This paper summarizes professor LIN Yi's clinical experience in treating brain metastases of triple-negative breast cancer （TNBC）. It is believed that the pathogenesis of this disease is fundamentally based on spleen and lung qi deficiency， with the binding of phlegm， stasis， and toxins acting as the critical link for disease progression， and qi stagnation serving as a major factor in its protracted course. The core therapeutic principle of "consolidating the root and cultivating the origin， resolving phlegm and dredging collaterals" is proposed. Clinically， the disease is staged into active， stable， and convalescent phases. During the active phase， characterized by spleen and lung qi deficiency alongside hyperactivity of phlegm-toxin pathogens， the treatment focuses on supplementing qi， fortifying the spleen， resolving phlegm， and dredging collaterals， utilizing the Yiqi Jiangtan Tongluo Formula （益气降痰通络方）. During the stable phase， marked by spleen deficiency， weak qi， and residual phlegm， stasis， and toxins lingering in the collaterals， the treatment aims to fortify spleen， cultivate the origin， expel pathogens， and dredge collaterals， using modified Baihua Qiling Formula （白花芪苓方）. During the convalescent phase， characterized by depletion of healthy qi， dysfunction of zang-fu （脏腑） organs， and deep-seated residual phlegm， stasis， and toxins within the brain collaterals， the treatment focuses on regulating qi movement， protecting body fluids， and applying constitution-based treatments， mostly using mild and nourishing medicinals.

This paper summarizes professor LIN Yi's clinical experience in treating brain metastases of triple-negative breast cancer （TNBC）. It is believed that the pathogenesis of this disease is fundamentally based on spleen and lung qi deficiency， with the binding of phlegm， stasis， and toxins acting as the critical link for disease progression， and qi stagnation serving as a major factor in its protracted course. The core therapeutic principle of "consolidating the root and cultivating the origin， resolving phlegm and dredging collaterals" is proposed. Clinically， the disease is staged into active， stable， and convalescent phases. During the active phase， characterized by spleen and lung qi deficiency alongside hyperactivity of phlegm-toxin pathogens， the treatment focuses on supplementing qi， fortifying the spleen， resolving phlegm， and dredging collaterals， utilizing the Yiqi Jiangtan Tongluo Formula （益气降痰通络方）. During the stable phase， marked by spleen deficiency， weak qi， and residual phlegm， stasis， and toxins lingering in the collaterals， the treatment aims to fortify spleen， cultivate the origin， expel pathogens， and dredge collaterals， using modified Baihua Qiling Formula （白花芪苓方）. During the convalescent phase， characterized by depletion of healthy qi， dysfunction of zang-fu （脏腑） organs， and deep-seated residual phlegm， stasis， and toxins within the brain collaterals， the treatment focuses on regulating qi movement， protecting body fluids， and applying constitution-based treatments， mostly using mild and nourishing medicinals.

Understanding the metabolism of endogenous and exogenous substances in the human body is essential for elucidating disease mechanisms and evaluating the safety and efficacy of drug candidates during the drug development process.Recent advancements in artificial intelligence(AI),particularly in machine learning(ML)and deep learning(DL)techniques,have introduced innovative approaches to metabolism research,enabling more accurate predictions and insights.This paper emphasizes computational and AI-driven methodologies,highlighting how ML enhances predictive modeling for human metabolism at the molecular level and facilitates integration into genome-scale metabolic models(GEMs)at the omics level.Challenges still remain,including data heterogeneity and model interpretability.This work aims to provide valuable insights and references for researchers in drug discovery and development,ultimately contributing to the advancement of precision medicine.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Objective: To investigate the protective effects and underlying mechanisms of sodium pyruvate (SP) on RBC storage lesions using an oxidative damage model. Methods: Six units of leukocyte-depleted suspended RBCs (discarded for non-infectious reasons within three days post-collection) were randomly assigned to four groups: negative control (NS), positive control (PS), experimental group 1 (SP1), and experimental group 2 (SP2). Oxidative stress was induced in the PS group by the addition of hydrogen peroxide (H O ), while SP1 and SP2 received SP supplementation at different concentrations (25 mM and 50 mM, respectively) in the presence of H O . After 1 hour of incubation, RBC morphology was assessed microscopically, and biochemical indicators including glutathione (GSH), malondialdehyde (MDA), methemoglobin (MetHb), adenosine triphosphate (ATP), and Na /K -ATPase activity were measured. Results: RBCs in the PS group exhibited pronounced morphological damage, including cell shrinkage and echinocyte formation, whereas both SP-treated groups showed significantly reduced structural injury. SP treatment led to elevated GSH levels and decreased concentrations of MDA and MetHb, suggesting attenuation of oxidative stress. Additionally, SP enhanced intracellular ATP levels and Na /K -ATPase activity, thereby contributing to membrane stability. Notably, the SP2 group (50 mM) demonstrated superior protective effects compared to SP1 (25 mM). Conclusion: Sodium pyruvate effectively attenuates oxidative storage lesions in RBCs, primarily through its antioxidant properties, energy metabolism supporting ability, and celluar membrane stabilizing function. These findings suggest SP as a promising additive for enhancing the quality and safety of stored RBCs.

BACKGROUND:Previous studies found that the proliferative scar-specific long non-coding RNA lncRNA HSFAS is a novel biomarker that can be used in the diagnosis of hypertrophic scar,but how it functions in hypertrophic scar is not clear. OBJECTIVE:To investigate the role and mechanism of lncRNA HSFAS in hypertrophic scar.METHODS:Fresh scar tissue and surrounding normal skin tissue samples from three patients with hypertrophic scar were collected,and tissue immunofluorescence was used to detect the expression of lncRNA HSFAS in frozen sections of two skin tissues. Primary fibroblasts were isolated from proliferative scarred skin tissue and normal skin tissue and cultured by enzyme digestion method. Quantitative real-time PCR was used to detect the mRNA expression of lncRNA HSFAS in cells. The proteins bound to lncRNA HSFAS were detected by RNA pull-down combined mass spectrometry. GO and KEGG were used to analyze the main functions and pathways of lncRNA HSFAS involved in hypertrophic scar progression. The targeted binding of lncRNA HSFAS to proteins was determined by catRAPID and RPISeq website analysis. RESULTS AND CONCLUSION:Compared with normal skin tissue and fibroblasts from normal skin tissue,the expression of lncRNA HSFAS in human hypertrophic scar tissue and primary fibroblasts from hypertrophic scar tissue was significantly increased (P<0.05). There were 510 proteins clearly bound to lncRNA HSFAS by RNA pull-down combined mass spectrometry. The results of GO and KEGG analyses showed that these proteins were mainly involved in RNA splicing and processing,chromosome synthesis and separation,and cell cycle. Among them,the proteins involved in RNA splicing and processing included scaffold attachment factor B2 and DICER1,and the binding fraction with lncRNA HSFAS was higher. The results of bioinformatics analysis showed that lncRNA HSFAS was bound to scaffold attachment factor B2 and DICER1 proteins. To conclude,lncRNA HSFAS may affect gene expression by interacting with scaffold attachment factor B2 and DICER1 proteins to regulate RNA splicing and processing modification,thus promoting the occurrence and development of hypertrophic scar.

OBJECTIVE To investigate the characteristics of influenza A and influenza B viruses infections in the children aged between 0 and 14 years old after COVID-19 was downgraded to category B management of infectious diseases.METHODS From Jan.2023 to Feb.2024,a total of 2349 children aged between 0 and 14 years old who were treated in Beijing Hospital of Traditional Chinese Medicine,Capital Medical University due to influenza-like symptoms of infection and received nucleic acid testing for influenza A and influenza B viruses were recruited as the research subjects.The gender and age of the children as well as the seasons were observed by chi-square test.RESULTS Totally 2349 children were included in the study,and the total positive rate of influenza was 49.85％(1171/2349);the positive rate of influenza A virus was 36.36％(854/2349),the positive rate of influenza B virus was 13.92％(327/2349),and the positive rate of the mixed infections of influenza A virus and influenza B virus was 0.43％(10/2349).The positive rate of influenza A of the girls was the highest(44.17％)(x2=8.980,P=0.011)among the children aged less than 5 years old;the positive rate of influenza B of the boys was the highest(17.19％)(x2=8.378,P=0.015)among the children aged between 5 and 10 years old.There was significant difference in the positive rate of influenza A virus among the seasons in 2023 to 2024(x2=268.12,P＜0.001);the prevalence rate was 60.93％in spring,44.40％in autumn,22.01％in winter.There was significant difference in the positive rate of influenza B virus among the seasons in 2023 to 2024(x2=373.16,P＜0.001),and the preva-lence rate was 25.44％in winter.CONCLUSIONS The influenza viruses are prevalent in spring,autumn and winter from 2023 to 2024,and the influenza A is dominant.The positive rate of influenza viruses shows an upward trend among the children aged between 0 and 14 years old after the COVID-19 is downgraded to category B management of infectious diseases,with the peak of prevalence lagging behind.

Objective:To investigate the impacts of total salvianolic acid(TSA)on macrophage polarization and mesenchymal macrophage infiltration in liver cancer bearing mice by regulating the Toll-like receptor 4(TLR4)/myeloid differentiation factor 88(MyD88)/nuclear factor-κB(NF-κB)pathway.Methods:Mice were randomly separated into liver cancer group,TSA low concentra-tion group,TSA medium concentration group,TSA high concentration group,TSA high concentration+TLR4 inhibitor(TAK242)group and control group,with 12 mice in each group.Except for control group,mice in all other groups were injected subcutaneously into the right axilla to construct liver cancer models by intraperitoneal transmission of third-generation H22 cell suspension.After suc-cessful modeling,administration was carried out once a day for 2 weeks.Changes in tumor weight,tumor volume,spleen index and thymus index were detected.Immunofluorescence was applied to detect proportions of CD86 and CD206 positive cells in tumor tissue.ELISA was applied to detect levels of inducible nitric oxide synthase(iNOS),IL-6 and IL-10 in tumor tissues.Flow cytometry was ap-plied to detect proportion of CD11b+F4/80+in tumor tissue.Western blot was applied to detect TLR4,p-NF-κB P65 and MyD88 pro-teins in tumor tissue.The life quality and survival rate of mice were observed.Results:Compared with control group,spleen index,thymus index,proportion of CD86 positive cells in tumor tissue,levels of iNOS and IL-6,and expressions of TLR4,p-NF-κB P65 and MyD88 proteins were reduced in liver cancer group,while proportion of CD206 positive cells and level of IL-10 in tumor tissue were increased(P<0.05).Compared with liver cancer group,tumor weight and volume of mice in TSA low,medium,high concentration groups were decreased,while survival rate,spleen index,thymus index,proportion of CD86 positive cells in tumor tissue,levels of iNOS and IL-6,and expressions of TLR4,p-NF-κB P65 and MyD88 proteins were increased,proportion of CD206 positive cells,level of IL-10,and proportion of CD11b+F4/80+in tumor tissue decreased(P<0.05).TAK242 reversed the effects of high concentration TSA on macrophage polarization and myeloid macrophage infiltration in liver cancer bearing mice.Conclusion:TSA may promote M1 polari-zation of macrophages in liver cancer bearing mice and inhibit myeloid macrophage infiltration by activating the TLR4/MyD88/NF-κB pathway.

Objective To conduct an in-depth analysis and feature extraction of the transcriptomics data of 10 types of cancers in order to realize the staging diagnosis of cancer samples.Methods The transcriptomics data of the top 10 cancers having the highest incidence were amassed from the UCSC Xena website,which comprised 4 938 samples and 59 428 genes.With the aid of variational autoencoder,we developed an incremental feature ranking and selection variational autoencoder(IFRSVAE)based on feature importance ranking and incorporating the masking algorithm and the Incremental Feature Selection(IFS).Subsequently,the performance efficiency of our IFRSVAE model was evaluated in conjunction with Random Forest(RF),Support Vector Machine(SVM),and eXtreme Gradient Boosting(XGboost),and it was also compared with other methods.Results Our research extracted 21 features for the ensuing classification.In comparison to the conventional variational autoencoder,recursive feature elimination,and Lasso regression models,the IFRSVAE model attained more favorable performance across all 3 classifiers(highest AUC value,and well performed other indicators).Notably,the IFRSVAE-RF exhibited the most outstanding performance,with an AUC value reaching 85.49%(95%CI:83.24%～87.74%).Moreover,Shapley additive explanations(SHAP)interpretable model illustrated well contributions of the features in our model.Conclusion Our developed IFRSVAE shows certain effectiveness in feature extraction.The constructed IFRSVAE-RF model demonstrates relatively good performance in the task of cancer staging diagnosis,which providing a new and referable idea for research orientation of deep-learning-based diagnostic methods for cancer staging.