In order to track the running status of the accelerator in real time, discover potential problems in time, reduce the failure rate, and ensure the safety of radiotherapy patients, a linear accelerator quality management monitoring system is designed based on log files. The system adopts B/S architecture, with the server written in Python3.7 language, and is built based on Django2.2.7 framework. The system uses Python3.7 and Pylinac packages to analyze the log files of each plan, obtaining the planned beam quantity, flux gamma pass rate, and position information of multileaf collimator, etc., to realize the quality monitoring of medical linear accelerator, and customize the development of accelerator spare parts and maintenance management modules. According to statistics, after the establishment of the quality management monitoring system, the accelerator has achieved a 16% reduction in failure rate and a 30% reduction in the downtime rate, which ensures its stable operation in clinical settings.
Particle Accelerators ; Quality Control ; Software

Objective To analyze the influencing factors of malaria infection of labor service exported to overseas in Langfang City, in order to establish a visualization tool to assist clinicians in predicting the risk of malaria. Methods A total of 4 774 expatriate employees of the Nibei Pipeline Project of the Pipeline Bureau from October 2021 to August 2023 were taken as the subjects, and the gender, age, overseas residence area and Knowledge of malaria controlscores of the study subjects were investigated by questionnaire survey, and the possible risk factors of malaria were screened by logistic regression model. At the same time, the nomogram prediction model was established, and the subjects were divided into the training group and the validation group at a ratio of 2:1, and the area under the curve (ROC) and the decision curve were plotted to evaluate the prediction ability and practicability of the prediction model in this study. Results Among the 4 774 study subjects, 96 cases of malaria occurred, and the detection rate was 2.01%. Junior school （OR=1.723，95% CI:1.361-2.173）， and residence in rural areas（OR=2.091，95%CI:1.760 -3.100）were risk factors (OR>1), while protective measures（OR=0.826，95% CI : 0.781 - 0.901） and high malaria education scores （OR=0.872，95% CI : 0.621 - 0.899）were protective factors.The nomogram prediction model results showed that the area under the curve of the nomogram prediction model in the training group was 0.94 (95% CI : 0.85 - 1.00), while the validation group was 0.93 (95% CI : 0.80 - 1.00). The results of the decision curve showed that when the threshold probability of the population was 0-0.9, the nomogram model was used to predict the risk of malaria occurrence with the highest net income. Conclusion The nomogram prediction model (including gender, education, region, protection and malaria education score) established and validated in this study is of great value for clinicians to screen high-risk patients with malaria.

Objective : To explore the effects and mechanisms of Kobophenol A ( KPA) on lipopolysaccharide ( LPS) -induced M1 macrophage polarization，and to provide a theoretical basis for the treatment of inflammatory immune diseases and the development of new drugs． Methods: The M1 macrophage polarization model of RAW264. 7 was established by LPS induction，and the peroxiredoxin 6 ( Prdx6) knockdown model was constructed using the Prdx6 inhibitor MJ33 and Prdx6-siRNA．RAW264. 7 cells，a mouse macrophage cell line，were treated with various concentrations of KPA． Cell viability was assessed using the CCK-8 assay．The expression levels of Prdx6 and M1 macrophage polarization-related proteins，including inducible nitric oxide synthase ( iNOS) and cyclooxygenase-2 ( COX-2) ，were detected by Western blot and immunofluorescence staining．The expression levels of Prdx6 and M1 macrophage polarization-related genes iNOS，interleukin-6 ( IL-6) ，and tumor necrosis factor α ( TNF-α) ，were measured by RT-qPCR. Flow cytometry was employed to detect the expression of cluster of differentiation 86 ( CD86) ，a marker of M1 macrophages． Results: Compared with the LPS-induced M1 macrophage polarization model ， KPA significantly reversed the morphological changes of M1 macrophage polarization in RAW264. 7 macrophages and decreased the expression of M1 macrophage polarization-related proteins iNOS，COX- 2，CD86 and related genes iNOS，IL-6，TNF-α ( all P＜0. 05) ．In addition，LPS significantly downregulated the expression of Prdx6 in RAW264. 7 macrophages，while KPA upregulated the expression of Prdx6．Moreover，treatment with the Prdx6 inhibitor MJ33 significantly upregulated the expression of iNOS，a marker of M1 macrophage polarization，in RAW264. 7 macrophages，whereas treatment with KPA significantly downregulated the expression of iNOS ( all P＜0. 05) ． Conclusion KPA inhibits LPS-induced M1 polarization of RAW264. 7 macrophages by upregulating the expression of Prdx6．

Objective To investigate the relationship between serum cyclophilin A(CypA),ischemia modi-fied albumin(IMA),galectin-3(Gal-3)levels and oxidative stress and cognitive impairment(CI)in patients with acute cerebral infarction(ACI)complicated with obstructive sleep apnea hypopnea syndrome(OSAHS).Methods A total of 168 patients with ACI complicated with OSAHS who were admitted to the hospital from December 2020 to October 2023 were selected,and the levels of serum CypA,IMA,Gal-3 and oxidative stress indexes[superoxide dismutase(SOD),malondialdehyde(MDA)]in patients with different severity(mild group,moderate group,severe group)were compared.The correlation between serum CypA,IMA,Gal-3 lev-els and oxidative stress indexes were analyzed by Pearson method.The incidence of CI in patients with ACI complicated with OSAHS were statistically analyzed,the levels of serum CypA,IMA and Gal-3 were com-pared between normal cognitive group and CI group,and the risk factors of CI in patients with ACI complicat-ed with OSAHS were analyzed by multivariate Logistic regression model.Results The levels of serum CypA,IMA,Gal-3 and MDA in mild group,moderate group and severe group increased in turn(P<0.05),and ser-um SOD level decreased in turn(P<0.05).Serum CypA,IMA and Gal-3 in ACI patients complicated with OSAHS were negatively correlated with SOD(P<0.05),and positively correlated with MDA(P<0.05).Of 168 ACI patients complicated with OSAHS,79 cases(47.02%)had CI and were included in the CI group.Compared with normal cognitive group,the serum levels of CypA,IMA and Gal-3 in CI group were signifi-cantly increased(P<0.05).Multivariate Logistic regression model analysis showed that apnea hypopnea in-dex(AHI)≥20 times/h,frontal and temporal lobe infarction,elevated CypA level,elevated IMA level,and el-evated Gal-3 level were risk factors for CI in ACI patients complicated with OSAHS(P<0.05).Conclusion The high expression of serum CypA,IMA and Gal-3 in patients with ACI complicated with OS-AHS is significantly correlated with oxidative stress and CI.The increase of serum CypA,IMA and Gal-3 lev-els indicates an increased risk of CI in patients with ACI complicated with OSAHS,and early detection of the three has good clinical value in evaluating the condition of patients with ACI complicated with OSAHS.

Objective To explore the expression and clinical significance of tissue inhibitor of matrix metal-loproteinases(TIMP)-1 and pentraxin-3(PTX3)in the serum of patients with obstructive sleep apnea-hypop-nea syndrome(OSAHS).Methods A total of 120 patients with OSAHS admitted to the hospital from 2021 to 2022 were selected as the study group,and another 114 healthy people who underwent the physical exami-nation in the same period were selected as the control group.The severity of OSAHS was determined accord-ing to the apnea-hypopnea index(AHI)and the minimum oxygen saturation(LSpO2),and the patients were divided into mild group(66 cases)and the moderate-severe group(54 cases).Serum TIMP-1 and PTX3 levels were measured by enzyme-linked immunosorbent assay.Pearson method was used to analyze the correlation between serum TIMP-1,PTX3 and AHI,LSpO2.Receiver operating characteristic(ROC)curve was used to analyze the predictive value of serum TIMP-1 and PTX3 on the severity of disease in patients with OSAHS.Logistic regression was used to analyze the factors influencing the severity of the disease in OSAHS patients.Results Serum TIMP-1,PTX3 and AHI levels in the study group were higher than those in the control group,and LSpO2 level was lower than that in the control group(P<0.05).The body mass index(BMI),the proportion of hypertension history,the proportion of coronary heart disease history,the levels of total choles-terol,triglycerides,low-density lipoprotein cholesterol,TIMP-1,PTX3 and AHI in the moderate-severe group were significantly higher than those in the mild group,and the high density lipoprotein cholesterol,LSpO2 lev-el was significantly lower than that in the mild group(P<0.05).Pearson method results showed that serum TIMP-1,PTX3 levels were positively correlated with AHI(r=0.428,0.392,P<0.05),and serum TIMP-1,PTX3 levels were negatively correlated with LSpO2(r=-0.645,-5.836,P<0.05).The results of the ROC curve showed that the area under the curve(AUC)of serum TIMP-1 and PTX3 alone predicted the severity of the patients'disease was 0.813 and 0.777,with cut-off values were 2.47 μg/L and 7.23 ng/L,with the sensi-tivity of 70.37%and 77.78%and the specificity of 77.27%and 72.23%,respectively.The AUC for predic-ting the severity of patients'disease by combining the two was 0.866,which was significantly higher than those of serum TIMP-1(Z=2.067,P=0.039)and PTX3 alone(Z=2.331,P=0.020).Logistic regression a-nalysis showed that TIMP-1,PTX3,history of hypertension,and history of coronary artery disease,AHI and LSpO2 were influential factors for severity of disease in patients with OSAHS(P<0.05).Conclusion TIMP-1 and PTX3 are both up-regulated in the serum of OSAHS patients and closely related to the severity of the disease,and they are the influential factors in the severity of OSAHS patients.

Objective To evaluate the roles of telomerase,interferon-γ(IFN-γ),adenosine deaminase(ADA)and T cell spot test(T-SPOT.TB)in the diagnosis of tuberculous and malignant pleural effusion.Methods Forty patients with early tuberculous pleurisy(tuberculosis group)and 40 patients with malignant pleural effusion(tumor group)were enrolled.Pleural effusion and fasting blood were extracted before treatment.The activity of telomerase and the concentration of IFN-γ were detected by enzyme-linked immunosorbent assay.The activity of ADA was detected by colorimetric analysis.The positive rate of T-SPOT.TB was detected by Elispot spot counting.Results Telomerase activity in the tuberculosis group was significantly lower than that in the tumor group([1.46±0.73]×10-3 nmol/L vs.[3.34±1.72]×10-3 nmol/L,P<0.01).The concentration of IFN-γ was(137.44±38.93)U/L and(27.94±8.46)U/L in the tuberculosis group and tumor group,respectively;ADA content was(68.42±9.58)U/L and(15.39±4.43)U/L.There were significant differences in IFN-γ and ADA between the 2 group(P<0.01).IFN-γ concentration,ADA activity and the positive rate of T-SPOT.TB in the tuberculosis group were significantly higher than those in the tumor group(P<0.01).The sensitivity and specificity of combined detection of telomerase,IFN-γ,ADA and T-SPOT.TB in differentiating tuberculous and malignant pleural effusion were 0.974 and 0.974,respectively.Conclusion The combined detection of telomerase,IFN-γ,ADA and T-SPOT.TB has important value in differential diagnosis of tuberculosis and malignant pleural effusion.

Objective:To investigate the diagnostic value of urine pH, serum uric acid and related clinical indicators in the diagnosis of urinary infection stones, and to construct a prediction nomogram.Methods:The clinical data of 432 patients with urinary calculi admitted to Xuzhou Central Hospital from August 2018 to November 2023 were retrospectively analyzed. The study included 289 males and 143 females, with an average age of (52.72±13.46) years old. Among the patients, there were 98 cases of hypertension, 67 cases of diabetes, and 100 cases of recurrent calculi. Kidney stones were present in 152 cases, ureteral stones in 242 cases, and bladder stones in 38 cases. Urine bacterial culture yielded positive results in 97 cases. According to the results of postoperative stone composition analysis, the two groups were categorized as infection and no-infection stone groups, and the differences in general data between the two groups were compared. Univariate and multivariate logistic regression analysis were conducted to assess the diagnostic value of urine pH, serum uric acid, and related clinical indicators for urinary infection stones. Receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to evaluate the clinical significance of urine pH, serum uric acid, and combined indexes in preoperatively diagnosing urinary infection stones, as well as constructing a nomogram prediction model.Results:There were 127 cases of infection stones and 305 cases of no-infection stones. The infection stone group exhibited a higher urine pH value [7.0(6.5, 7.5) vs. 6.0(5.5, 6.5), P<0.001], lower serum uric acid levels [(301.38±70.12) vs. (358.88±88.99) μmol/L, P<0.001], a higher proportion of females [55.1%(70/127) vs. 23.9%(73/305), P<0.001], younger age [(48.36±14.83)vs. (53.12±12.61)years old, P<0.001], a higher proportion of recurrence stones [34.6 %(44/127) vs. 18.4%(56/305), P<0.001], and a higher rate of positive urine bacteria culture[29.9%(38/127)vs. 19.3%(59/305), P=0.016]and nitrite test results [18.9%(24/127)vs. 6.3%(19/305), P <0.001]. Univariate logistic regression analysis revealed that urine pH value, serum uric acid levels, gender, age, recurrent stones, urine bacterial culture, and urine nitrite were associated with urinary infection stones ( P< 0.05). Multivariate logistic regression analysis revealed that urine pH value ( OR= 4.836, 95% CI 3.342-6.997), female gender( OR=2.320, 95% CI 1.286-4.186), recurrent stones ( OR=2.225, 95% CI 1.208-4.101), positive urine bacterial culture ( OR=2.061, 95% CI 1.094-3.883), serum uric acid ( OR=0.992, 95% CI 0.949-0.989), age ( OR=0.969, 95% CI 0.949-0.990) were independent risk factors for urinary infection stones ( P<0.05). The combined diagnostic value of six indicators was the highest, with an AUC of 0.874 (95% CI 0.837-0.911). Following this, urine pH exhibited an AUC of 0.818 (95% CI 0.778-0.858), while serum uric acid had an AUC of 0.704 (95% CI 0.652-0.756). The nomogram model was successfully constructed based on the six indicators. The mean AUC of the ROC curve after 1 000 resamples of the Bootstrap method was 0.864 (95% CI 0.828-0.900), and the calibration curve showed that the predicted curve fit the ideal curve well, with a mean absolute error of 0.005 and a Hosmer-Lemeshow test of P>0.05. Clinical decision curve analysis (DCA) showed that the model had a higher net clinical benefit when the model had a threshold probability value≥0.01. Conclusions:Urine pH and serum uric acid are closely related to urinary infection stones. A nomogram model combining these factors with gender, age, recurrent stones, and urine culture results can effectively predict the probability of infection-related stones, providing significant clinical value.

Objective:To investigate the diagnostic value of urine pH, serum uric acid and related clinical indicators in the diagnosis of urinary infection stones, and to construct a prediction nomogram.Methods:The clinical data of 432 patients with urinary calculi admitted to Xuzhou Central Hospital from August 2018 to November 2023 were retrospectively analyzed. The study included 289 males and 143 females, with an average age of (52.72±13.46) years old. Among the patients, there were 98 cases of hypertension, 67 cases of diabetes, and 100 cases of recurrent calculi. Kidney stones were present in 152 cases, ureteral stones in 242 cases, and bladder stones in 38 cases. Urine bacterial culture yielded positive results in 97 cases. According to the results of postoperative stone composition analysis, the two groups were categorized as infection and no-infection stone groups, and the differences in general data between the two groups were compared. Univariate and multivariate logistic regression analysis were conducted to assess the diagnostic value of urine pH, serum uric acid, and related clinical indicators for urinary infection stones. Receiver operating characteristic (ROC) curve and area under curve (AUC) were utilized to evaluate the clinical significance of urine pH, serum uric acid, and combined indexes in preoperatively diagnosing urinary infection stones, as well as constructing a nomogram prediction model.Results:There were 127 cases of infection stones and 305 cases of no-infection stones. The infection stone group exhibited a higher urine pH value [7.0(6.5, 7.5) vs. 6.0(5.5, 6.5), P<0.001], lower serum uric acid levels [(301.38±70.12) vs. (358.88±88.99) μmol/L, P<0.001], a higher proportion of females [55.1%(70/127) vs. 23.9%(73/305), P<0.001], younger age [(48.36±14.83)vs. (53.12±12.61)years old, P<0.001], a higher proportion of recurrence stones [34.6 %(44/127) vs. 18.4%(56/305), P<0.001], and a higher rate of positive urine bacteria culture[29.9%(38/127)vs. 19.3%(59/305), P=0.016]and nitrite test results [18.9%(24/127)vs. 6.3%(19/305), P <0.001]. Univariate logistic regression analysis revealed that urine pH value, serum uric acid levels, gender, age, recurrent stones, urine bacterial culture, and urine nitrite were associated with urinary infection stones ( P< 0.05). Multivariate logistic regression analysis revealed that urine pH value ( OR= 4.836, 95% CI 3.342-6.997), female gender( OR=2.320, 95% CI 1.286-4.186), recurrent stones ( OR=2.225, 95% CI 1.208-4.101), positive urine bacterial culture ( OR=2.061, 95% CI 1.094-3.883), serum uric acid ( OR=0.992, 95% CI 0.949-0.989), age ( OR=0.969, 95% CI 0.949-0.990) were independent risk factors for urinary infection stones ( P<0.05). The combined diagnostic value of six indicators was the highest, with an AUC of 0.874 (95% CI 0.837-0.911). Following this, urine pH exhibited an AUC of 0.818 (95% CI 0.778-0.858), while serum uric acid had an AUC of 0.704 (95% CI 0.652-0.756). The nomogram model was successfully constructed based on the six indicators. The mean AUC of the ROC curve after 1 000 resamples of the Bootstrap method was 0.864 (95% CI 0.828-0.900), and the calibration curve showed that the predicted curve fit the ideal curve well, with a mean absolute error of 0.005 and a Hosmer-Lemeshow test of P>0.05. Clinical decision curve analysis (DCA) showed that the model had a higher net clinical benefit when the model had a threshold probability value≥0.01. Conclusions:Urine pH and serum uric acid are closely related to urinary infection stones. A nomogram model combining these factors with gender, age, recurrent stones, and urine culture results can effectively predict the probability of infection-related stones, providing significant clinical value.

Objective:To analyze the correlation between serum ferritin (SF), perilipin, leptin and the outcome of patients with gestational diabetes mellitus (GDM).Methods:From October 2017 to December 2019, 126 patients with GDM who underwent maternity checkups in Baoding Fourth Central Hospital and gave birth were selected as the GDM group, and 82 normal pregnant women during the same period were selected as the control group for retrospective analysis. The levels of serum SF, perilipin, and leptin in the GDM group and the control group were measured and compared, and the expressions of serum indexes of patients with different blood glucose control and different pregnancy outcomes in the GDM group were measured. Pearson correlation analysis was used to explore the correlation between the expression of serum indexes in GDM patients and fasting blood glucose (FPG), 2 h postprandial blood glucose (2 h PG), and insulin resistance index (HOMA-IR). Logistic regression was used to analyze the relationship between the expression of serum indicators and adverse pregnancy outcomes in GDM patients. The receiver operating characteristic (ROC) curve was used to observe the value of single serum indexes and to predict the pregnancy outcome of GDM patients.Results:The levels of SF, perilipin and leptin in GDM group were higher than those in control group: (152.48 ± 37.64) μg/L vs. (109.27 ± 32.16) μg/L, (857.06 ± 192.35) ng/L vs. (262.83 ± 104.7) ng/L, (23.54 ± 2.28) μg/L vs.(14.62 ± 1.83) μg/L, the differences were statistically significant ( P<0.05). The levels of SF, perilipin and leptin in patients with good blood glucose control in GDM group were lower than those in patients with poor blood glucose control: (132.10 ± 36.52) μg/L vs. (176.37 ± 40.06) μg/L, (176.37 ± 40.06) ng/L vs. (946.42 ± 205.37) ng/L, (21.49 ± 2.16) μg/L vs. (25.94 ± 2.40) μg/L, the differences were statistically significant ( P<0.05). The levels of serum SF, perilipin and leptin in GDM patients were positively correlated with FPG, 2 h PG and HOMA-IR levels ( P<0.05). The levels of serum SF, perilipin and leptin in GDM patients with adverse pregnancy outcomes were higher than those in patients without occurrence: (182.86 ± 42.29) μg/L vs. (138.86 ± 35.47) μg/L, (1 013.35 ± 216.07) ng/L vs. (787.00 ± 183.49) ng/L, (27.04 ± 2.5) μg/L vs. (21.97 ± 2.07) μg/L, the differences were statistically significant ( P<0.05). Logistic regression analysis showed that serum SF, perilipin and leptin were closely related to the adverse pregnancy outcomes in GDM patients ( P<0.05). ROC curve analysis showed that the sensitivity and the specificity of SF, perilipin, leptin combined detection to predict GDM patients with adverse pregnancy outcomes was 76.92% and 83.91%. Conclusions:The serum SF, perilipin and leptin are abnormally high expression in GDM patients, and it is positively correlated with blood glucose level and HOMA-IR. Joint detection can improve the predictive value of adverse pregnancy outcomes and provide a basis for early intervention.

Objective:To evaluate the implementation of the China Healthcare Improvement Initiative(CHII)from 2018 to 2020 in 143 tertiary public hospitals in China.Methods:In March 2019 and from January to March in 2021, 143 tertiary public hospitals in 31 provinces of China were investigated using the unified " medical institution questionnaire Ⅰ" and " medical institution Questionnaire Ⅱ" . The data were collected by means of hospital self-report and expert on-site scoring. Descriptive and inferential statistical analysis were used to analyze the data, and the data of two cross-sectional surveys were compared and analyzed.Results:The average score rate of implementing CHII in 143 sample hospitals in 2020 was 88.9%, which was higher than that in 2018(84.4%). The appointment diagnosis and treatment system, clinical pathway management system, day service, smart hospital and humanistic service were significantly improved. In 2020, the average score rate of logistics service, high quality nursing service and clinical pathway management system was higher than 95%, while the average score rate of day service, telemedicine system and medical social work system was lower than 85%. The total score rate of general hospitals was significantly higher than that of specialized hospitals( P<0.001). In 2020, the proportion of hospitals with full marks in 29 secondary indicators(74.4%)was more than 80%, reaching the standard level. Conclusions:The implementation level of CHII in tertiary public hospitals in China has been improved continuously and made significant progress, but some dimensions and indicators need to be further improved.