Objective:The differentially expressed genes(DEGs)and activated signaling pathways in systemic sclerosis(SSc)were screened by bioinformatics methods,and Chinese medicines for potential treatment of SSc were explored,providing a new theoretical basis for the study of SSc and the screening of potential markers.Methods:The data sets GSE58095,GSE130953,GSE33463 and GSE58613 were selected from GEO database and divided into skin group and peripheral blood group according to the sample source.The DEGs of SSc patients was analyzed by R language,and the Wayne diagram was drawn to take the intersection of the two groups.Metascape was used for GO enrichment analysis and KEGG pathway enrichment analysis,and STRING and Cytoscape were used for protein interaction network analysis to find key pathways and hub genes.The core genes were mapped to the medical on-tology information retrieval platform,and related Chinese medicines for SSc treatment were screened.The effective components of Chi-nese medicines were obtained through TCMSP and HERB databases,and the target letters of active ingredients were obtained through swiss database.The"drug-active ingredient-target"network was constructed by Cytoscape.Results:Total 218 DEGs were identified from the skin group of patients with SSc,and 283 DEGs were screened from peripheral blood of patients with SSc.Among them,there were 7 DEGs co-upregulated in skin and peripheral blood,namely ISG15,LGALS3BP,BST2,C1QB,IFI27,CEACAM1 and FBP1.CAMK2N1 was up-regulated in skin but down-regulated in peripheral blood,ARG1 was down-regulated in skin but up-regulated in pe-ripheral blood.GO and KEGG analysis of SSc DEGs showed that these genes were significantly enriched in inflammatory response,he-moglobin complex,immune receptor activity and extracellular matrix.The results of protein interaction network suggest that more than 10 genes such as COL1A1,CTGF12,IL1B,IFNG and JUN may be potential markers of SSc and core genes of therapeutic targets.The potential Chinese medicines screened for SSc treatment include ginseng,sanguisorba,convolvula,wolfberry,safflower,etc.The main components of these herbs were β-sitosterol,quercetin,kaempferol,stigmasterol,luteolin,sitosterol,Spinasterol,and the target were AKR1B1,AR,CYP1B1,XDH,etc.Conclusion:This study uses bioinformatics to screen out core genes that may be potential markers and therapeutic targets for SSc,which is expected to be a new target for the early diagnosis and mechanism research of SSc.Meanwhile,the mapped Chinese medicine and its effective components can provide ideas for the research and development of Chinese medicine compounds for the treatment of SSc.

Objective:The differentially expressed genes(DEGs)and activated signaling pathways in systemic sclerosis(SSc)were screened by bioinformatics methods,and Chinese medicines for potential treatment of SSc were explored,providing a new theoretical basis for the study of SSc and the screening of potential markers.Methods:The data sets GSE58095,GSE130953,GSE33463 and GSE58613 were selected from GEO database and divided into skin group and peripheral blood group according to the sample source.The DEGs of SSc patients was analyzed by R language,and the Wayne diagram was drawn to take the intersection of the two groups.Metascape was used for GO enrichment analysis and KEGG pathway enrichment analysis,and STRING and Cytoscape were used for protein interaction network analysis to find key pathways and hub genes.The core genes were mapped to the medical on-tology information retrieval platform,and related Chinese medicines for SSc treatment were screened.The effective components of Chi-nese medicines were obtained through TCMSP and HERB databases,and the target letters of active ingredients were obtained through swiss database.The"drug-active ingredient-target"network was constructed by Cytoscape.Results:Total 218 DEGs were identified from the skin group of patients with SSc,and 283 DEGs were screened from peripheral blood of patients with SSc.Among them,there were 7 DEGs co-upregulated in skin and peripheral blood,namely ISG15,LGALS3BP,BST2,C1QB,IFI27,CEACAM1 and FBP1.CAMK2N1 was up-regulated in skin but down-regulated in peripheral blood,ARG1 was down-regulated in skin but up-regulated in pe-ripheral blood.GO and KEGG analysis of SSc DEGs showed that these genes were significantly enriched in inflammatory response,he-moglobin complex,immune receptor activity and extracellular matrix.The results of protein interaction network suggest that more than 10 genes such as COL1A1,CTGF12,IL1B,IFNG and JUN may be potential markers of SSc and core genes of therapeutic targets.The potential Chinese medicines screened for SSc treatment include ginseng,sanguisorba,convolvula,wolfberry,safflower,etc.The main components of these herbs were β-sitosterol,quercetin,kaempferol,stigmasterol,luteolin,sitosterol,Spinasterol,and the target were AKR1B1,AR,CYP1B1,XDH,etc.Conclusion:This study uses bioinformatics to screen out core genes that may be potential markers and therapeutic targets for SSc,which is expected to be a new target for the early diagnosis and mechanism research of SSc.Meanwhile,the mapped Chinese medicine and its effective components can provide ideas for the research and development of Chinese medicine compounds for the treatment of SSc.

Objective To explore the general rules of complications of hemophilia based on the disease network and predict the possible complications of hemophilia patients. Methods The PubMed database was searched for literature related to hemophilia. Disease entities were extracted from the titles and abstracts of the literature using the MetaMap tool. A disease network was constructed based on the co-occurrence relationship of disease pairs, and the overall characteristics, node characteristics, and structural characteristics of the disease network were analyzed. The disease entity network was analyzed for association rules to explore the general patterns of hemophilia complications. The link prediction algorithm was used to predict potential complications of hemophilia. Results The association network composed of hemophilia and its complications satisfied the characteristics of small-world networks and evenly distributed cohesive subgroups in terms of network structure. Cohesive subgroup analysis showed that hemophilia complications can be divided into four categories: inherited diseases, blood system diseases, infectious diseases, and chronic diseases. Association rule analysis identified 133 rules with a confidence level ≥0.8, and link prediction further identified many well-documented disease pairs. Conclusion Based on the disease network, hemophilia complication association analysis and link prediction can effectively predict potential hemophilia complications, providing decision support for clinical diagnosis and treatment of hemophilia.

Objective To analyze the phenotypic characteristics of albinism and their correlations. Methods Literatures related to albinism in PubMed database before June 10, 2023 were obtained, and phenotypic entities were extracted from their abstract texts to construct a phenotypic co-occurrence network. GePhi and VOSviewer software were used to analyze the overall characteristics and phenotypic clustering of the network. The Apriori algorithm was used to mine the association rules between phenotypes. The AA index was used for link prediction, predicting possible combinations of albino phenotypes. Results The phenotypic co-occurrence network of albinism had a small-world characteristic, and nystagmus, hypopigmentation of skin and foveal dysplasia of retina were the main phenotypes. Phenotypic abnormalities of albinism were mainly divided into five categories, including visual system abnormalities, immune system abnormalities, skin and hair system abnormalities, nervous system abnormalities, and respiratory as well as digestive system abnormalities. A variety of ocular abnormalities were associated with nystagmus. The combination of abnormal phenotypes that may occur in albinism included pneumonia with hypopigmentation of the skin, foveal dysplasia of the retina and atrophy of the optic nerve. Conclusion Predicting and analyzing the phenotypic characteristics of albinism and the associative patterns among phenotypes, as well as the potential co-occurrence of phenotypes in albinism patients can provide valuable references for identifying research directions for albinism and for the recognition, diagnosis, and prediction of albinism development.

ObjectiveTo analyze the online public Q&A texts on HPV vaccine， focus on the important issues related to HPV vaccination and cervical cancer prevention in China， and propose strategies and suggestions. MethodsThe latent Dirichlet allocation （LDA） topic model was employed to extract key topics of 15 565 Q&A texts related to HPV vaccines from the social Q&A platform "Zhihu". The Baidu AI sentiment analysis tool was used to analyze the emotional tendencies of the texts corresponding to each topic， and the topics were classified based on the strategic coordinate method. ResultsOnline users focused on eight topics about HPV vaccine information. Among them， vaccination knowledge， HPV vaccination hesitation， and HPV vaccine development and marketing belonged to the low positivity-high negativity emotional topics， HPV infection and high-risk factors belonged to the low positivity-low negativity emotional topics， and HPV vaccine appointment channels， comparison between domestic and imported vaccines， HPV vaccines and cervical cancer prevention， and HPV vaccine types and selection were grouped under high positivity-low negativity emotional topics. ConclusionPublic concerns regarding HPV vaccines can be classified into three major dimensions： health knowledge， health beliefs， and health behaviors. Overall， the public's views and attitudes towards vaccine-related issues are not optimistic. Strengthening science publicity and education， enhancing vaccine supervision， and encouraging enterprises’ innovative research and development capability are effective strategies to improve public awareness of cervical cancer prevention and accelerate the full HPV vaccination coverage.

OBJECTIVE To mine the focus and emotional attitude of the public on rare diseases， and to provide decision- making reference for relevant departments to formulate and implement relevant policies， systems and strategies for medical security of rare diseases. METHODS Latent Dirichlet allocation （LDA） topic model and sentiment analysis method were used to analyze the comment text of short videos related to the “nosinasine” medical insurance admission event on the Bilibili video website， mine the theme and sentiment tendency of the text， and put forward relevant strategy suggestions. RESULTS A total of 8 videos with tens of thousands of playback and 7 109 text data were obtained. According to the LDA analysis， online public paid attention to 9 topics related to rare diseases （the price of rare disease drugs， the inclusion of rare disease drugs in medical insurance， the status quo of research and development of rare disease drugs， the scope of medical insurance and the medical security system， the plight of rare disease patients， the prevention and screening of rare diseases， the value of rare disease drugs in medical insurance， the Chinese and western medical methods of rare diseases， and the supply and demand status of rare disease drugs）， which could be summarized into 4 categories according to the objects of concern （rare disease drugs， rare disease medical insurance， rare disease medical and health services and rare disease patient groups）. On the whole， the emotional tendency of the Internet public towards each topic showed a low positive and high negative tendency. CONCLUSIONS The public paid more attention to the price， research and development， supply and demand of rare disease drugs， and was deeply worried about the current medical status of rare diseases in China. To strengthen and improve the medical security for patients with rare diseases， such as actively carrying out public health services for rare diseases， strengthening cooperation in the diagnosis and treatment of rare diseases， and researching rare disease drugs， etc. Chinese medical and health departments can make concerted efforts in medical and health services， drug supply security， medical security and other social security.

Objective To reveal the subjects and hotspots in domestic studies on information behaviors by analyzing the domestic papers on information behaviors. Methods The key words in domestic papers on information behaviors were analyzed by factor analysis and co-word clustering analysis with the structure of subjects in domestic studies on information behaviors elaborated. Results The domestic studies on information behaviors were focused on the fol-lowing 12 aspects, such as information literacy, network information behaviors, information behavior model, infor-mation dissemination, and information service in libraries. Conclusion The hotspots in domestic studies on informa-tion behaviors are characterized by the various objects, scattered subjects, and balanced degrees.

The social tagging system on Internet is a new model for the organization and communication of information resources in the modern network environment.After the social tagging system and information communication model were outlined,the information communication model in social tagging system and its advantages and disadvantages were analyzed with Watercress Network as an example,and suggestions were put forward for its optimization.

The knowledge atlas for researches of invisible knowledge management was plotted after the key words and their relationship in papers on invisible knowledge published in the past 5 years were quantitatively and qualitatively analyzed by social network analysis, co-words cluster analysis, and impact factor analysis with the journal articles covered in CNKI, Wanfang, VIP Chinese Scientific and Technological Journals Databases as the data source.The hotspots and structure in researches of invisible knowledge management were then studied in order to provide reference for the innovative development and future research of invisible knowledge management.

The functions and service of WeChat platform in domestic academic libraries were summarized in order to find out the satisfied aspects ( such as its response speed, interface design and operation) and unsatisfied aspects (interaction efficiency, push quality and popularization) of users with the functions and service of WeChat plat-form. Measures should be taken for improving the unsatisfied aspects in order to meet the users' requirements, and suggestions were put forward for optimizing the functions of WeChat platform and perfecting its service, such as atta-ching importance to the WeChat public platform construction and improving its service in order to transform the aca-demic libraries into intelligent libraries.