67% and -9.81%, respectively. Both models had good prediction accuracy (MAPE=33.55%, MAPE=38.22%). Conclusion:The average reported incidence rate of pulmonary tuberculosis in the Kashgar area shows a rising trend first and then a declining trend. The patients are mainly men and farmers, and attention should be paid to the prevention and control of tuberculosis among the elderly in winter and spring. The SARIMA ( 1, 1, 2) ( 0, 1, 1) 12 model and SARIMA ( 0, 1, 1)( 0, 1, 1) 12 model can fit the trend of reported tuberculosis incidence in the Kashgar area well and have good predictive performance.

Objective:To analyze the epidemic characteristics of reported tuberculosis incidence in Kashgar from 2015 to 2022, and use the seasonal autoregressive integrated moving average (SARIMA) model to predict the incidence, providing references for the local control of pulmonary tuberculosis.Methods:The reported incidence data of tuberculosis in the Kashgar area of Xinjiang from January 2015 to August 2023 were collected through the"Infectious Disease Monitoring System", a subsystem of the "Chinese Disease Prevention and Control Information System". The epidemic characteristics of reported incidence in this area from 2015 to 2022 were analyzed. Two SARIMA models of monthly reported incidence number and rate were established. The prediction performance of the two models was evaluated using the reported incidence data of tuberculosis from January 2023 to August 2023. The χ2 test was used to analyze population characteristics, and the Cochran-Armitage trend test was used to analyze annual incidence. Results:From 2015 to 2022, 133 972 cases of pulmonary tuberculosis were reported in Kashgar, with a yearly reported incidence rate of 383.64/100 000, showing a rising trend ( TCA=77.03, P<0.001) and then a declining trend ( TCA=176.16, P<0.001). The proportion of pathogenic positive pulmonary tuberculosis had increased yearly ( TCA=132.66, P<0.001). The reported onset time was concentrated from January to June each year, with a peak in April. Yengisar County, Zepu County and Yopurga County had the highest reported incidence rate in Kashgar. The sex ratio of men to women was 1.03∶1, and the reported incidence rate of men was higher than that of women ( χ2=27.04, P<0.001). The reported incidence rate of the group aged 60 years and older was the highest. The patient′s occupation was mainly farmers (84.99%). The average relative errors of the SARIMA ( 1, 1, 2) ( 0, 1, 1) 12 model and SARIMA ( 0, 1, 1)( 0, 1, 1) 12 model in predicting the reported monthly incidence number and rate were 11.67% and -9.81%, respectively. Both models had good prediction accuracy (MAPE=33.55%, MAPE=38.22%). Conclusion:The average reported incidence rate of pulmonary tuberculosis in the Kashgar area shows a rising trend first and then a declining trend. The patients are mainly men and farmers, and attention should be paid to the prevention and control of tuberculosis among the elderly in winter and spring. The SARIMA ( 1, 1, 2) ( 0, 1, 1) 12 model and SARIMA ( 0, 1, 1)( 0, 1, 1) 12 model can fit the trend of reported tuberculosis incidence in the Kashgar area well and have good predictive performance.

Objective:To explore the value of baseline PET/CT parameters for predicting prognosis in patients with double-expression lymphoma (DEL).Methods:The clinical and 18F-FDG PET/CT data of 118 patients (66 males, 52 females; age: 28-85 years) with diffuse large B-cell lymphoma (DLBCL) diagnosed in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University and the First Affiliated Hospital of Nanjing Medical University from June 2015 to September 2022 were retrospectively analyzed. The optimal thresholds for SUV max, total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) in predicting overall survival (OS) rate were determined using ROC curve analysis. Univariate and multivariate analyses, along with Kaplan-Meier survival analysis were performed to construct a survival prediction model. The effect of the model was evaluated by the calibration curve for the model, the time-dependent ROC curve analysis and decision curve analysis. Results:As of the last follow-up, 25 patients died, and the OS rate was 78.8%(93/118). The AUC of the ROC curve for TMTV was 0.705, with a corresponding optimal threshold of 230.9 cm 3. In multivariate analysis, Eastern Cooperative Oncology Group performance status (ECOG PS) score (hazard ratio ( HR)=3.886, 95% CI: 1.455-10.375; P=0.007) and TMTV ( HR=4.649, 95% CI: 1.665-12.979; P=0.003) were identified as independent predictors of OS. The combined model of ECOG PS score and TMTV was superior to ECOG PS score model and TMTV model alone in predicting OS. Conclusion:TMTV, a metabolic indicator, and ECOG PS score, a clinical risk factor, are independent predictors of OS in patients with DEL, and their combination can provide more accurate prognostic predictions.

Objective:To explore the mechanisms of Qianlie Jindan Tablets(QLJD)acting on chronic nonbacterial prostatitis(CNP)in rats based on non-targeted urine metabolomics.Methods:According to the body mass index,we equally randomized 30 eight-week-old male SD rats into a blank control,a CNP model control and a QLJD medication group.We established the CNP model in the latter groups and,from the 4th day of modeling,treated the rats in the blank and model control groups intragastrically with nor-mal saline and those in the QLJD medication group with QLJD suspension,qd,for 30 successive days.Then we detected the changes in the metabolites of the rats by ultra-high-performance liquid chromatography-tandem mass spectrometry,and identified the differential metabolites in different groups by multivariate statistical analysis,followed by functional annotation of the differential metabolites.Results:Eight common metabolites were identified by metabolomics analysis,of which 5 were decreased in the CNP model controls and increased in the QLJD medication group,while the other 3 increased in the former and decreased in the latter group.Creatinine and genistein were important differential metabolites,and the arginine and proline metabolic pathways and isoflavone biosynthesis pathways were the main ones for QLJD acting on CNP.Compared with the blank controls,the model controls showed up-regulated arginine and proline metabolic pathways,increased production of creatinine,down-regulated isoflavone biosynthetic pathway and decreased produc-tion of genistein.The above changes in the model controls were all reversed in the QLJD medication group.Conclusion:QLJD acts effectively on CNP in male rats by regulating L-arginine and proline metabolic pathways,as well as the isoflavone biosynthesis pathway and naringenin metabolism.

Humans ; Carcinoma, Renal Cell/pathology* ; Kidney Neoplasms/pathology* ; Thinking ; World Health Organization

Purpose: The consequences of severe traumatic injury extend beyond hospital admission and have the potential for long-term functional, psychological, and economic sequalae. This study investigated patient outcomes 6 months following major trauma. Methods: Using the National Trauma Registry, database of patients who were admitted between 2016-18 in a tertiary trauma hospital for major trauma [Injury Severity Score (ISS) ≥ 16] a review was performed on 6-month outcomes [including functional outcomes, self-reported state of health and outcome scores (EuroQol-5 Dimension score and Glasgow Outcome Scale Extended)].Result: There were 637 patients who were treated for major trauma (ISS ≥ 16); the median age was 64 years (range 16-100) and 435 (68.3%) patients were male. The most common injury mechanisms included falling from height (56.5%) and motor vehicle accident (27.0%). The median ISS was 24 (range 16-75). After 6 months, 87.6% of responders were living at home, 25.0% were back to work, and 55.1% were ambulating independently. The median self-rated state of health was 73 at baseline and 64 at 6 months. Age and length of stay were independent predictors of return to ambulation using multivariate analysis. Age, Abbreviated Injury Scale external, Glasgow Coma Scale on Emergency Department arrival, heart rate, and need for transfusion were independent predictors of failure to return to work at 6 months using multivariate analysis. Charlson Comorbidity Index, Glasgow Coma Scale on arrival, temperature, pain and need for inpatient rehabilitation were independent predictors of mortality at 6 months. Conclusion Recovery from major trauma is multi-faceted and requires a team-based approach well beyond discharge.

Objective:To assess the prognostic value of pretreatment 18F-FDG PET/CT metabolic parameters in patients with metastatic malignant melanoma treated with anti-programmed cell death-1 (PD1) immunotherapy. Methods:A retrospective analysis of 29 patients (15 males, 14 females, age (59.1±13.0) years) with pathologically diagnosed metastatic malignant melanoma in Nanjing Drum Tower Hospital between June 2017 and October 2020 was conducted. Anti-PD1 immunotherapy were performed in all patients after 18F-FDG PET/CT imaging. 18F-FDG PET/CT parameters including SUV max, bone marrow-to-liver SUV max ratio (BLR), spleen-to-liver SUV max ratio (SLR) were obtained. Total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) of primary lesions were measured automatically using the thresholds of 40%SUV max. The median value of each PET parameter was regarded as the threshold value and was used to divide patients into 2 groups (≥ and < the median value, respectively). Kaplan-Meier survival curve and Cox proportional risk model were used to analyze the overall survival (OS) differences between groups. Results:The median follow-up time was 15.0 months and 13 patients died. The median OS was 26.0(95% CI: 20.4-31.6) months. The median SUV max, TMTV, TLG, BLR and SLR were 6.2, 8.2 cm 3, 38.6 g, 0.82 and 0.84 respectively. Kaplan-Meier method and log-rank test showed that differences of OS between SUV max≥6.2 and <6.2 groups, TLG≥38.6 g and <38.6 g groups, BLR≥0.82 and <0.82 groups, SLR≥0.84 and <0.84 groups were not significant ( χ2 values: 0.01-0.35, P values: 0.061-0.929), while patients with TMTV≥8.2 cm 3 suffered from poorer OS compared with those with TMTV<8.2 cm 3 ( χ2=5.90, P=0.015). Cox multivariate analysis showed that TMTV (hazard risk ( HR)=6.347, 95% CI: 1.039-38.789) was a significant predictor of OS ( P=0.045). Conclusion:18F-FDG PET/CT parameter TMTV is the independent predictive factor of OS in metastatic melanoma treated with anti-PD1 immunotherapy.

Objective:To investigate the prognostic value of metabolic parameters measured by 18F-FDG PET/CT in patients with primary advanced cutaneous malignant melanoma (CMM). Methods:A retrospective analysis was comprised of 42 patients with advanced CMM (15 males and 27 females; median age: 60.0 years) from Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School between June 2014 and December 2019. All patients were initially diagnosed by pathology, and underwent 18F-FDG PET/CT imaging. 18F-FDG PET/CT parameters including SUV max, SUV mean, total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) of metastatic lesions were measured. ROC curve analysis was performed to obtain the optimal cut-off values of those metabolic parameters for predicting progression-free survival (PFS) and over-all survival (OS). Patients were divided into different groups based on their metabolic parameters (≥cut-off values or

Objective:To explore the prognostic value of 18F-FDG PET-based radiomics features by machine learning in older patients(≥60 years) with diffuse large B-cell lymphoma (DLBCL). Methods:A total of 166 older patients (88 males, 78 females, age: 60-93 years) with DLBCL who underwent pre-therapy 18F-FDG PET/CT from March 2011 to November 2019 were enrolled in the retrospective study. There were 115 patients in training cohort and 51 patients in validation cohort. The lesions in PET images were manually drawn and the obtained radiomics features from patients in training cohort were selected by the least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (Xgboost), and then classified by support vector machine (SVM) to build radiomics signatures (RS) for predicting overall survival (OS). A multi-parameter model was constructed by using Cox proportional hazard model and assessed by concordance index (C-index). Results:A total of 1 421 PET radiomics features were extracted and 10 features were selected to build RS. The univariate Cox regression analysis showed that RS was a predictor of OS (hazard ratio ( HR)=5.685, 95% CI: 2.955-10.939; P<0.001). The multi-parameter model that incorporated RS, metabolic metrics, and clinical risk factors, exhibited significant prognostic superiority over the clinical model, PET-based model, and the National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) in terms of OS (training cohort: C-index: 0.752 vs 0.737 vs 0.739 vs 0.688; validation cohort: C-index: 0.845 vs 0.798 vs 0.844 vs 0.775). Conclusions:RS can be used as a survival predictor for older patients(≥60 years) with DLBCL. Furthermore, the multi-parameter model incorporating RS is able to successfully predict prognosis.

Objective:To explore whether baseline PET metabolic parameters combined with B-cell lymphoma-2 (Bcl-2)/cellular-myelocytomatosis viral oncogene (c-Myc) dual expression (DE) can improve the prognostic stratification of patients with primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL).Methods:From March 2011 to November 2019, 74 patients (33 males, 41 females; age: 20-87 years) pathologically diagnosed with PGI-DLBCL prior to treatment in Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School and the First Affiliated Hospital of Nanjing Medical University were retrospectively included. Baseline PET/CT scans were calculated automatically using the boundaries of voxels presenting a SUV max≥2.5, and metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were determined. Expressions of Bcl-2 and c-Myc were detected at protein levels by immunohistochemistry (IHC). A predicting model comprised of MTV and DE was constructed and patients were divided into 3 groups, including low-risk group (low MTV and non-DE), mediate-risk group (high MTV or DE) and high-risk group (high MTV and DE). The distributions of progression-free survival (PFS) and overall survival (OS) rates were estimated using the Kaplan-Meier method, log-rank test and Cox proportional hazards model. Results:Of 74 patients, 20 relapsed or progressed, 13 died, and 29.7%(22/74) patients were DE positive. Multivariate analysis revealed that MTV (hazard ratio ( HR)=9.110, 95% CI: 1.429-18.615, P=0.012) and DE ( HR=9.837, 95% CI: 1.690-57.260, P=0.011) were independent predictors of PFS, while MTV ( HR=12.470, 95% CI: 3.356-46.336, P<0.001) was the only independent predictor of OS. In the predicting model for PFS, low-risk group ( n=42) and mediate-risk group ( n=20) exhibited significant difference ( χ2=7.84, P=0.005), and mediate-risk group and high-risk group ( n=12) also exhibited significant difference ( χ2=18.72, P<0.001). Conclusions:MTV and DE can independently predict PFS of patients with PGI-DLBCL, and MTV can independently predict OS. The predicting model for PFS combining MTV with DE may further improve the ability of clinicians to stratify patients in terms of differential prognoses.