Digital and intelligent technologies serve as the core engine driving the inheritance of the essence and the innovation while upholding the fundamentals of traditional Chinese medicine（TCM）. Currently， the digital and intelligent transformation of TCM has undergone four developmental stages， exhibiting inherent characteristics such as long-term inevitability， objective standardization， and ecological evolution. By introducing quantitative metrics， digital and intelligent technologies have achieved breakthroughs in TCM knowledge inheritance and innovation， clinical diagnosis and treatment， and herbal medicine supply. The practical applicability of methodological innovations has been empirically validated， though significant disparities exist in technological adaptability and application depth across different fields. Overall， the digital and intelligent transformation of TCM remains in its nascent stage， grappling with multiple structural challenges：weak data foundations， inadequate technological adaptability， incomplete institutional frameworks， shortages of multidisciplinary talent， lagging policies and regulations， and urban-rural digital divide. In order to foster sustainable development and modernization of TCM， this paper establishes a six-dimensional collaborative governance framework of encompassing data， technology， organization， institutions， environment and ethics， which is rooted in data governance and digital governance theories. Future efforts should center on standardization， integration， and ecosystem development to build a data and technology foundation. Focus should be placed on deepening innovation and application of key TCM-specific technologies， while simultaneously strengthening interdisciplinary talent cultivation， improving institutional mechanisms and policy frameworks， and increasing support for rural areas. By adopting a people-centered and technology-empowered approach， we can overcome developmental constraints and unleash the powerful driving force of digital and intelligent technologies for the inheritance of TCM.

Arsenic (organoarsenic) compound is one of the oldest drugs used by humans to treat various diseases. From its initial application in treating various skin diseases to the 1970s when arsenic trioxide (ATO) was proven to be able to significantly relieve acute promyelocytic leukemia (APL), arsenic (organoarsenic) compounds gradually occupied an important position in the history of medical development. This article reviews the pharmaceutical research progress of inorganic arsenic compounds and organic arsine compounds, covering anticancer, antiparasitic, antiviral and antibiotic aspects. It further explores the potential for developing new arsenic (organoarsenic) drugs with higher efficacy and lower toxicity, aiming to provide new research directions and ideas for the application of arsenic (organoarsenic) compounds in disease treatment.

Arsenic (organoarsenic) compound is one of the oldest drugs used by humans to treat various diseases. From its initial application in treating various skin diseases to the 1970s when arsenic trioxide (ATO) was proven to be able to significantly relieve acute promyelocytic leukemia (APL), arsenic (organoarsenic) compounds gradually occupied an important position in the history of medical development. This article reviews the pharmaceutical research progress of inorganic arsenic compounds and organic arsine compounds, covering anticancer, antiparasitic, antiviral and antibiotic aspects. It further explores the potential for developing new arsenic (organoarsenic) drugs with higher efficacy and lower toxicity, aiming to provide new research directions and ideas for the application of arsenic (organoarsenic) compounds in disease treatment.

Objective:To establish and optimize a novel method, focus forming assay (FFA), for quantitation of influenza A virus (FluA) and compare its application performance with traditional plague forming assay (PFA).Methods:The foci chromogenic effects of three peroxidase substrates in immunostaining were compared. The PFA and FFA methods were used to explore FluA incubation times and plaque morphology on 12-well plates, and to determine optimal incubation times and virus adsorption volumes for different FluA subtypes on 96-well plates. The correlation between FFA and PFA was evaluated, and the optimized FFA was applied to the in vitro antiviral efficacy analysis of Favipiravir and neutralization test against different subtypes of FluA. Results:TRUEBLUE substrate was identified as the optimal substrate for foci visualization. Compared with the PFA, the FFA showed improved sensitivity and reduced detection time in FluA titration, and good correlation was shown between the two methods′ results. By replacing the 96-well plate with the 12-well plate for FFA titration of different subtypes of FluA, the detection time was shortened, and the amount of serum samples used could be further reduced by optimizing the virus adsorption volume. The half-maximal effective concentration of favipiravir against influenza viruses assessed by the FFA and PFA methods showed no significant difference, and was consistent with the results obtained from quantitative PCR. Additionally, the focus reduction neutralization test and hemagglutination inhibition assays demonstrated strong correlation in determining antibody titers against FluA in serum neutralization assays.Conclusions:The improved FFA method developed here provides a more efficient experimental tool for FluA titration, antiviral drug screening and broad-spectrum vaccine evaluation.

Objective:To investigate the epidemiological and genetic characteristics of hand, foot and mouth disease (HFMD) caused by coxsackievirus A6 (CVA6) in Xi′an city from 2021 to 2023.Methods:Collected clinical cases of HFMD, epidemiological information and samples were obtained. The specimens were tested by the real-time RT-PCR for enterovirus A71(EVA71), CVA16, CVA6 and CVA10, respectively. The VP1 regions of CVA6 were amplified and sequenced, MEGA X was used for phylogenetic analysis.Results:From 2021 to 2023, a total of 1 393 HFMD samples were collected, 1 106 (79.40%, 1 106/1 393) of which were positive for enteroviruses. The proportions of EVA71, CVA16, CVA6 and CVA10 were 0.45% (5/1 106), 16.64% (184/1 106), 72.42% (801/1 106) and 2.17% (24/1 106). A total of 801 HFMD cases tested positive for CAV6, including 783 mild cases and 18 severe cases, mainly in children aged ≤5 years (86.02%, 689/801), with a male/female ratio of 1.49∶1. The composition ratio of CVA6 infection differed with year(χ 2=332.62, P<0.01), and the highest composition ratio of CVA6 was in 2023 (91.01%, 638/701). The nucleotide and amino acid similarities in the VP1 region of Xi′an strains of CVA6 were 92.4%-99.8% and 98.3%-100.0%, respectively. Compared with the CVA6 prototype strain(Gdula), the nucleotide and amino acid similarities in the VP1 region of Xi′an strains were 82.2%-84.0% and 95.4%-96.0%, respectively, and there were 18 amino acid mutations in different degrees. Based on the phylogenetic analysis of VP1 region sequences, the CVA6 strains in Xi′an city from 2021 to 2023 belonged to D3a subtype, and could be divided into two clusters with 18 strains in cluster 1 while two strain in cluster 2. Conclusions:The sub-genotype D3a of CVA6 is the predominant virus causing HFMD in Xi′an city from 2021 to 2023, and there are two transmission chains. The monitoring and prevention of CVA6 should be strengthened.

Regarded as a pivotal strategy for comprehensively upgrading the healthcare system,Digital transformation is highly valued by policymakers.The essence of digital transformation in healthcare encompasses transformation practices across multiple facets,including healthcare facility administrators,service providers,patients,regulators and payers.However,digital transformation also poses numerous challenges,such as data security,technological adaptation,doctor-patient communication,regulatory balance and payment process optimization.To address these challenges,it is recommended to enhance data security and privacy protection,optimize technology learning and adaptation,balance technology application with clinical experience,improve data governance and business processes,strengthen patients'digital literacy,balance standardization with innovation,and optimize payment processes.These suggestions provide a reference for advancing the digitalization process of China's healthcare industry.

Objective To develop a risk prediction model for moderate-to-severe catheter-related bladder discomfort(CRBD)after non-transurethral surgery based on various machine-learning algorithms and to compare the performance of the models,so as to provide a reference for accurately identification and prevention of the postoperative moderate-to-severe CRBD.Methods A convenience sampling method was employed to recruit 719 patients as study subjects.The patients received non-transurethral surgery and intraoperative urinary catheterisation in a Tier-ⅢA hospital in Shanxi Province between January and May 2024.The clinical data were collected,with 70％of the randomly selected data was assigned to a training dataset(n=503)for the model building and the rest of 30％of data was used as the testing dataset(n=216)for internal model validation.Predictors were determined using least absolute shrinkage and selection operators(LASSO).Seven machine learning methods of logistic regression,K-nearest neighbours,random forest,artificial neural network,decision tree,light gradient boosting machine(LightGBM)and elastic net were employed to establish the risk prediction models.Performance of the models was evaluated based on the area under receiver operating characteristic curve(AUR-ROC),accuracy,precision,recall and F1 score.Results A total of 719 patients who underwent non-transurethral surgery were included in the study.It was found that 154(21.4％)patients presented with moderate to severe CRBD and 565(78.6％)patients were without or only with a mild CRBD.The predictors were deduced to six variables:gender,abdominal surgery,type of surgery,administration of dexmedetomidine before surgery,intraoperative administration of flurbiprofenate,and use of tramadol by the completion of surgery.It was found that the LightGBM model demonstrated a high stability,with 0.793 in AUC-ROC,0.763 in accuracy,0.879 in precision,0.747 in recall and 0.808 in F1.Conclusion The risk prediction model established through LightGBM for moderate-to-severe CRBD after a non-transurethral surgery exhibits a high stability.It offers a reference for medical practitioners to identify the patients with high-risk of moderate-to-severe CRBD and prepares for relevant interventions.

Objective:To establish and optimize a novel method, focus forming assay (FFA), for quantitation of influenza A virus (FluA) and compare its application performance with traditional plague forming assay (PFA).Methods:The foci chromogenic effects of three peroxidase substrates in immunostaining were compared. The PFA and FFA methods were used to explore FluA incubation times and plaque morphology on 12-well plates, and to determine optimal incubation times and virus adsorption volumes for different FluA subtypes on 96-well plates. The correlation between FFA and PFA was evaluated, and the optimized FFA was applied to the in vitro antiviral efficacy analysis of Favipiravir and neutralization test against different subtypes of FluA. Results:TRUEBLUE substrate was identified as the optimal substrate for foci visualization. Compared with the PFA, the FFA showed improved sensitivity and reduced detection time in FluA titration, and good correlation was shown between the two methods′ results. By replacing the 96-well plate with the 12-well plate for FFA titration of different subtypes of FluA, the detection time was shortened, and the amount of serum samples used could be further reduced by optimizing the virus adsorption volume. The half-maximal effective concentration of favipiravir against influenza viruses assessed by the FFA and PFA methods showed no significant difference, and was consistent with the results obtained from quantitative PCR. Additionally, the focus reduction neutralization test and hemagglutination inhibition assays demonstrated strong correlation in determining antibody titers against FluA in serum neutralization assays.Conclusions:The improved FFA method developed here provides a more efficient experimental tool for FluA titration, antiviral drug screening and broad-spectrum vaccine evaluation.

Objective:To investigate the epidemiological and genetic characteristics of hand, foot and mouth disease (HFMD) caused by coxsackievirus A6 (CVA6) in Xi′an city from 2021 to 2023.Methods:Collected clinical cases of HFMD, epidemiological information and samples were obtained. The specimens were tested by the real-time RT-PCR for enterovirus A71(EVA71), CVA16, CVA6 and CVA10, respectively. The VP1 regions of CVA6 were amplified and sequenced, MEGA X was used for phylogenetic analysis.Results:From 2021 to 2023, a total of 1 393 HFMD samples were collected, 1 106 (79.40%, 1 106/1 393) of which were positive for enteroviruses. The proportions of EVA71, CVA16, CVA6 and CVA10 were 0.45% (5/1 106), 16.64% (184/1 106), 72.42% (801/1 106) and 2.17% (24/1 106). A total of 801 HFMD cases tested positive for CAV6, including 783 mild cases and 18 severe cases, mainly in children aged ≤5 years (86.02%, 689/801), with a male/female ratio of 1.49∶1. The composition ratio of CVA6 infection differed with year(χ 2=332.62, P<0.01), and the highest composition ratio of CVA6 was in 2023 (91.01%, 638/701). The nucleotide and amino acid similarities in the VP1 region of Xi′an strains of CVA6 were 92.4%-99.8% and 98.3%-100.0%, respectively. Compared with the CVA6 prototype strain(Gdula), the nucleotide and amino acid similarities in the VP1 region of Xi′an strains were 82.2%-84.0% and 95.4%-96.0%, respectively, and there were 18 amino acid mutations in different degrees. Based on the phylogenetic analysis of VP1 region sequences, the CVA6 strains in Xi′an city from 2021 to 2023 belonged to D3a subtype, and could be divided into two clusters with 18 strains in cluster 1 while two strain in cluster 2. Conclusions:The sub-genotype D3a of CVA6 is the predominant virus causing HFMD in Xi′an city from 2021 to 2023, and there are two transmission chains. The monitoring and prevention of CVA6 should be strengthened.

Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.