Objective To perform visual analysis for the literatures related to the application of new technologies in academic journal publishing,and to explore the research hotspots and development trends of new technologies applied to academic journal publishing in China.Methods We searched literatures in CNKI with the search formula SU%='Academic Journal Publishing'*('New Technology'+'5G'+'Big Data'+'Artificial Intelligence'+'Blockchain'+'Mobile Terminal'+'Cloud Computing'+'Internet'+'Database'+'VR/AR'+'Multimedia'),and using CiteSpace software,we analyzed the research hotspots and development trends of new technologies applied to academic journal publishing.Results A total of 436 articles were included in this study.The journal with the largest number of articles was China Science and Technology Journal Research.There were 34 core authors in the literatures included,and the collaboration between authors was relatively loose.The cooperation and communication between research institutions were not sufficient,and the cross-institutional cooperation needed to be strengthened.The keywords related to dimensional analysis,such as co-occurrence,clustering,and highlighting had significant characteristics.The research mainly focused on"the integrated development of academic journals and digital publishing","the innovation and development of the publishing under the background of internet+","media integration and communication strategy of academic journals","research on the application of artificial intelligence in the publishing",and"research on the communication effect of scientific and technical journals on cnki and other platforms".Conclusion The research of new technologies applied to academic journal publishing is still at a primary stage.The research mainly focuses on digital publishing,new media integration,talent training,and journal publishing reform,aiming to explore the way of talent training,academic dissemination strategy,innovative development path,and integrative development direction of academic journals in the digital era.

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Objective To study the communication power of WeChat official accounts of popular health science periodicals based on WCI.Methods Six popular health science periodicals were selected from the catalog of national excellent popular science periodicals(2020),namely Family Medicines,Family Doctor,Home Medicine,TCM Healthy Life-Nurturing,Health and Life,and Popular Medicine.The indicators related to the communication power of their WeChat official accounts were collected,and the WCI was calculated to evaluate their communication power.Results The average WCI of WeChat official accounts of the 6 popular health science periodicals from August 2023 to January 2024 in descending order was as follows:Family Doctor,TCM Healthy Life-Nurturing,Popular Medicine,Home Medicine,Family Medicines,and Health and Life.The average WCI of Family Doctor was excellent,the average WCI of Health and Life was poor,and the others were medium.From August 2023 to January 2024,the average number of articles published in the WeChat official accounts of the 6 health science periodicals in descending order was as follows:Family Doctor,Family Medicines,Home Medicine,Popular Medicine,Health and Life,and TCM Healthy Life-Nurturing.Conclusion The communication power of WeChat official accounts of outstanding popular health science journals in China still needs to be improved.It can be improved by optimizing the content of tweets,strengthening interaction with users,improving the utilization of modern technologies such as digitalization,big data and artificial intelligence,and strengthening multi-party cooperation.These measures can help journals to better disseminate health knowledge,meet needs of health education,and improve the national health level.

Objective:To analyze the bibliometric indicators of Chinese Journal of Nautical Medicine and Hyperbaric Medicine from 2014 to 2018, so as to improve its academic level and influence. Methods:Based on the statistical data from the core edition of the Chinese S& T Journal Citation Reports and part of the data provided by Wanfang Database Journal Bibliometric Evaluation Center, the changes of bibliometric indicators of Chinese Journal of Nautical Medicine and Hyperbaric Medicine from 2014 to 2018 were analyzed, including the impact factor, the citation frequency, the immediacy index, the cited half-life, the amount of published papers, the ratio of funded papers, and the number of papers published by high impact authors. Results:Among the cited indicators of the journal from 2014 to 2018, the impact factor showed an increasing trend year by year, and the highest year was in 2018 (0.757); the lowest citation frequency was in 2014 (86 times), the highest one was in 2018 (148 times), and there was a slightly fluctuation of that from 2015 to 2017; the lowest immediacy index was in 2014 (0.055), the highest one was in 2017 (0.105), and there was a slight decrease in the immediacy index in 2018 compared with that in 2017; the cited half-life showed a decreasing trend year by year, with the highest in 2014 (6.4 years) and the lowest in 2018 (4.3 years); among the source indicators, the amount of published papers slightly fluctuated from 2014 to 2018, with the lowest in 2018 (129 articles) and the highest in 2015 (187 articles); the highest ratio of funded papers was in 2015 (38.0%, 71/187) and the lowest was in 2016 (19.8%, 34/172); from 2014 to 2018, the number of papers published by high impact authors decreased year by year, with the highest in 2014 and 2015 (both were 94 articles) and the lowest in 2018 (39 articles).Conclusion:The bibliometric indicators of Chinese Journal of Nautical Medicine and Hyperbaric Medicine from 2014 to 2018 are generally good, and the information output, academic influence and level of the journal are steadily improving. Yet, more active measures should be taken to maintain and improve the academic quality of papers published on the journal to increase its academic influence and international dissemination.

Objective:To analyze the bibliometric indicators of Chinese Journal of Nautical Medicine and Hyperbaric Medicine from 2014 to 2018, so as to improve its academic level and influence. Methods:Based on the statistical data from the core edition of the Chinese S& T Journal Citation Reports and part of the data provided by Wanfang Database Journal Bibliometric Evaluation Center, the changes of bibliometric indicators of Chinese Journal of Nautical Medicine and Hyperbaric Medicine from 2014 to 2018 were analyzed, including the impact factor, the citation frequency, the immediacy index, the cited half-life, the amount of published papers, the ratio of funded papers, and the number of papers published by high impact authors. Results:Among the cited indicators of the journal from 2014 to 2018, the impact factor showed an increasing trend year by year, and the highest year was in 2018 (0.757); the lowest citation frequency was in 2014 (86 times), the highest one was in 2018 (148 times), and there was a slightly fluctuation of that from 2015 to 2017; the lowest immediacy index was in 2014 (0.055), the highest one was in 2017 (0.105), and there was a slight decrease in the immediacy index in 2018 compared with that in 2017; the cited half-life showed a decreasing trend year by year, with the highest in 2014 (6.4 years) and the lowest in 2018 (4.3 years); among the source indicators, the amount of published papers slightly fluctuated from 2014 to 2018, with the lowest in 2018 (129 articles) and the highest in 2015 (187 articles); the highest ratio of funded papers was in 2015 (38.0%, 71/187) and the lowest was in 2016 (19.8%, 34/172); from 2014 to 2018, the number of papers published by high impact authors decreased year by year, with the highest in 2014 and 2015 (both were 94 articles) and the lowest in 2018 (39 articles).Conclusion:The bibliometric indicators of Chinese Journal of Nautical Medicine and Hyperbaric Medicine from 2014 to 2018 are generally good, and the information output, academic influence and level of the journal are steadily improving. Yet, more active measures should be taken to maintain and improve the academic quality of papers published on the journal to increase its academic influence and international dissemination.

Objective: To evaluate the long-term efficacy and prognostic factors of childhood acute lymphoblastic leukemia (ALL) enrolled in Shanghai Children's Medical Center-Acute Lymphoblastic Leukemia-2005(SCMC-ALL-2005) multicenter study. Methods: Between May 2005 and December 2014, 1 497 newly diagnosed ALL patients were enrolled and treated in 5 hospitals of SCMC-ALL-2005 study group, using risk-stratified SCMC-ALL-2005 protocol. Risk group classification and treatment intensity were based on clinical features, genetic abnormalities, early response to treatment and levels of minimal residual disease (MRD). Kaplan-Meier method was used to generate overall survival (OS) and event-free survival(EFS) curves. Cox proportional hazards models were used for multivariate analyses. Results: The patients were followed up to December 31, 2016, the median follow-up time was 69 months (24-141 months). The 5-year and 10-year OS rates were (80.0±1.0)% and (76.0±2.0)%. The 5-year and 10-year EFS rates were (69.0±1.0)% and (66.0±2.0)%. The 5-year and 10-year relapse rates were (23.0±1.0)% and (25.0±2.0)%. The 5-year OS and EFS for low risk (LR), intermediate risk (IR) and high risk (HR) were (91.1±1.4)% and (83.3±1.8)%, (79.2±1.5)% and (68.9±1.7)%, (52.9±4.4)% and (30.0±3.8)%, respectively. MRD negative status (<0.01%) on day 55 was seen in 792 patients (82.8%) and positive MRD on day 55 was associated with poor prognosis (OR=1.9, 95%CI: 1.3-2.7, P=0.001). Twenty-four HR patients received allogeneic hematopoietic stem cell transplantation and 17(70.8%) of them were alive and in remission. A total of 164 severe adverse events occurred, 46 of them died, treatment-related mortality was 3.1%. Conclusions In this large sample research, the overall outcome for multi-center SCMC-ALL-2005 study was favorable. This helps to promote the standardized treatment of childhood ALL to the whole country. MRD results on day 55 of induction therapy have important prognostic and therapeutic implications.