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.

In the era of big data,artificial intelligence(AI)technology has developed rapidly,with medical field being one of its most deeply penetrated application domains.Leveraging the advantages of big data and AI requires the sharing and integration of medical data,yet balancing privacy protection and data sharing poses significant challenges.This paper analyzes the focus issues of patient privacy and data security in medical AI from a global perspective across 6 dimensions:challenges in data sovereignty and cross-border flow compliance,technical vulnerabilities in de-anonymization and re-identification risks,failure of informed consent mechanisms and dynamic authorization needs,regulatory gaps in algorithmic"black boxes"and data misuse,technological dependency and supply chain security risks,and the dilemma of balancing privacy protection with public health interests.Corresponding solutions and strategies are also proposed.

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.

A novel technology is proposed for non-contact and real-time detection of atrial fibrillation using millimeter-wave radar.A 60 GHz PCR millimeter wave radar is used to continuously detect the chest echo signal of the subject.After signal acquisition,I-Q signal is generated through I-Q demodulation,and the signal phase information is extracted using effective points phase trend evaluation for obtaining the signals from oscillations in the chest wall,from which the respiratory signals and cardiac signals are extracted through digital filtering for the analysis of cardiac movement.Whether the atrial fibrillation occurs or not is determined by the characteristics of atrial fibrillation wave in the time domain.The effective points phase trend evaluation for extracting more accurate signal phase information and the time-domain method for real-time atrial fibrillation detection are the innovations of the study.The experimental results show that the proposed method achieves a detection accuracy of 99.2%in clinic.

OBJECTIVE To provide reference for Smilax glabra quality control. METHODS UPLC method was established to simultaneously determine the contents of 5-O-caffeoylshikimic acid， neoastilbin， astilbin， neoisoastilbin， isoastilbin， engelitin， resveratrol and isoengelitin in 20 batches of S. glabra from different areas （No. S1-S20）. The quality evaluation of 20 batches of samples was performed by chemometrics； the differential biomarkers that affected the quality of S. glabra were screened. RESULTS The measured 8 components had good linear relationship within the range of measured concentration （r≥0.999 6）. RSDs of precision， repeatability and stability tests （24 h） were all lower than 2.00% （n＝6）. The average recoveries varied between 97.60% and 106.40% （RSDs were all lower than 2.00%， n＝6）. Cluster analysis showed that the samples produced in Zhejiang （S1-S5） and Jiangxi （S6-S10） were clustered into one category； the samples produced in Hunan （S11-S15） were clustered into one category； the samples produced in Yunnan （S16-S20） were clustered into one category. Principal component analysis showed that the first two principal components could represent 85.60% information of 8 components in S. glabra. Partial least squares-discriminant analysis showed that variable importance projection values of 5-O-caffeoylshikimic acid， astilbin， isoastilbin and neoastilbin were all greater than 1. CONCLUSIONS There are differences in the contents of the above 8 components in S. glabra from different origins； 5-O-caffeoylshikimic acid， astilbin， isoastilbin and neoastilbin may be differential markers affecting the quality of S. glabra.

Objective To analyze the related research literatures of"Mission Harmony"of hospital ship by bibliometrics,and to summarize the practical experiences and strategies of thematic soliciting contributions.Methods Previous tasks of"Mission Harmony"of hospital ship were summarized based on database and Internet.Based on WANFANG database,the relevant research literatures were statistically analyzed according to the types of papers,years,keywords,authors,institutions,and periodicals using bibliometrics.The soliciting contributions for"Mission Harmony"was analyzed.Results A total of 271 articles were retrieved.There were 264(97.42%)journal articles.Most of them were published in 2011.The top three keywords were"Hospital ship","Medical service",and"Mission Harmony".The top three authors were Sun Tao,Huang Yeli,and Zhou Shan.The top three institutions were the Navy General Hospital(Sixth Medical Center of the General Hospital of PLA),No.411 Hospital of PLA,and No.413 Hospital of PLA.The top three journals in terms of the number of published articles were Chinese Journal of Nautical Medicine and Hyperbaric Medicine,China Journal of Emergency Resuscitation and Disaster Medicine,and Journal of Navy Medicine.Up to December 1,2023,a total of 51 articles related to"Mission Harmony"had been received by Journal of Navy medicine,of which 48 had passed the initial review,and 36 articles had been approved for peer review.Fourteen experts were invited for a final draft meeting.Four articles were accepted,7 articles were accepted after revision,19 articles were reviewed after revision,and 6 articles were rejected.Finally,the"Mission Harmony"column was serialized in the 3rd to 5th issues of the Journal of Navy Medicine in 2024,and 11 papers were published.Conclusion The editorial office should keep up with the development of naval medicine,report the theoretical innovations and significant progress of naval medicine in a timely manner by topic selection,author cultivation,and process management,contributing to the high-quality development of naval medicine.

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 investigate the efficacy and safety of dual antiplatelet therapy (DAPT) in patients with minor ischemic stroke (MIS) and tiny unruptured intracranial aneurysm (UIA).Methods:Patients with MIS and tiny UIA admitted to the Department of Neurology, Weifang People's Hospital from October 1, 2022 to February 29, 2024 were included retrospectively. MIS was defined as baseline National Institutes of Health Stroke Scale (NIHSS) score ≤3. Tiny UIA was defined as UIA with a diameter of ≤3 mm. According to the antiplatelet therapy regimen, the patients were divided into an aspirin alone group and an aspirin+clopidogrel DAPT group. The main outcome measure was the clinical outcome at 90 days after onset. The modified Rankin Scale (mRS) score 0-1 was defined as a good outcome and >1 was defined as a poor outcome. Secondary outcome measures included aneurysm rupture, cerebral hemorrhage, and recurrence of cerebral ischemic events. Multivariate logistic regression analysis was used to identify the independent influencing factors for poor outcome. Results:A total of 183 patients with MIS and tiny UIA were included, including 108 males (59.0%), median aged 68 years (interquartile range, 61-73 years). All the UIAs were solitary. The mRS score of all patients before onset was 0; 152 patients (83.1%) had good outcome at 90 days after onset, 31 (16.9%) had poor outcome, and no UIA occurred rupture bleeding. Of the 94 patients (51.4%) who received aspirin monotherapy, 14 patients (14.9%) experienced recurrent cerebral ischemic events during follow-up, and 73 (77.7%) had good outcome. Of the 89 patients (48.6%) who received DAPT, 5 (5.6%) experienced recurrent ischemic events during follow-up, and 79 (88.8%) had good outcome. The recurrence rate of cerebral ischemic events in the aspirin group was significantly higher than that in the DAPT group ( χ2=4.227, P=0.040), while the good outcome rate was significantly lower than that in the DAPT group ( χ2=4.006, P=0.045). Multivariate logistic regression analysis showed that baseline NIHSS score was an independent risk factor for poor outcome (odds ratio 4.597, 95% confidence interval 1.864-11.339; P=0.001), while DAPT was an independent protective factor for good outcome (odds ratio 0.265, 95% confidence interval 0.079-0.892; P=0.032). Conclusion:Compared with aspirin monotherapy, the short-term combination of aspirin and clopidogrel in patients with MIS and tiny UIA may improve the outcome, reduces the recurrence of cerebral ischemic events, and has good safety.

SGLT2 inhibitors currently have clear benefits in the treatment of heart failure whether combined with diabetes or not. Ventricular remodeling after myocardial infarction leads to the occurrence and development of heart failure, and eventually leads to death. There are relatively few studies on SGLT2 inhibitors in patients with myocardial infarction. The purpose of this article is to review the research progress of SGLT2 inhibitors application before and after myocardial infarction.