Combined hepatocellular and cholangiocarcinoma (HCC-CC) is a rare primary hepatic neoplasm (PHN) with features of both hepatocellular and biliary differentiation. Hepatitis B and hepatitis C are the major causes of HCC-CC. Surgical treatment is the main therapeutic method for HCC-CC. For patients with unresectable lesions, curative or palliative locoregional therapy is applied, including radiofrequency ablation (RFA), transarterial chemoembolization (TACE) and supportive treatment. Because of the rare occurrence and ambiguous clinical features of HCC-CC, it is most often misdiagnosed with the other two types of primary liver cancer. Thus, the realization of the current progress of combined hepatocellular and cholangiocarcinoma is particularly important for us. This article aims to summarize the epidemiology and clinical futures, the treatment and prognosis, the progress of genetics and molecular analysis of HCC-CC.

Background Ozone (O₃) pollution has gradually become a primary problem of air pollution in recent years. Conducting epidemiological studies on the correlation between O₃ concentration variation and risk of cardiovascular and cerebrovascular diseases can provide reference data for O₃ risk assessment and related policy making. Objective To quantitatively evaluate the effects of O₃ exposure on mortalities of cardiovascular and cerebrovascular diseases among residents in Minhang District, Shanghai. Methods Data of mortalities of cardiovascular and cerebrovascular diseases, air pollutants, and meteorological factors in Minhang District of Shanghai from January 1, 2016 to December 31, 2021 were collected. Associations between O₃ concentration and the mortalities due to total cardiovascular and cerebrovascular diseases, coronary heart disease, and stroke were analyzed by generalized additive models with a quasi Poisson distribution with different lag patterns, such as current day effect (lag0), single-day lag effects (lag1-lag3), and cumulative lag effects (lag01-lag03). The subgroup analyses of age, sex, and season were conducted. Furthermore, temperature was divided into low, middle, and high levels based on the 25th percentile (P₂₅) and the 75th percentile (P₇₅) to perform hierarchical analyses. Increased excess risks (ER) of death from target diseases caused by a 10 µg·m⁻³ increase in daily maximum 8 h concentration of O₃ (O₃-8 h) and their 95% confidence intervals (CI) were used to indicate the effects of O₃. Results The associations between O₃ and the risks of death from cardiovascular and cerebrovascular diseases were statistically significant at lag2, lag3, lag02, and lag03 (P<0.05), with the greatest effect size observed at lag03. The ER values of death from cardiovascular and cerebrovascular diseases in general population, male residents, and people aged 65 years and older, from coronary heart disease in male residents, and from stroke in general population increased by 1.02% (95%CI: 0.36%, 1.69%), 1.40% (95%CI: 0.47%, 2.34%), 0.87% (95%CI: 0.19%, 1.55%), 1.96% (95%CI: 0.49%, 3.44%), and 1.02% (95%CI: 0.07%, 1.98%) for a 10 µg·m⁻³ increase in O₃-8 h concentration at lag03, respectively. During the warm season (from April 1 to September 30), the ER values of death from cardiovascular and cerebrovascular diseases and coronary heart disease per 10 µg·m⁻³ increase in O₃ were 1.18% (95%CI: 0.33%, 3.33%) and 2.69% (95%CI: 0.39%, 5.03%), while the O₃ effect was only statistically significant on cardiovascular and cerebrovascular diseases during the cold season (from October 1 to March 31 next year). At the middle and high temperature levels, the ER values of death from cardiovascular and cerebrovascular diseases increased by 1.63% (95%CI: 0.32%, 2.96%) and 1.14% (95%CI: 0.17%, 2.12%) respectively. The two-pollutant models showed similar results after including other pollutants (carbon monoxide, nitrogen dioxide, sulfur dioxide, fine particulate matter, or inhalable particulate matter). Conclusion Ambient O₃ pollution may increase the mortality risks of cardiovascular and cerebrovascular diseases, coronary heart disease, and stroke in Minhang District of Shanghai.

Objective:To analyze the temporal trends of the incidence rate of tuberculosis (TB) in Shaanxi Province and provide a reference for WHO to control the prevalence of TB effectively.Methods:Joinpoint regression was used to analyze the trend of the incidence rate of TB in Shaanxi Province from 2004 to 2022, and the seasonal autoregressive moving average model was used to forecast the incidence rate of TB in Shaanxi Province to 2030.Results:The incidence rate of TB in Shaanxi Province decreased from 90.896/100 000 in 2004 to 35.364/100 000 in 2022, showing a general downward trend (AAPC=-7.72%, P<0.001). From 2014 to 2019, the reduction trend slowed down (APC=-0.69%, P=0.814), of which the largest decline occurred from 2019 to 2022 (APC=-13.26%, P=0.010). The predicted incidence rate of TB in Shaanxi Province from 2020 to 2022 was higher than the reported incidence rate, with the expected incidence rate of 51.342/100 000 in 2022 and 43.468/100 000 in 2030. Conclusion:The incidence rate of TB in Shaanxi Province shows a downward trend from 2004 to 2022, but the decline has shrunk in recent years. It is predicted that the downward trend will continue to slow down by 2030.

Background and purpose:The standard therapy for locally advanced rectal cancer(LARC)is neoadjuvant chemoradiotherapy(nCRT)followed by surgery.NCRT can make the tumor regress and downstage,and increase the R0 resection rate.However,individual differences in rectal cancer are large,and some patients respond poorly to nCRT and cannot benefit from nCRT.Therefore,it is necessary to establish effective screening measures to identify patients with poor response to nCRT.This study aimed to analyze the influencing factors of nCRT for LARC and construct the tumor regression prediction model.Methods:Data of 158 LARC patients who underwent total mesenteric resection after receiving nCRT at the First Hospital Affiliated to Air Force Medical University from January 2016 to December 2020 were collected.Baseline clinical indicators before nCRT were collected,including laboratory examination,tumor markers and magnetic resonance imaging(MRI).According to the tumor size reported by MRI before and after nCRT,Response Evaluation Criteria in Solid Tumors(RECIST)was used to evaluate the extent of tumor regression after nCRT.After receiver operating characteristic(ROC)curve was used to standardize the clinical baseline indicators,logistic regression analysis was carried out to screen the factors affecting the tumor regression.The tumor regression prediction model was constructed by logistic regression,and the performance of the model was evaluated based on decision curve analysis(DCA)and the calibration curve.The accuracy of the model was tested by 10-fold cross-validation.Results:This retrospective cohort study enrolled 158 patients,in which,98 patients achieved complete response(CR)or partial response(PR).The objective response rate was 62%.Sixty patients had poor response to nCRT,either stable disease(SD)or progressive disease(PD).Multivariate logistic regression analysis showed that tumor diameter before treatment(P＜0.001),time to surgery after nCRT(P = 0.006),D-dimer(P = 0.010),prognostic nutrition index(PNI)(P = 0.035),carcinoembryonic antigen(CEA)(P = 0.004)and extramural vascular invasion(EMVI)(P = 0.026)were significantly related to tumor regression after nCRT.The area under ROC curve(AUC)of tumor regression after nCRT prediction model for LARC was 0.84(95%CI:0.780-0.899),sensitivity was 85.0%,and specificity was 72.4%.In the calibration curve,the predicted results were in good agreement with the actual results,and the prediction accuracy was good.The DCA showed that the tumor regression prediction model could bring clinical net benefit to diagnosis.Conclusion:Tumor diameter before treatment,time to surgery after nCRT,D-dimer,PNI,CEA and EMVI are independent risk factors for the tumor regression after nCRT in LARC patients.The tumor regression prediction model based on the above factors has good predictive efficacy for the tumor regression after nCRT in LARC patients.

Objective:To analyze the temporal trends of the incidence rate of tuberculosis (TB) in Shaanxi Province and provide a reference for WHO to control the prevalence of TB effectively.Methods:Joinpoint regression was used to analyze the trend of the incidence rate of TB in Shaanxi Province from 2004 to 2022, and the seasonal autoregressive moving average model was used to forecast the incidence rate of TB in Shaanxi Province to 2030.Results:The incidence rate of TB in Shaanxi Province decreased from 90.896/100 000 in 2004 to 35.364/100 000 in 2022, showing a general downward trend (AAPC=-7.72%, P<0.001). From 2014 to 2019, the reduction trend slowed down (APC=-0.69%, P=0.814), of which the largest decline occurred from 2019 to 2022 (APC=-13.26%, P=0.010). The predicted incidence rate of TB in Shaanxi Province from 2020 to 2022 was higher than the reported incidence rate, with the expected incidence rate of 51.342/100 000 in 2022 and 43.468/100 000 in 2030. Conclusion:The incidence rate of TB in Shaanxi Province shows a downward trend from 2004 to 2022, but the decline has shrunk in recent years. It is predicted that the downward trend will continue to slow down by 2030.