OBJECTIVE To investigate the effects of ertugliflozin on pharmacokinetic of sorafenib and donafenib in rats and explore the mechanism. METHODS Twenty-four male SD rats were randomly divided into four groups， with 6 rats in each group. Groups A and B were respectively gavaged with 0.5% sodium carboxymethyl cellulose solution and ertugliflozin （1.5 mg/kg） for 7 consecutive days， and both were given sorafenib （100 mg/kg） on the 7th day. Groups C and D were administered intragastrically in the same way as those in Groups A and B， respectively， for the first 7 days； after the drug administration on the 7th day， all rats in Groups C and D were further gavaged with donafenib （40 mg/kg）. Blood samples were collected at different time points before and after administration of sorafenib or donafenib， the concentrations of sorafenib in plasma of rats in groups A and B and donafenib in groups C and D were determined by UPLC-MS/MS method. The pharmacokinetic parameters were calculated by DAS 2.1.1 software. Six additional rats were randomly divided into blank control group and ertugliflozin group， with three rats in each group. Blank control group was given 0.5% sodium carboxymethyl cellulose intragastrically， while rats in ertugliflozin group were given ertugliflozin （1.5 mg/kg） once a day for 7 consecutive days. After the last administration， the mRNA expression levels of uridine diphosphate glucuronosyl transferase 1A7 （UGT1A7）， breast cancer resistance protein （BCRP）， and P-glycoprotein （P-gp） in the liver and small intestine tissues of the rats were detected. RESULTS Compared with group A， the AUC0-t， AUC0-∞， cmax， tmax， MRT0-t and MRT0-∞ of sorafenib in group B were decreased significantly， while CL and V were increased significantly. Compared with group C， the AUC0-t， AUC0-∞ ， tmax， cmax and MRT0-t of Δ donafenib in group D were decreased significantly， while V and CL were increased significantly （P＜0.05）. mRNA expression of UGT1A7， P-gp and BCRP in the liver tissue and small intestine of rats were not significantly affected after intragastric administration of ertugliflozin for 7 consecutive days. CONCLUSIONS Ertugliflozin can affect the pharmacokinetics of sorafenib and donafenib in rats and decrease the plasma exposure of them significantly. However， its mechanism of action may not be through the regulation of related metabolic enzymes and transporters. When using drugs in combination clinically， one should be vigilant about the potential for disease progression due to poor therapeutic effects.

A method for the pretreatment and qualitative detection of 26 trace cathinone new psychoactive substances in wastewater was established and applied in actual wastewater cases. The effluent samples were eluted on the Oasis PRiME HLB solid phase extraction column by ultra-pure water drenching and methanol solution, then dried with nitrogen at 40 ℃, and finally re-dissolved with 0.1% formic acid-acetonitrile solution (95∶5), and detected by liquid chromatography-tandem mass spectrometry, The effluent sample was determined by high-performance liquid chromatography-Tandem mass spectrometry (HPLC-MS/MS) using selected reaction monitoring (SRM) mode and separated on chromatographic column UPLC BEH C18(100 mm×2.1 mm, 1.7 μm） at 35 ℃ with a mobile phase consisting of acetonitrile-0.1% formic acid in aqueous solution gradient elution. After methodological validation, the lower quantification of 26 cathinone new psychoactive substances could reach 1.50−3.00 ng/L. Among these, 21 analytes fell within the concentration range of 1.50−375.0 ng/L, while 5 were detected in the range of 3.00−750.0 ng/L, the correlation coefficient was 0.99, within-and between-batch precision was less than 7.71% and 13.91%, respectively, and the extraction recoveries were higher than 92.64% . The method is simple, accurate, and sensitive, and can be used for cathinone detection and abuse monitoring.

Objective: To investigate the health-related quality of life and its influencing factors in elderly patients with metabolic syndrome (MS), so as to provide the evidence for improving health-related quality of life in older adults with chronic diseases. Methods: In 2021, elderly MS patients aged ≥60 years from four districts in Nanjing City were selected as the study subjects using a multi-stage random sampling method. Data on social demographic information, lifestyle, disease history and blood biochemical indicators were collected through questionnaire surveys, physical examination and laboratory tests. Health utility value and EuroQol Visual Analog Scale (EQ-VAS) score were assessed using the EuroQol 5-dimension 3-level questionnaire. Factors affecting health-related quality of life were identified with the Tobit regression model and multiple linear regression model. Results: A total of 3 378 elderly MS patients were included, with a median age of 67.00 (interquartile range, 7.00) years. There were 1 558 males (46.12%) and 1 820 females (53.88%). The median (interquartile range) of health utility value and EQ-VAS score were 1.00 (0.03) and 80.00 (15.00). Tobit regression and multiple linear regression analysis showed that gender (female, β=-0.034), education level (middle school, β=0.024; junior college and above, β=0.046), marital status (married, β=0.014), physical activity (sufficient, β=0.013), vegetable intake (meet standard, β=-0.009) and fruit intake (meet standard, β=0.016) were the influencing factors of health utility value. Residence (urban area, β=1.933) and alcohol consumption (yes, β=1.761) were influencing factors of EQ-VAS score. Age, cardiovascular and cerebrovascular diseases, malignant tumors and chronic respiratory diseases were the influencing factors of health utility value and EQ-VAS score. Conclusion Age, sex, marital status, residence, lifestyle and disease are mainly associatied with the health-related quality of life in elderly MS patients.

Objective To investigate the frequency of therapy-oriented oral radiation in Nanping, China and its distribution, and to provide a basis for the rational application of therapy-oriented oral radiation and the effective allocation of resources in Nanping. Methods A questionnaire was designed to investigate the frequency of therapy-oriented oral radiation in all oral radiation diagnosis and treatment institutions in Nanping. Results In 2021, there were 54 oral radiation diagnosis and treatment institutions and 79 oral radiation machines in Nanping. The total frequency of therapy-oriented oral radiation was 61593 visits and the radiation frequency was 19.54 visits per thousand patients. The average annual frequency of medical institutions at all levels was 721.87 to 3713.25 visits per institution; the male-to-female composition ratio of frequency of therapy-oriented oral radiation in December 2021 was 50.5%:49.5%. The proportion of radiation frequency of different devices was as follows: 38.7% (intraoral dental film), 46.5% (oral panorama), 10.3% (oral computed tomography [CT]), and 4.5% (cranial photography). The proportion of radiation frequency in patients of different ages was as follows: 17.1% (0−15 years), 48.2% (15−40 years), and 34.7% (over 40 years). The frequency of therapy-oriented oral radiation grew by 77.43%, 35.18%, and 8.16% every two years from 2015 to 2021, respectively. Conclusion The frequency level of therapy-oriented oral radiation in Nanping is at the level of Class II health care. The distribution of therapy-oriented oral radiation is highly unbalanced and is related to the level of economic development. Private healthcare institutions are growing rapidly, and public healthcare institutions of grade two and above occupy the main healthcare resources. The oral panorama accounts for the most, cranial photography accounts for the least, and oral CT is the fastest-growing portion. Therapy-oriented oral radiation is predominantly performed in the young and middle-aged populations, regardless of sex. Except for intraoral dental films, the general trend is upward.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

This paper summarized Professor LI Yueqing's clinical experience in treating prostate cancer by stages from the perspective of deficiency and stasis. It is believed that the onset of prostate cancer is due to kidney deficiency， while blood stasis is the core pathogenesis， and dampness-heat， phlegm-turbid， and cancer toxins are the key pathological factors in the progression of the disease. The pathogenesis in the early stage of the disease is kidney qi depletion and dampness， heat and phlegm coagulation； in the middle stage， it is spleen and kidney depletion， phlegm coagulation and blood stasis； and in the late stage， the pathogenesis changes into yin deficiency and essence depletion， and stasis-turbid toxin obstruction. For treatment， the basic principle is to supplement and boost kidney qi， enrich and nourish the kidney yin. The main treatment methods are draining dampness， dissolving phlegm， dispelling stasis， clearing heat and resolving toxins， and the method of invigorating blood and dispelling stasis runs through the whole course of treatment. In the early stage， radical treatment is mainly used， and Longshe Yangquan Decoction （龙蛇羊泉汤） with modifications is supplemented to clear and drain dampness and heat. In the middle stage， androgen deprivation therapy is the basic treatment， and Bushen Tongqiao Decoction （补肾通窍汤） with modifications is used in combination to nourish the spleen and kidney， dissolve phlegm and dispel stasis. In the late stage， Dabuyin Pills and Liuwei Dihuang Pills （大补阴丸合六味地黄丸） with modifications is mainly used to enrich yin and supplement essence， resolve toxins and dissolve stasis， and prevent cancer recurrence.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Objective:To compare the difference between the Evidence Quality Grading System for Public Health Decision-making(PHE-Grading)and the Grading of Recommendations Assessment,Development and Evaluation(GRADE)System in evaluating the quality of evidence for public health decision-making.Methods:Systematic reviews about topic"Public health"were electronically searched in the Cochrane Library database from inception to February 27,2024.EndNote 20 software was used for literature screening,Excel 2021 and SPSS 22.0 software were used for data collation and analysis,and the forest plot was drawn by RevMan 5.4.1 software.Results:A total of 61 systematic reviews were finally included for evidence quality evaluation.The forest plot of GRADE and PHE-Grading evidence grading results showed that high grade[OR:2.39,95%CI(1.21 to 4.75)],moderate grade[OR:0.40,95%CI(0.31 to 0.52)],low grade[OR:0.37,95%CI(0.29 to 0.46)],and extremely low grade[OR:85.11,95%CI(34.80 to 208.11)],and the differences in evidence quality grading results between the two systems were statistically significant.Conclusions:Compared with GRADE,PHE-Grading may be more accurate in grasping the certainty of public health decision-making evidence.Currently,the quality of public health decision-making evidence is still concentrated in low and middle level,and high-quality research still needs to be strengthened to support scientific decision-making.