ObjectiveTo investigate the expression of C1q tumor necrosis factor-related protein 3 （C1QTNF3） in liver cancer tissue， its association with the clinicopathological features of patients， and its potential value in predicting the prognosis of liver cancer. MethodsRelated data were collected from TIMER， UALCAN， TNMplot， and GEO databases， and the bioinformatics methods were used to measure the expression level of C1QTNF3 in pan-cancer， normal tissue/liver cancer tissue， and cancerous tissue/paracancerous tissue. Cancerous and paracancerous tissue samples were collected from 90 patients with liver cancer， and related clinical data were collected， including age， sex， tumor diameter， and tumor number. The independent-samples t test or the paired t-test was used for comparison of continuous data between groups， and the chi-square test was used for comparison of categorical data between groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used to investigate the association between the expression level of C1QTNF3 and the survival of patients with liver cancer. The Cox regression model was used to identify the risk factors for the prognosis of patients with liver cancer， and the receiver operating characteristic （ROC） curve was used to analyze the ability of C1QTNF3 expression at different time points for predicting the prognosis of patients with liver cancer. ResultsThe bioinformatics analysis showed that the expression of C1QTNF3 was upregulated in various malignant tumors， especially in liver cancer tissue （P<0.001）， and the expression level of C1QTNF3 in liver cancer tissue was significantly higher than that in normal tissue and paracancerous tissues （all P<0.01）. The immunohistochemical staining results of 90 patients with liver cancer showed that C1QTNF3 was mainly expressed in cytoplasm， with a small amount in nucleus， and it had negative expression in paracancerous tissue and positive expression in liver cancer tissue. The positive expression rate and strong positive expression rate of C1QTNF3 protein in liver cancer tissue were significantly higher than those in paracancerous tissue （positive expression rate： 76.67% vs 33.33%， χ²=34.141， P<0.01； strong positive expression rate： 54.44% vs 5.56%， χ²=51.217， P<0.01）. The liver cancer patients with a tumor diameter of ≥5 cm， an advanced stage， the presence of liver cirrhosis， negative HBsAg， and gamma-glutamyl transpeptidase （GGT）≥50 U/L had a significantly higher strong positive expression rate of C1QTNF3 protein than those with a tumor diameter of <5 cm， an early stage， the absence of liver cirrhosis， positive HBsAg， and GGT<50 U/L （all P<0.05）. The univariate Cox regression analysis showed that tumor diameter， recurrence， and C1QTNF3 expression were influencing factors for the prognosis of patients with liver cancer （all P<0.05）， and the multivariate Cox regression analysis showed that the expression level of C1QTNF3 and recurrence were independent risk factors for the survival of patients with liver cancer （both P<0.05）. The survival curve analysis showed that for all patients with liver cancer， the patients with high （strong positive） expression of C1QTNF3 had significantly lower overall survival rate and disease-free survival rate than those with low expression （χ²=17.010 and 13.647， both P<0.001）； for liver cancer patients with a tumor diameter of ≥5 cm， an early/advanced stage， recurrence， the presence of liver cirrhosis， positive HBsAg， alanine aminotransferase （ALT） <40 U/L， ALT≥40 U/L， and GGT≥50 U/L， the patients with high expression of C1QTNF3 had a significant reduction in overall survival rate （χ²=11.086， 5.578， 5.295， 19.159， 16.391， 13.774， 10.119， 8.152， and 12.035， all P<0.05）. The ROC curve analysis showed that C1QTNF3 expression had the strongest predictive potential at 5 years， with an area under the ROC curve of 0.77. ConclusionC1QTNF3 is highly expressed in liver cancer tissue， and the expression level of C1QTNF3 and recurrence are closely associated with the survival of patients with liver cancer. Patients with high expression of C1QTNF3 protein tend to have a lower survival rate.

Objective:To explore the impact of adolescent mental health status on smartphone addiction, and construct a predictive model for smartphone addiction based on the eXtreme Gradient Boosting(XGBoost) algorithm and multivariate Logistic regression.Methods:In April 2023, a cross-sectional survey was conducted among 14 666 adolescents.All participants were systematically evaluated using a self-developed general information questionnaire, the middle school student mental health scale(MSSMHS), the adolescents self-harm scale(ASHS), the interaction anxiousness scale(IAS), the mobile phone addiction index(MPAI), the middle school students shame scale(MSSS), the UCLA loneliness scale(UCLA-LS), the multidimensional peer victimization scale(MPVS), and the basic psychological needs scale(BPNS).R software version 4.3.2 was used for data analysis. Participants were randomly divided into training set and validation set at the ratio of 7∶3.The XGBoost model and multivariate logistic regression model were constructed to predict the risk of smartphone addiction, and a nomogram was plotted.Model performance was evaluated using the Hosmer-Lemeshow test, area under the curve(AUC), and accuracy(ACC).Results:(1) A total of 14 036 high school students were included in the study, with 5 069(36.1%) exhibited smartphone addiction.The training set comprised 9 826 students, with 3 549(36.1%) being smartphone addicts.The validation set included 4 210 students, with 1 520(36.1%) being smartphone addicts.(2) The XGBoost model identified shame-proneness and social anxiety as the two main predictors of smartphone addiction.(3) Multivariate Logistic regression analysis revealed that anxiety( B=0.328, OR(95% CI)=1.39(1.07-1.81), P=0.015), interpersonal sensitivity( B=0.311, OR(95% CI)=1.36(1.05-1.77), P=0.018), learning pressure( B=0.606, OR(95% CI)=1.83(1.46-2.31), P<0.001), mood swings( B=0.775, OR(95% CI)=2.17(1.70-2.78), P<0.001), social anxiety( B=0.024, OR(95% CI)=1.02(1.01-1.04), P<0.001), shame-proneness( B=0.049, OR(95% CI)=1.05(1.04-1.06), P<0.001), and peer victimization( B=0.037, OR(95% CI)=1.04(1.02-1.06), P<0.001) were significant predictors of smartphone addiction.(4) The ACC and AUC values of the XGBoost model were 0.890 and 0.929 in the training set, and 0.865 and 0.864 in the validation set, respectively.The multivariate Logistic regression model achieved ACC and AUC values of 0.870 and 0.854 in the training set, and 0.867 and 0.859 in the validation set, respectively. Conclusion:Anxiety, interpersonal sensitivity, learning pressure, mood swings, social anxiety, shame-proneness, and peer victimization are identified risk predictors of smartphone addiction in high school adolescents.

Immunization represents the most effective strategy for the prevention and control of diseases. Nevertheless, some people may still get infected and contract the disease even after being fully vaccinated, which is known as a "breakthrough case." The presence of breakthrough cases shows that although vaccines significantly lower the rates of disease and death, they do not entirely eliminate the risk of illness.Addressing breakthrough cases, comprehending their epidemiological characteristics, and identifying the associated factors carry substantial public health implications for vaccine development, the optimization of vaccination strategies, and the implementation of intervention efforts. This review aims to provide a scientific reference for enhancing the prevention and control of vaccine-preventable diseases by summarizing the definitions, epidemiological characteristics, and relevant factors related to breakthrough infection cases across various diseases.

Objective:To explore the impact of adolescent mental health status on smartphone addiction, and construct a predictive model for smartphone addiction based on the eXtreme Gradient Boosting(XGBoost) algorithm and multivariate Logistic regression.Methods:In April 2023, a cross-sectional survey was conducted among 14 666 adolescents.All participants were systematically evaluated using a self-developed general information questionnaire, the middle school student mental health scale(MSSMHS), the adolescents self-harm scale(ASHS), the interaction anxiousness scale(IAS), the mobile phone addiction index(MPAI), the middle school students shame scale(MSSS), the UCLA loneliness scale(UCLA-LS), the multidimensional peer victimization scale(MPVS), and the basic psychological needs scale(BPNS).R software version 4.3.2 was used for data analysis. Participants were randomly divided into training set and validation set at the ratio of 7∶3.The XGBoost model and multivariate logistic regression model were constructed to predict the risk of smartphone addiction, and a nomogram was plotted.Model performance was evaluated using the Hosmer-Lemeshow test, area under the curve(AUC), and accuracy(ACC).Results:(1) A total of 14 036 high school students were included in the study, with 5 069(36.1%) exhibited smartphone addiction.The training set comprised 9 826 students, with 3 549(36.1%) being smartphone addicts.The validation set included 4 210 students, with 1 520(36.1%) being smartphone addicts.(2) The XGBoost model identified shame-proneness and social anxiety as the two main predictors of smartphone addiction.(3) Multivariate Logistic regression analysis revealed that anxiety( B=0.328, OR(95% CI)=1.39(1.07-1.81), P=0.015), interpersonal sensitivity( B=0.311, OR(95% CI)=1.36(1.05-1.77), P=0.018), learning pressure( B=0.606, OR(95% CI)=1.83(1.46-2.31), P<0.001), mood swings( B=0.775, OR(95% CI)=2.17(1.70-2.78), P<0.001), social anxiety( B=0.024, OR(95% CI)=1.02(1.01-1.04), P<0.001), shame-proneness( B=0.049, OR(95% CI)=1.05(1.04-1.06), P<0.001), and peer victimization( B=0.037, OR(95% CI)=1.04(1.02-1.06), P<0.001) were significant predictors of smartphone addiction.(4) The ACC and AUC values of the XGBoost model were 0.890 and 0.929 in the training set, and 0.865 and 0.864 in the validation set, respectively.The multivariate Logistic regression model achieved ACC and AUC values of 0.870 and 0.854 in the training set, and 0.867 and 0.859 in the validation set, respectively. Conclusion:Anxiety, interpersonal sensitivity, learning pressure, mood swings, social anxiety, shame-proneness, and peer victimization are identified risk predictors of smartphone addiction in high school adolescents.

Objective To explore the predictive value of the atherogenic index of plasma(AIP),triglyceride-glucose(TyG)index,and cerebral small vascular disease(CSVD)imaging load score regarding the early prognosis of patients with acute ischemic stroke(AIS)after intravenous thrombolysis.Methods A total of 379 inpatients diagnosed with AIS at the Shengli Oilfield Central Hospital and treated with intravenous thrombolysis from January 2022 to December 2023 were retrospectively analyzed.Relevant data were collected,and the CSVD imaging load score was evaluated.The patients were classified into the good prognosis group(≥18％)and the poor prognosis group(＜18％)based on the early neurological improvement rate 14 d after thrombolysis.An investigation into the independent risk factors influencing the early prognostic outcomes in patients suffering from AIS was conducted utilizing binary Logistic regression analysis.The efficacy of early prognosis prediction in patients undergoing intravenous thrombolysis was assessed through receiver operating characteristic(ROC)curve analysis.Results Systolic blood pressure,AIP,TyG index,neutrophil to lymphocyte ratio(NLR),cerebral microbleeds(CMB),enlarged perivascular spaces(EPVS)and a CSVD imaging load score of 2 points or higher served as independent risk factors influencing the early prognosis in AIS patients undergoing thrombolysis.The ROC curve analysis revealed that the area under the curve(AUC)for the CSVD imaging load score was 0.821,with a sensitivity of 80.4％and a specificity of 74％.The AUC of the AIP was 0.951,with a sensitivity of 89.2％and a specificity of 91.7％.The AUC of the TyG index was 0.918,with a sensitivity of 93.1％and a specificity of 82.7％.Conclusions The AIP,TyG index,and CSVD imaging load score serve as efficacious indicators in assessing the premature prognostication of AIS patients who underwent subsequently to intravenous thrombolytic therapy.

Objective: To explore the associations between caregivers nutrition literacy and pediatric nonalcoholic fatty liver disease (NAFLD), so as to provide scientific evidence for the key contents of family intervention measures. Methods: In September 2022, a study involving 1 609 thirdgrade students and their caregivers from six schools in Yinzhou, Haishu, and Zhenhai Districts of Ningbo City, Zhejiang Province, was conducted. Venous blood samples were collected to measure lipid profiles and investigate the prevalence of nonalcoholic fatty liver disease (NAFLD) among the children. Family Food Environment Questionnaire was used to assess the nutrition literacy levels of the caregivers. Generalized linear regression analysis was employed to explore the correlation between caregivers nutrition literacy levels and the prevalence of NAFLD in children. Results: Among the surveyed students, 191 were in the NAFLD group, whereas 1 418 were in the nonNAFLD group. The median nutrition literacy score of caregivers in the NAFLD group and nonNAFLD group all were 11.00 (9.00,12.00), which was not significantly different (Z=-0.40, P=0.71). The generalized linear regression results revealed that the level of nutrition literacy of caregivers had no significant effect on childrens Triglyceride-glucose (TyG) index and Triglyceride-glucose-Waisttoheight ratio (TyG-WHtR) [β(95%CI) were 0.001(-0.005-0.006) and 0.000(-0.014-0.014), P>0.05]. Conclusions The nutrition literacy level of caregivers has no significant correlation with the direct incidence of NAFLD in children. As for family intervention measures, it is necessary not only to improve the nutrition literacy level of caregivers but also to effectively apply nutritional knowledge in practice to optimize health management.

Spontaneous intracerebral hemorrhage (ICH) is the second common subtype of stroke, characterized by high incidence, high mortality and high disability rates. The recurrent ICH not only brings physical pain to patients, but also increases the burden on families and society. In recent years, researches on the risk factors for recurrent ICH have been increasing day by day. This article reviews the risk factors for recurrent ICH from the perspectives of clinical features, biomarkers, and imaging characteristics, in order to provide a basis for the secondary prevention of ICH.

Objective To investigate the expression of C1q tumor necrosis factor-related protein 3(C1QTNF3)in liver cancer tissue,its association with the clinicopathological features of patients,and its potential value in predicting the prognosis of liver cancer.Methods Related data were collected from TIMER,UALCAN,TNMplot,and GEO databases,and the bioinformatics methods were used to measure the expression level of C1QTNF3 in pan-cancer,normal tissue/liver cancer tissue,and cancerous tissue/paracancerous tissue.Cancerous and paracancerous tissue samples were collected from 90 patients with liver cancer,and related clinical data were collected,including age,sex,tumor diameter,and tumor number.The independent-samples t test or the paired t-test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.The Kaplan-Meier method was used to plot survival curves,and the Log-rank test was used to investigate the association between the expression level of C1QTNF3 and the survival of patients with liver cancer.The Cox regression model was used to identify the risk factors for the prognosis of patients with liver cancer,and the receiver operating characteristic(ROC)curve was used to analyze the ability of C1QTNF3 expression at different time points for predicting the prognosis of patients with liver cancer.Results The bioinformatics analysis showed that the expression of C1QTNF3 was upregulated in various malignant tumors,especially in liver cancer tissue(P<0.001),and the expression level of C1QTNF3 in liver cancer tissue was significantly higher than that in normal tissue and paracancerous tissues(all P<0.01).The immunohistochemical staining results of 90 patients with liver cancer showed that C1QTNF3 was mainly expressed in cytoplasm,with a small amount in nucleus,and it had negative expression in paracancerous tissue and positive expression in liver cancer tissue.The positive expression rate and strong positive expression rate of C1QTNF3 protein in liver cancer tissue were significantly higher than those in paracancerous tissue(positive expression rate:76.67%vs 33.33%,χ2=34.141,P<0.01;strong positive expression rate:54.44%vs 5.56%,χ2=51.217,P<0.01).The liver cancer patients with a tumor diameter of≥5 cm,an advanced stage,the presence of liver cirrhosis,negative HBsAg,and gamma-glutamyl transpeptidase(GGT)≥50 U/L had a significantly higher strong positive expression rate of C1QTNF3 protein than those with a tumor diameter of<5 cm,an early stage,the absence of liver cirrhosis,positive HBsAg,and GGT<50 U/L(all P<0.05).The univariate Cox regression analysis showed that tumor diameter,recurrence,and C1QTNF3 expression were influencing factors for the prognosis of patients with liver cancer(all P<0.05),and the multivariate Cox regression analysis showed that the expression level of C1QTNF3 and recurrence were independent risk factors for the survival of patients with liver cancer(both P<0.05).The survival curve analysis showed that for all patients with liver cancer,the patients with high(strong positive)expression of C1QTNF3 had significantly lower overall survival rate and disease-free survival rate than those with low expression(χ2=17.010 and 13.647,both P<0.001);for liver cancer patients with a tumor diameter of≥5 cm,an early/advanced stage,recurrence,the presence of liver cirrhosis,positive HBsAg,alanine aminotransferase(ALT)<40 U/L,ALT≥40 U/L,and GGT≥50 U/L,the patients with high expression of C1QTNF3 had a significant reduction in overall survival rate(χ2=11.086,5.578,5.295,19.159,16.391,13.774,10.119,8.152,and 12.035,all P<0.05).The ROC curve analysis showed that C1QTNF3 expression had the strongest predictive potential at 5 years,with an area under the ROC curve of 0.77.Conclusion C1QTNF3 is highly expressed in liver cancer tissue,and the expression level of C1QTNF3 and recurrence are closely associated with the survival of patients with liver cancer.Patients with high expression of C1QTNF3 protein tend to have a lower survival rate.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Immunization represents the most effective strategy for the prevention and control of diseases. Nevertheless, some people may still get infected and contract the disease even after being fully vaccinated, which is known as a "breakthrough case." The presence of breakthrough cases shows that although vaccines significantly lower the rates of disease and death, they do not entirely eliminate the risk of illness.Addressing breakthrough cases, comprehending their epidemiological characteristics, and identifying the associated factors carry substantial public health implications for vaccine development, the optimization of vaccination strategies, and the implementation of intervention efforts. This review aims to provide a scientific reference for enhancing the prevention and control of vaccine-preventable diseases by summarizing the definitions, epidemiological characteristics, and relevant factors related to breakthrough infection cases across various diseases.