Objective To establish an ultra-high performance liquid phase tandem triple quadrupole mass spectrometry method for the determination of L-synephrine in rat plasma and to study its pharmacokinetics.Methods The plasma samples were precipitated by acetonitrile vortex,centrifuged,dried by nitrogen,dissolved by mobile phase,and then analyzed.Chromatographic column:Shiseido CAPCELL PAK CR(1∶4)column(2.0 mm × 150.0 mm,5 μm),temperature:25 ℃.Mobile phase:Acetonitrile:0.1％formic acid solution(containing 10 mmoL·L-1 ammonium formate)(73∶27)with flow rate:0.3 mL·min-1 and injection volume was 2 μL.The electrospray ion source ionization and positive ion multiple reaction monitoring mode were used for mass spectrometry detection,and biological sample methodology verification was carried out according to requirements.After intragastric administration with 5 mg·kg-1 dose of L-synephrine,blood samples were collected at different time points to investigate the pharmacokinetic characteristics of L-synephrine in rats.Results L-synephrine showed a good linear relationship in the range of 2-800 ng·mL-1,the lowest limit of quantification of L-synephrine was 2 ng·mL-1.Precision,extraction recovery,matrix effect,accuracy,dilution effect and residual effect all meet the requirements all met the requirements.The main pharmacokinetic parameters:Cmax were(464.83±76.68)ng·L-1,tmax were(0.67±0.26)h,t1/2z were(1.89±0.48)h,AUC0-t were(602.26±42.25)ng·mL-1·h-1,AUC0-∞ were(612.28±41.18)ng·mL-1·h-1.Conclusion The established ultra high performance liquid chromatography-tandem triple quadrupole mass spectrometry method for the determination of L-synephrine in rat plasma is simple and rapid,and can be used for the determination of L-synephrine in plasma.

Objective To observe the safety and effectiveness of single dose intravenous infusion of tranexamic acid(TX-A)in dual level posterior lumbar interbody fusion(PLIF),and to explore the changes and trends in perioperative white blood cell(WBC),erythrocyte sedimentation rate(ESR),and C-reactive protein(CRP).Methods Between October 2020 and September 2022,46 patients with lumbar degenerative disease were treated with dual level PLIF,including 18 males and 28 females,with an average age of(60.24±10.68)years old,from 34 to 80 years old.They were divided into observation group and control group according to different treatment methods.There were 28 patients in the observation group,including 12 males and 16 females,with an average age of(61.04±9.03)years old.There were 3 cases with lumbar disc herniation(LDH),lumbar spinal stenosis(LSS)18 cases,lumbar spondylolisthesis(LS)7 cases.TXA(1 g/100 ml)was administered intravenously 15 min before skin incision after general anesthesia.The control group consisted of 18 patients,including 6 males and 12 females,with an average age of(59.00±13.04)years old.There were 5 cases with LDH,LSS 9 cases,LS 4 cases,and TXA was not used.The operation time,intraoperative bleeding volume,postoperative drainage volume,postoperative deep vein thrombosis(DVT),postoperative hospital stay,postoperative activated partial thromboplastin time(APTT),prothrombin time(PT),thrombin time(TT),fibrinogen(FIB),platelet(PLT),red blood cell(RBC),hemoglobin(HB),hematocrit(HCT),the first day,the fourth day,the seventh day and the last tested after operation WBC,ESR and CRP were recorded.Results The postop-erative wounds of the patients healed well and there was no DVT.46 patients were followed up from 3 to 6 months.The intraop-erative blood loss was 400.0(300.0,500.0)ml and the postoperative drainage was 260.0(220.0,450.0)ml in the observation group,which were lower than the control group[600.0(400.0,1000.0)ml,395.0(300.0,450.0)ml],P＜0.05.There was no significant difference between the two groups in operation time,postoperative hospital stay,postoperative APTT,PT,TT,FIB,PLT,RBC,HB,HCT,and postoperative WBC,ESR and CRP at different times(P＞0.05).Conclusion Single dose intravenous infusion of TXA can reduce the blood loss of bi-segmental PLIF,and has no significant effect on WBC,ESR and CRP after op-eration.

Objectives: . Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model. Methods: . We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression. Results: . Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways. Conclusion . Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.

Objectives: . Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model. Methods: . We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression. Results: . Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways. Conclusion . Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.

Objectives: . Our study aimed to explore the role of the potassium channel KCNK1 in head and neck squamous cell carcinoma, focusing on its impact on tumor growth, invasion, and metastasis. We also investigated the therapeutic potential of quinidine, a known KCNK1 inhibitor, in both in vitro cell lines and a zebrafish patient-derived xenograft (PDX) model. Methods: . We established primary cell cultures from head and neck cancer tissues and employed the FaDu cell line for in vitro studies, modulating KCNK1 expression through overexpression and knockdown techniques. We evaluated cell migration, invasion, and proliferation. Additionally, we developed a zebrafish PDX model to assess the impact of quinidine on tumor growth and metastasis in vivo. RNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to elucidate the molecular mechanisms underlying the role of KCNK1 in cancer progression. Results: . Overexpression of KCNK1 in FaDu cells resulted in enhanced cell migration and invasion, whereas its knockdown diminished these processes. In the zebrafish PDX model, quinidine markedly inhibited tumor growth and metastasis, demonstrating a significant reduction in tumor volume and micrometastasis rates compared to the control groups. The molecular analyses indicated that KCNK1 plays a role in critical signaling pathways associated with tumor growth, such as the Ras and MAPK pathways. Conclusion . Our findings highlight the critical role of KCNK1 in promoting tumor growth and metastasis in head and neck cancer. The inhibitory effect of quinidine on tumor progression in the zebrafish PDX model highlights the therapeutic potential of targeting KCNK1. These results suggest that KCNK1 could serve as a valuable therapeutic target for head and neck cancer, warranting further investigation into treatments that target KCNK1.

Objective: To report the long-term survival of renal cell carcinoma (RCC) patients treated with radical nephrectomy in Sun Yat-sen University Cancer Center. Methods: We retrospectively analyzed the clinical, pathological and follow-up records of 1 367 non-metastatic RCC patients treated with radical nephrectomy from 1999 to 2020 in this center. The primary endpoint of this study was overall survival rate. Survival curves were estimated using the Kaplan-Meier method, and group differences were compared through Log-rank test. Univariate and multivariate Cox analysis were fit to determine the clinical and pathological features associated with overall survival rate. Results: A total of 1 367 patients treated with radical nephrectomy with complete follow-up data were included in the study. The median follow-up time was 52.6 months, and 1 100 patients survived and 267 died, with the median time to overall survival not yet reached. The 5-year and 10-year overall survival rates were 82.8% and 74.9%, respectively. The 5-year and 10-year overall survival rates of Leibovich low-risk patients were 93.3% and 88.2%, respectively; of Leibovich intermediate-risk patients were 82.2% and 72.3%, respectively; and of Leibovich high-risk patients were 50.5% and 30.2%, respectively. There were significant differences in the long-term survival among the three groups (P<0.001). The 10-year overall survival rates for patients with pT1, pT2, pT3 and pT4 RCC were 83.2%, 73.6%, 55.0% and 31.4%, respectively. There were significant differences among pT1, pT2, pT3 and pT4 patients(P<0.001). The 5-year and 10-year overall survival rates of patients with lymph node metastasis were 48.5% and 35.6%, respectively, and those of patients without lymph node metastasis were 85.1% and 77.5%, respectively. There was significant difference in the long-term survival between patients with lymph node metastasis and without lymph node metastasis. The 10-year overall survival rate was 96.2% for nuclear Grade 1, 81.6% for nuclear Grade 2, 60.5% for nuclear Grade 3, and 43.4% for nuclear Grade 4 patients. The difference was statistically significant. There was no significant difference in the long-term survival between patients with localized renal cancer (pT1-2N0M0) who underwent open surgery and minimally invasive surgery (10-year overall survival rate 80.5% vs 85.6%, P=0.160). Multivariate Cox analysis showed that age≥55 years (HR=2.11, 95% CI: 1.50-2.96, P<0.001), T stage(T3+ T4 vs T1a: HR=2.37, 95% CI: 1.26-4.46, P=0.008), local lymph node metastasis (HR=3.04, 95%CI: 1.81-5.09, P<0.001), nuclear grade (G3-G4 vs G1: HR=4.21, 95%CI: 1.51-11.75, P=0.006), tumor necrosis (HR=1.66, 95% CI: 1.17-2.37, P=0.005), sarcomatoid differentiation (HR=2.39, 95% CI: 1.31-4.35, P=0.005) and BMI≥24kg/m(2) (HR=0.56, 95%CI: 0.39-0.80, P=0.001) were independent factors affecting long-term survival after radical nephrectomy. Conclusions: The long-term survival of radical nephrectomy in patients with renal cell carcinoma is satisfactory. Advanced age, higher pathological stage and grade, tumor necrosis and sarcomatoid differentiation were the main adverse factors affecting the prognosis of patients. Higher body mass index was a protective factor for the prognosis of patients.
Humans ; Middle Aged ; Carcinoma, Renal Cell/secondary* ; Lymphatic Metastasis ; Retrospective Studies ; Neoplasm Staging ; Kidney Neoplasms/pathology* ; Prognosis ; Nephrectomy ; Survival Analysis ; Necrosis/surgery* ; Survival Rate

Objective To propose a neural network-based ventilator fault prediction method with a self-developed underlying data preprocessing method for ventilator IoT data.Methods Firstly the ventilator IoT data were sorted,categorized and cleaned.Secondly nondimensionalization and encoding of all the data were implemented via feature engineering methods based on data distribution.Thirdly data dimensionality reduction was carried out with a self-encoder.Finally,an artificial neural network was used for training with the abnormal data as the training label and predicting the abnormal data faults as the training objective,and the prediction performance of the neural network model was evaluated by calculating the accuracy,precision,recall rate,negative prediction value and specificity.Results The neural network model behaved well in learning with the accuracy being 99.68％,the precision being 99.66％,the recall rate being 99.99％,the negative prediction value being 99.95％and the specificity being 96.52％.Conclusion The proposed ventilator fault prediction model based on underlying data preprocessing and neural network can be used for the prediction of specific faults,and references are provided for IoT data-based medical equipment operation and maintenance management.[Chinese Medical Equipment Journal,2023,44(9):8-13]

Objective: To explore the related factors of negative conversion time (NCT) of nucleic acid in children with COVID-19. Methods: A retrospective cohort study was conducted. A total of 225 children who were diagnosed with COVID-19 and admitted to Changxing Branch of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 3^rd to May 31^st 2022 were enrolled in the study. The infection age, gender, viral load, basic disease, clinical symptoms and information of accompanying caregivers were retrospectively analyzed. According to age, the children were divided into<3 years of age group and 3-<18 years of age group. According to the viral nucleic acid test results, the children were divided into positive accompanying caregiver group and negative accompanying caregiver group. Comparisons between groups were performed using Mann-Whitney U test or Chi-square test. Multivariate Logistic regression analysis was used to analyze the related factors of NCT of nucleic acid in children with COVID-19. Results: Among the 225 patients (120 boys and 105 girls) of age 2.8 (1.3, 6.2) years, 119 children <3 years and 106 children 3-<18 years of age, 19 cases were diagnosed with moderate COVID-19, and the other 206 cases were diagnosed with mild COVID-19. There were 141 patients in the positive accompanying caregiver group and 84 patients in the negative accompanying caregiver group.Patients 3-<18 years of age had a shorter NCT (5 (3, 7) vs.7 (4, 9) d, Z=-4.17, P<0.001) compared with patients <3 years of age. Patients in the negative accompanying caregiver group had a shorter NCT (5 (3, 7) vs.6 (4, 9) d,Z=-2.89,P=0.004) compared with patients in the positive accompanying caregiver group. Multivariate Logistic regression analysis showed that anorexia was associated with NCT of nucleic acid (OR=3.74,95%CI 1.69-8.31, P=0.001). Conclusion: Accompanying caregiver with positive nucleic acid test may prolong NCT of nucleic acid, and decreased appetite may be associated with prolonged NCT of nucleic acid in children with COVID-19.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Young Adult ; China/epidemiology* ; COVID-19/genetics* ; Nucleic Acids ; Retrospective Studies

Circadian rhythm is an internal regulatory mechanism formed in organisms in response to the circadian periodicity in the environment, which modulates the pathophysiological events, occurrence and development of diseases, and the response to treatment in mammals. It significantly influences the susceptibility, injury, and recovery of ischemic stroke, and the response to therapy. Accumulating evidence indicates that circadian rhythms not only regulate the important physiological factors of ischemic stroke events, such as blood pressure and coagulation-fibrinolysis system, but also participate in the immuno-inflammatory reaction mediated by glial cells and peripheral immune cells after ischemic injury and the regulation of neurovascular unit(NVU). This article aims to link molecular, cellular, and physiological pathways in circadian biology to the clinical consequences of ischemic stroke and to illustrate the impact of circadian rhythms on ischemic stroke pathogenesis, the regulation of NVU, and the immuno-inflammatory responses. The regulation of circadian rhythm by traditional Chinese medicine is reviewed, and the research progress of traditional Chinese medicine intervention in circadian rhythm is summarized to provide a reasonable and valuable reference for the follow-up traditional Chinese medicine research and molecular mechanism research of circadian rhythm.
Animals ; Ischemic Stroke ; Medicine, Chinese Traditional ; Circadian Rhythm ; Blood Coagulation ; Blood Pressure ; Mammals

OBJECTIVE: To develop and validate a three-year risk prediction model for new-onset cardiovascular diseases (CVD) among female patients with breast cancer. METHODS: Based on the data from Inner Mongolia Regional Healthcare Information Platform, female breast cancer patients over 18 years old who had received anti-tumor treatments were included. The candidate predictors were selected by Lasso regression after being included according to the results of the multivariate Fine & Gray model. Cox proportional hazard model, Logistic regression model, Fine & Gray model, random forest model, and XGBoost model were trained on the training set, and the model performance was evaluated on the testing set. The discrimination was evaluated by the area under the curve (AUC) of the receiver operator characteristic curve (ROC), and the calibration was evaluated by the calibration curve. RESULTS: A total of 19 325 breast cancer patients were identified, with an average age of (52.76±10.44) years. The median follow-up was 1.18 [interquartile range (IQR): 2.71] years. In the study, 7 856 patients (40.65%) developed CVD within 3 years after the diagnosis of breast cancer. The final selected variables included age at diagnosis of breast cancer, gross domestic product (GDP) of residence, tumor stage, history of hypertension, ischemic heart disease, and cerebrovascular disease, type of surgery, type of chemotherapy and radiotherapy. In terms of model discrimination, when not considering survival time, the AUC of the XGBoost model was significantly higher than that of the random forest model [0.660 (95%CI: 0.644-0.675) vs. 0.608 (95%CI: 0.591-0.624), P < 0.001] and Logistic regression model [0.609 (95%CI: 0.593-0.625), P < 0.001]. The Logistic regression model and the XGBoost model showed better calibration. When considering survival time, Cox proportional hazard model and Fine & Gray model showed no significant difference for AUC [0.600 (95%CI: 0.584-0.616) vs. 0.615 (95%CI: 0.599-0.631), P=0.188], but Fine & Gray model showed better calibration. CONCLUSION It is feasible to develop a risk prediction model for new-onset CVD of breast cancer based on regional medical data in China. When not considering survival time, the XGBoost model and the Logistic regression model both showed better performance; Fine & Gray model showed better performance in consideration of survival time.
Humans ; Female ; Adult ; Middle Aged ; Adolescent ; Breast Neoplasms/epidemiology* ; Cardiovascular Diseases/etiology* ; Proportional Hazards Models ; Logistic Models ; China/epidemiology*