Objective:To investigate the expression, prognosis, and role of G protein-coupled receptor kinase-interacting protein 1 (GIT1) in patients with hepatocellular carcinoma (HCC) tumor micro environments.Methods:Clinical data of 140 cases who underwent complete HCC surgical resection from January 2015 to December 2021 in Subei People's Hospital affiliated to Yangzhou University, Jiangsu Province, were included. Tumor tissue and adjacent tissue samples were collected for immunohistochemical analysis. The patients were divided into a high expression group and a low expression group according to the expression of GIT1. Cox regression was used to analyze the risk factors for prognosis in patients with HCC. Fifteen pairs of cancer tissues and adjacent tissues were randomly matched for quantitative polymerase chain reaction (RT-PCR), western blot (WB), and immunohistochemical analysis. GITI knockout or overexpression cell lines of human hepatoma cell lines HepG2, HuH7 and MHCC97-H, and mouse hepatoma cell line Hepa 1-6 were constructed. The effects on M2 macrophage polarization were analyzed by flow cytometry. A mice tumor model was constructed. The growth curve of tumor tissue overexpressing GIT1 was plotted. Bioinformatics analysis of the Cancer Genome Atlas (TCGA) data was performed using OncoLnc, Kaplan-Meier Plotter, UALCAN, and GEPIA databases to explore the differential expression of GIT1 in HCC patients and its effect on prognosis.Results:Bioinformatics analysis showed that the expression level of GIT1 was significantly higher in HCC tissues than in normal liver tissues ( P<0.05). RT-PCR and WB experiments showed that GIT1 was highly expressed in HCC. The follow-up results showed that high expression of GIT1 was associated with poor prognosis in patients with HCC. The high expression of GIT1 was an independent risk factor for the prognosis in patients with HCC ( HR=2.562, 95% CI: 0.231-0.704, P<0.05). Functional enrichment analysis combined with TIMER database analysis found that GIT1 expression level was associated with multiple immune cell infiltrations in HCC, but the correlation coefficient with macrophage infiltration was the highest ( r=0.545, P<0.001). Mice tumorigenesis experiments showed that the tumor volume of GIT1-overexpressing mice was significantly increased ( P<0.05). Additionally, flow cytometry indicated that after GIT1 overexpression, there was a low degree of M1 infiltration/polarization (wild type: 5.06%±0.11%, overexpression type: 4.09%±0.04%; P<0.05) and a high degree of M2 infiltration/polarization (wild type: 10.20%±0.33%, overexpression type: 14.7%±0.12%; P<0.05). Conclusion:GIT1 serves as a prognostic biomarker in HCC, promoting tumor progression through its high expression and enhances M2 macrophage infiltration.

Objective:To investigate the expression, prognosis, and role of G protein-coupled receptor kinase-interacting protein 1 (GIT1) in patients with hepatocellular carcinoma (HCC) tumor micro environments.Methods:Clinical data of 140 cases who underwent complete HCC surgical resection from January 2015 to December 2021 in Subei People's Hospital affiliated to Yangzhou University, Jiangsu Province, were included. Tumor tissue and adjacent tissue samples were collected for immunohistochemical analysis. The patients were divided into a high expression group and a low expression group according to the expression of GIT1. Cox regression was used to analyze the risk factors for prognosis in patients with HCC. Fifteen pairs of cancer tissues and adjacent tissues were randomly matched for quantitative polymerase chain reaction (RT-PCR), western blot (WB), and immunohistochemical analysis. GITI knockout or overexpression cell lines of human hepatoma cell lines HepG2, HuH7 and MHCC97-H, and mouse hepatoma cell line Hepa 1-6 were constructed. The effects on M2 macrophage polarization were analyzed by flow cytometry. A mice tumor model was constructed. The growth curve of tumor tissue overexpressing GIT1 was plotted. Bioinformatics analysis of the Cancer Genome Atlas (TCGA) data was performed using OncoLnc, Kaplan-Meier Plotter, UALCAN, and GEPIA databases to explore the differential expression of GIT1 in HCC patients and its effect on prognosis.Results:Bioinformatics analysis showed that the expression level of GIT1 was significantly higher in HCC tissues than in normal liver tissues ( P<0.05). RT-PCR and WB experiments showed that GIT1 was highly expressed in HCC. The follow-up results showed that high expression of GIT1 was associated with poor prognosis in patients with HCC. The high expression of GIT1 was an independent risk factor for the prognosis in patients with HCC ( HR=2.562, 95% CI: 0.231-0.704, P<0.05). Functional enrichment analysis combined with TIMER database analysis found that GIT1 expression level was associated with multiple immune cell infiltrations in HCC, but the correlation coefficient with macrophage infiltration was the highest ( r=0.545, P<0.001). Mice tumorigenesis experiments showed that the tumor volume of GIT1-overexpressing mice was significantly increased ( P<0.05). Additionally, flow cytometry indicated that after GIT1 overexpression, there was a low degree of M1 infiltration/polarization (wild type: 5.06%±0.11%, overexpression type: 4.09%±0.04%; P<0.05) and a high degree of M2 infiltration/polarization (wild type: 10.20%±0.33%, overexpression type: 14.7%±0.12%; P<0.05). Conclusion:GIT1 serves as a prognostic biomarker in HCC, promoting tumor progression through its high expression and enhances M2 macrophage infiltration.

Objective To investigate the occurrence of anxiety before anesthesia and identify the risk factors for anxiety. Methods A total of 500 patients of both sexes, aged 18-80 yr, of American So-ciety of Anesthesiologists physical statusⅠ-Ⅲ, scheduled for elective surgery, were selected. The patients were investigated using the Generalized Anxiety Disorder 7-item scale and anxiety factor questionnaires. It was evaluated whether the patient had anxiety before anesthesia according to the scale score, and then the patients were divided into anxiety group and non-anxiety group. The possible risk factors for anxiety were compared, and the statistically significant variables were further analyzed by Logistic regression to stratify the risk factors. Results The incidence of pre-anesthesia anxiety was 46. 80％. Logistic regression analysis showed that gender, lack of understanding of the next treatment, fear of death, fear of surgical failure, fear of intraoperative and postoperative pain were independent risk factors for anxiety before anesthesia. Conclusion The incidence of pre-anesthesia anxiety is 46. 80％, and gender, lack of understanding of the next treatment, fear of death, fear of surgical failure, fear of intraoperative and postoperative pain are in-dependent risk factors for pre-anesthesia anxiety in the patients undergoing surgery.

Objective: To investigate the clinical effect and safety of long-acting pegylated interferon-α-2b (Peg-IFN-α-2b) (Y shape, 40 kD) injection (180 μg/week) in the treatment of HBeAg-positive chronic hepatitis B (CHB) patients, with standard-dose Peg-IFN-α-2a as positive control. Methods: This study was a multicenter, randomized, open-label, and positive-controlled phase III clinical trial. Eligible HBeAg-positive CHB patients were screened out and randomized to Peg-IFN-α-2b (Y shape, 40 kD) trial group and Peg-IFN-α-2a control group at a ratio of 2:1. The course of treatment was 48 weeks and the patients were followed up for 24 weeks after drug withdrawal. Plasma samples were collected at screening, baseline, and 12, 24, 36, 48, 60, and 72 weeks for centralized detection. COBAS® Ampliprep/COBAS® TaqMan® HBV Test was used to measure HBV DNA level by quantitative real-time PCR. Electrochemiluminescence immunoassay with Elecsys kit was used to measure HBV markers (HBsAg, anti-HBs, HBeAg, anti-HBe). Adverse events were recorded in detail. The primary outcome measure was HBeAg seroconversion rate after the 24-week follow-up, and non-inferiority was also tested. The difference in HBeAg seroconversion rate after treatment between the trial group and the control group and two-sided confidence interval (CI) were calculated, and non-inferiority was demonstrated if the lower limit of 95% CI was > -10%. The t-test, chi-square test, or rank sum test was used according to the types and features of data. Results: A total of 855 HBeAg-positive CHB patients were enrolled and 820 of them received treatment (538 in the trial group and 282 in the control group). The data of the full analysis set showed that HBeAg seroconversion rate at week 72 was 27.32% in the trial group and 22.70% in the control group with a rate difference of 4.63% (95% CI -1.54% to 10.80%, P = 0.1493). The data of the per-protocol set showed that HBeAg seroconversion rate at week 72 was 30.75% in the trial group and 27.14% in the control group with a rate difference of 3.61% (95% CI -3.87% to 11.09%, P = 0.3436). 95% CI met the non-inferiority criteria, and the trial group was non-inferior to the control group. The two groups had similar incidence rates of adverse events, serious adverse events, and common adverse events. Conclusion In Peg-IFN-α regimen for HBeAg-positive CHB patients, the new drug Peg-IFN-α-2b (Y shape, 40 kD) has comparable effect and safety to the control drug Peg-IFN-α-2a.

Objective To explore the prospect of nonlinear autoregressive neural network in fitting and predicting the incidence tendency of hemorrhagic fever with renal syndrome (HFRS),in the mainland of China.Methods Monthly reported case series of HFRS in China from 2004 to 2013 were used to build both ARIMA and NAR neural network models,in order to predict the monthly incidence of HFRS in China in 2014.Fitness and prediction on the effects of these two models were compared.Results For the Fitting dataset,MAE,RMSE and MAPE of the ARIMA model were 148.058,272.077 and 12.678％ respectively,while the MAE,RMSE and MAPE of NAR neural network appeared as 119.436,186.671 and 11.778％ respectively.For the Predicting dataset,MAE,RMSE and MAPE of the ARIMA model appeared as 189.088,221.133 and 21.296％,while the MAE,RMSE and MAPE of the NAR neural network as 119.733,151.329 and 11.431％ respectively.Conclusion The NAR neural network showed better effects in fitting and predicting the incidence tendency of HFRS than using the traditional ARIMA model,in China.NAR neural network seemed to have strong application value in the prevention and control of HFRS.

objective To understand the baseline data of mortality from malignant tumor from 2006 to 2009 around Hongyanhe Nuclear Power Plant in Wafangdian City,Liaoning Province,so as to provide scientific basis for evaluating the impact of normal operation of nuclear power plant on the health of the residents nearby.Methods Thirty small towns near Hongyanhe Nuclear Power Plant were divided into 5 investigated areas according to the distances away therefrom(0.,10.,20-,30-,and 40-km).The data about from malignant tumor were obtained from the Center for Disease Control and Prevention of Wafangdian.The mortality distribution of difierent malignant tumors was analyzed,including the radiosensitive malignant tumors,especially leukemia,breast cancer,and thyroid gland cancer in different area,gender,and age groups.Results The mortality from malignant tumor was 151.97/105,and the standardized mortality rate(SMR)was 97.76/105.The mortality from malignant tumor among the males was 188.28/105(with the SMR of 116.76/105),and that among the females was 113.47/105(with the SMR of 75.89/105).with a sex ratio of 1.71.The first five cancers in the rank of death causes were lung,liver,stomach,colorectal,and esophageal cancers with mortality of 46.19/105,23.51/105,20.30/105,8.06/105 and 5.45/105,respectively.The mortality from mal.ignant tumor in the areas around the nuclear power plant from the near to the distant were 99.85/105, 137.40/105,138.73/105,156.30/105,and 154.16/105,respectively.The mortality from radiosensitive malignant tumors,leukemia,breast cancer,and thyroid gland cancer were 4.57/105,4.06/105,and 0.26/105,respectively.Conclusions Lung cancer and digestive tract malignant tumors are the main causes of death from malignant tumors in Wafangdian area before the nuclear power plant began to operate.There are no significant differences in the mortality distribution of malignant tumors among different areas,genders,and age groups.There are not significant differences in the mortality distribution of leukemia and breast cancer among different areas and age groups.

Objective To study the relationship between serum trace elements and renal cell carcinoma.Methods The serum concentrations of multi-elements in 34 patients with renal cell carcinoma and 28 healthy volunteers were determined by inductively coupled plasma mass spectrometry(ICP-MS).The results were analyzed by partial least square discriminant analysis (PLS-DA) and Fisher discriminant.Results Compared with healthy voluteers,the levels of vanadium (5 034.56 ng/L:4 401.23 ng/L ),cobalt (211.34 ng/L:158.67 ng/L),nickel(l 850.55 ng/L:1 587.12 ng/L),manganese(1 873.35 ng/L:932.68 ng/L) and cadmium(95.63 ng/L:36.43 ng/L) were significantly higher in patients with renal cell carcinoma (P ＜ 0.05 ).While,the concentrations of calcium( 10.83 mg/L:11.78 mg/L) and zinc(67.11 μg/L:70.92 pg/L)were significantly lower ( P ＜ 0.05 ).Discriminant analysis showed that the serum elements levels in the patients with renal cell carcinoma were significantly different from the healthy volunteers.The scores plot showed distinct clustering between patients and controls,the points of patients were obviously offset from the controls.The classification accuracy of Fisher discriminant function was 97.61％.Conclusion Trace elements in serum are significantly different in patients with renal cell carcinoma and healthy volunteers.Discriminant analysis of serum samples based on trace element levels is possible.Thus,it is feasible for early diagnosis of renal cell carcinoma by determination of trace elements and discriminant analysis.