The prescription of Qidong Yixin oral liquid is derived from the experience of national medical master Ren Jixue in treating viral myocarditis （VMC）. It has the functions of tonifying Qi， nourishing the heart，calming the mind， and relieving palpitations. It is used to treat VMC and angina pectoris of coronary heart disease caused by deficiency of both Qi and Yin. However，the understanding of its efficacy evidence， advantageous aspects， dosage and administration， and medication safety remains insufficient in clinical practice. Therefore，the development of the Expert Consensus on the Clinical Application of Qidong Yixin Oral Liquid （hereinafter referred to as consensus） was initiated. Consensus strictly followed the process and methods of the expert consensus on the clinical application of Chinese patent medicines of the China Association of Chinese Medicine，successively completing multiple tasks such as the consensus project initiation，determination of clinical problems，evidence search and evaluation，formation of recommendation opinions and consensus suggestions，solicitation of opinions，peer review， submission for review and release， and so on. Consensus formed a total of 10 recommendation opinions and 12 consensus suggestions，clarifying the clinical positioning，efficacy advantages，syndrome differentiation，dosage and administration，combination therapy，timing of medication，adverse reactions，contraindications， and precautions of Qidong Yixin oral liquid，indicating that it has good clinical advantages and safety in the treatment of VMC and angina pectoris of coronary heart disease，providing norms and references for physicians to safely and rationally apply Qidong Yixin oral liquid. Consensus was reviewed and approved for release by the Standardization Office of the China Association of Chinese Medicine on December 23， 2024. Standard number：GSCACM-376-2024.

Allergic diseases exhibited the characteristics of latent concealment and dynamic transmutation， which highly align with the pathogenic features of "latency and transformative change" described in the theory of latent pathogens. Based on the "latent pathogens with transformative potential" theory， this paper systematically explored the mechanisms of occurrence， transmission， and outcome of allergic diseases. It proposed that the insufficiency of kidney essence is the root cause enabling pathogens to lurk internally， leading to disease onset due to deficient healthy qi and lurking pathogens； the dysfunction of sanjiao serves as the pathway for pathogen stagnation， driving multi-system transmission； the accumulation of phlegm， stasis， and toxins constitutes the predicament of a protracted course， ultimately resulting in intractable pathological entanglement. Accordingly， a tiered intervention strategy is formulated，i.e. during the latency period， treatment should tonify the kidney and replenish essence to consolidate the foundation and halt the tendency of pathogens to lurk internally； during the transmission period， treatment should regulate sanjiao to intercept disease transmission and curb multi-system proliferation； during the protracted period， treatment should purge phlegm and resolve stasis to eliminate stubborn lesions， and break the vicious cycle of chronic accumulation and damage.

OBJECTIVE To prepare an intelligent responsive liposome-hydrogel nanopreparation co-loaded with gambogic acid （GA）， and characterize its antitumor activity in vitro . METHODS GA-ICG-Lip-gel was prepared by ethanol injection and cold dissolution， incorporating GA and the photosensitizer indocyanine green （ICG）. The appearance and microscopic morphology of GA-ICG-Lip-gel were observed， its encapsulation efficiency and drug loading capacity were measured， and its photothermal conversion performance， photothermal stability， and infrared imaging properties were investigated， along with the determination of its in vitro release profile. Human breast cancer MCF-7 cells were used as objects to investigate the effects of GA-ICG-Lip-gel （or with near-infrared light irradiation） on cell viability， migration ability， and the cellular uptake capacity of GA-ICG-Lip-gel. RESULTS GA-ICG-Lip-gel existed in a solution state at room temperature and transformed into a gel state at 37 ℃. Its microstructure was dense with small pores， and its encapsulation efficiency and drug loading were （96.07±0.86） % and （6.28±1.16） %， respectively. After exposure to near-infrared light， the temperature of GA-ICG-Lip-gel rose above 42 ℃， with no significant attenuation observed in the heating curve. The heating efficiency was dependent on both the irradiation time and drug concentration. Compared to media without gelatinase， the cumulative release rate of GA-ICG-Lip-gel increased in media containing gelatinase. In vitro studies showed that GA-ICG-Lip-gel could be efficiently taken up by MCF-7 cells； GA-ICG-Lip-gel significantly inhibited the viability and migration ability of MCF-7 cells （ P ＜0.05）， and this inhibitory effect was further enhanced under near-infrared light irradiation. CONCLUSIONS This study successfully prepares GA-ICG-Lip-gel， which exhibits favorable photothermal conversion properties and temperature/enzyme dual-responsive drug release characteristics， and demonstrates significant inhibitory effects on the proliferation and migration of breast cancer cells.

Puji Xiaoduyin， a specialized formula for the swollen-head epidemic， was recorded in the Catalogue of Ancient Classical Formula （the Second Batch）-Han Medicine， published in September 2023. It had been inherited and developed by medical experts of successive generations and passed down to this day. This paper sorted out the historical evolution of this formula using bibliometric methods. It also comprehensively analyzed key information on the formula name， historical origin， drug dosage， herb origin， processing methods， decocting methods， function， and clinical applications. Additionally， this paper analyzed the application of this formula in both modern and ancient times. Results showed that the formula was first recorded as "Puji Xiaodu Yinzi" in LI Dongyuan's Proven Formulas written by LI Gao from the Jin dynasty. The medicinal composition and dosage were： Scutellariae Radix and Coptidis Rhizoma （20.65 g each）， Ginseng Radix et Rhizoma 12.39 g， Scrophulariae Radix， Citri Reticulatae Pericarpium， and Glycyrrhizae Radix et Rhizoma （8.26 g each）， Forsythiae Fructus， Arctii Fructus， Isatidis Radix， and Lasiosphaera Calvatia （4.13 g each）， Bombyx Batryticatus and Cimicifugae Rhizoma （2.891 g each）， Bupleuri Radix and Platycodonis Radix （8.26 g each）. These medicines were grounded to fine powder. One dose， including 20.65 g of the powder， was mixed with 600 mL of water and decocted to 300 mL. After abandoning slag， the medicine should be taken warm frequently. In the formula， Bombyx Batryticatus is stir-fired. With the effect of dispersing wind and clearing heat， removing stagnation and dissipating mass， the formula is specialized in swollen-head epidemic， pestilence， red and swelling head， face， and neck， dry mouth and tongue， as well as other diseases resulting from toxic heat stagnated in the upper jiao. The formula is widely used in treating diseases involving the respiratory， dermal， ophthalmologic， otolaryngologic， and nervous systems. The formula is most frequently used for respiratory diseases， with a wide range of symptoms including parotitis/mumps （66 times）， followed by tonsillitis （28 times）. In conclusion， the broadly applied formula has accurate efficacy and great development value.

OBJECTIVE To construct a preoperative medication reconciliation model assisted by a localized large language model （LLM） for gastric cancer and evaluate its clinical efficacy. METHODS A total of 249 gastric cancer patients with a history of continuous medication before admission in the Gastric Surgery Department of Jiangsu Cancer Hospital were retrospectively enrolled. Patients were divided into training set （154 cases） and validation set （95 cases） based on the order of time. Based on guidelines， drug package inserts， and other evidence， a standardized medication reconcili ation process and a structured knowledge base were constructed. DeepSeek-V3 LLM was deployed privately in the hospital， combined with retrieval-augmented generation technology， to achieve automated integration of medication information， risk screening， and generation of personalized recommendations. The quality of LLM-generated recommendations was evaluated using automatic metrics （BERT Score and ROUGE-1， 2， L） and manual scoring [seven-dimensional index （7DI） ] . Spearman correlation analysis was performed to explore the correlation between automatic scores and manual scores. Cronbach’s α coefficient was used to test the internal consistency of manual scoring results. The time consumed by manual and LLM-assisted medication reconciliation was compared across tasks of different difficulty levels （simple， moderate， and high）. RESULTS A structured knowledge base covering 8 major drug categories was finally established， covering common and high-risk preoperative medication scenarios and providing structured retrieval support for the LLM. For automatic evaluation， the precision， recall， and F1-score of BERT Score were 0.783±0.033， 0.811±0.038， and 0.796±0.028， respectively. The F1-scores of ROUGE-1， ROUGE-2 and ROUGE-L were 0.566±0.067， 0.338±0.076 and 0.468±0.082， respectively. The 7DI scores from three manual raters ranged from 32.06 to 33.45. The F1-score of automatic scoring was significantly positively correlated with the 7DI score of manual scoring （maximum coefficient of determination＝0.611， P ＜0.001）， and the internal consistency of manual scoring was good （Cronbach’s α ＝ 0.876）. In terms of efficiency， LLM-assisted medication reconciliation reduced time consumption by more than 90% compared with manual reconciliation in the simple， moderate， and high-difficulty groups （ P ＜0.001）. CONCLUSIONS The medication reconciliation model constructed based on a localized LLM and structured knowledge base shows high accuracy， consistency， and clinical applicability in complex preoperative medication scenarios for gastric cancer. It can improve the efficiency of medication reconciliation and reduce potential medication risks.

Objective: To investigate the prevalence of overweight and obesity among children and adolescents in Yangzhou City, and its association with screen behaviors, so as to provide scientific evidence for weight management among students. Methods: In May 2025, an electronic questionnaire survey was conducted among children and adolescents in Yangzhou City. A total of 3 722 participants were selected from grades 4 to 12 in 18 primary and secondary schools (108 classes) by using stratified cluster random sampling. The Chi square test was used to compare the differences in the detection rates of overweight and obesity among children and adolescents with 5 types of screen behaviors (watching TV, playing electronic games, scrolling short videos, screen based learning, electronic socializing) in different time groups each day (never, >0~<2 h, ≥2 h). Multivariate Logistic regression analysis was performed to examine the associations of five types of screen behaviors, presence of electronic devices in the bedroom, and screen use during meals on the weight status of children and adolescents. Results: The prevalence of overweight and obesity among children and adolescents was 37.3%. For all five types of screen behaviors, the differences in the distribution of overweight and obesity detection rates among children and adolescents across the three time spent categories were statistically significant ( χ 2=30.76- 70.78 , all P <0.01). After adjusting for confounding factors, multivariate Logistic regression analysis revealed that frequent or always using screens during meals( OR =1.63, 95％ CI =1.14~2.31), playing video games ( OR =1.28, 95% CI =1.11-1.48), browsing short videos ( OR =1.29, 95％ CI=1.09-1.54), and screen based learning ( OR =1.26, 95％ CI =1.10-1.44) were significantly associated with overweight and obesity among children and adolescents (all P <0.05). Conclusions Excessive screen use is positively correlated with the incidence of overweight and obesity in children and adolescents. Targeted interventions on screen behaviors among children and adolescents are therefore warranted.

ObjectiveTo investigate the regulatory effect of overexpressed protein tyrosine phosphatase non-receptor type 2 （Ptpn2） on the inflammatory response of mouse alveolar macrophages （MH-S） induced by SiO₂. MethodsCells with overexpressed Ptpn2 were constructed and induced by SiO₂. The experimental groups were divided into four groups： the negative control group with an empty vector （NC）， the overexpressed Ptpn2 group （P）， the negative control group with an empty vector + SiO₂ induction （NS）， and the overexpressed Ptpn2 + SiO₂ induction group （PS）. Isobaric tags for relative and absolute quantification （iTRAQ） combined with liquid chromatography-tandem mass spectrometry （LC-MS/MS） were used to screen differential proteins， followed by Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） database analyses. Immunofluorescence staining was used to detect the expressions of Tumor necrosis factor （TNF） α， Gasdermin D （GSDMD）， and Transforming growth factor （TGF）-β1. Western blot was used to detect the protein expression levels of PTPN2， Toll-like receptor 4 （TLR4）， tumor necrosis factor-α （TNF-α）， nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3）， and proteins related to the TGF-β1 signaling pathway in the cells of each group. ResultsiTRAQ results identified 144 differential proteins among the four groups. GO analysis showed that in biological processes （BP）， these differential proteins were mainly enriched in IκB kinase/nuclear factor-κB （NF-κB） signaling， cell activation and signal transduction involved in immune responses， and regulation of receptor signaling pathways by signal transducer and activator of transcription （STAT）， etc. KEGG analysis revealed that the differential proteins were mainly enriched in Toll-like receptor signaling pathway， NF-κB signaling pathway， NOD-like receptor signaling pathway， TGF-β signaling pathway， and TNF signaling pathway. The results of immunofluorescence staining showed that compared with the NC group， the expressions of TNF α， GSDMD， and TGF-β1 in the cells of the NS group increased （P < 0.05）； compared to the NS group， the expression of the aforementioned proteins in the PS group decreased in cellular proteins（P < 0.05）. The results of Western blot showed that compared with the NC group， the protein expression levels of PTPN2， p-NF-κB，MyD88，TLR4，NLRP3，GSDMD，Caspase-1，IL-1β， TGF-βR1， TGF-βR，p-Smad2/3 in the NS group were significantly upregulated （P < 0.05）； compared with the NS group， the expression levels of the aforementioned proteins in the PS group were significantly downregulated （P < 0.05）. ConclusionOverexpression of Ptpn2 can inhibit the protein expressions of TLR4-TNF-α signaling， NLRP3 signaling， and TGF-β1 signaling closely related to inflammatory response in SiO₂-mediated MH-S macrophages.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.