ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

p21 (encoded by the CDKN1A gene) is a critical cell cycle regulatory protein endowed with versatile biological functions. In various sex hormone-related cancers, p21 exhibits a paradoxical dual role, capable of both inhibiting tumorigenesis and promoting cancer progression, exerting dual, often opposing, effects on cellular fate that are dictated by the specific context. The clinical targeting of p21 remains elusive, largely due to its functionally pleiotropic and context-dependent nature within intricate regulatory networks. During the initial, hormone-dependent phase of cancers like breast and prostate cancer, p21 expression and activity are largely governed by the transcriptional programs of estrogen or androgen receptor signaling. This hormonal regulation contributes to the control of tumor cell proliferation and underpins the initial efficacy of endocrine therapies. In contrast, as these diseases advance to late stages or evolve into non-hormone-dependent subtypes—exemplified by castration-resistant prostate cancer (CRPC) and specific forms of triple-negative breast cancer (TNBC)—these conventional hormonal control mechanisms often become dysfunctional or are entirely bypassed. This fundamental transition creates a critical therapeutic void, highlighting the urgent need to identify and exploit alternative molecular pathways to effectively target p21’s function. Promising strategies may include the precise modulation of its upstream transcriptional regulators, downstream effector proteins, or the intersecting parallel signaling networks that critically influence its activity. This review provides a systematic synthesis of the intricate and interconnected mechanisms that underpin the dual effects of p21 in sex hormone-related tumors. These mechanisms are categorized into three core, interrelated functional domains. (1) cell cycle regulation: p21 executes its canonical tumor-suppressive role by binding to and inhibiting cyclin-dependent kinases (CDKs) and by directly interacting with proliferating cell nuclear antigen (PCNA), thereby inducing cell cycle arrest, predominantly at the G1/S checkpoint; (2) apoptosis modulation: p21 exerts a highly context-dependent influence on programmed cell death, functioning either as a pro-apoptotic agent under severe genotoxic stress or as a pro-survival factor by inhibiting apoptosis through interactions with proteins like Bcl-2; (3) hormonal and signaling crosstalk: p21 is an integral node within broader cellular networks, engaging in direct physical interactions with hormone receptors(e.g., AR, ER) and participating in complex feedback loops with key oncogenic pathways, including PI3K/AKT, MAPK/ERK, and p53. Critically, the role of p21 is not static but highly dynamic. It can undergo a functional switch from tumor-suppressive to tumor-promoting in response to therapeutic pressures, metabolic alterations, or evolving tumor microenvironment cues. These adaptive shifts are frequently implicated in the development of therapy resistance and disease recurrence, particularly in advanced, hormone-resistant cancers. By synthesizing these insights, this review aims to establish a coherent theoretical framework to guide the future development of novel therapeutic strategies that target the p21 pathway. It underscores the necessity of moving beyond a simplistic, binary view of p21 and emphasizes the forthcoming challenges, such as the discovery of reliable biomarkers to predict its functional state and the rational design of context-specific pharmacological modulators to selectively harness its therapeutic potential.

Atherosclerosis （AS） is a chronic and inflammatory vascular disease. Macrophages are common immune cells and play an important role in the development of AS. In recent years， research has found that the formation of AS plaques is closely related to pathological and physiological processes such as macrophage polarization， energy metabolism， and lipid phagocytosis. This review aims to summarize the mechanism of macrophages in the development of AS， and to explore potential therapeutic methods for delaying AS by regulating macrophages， providing new ideas for the treatment and research of AS.

Objective:Based on outpatient and emergency visit data,this study employs a staged VaDE model to uncover the heterogeneity structure of residents'healthcare-seeking behaviors and reveal cross-district mobility patterns.Methods:Outpatient and emergency visit records of permanent residents in District A,Shanghai,in 2024 were used.Each individual visit served as the analytical unit.A staged VaDE approach was applied for nonlinear dimensionality reduction and clustering,followed by feature analysis with cross-district visit rates.Results:The proposed model outperformed K-Means and VAE+K-Means in clustering performance,identifying seven typical healthcare-seeking patterns with significant differences in cross-district rates,demographic characteristics,care structures,and disease profiles.Cluster 1 comprised elderly patients with severe conditions and high cross-district rates;Cluster 2,young and middle-aged cross-district commuters;Cluster 3,mild-case or maternity-oriented visits;Cluster 4,infrequent visits by middle-aged and elderly patients;and Clusters 5～7,local chronic disease or low-burden visits.Conclusion:The staged VaDE model demonstrates strong capability in characterizing behavioral heterogeneity and identifying key cross-district mobility types,providing evidence for refined healthcare service management and regional coordination.

Aim To investigate the role of FRMD4A in autophagy of placental trophoblast cells in preeclampsia(PE).Methods The placental tissues and clinical data of normal pregnancy and PE were obtained,and the histopathological changes were observed by HE staining.An in vitro model of hypoxia-induced HTR-8/SVneo trophoblast cells was established.The expres-sions of LC3B Ⅱ/Ⅰ and p62 in placental tissues and hypoxic cell models were analyzed by Western blot.The expression of FRMD4A was detected by qRT-PCR,Western blot and immunofluorescence,and the correlation between the expression level of FRMD4A and the clinical characteristics of the subjects was ana-lyzed by Pearson correlation analysis.Hypoxia induced trophoblast cells were transfected with si-FRMD4A,and the expression of LC3 B Ⅱ/Ⅰ and p62 was analyzed by Western blot.Results Compared with the normal group,the expression of LC3B Ⅱ/Ⅰ in PE placental tissues and hypoxia-induced trophoblast models was significantly upregulated,while the expression of p62 was significantly downregulated.Meanwhile,the ex-pression of FRMD4A increased significantly.Moreo-ver,its expression was positively correlated with the maternal systolic blood pressure,diastolic blood pres-sure,and platelet count,but negatively correlated with the neonatal weight(P＜0.01).In addition,hypoxia-induced trophoblast cells transfected with si-FRMD4A showed a significant decrease in LC3B Ⅱ/Ⅰ and an increase in p62 expression.Conclusions The expres-sion of FRMD4A is upregulated in PE placenta and hy-poxia-induced trophoblast cell model.Interfering with it can significantly hinder the autophagy process of trophoblast cells,suggesting that it may serve as a po-tential molecular target to participate in the pathologi-cal process of PE.

Aim To investigate the role of triggering receptor expressed on myeloidcells 2(TREM2)in syn-aptic plasticity induced by cocaine addiction.Methods C57BL/6J mice and Trem2 knockout mice were uti-lized in this study to evaluate the alterations in postsyn-aptic density protein 95(PSD-95)and synapsin 1(SYN1)within the cortex and hippocampus of co-caine-addicted mice by using immunological tech-niques.Results HE staining and Nissl staining showed increased neuronal damage in the hippocampus and cortex of mice after cocaine addiction.The results of immunohistochemistry and fluorescence of PSD-95 and SYN1 were consistent with the expression trend of Western blot.In the wild type mouse model,the ex-pression level of PSD-95 in the hippocampus and cortex was lower than that in the saline group,and the ex-pression of SYN1 was higher than that in the saline group.In the knockout mouse model,the expression levels of PSD-95 and SYN1 in the hippocampus and cortex were significantly higher than those in the saline group after cocaine addiction.The expression levels of PSD-95 and SYN1 in the hippocampus and cortex of cocaine knockout mice were higher than those of co-caine wild type mice.Conclusion Cocaine addiction can change the synaptic plasticity,and TREM2 plays a regulatory role in the synaptic plasticity of hippocampus and cortex in mice with cocaine injury.TREM2 is ex-pected to be a new target for studying the mechanism of cocaine addiction.

Objective To develop a deep learning method for small sample multi-omics data using attention mechanism and Meta-learning for the establishment of autism diagnosis model.Methods MLAN(Meta-learning based attentive network)consisting of the omics feature pre-reduction module,the multi-omics data fusion and feature learning module,and the parameter optimization module was designed.Firstly,differential expression analysis was performed on high-dimensional multi-omics data to preliminarily screen out unimportant features.Secondly,a multi-channel attention mechanism was used to learn the importances of every set of omics data and to realize data fusion,and a two-layer fully connected network was constructed to further extract latent features and realize the diagnosis task.Finally,the Meta-learning algorithm Reptile was used to optimize the initial parameters of the above model to obtain the optimal parameters.A total of 58 children's saliva samples were collected,including 21 children diagnosed with autism,12 children with social disorders,and 25 healthy controls,and the protein and metabolomics data were detected by mass spectrometry.All data were randomly divided into training set and test set by 4∶1,and the training set was divided into training data and validation data in the same way for model training and validation.The test set was used for the final evaluation of the model effect.Five baseline models and three ablated models were constructed and evaluated along with MLAN based on metrics including multi-classification accuracy,F1-macro and F1-weighted scores.Results The constructed multi-classification autism diagnosis model MLAN achieved multi-classification accuracy,F1-macro and F1-weighted scores of 0.850±0.066,0.817±0.103 and 0.834±0.087.The values of all three indicators were better than those of baseline models and the ablated models.Conclusion The proposed MLAN can effectively deal with heterogeneous multi-omics data with small samples and achieve good results,which is expected to provide assistance for the clinical diagnosis of autism.

Aim To investigate the effect of oroxylin A(OA)on apoptosis in Ishikawa cell line of endometrial cancer and the underlying mechanism through the phosphatidylinositol-3 kinase/protein kinase B(PI3K/AKT)signaling pathway.Methods Ishikawa cells were treated with different concentrations of OA(0,4,8,10,12,and 20 μmol·L-1)for 24 h-72 h,the cell viability was detected by CCK-8 assay,apoptosis was detected by flow cytometry,and the protein ex-pression levels of B-cell lymphoma-2(Bcl-2),Bcl-2-associated X protein(Bax),PI3K/AKT,recombinant cytochrome P450 1B1(CYP1B1),and catechol-O-methyltransferase(COMT)were detected by Western blot technique.Results OA inhibited the prolifera-tion of Ishikawa cells in a concentration-and time-de-pendent manner.Compared with the blank control group,the expression of Bax protein increased signifi-cantly,while the expression of Bcl-2 protein decreased significantly with the increase of OA concentration.The expression of COMT protein increased significant-ly,while the expression of CYP1B1 protein decreased significantly.PI3K/AKT:IGF-1(PI3 K agonist)sup-plementation reversed the effect,the expression of COMT protein significantly decreased,and the expres-sion of CYP1B1 protein significantly increased.Con-clusions OA exerts anti-tumor effects in Ishikawa cells of endometrial cancer,which may be related to cell apoptosis mediated by the inhibition of the PI3K/AKT signaling pathway.

To investigate the phenotype and genomic characterization of a mucoid-type Salmonella Saintpaul ST50 isolate from a urinary tract infection patient,promoting clinical diagnosis and treatment for urinary tract infections caused by Salmo-nella spp.Culture-based quantitative counts of midstream urine sample from the patient were conducted,and further biochemi-cal identification,mass spectrometry detection,serum agglutination test and antimicrobial susceptibility test(AST)were con-ducted on Salmonella isolate(2024JD5).Whole-genome sequencing(WGS)was performed on isolate 2024JD5 to predict sero-type,multilocus sequence type(MLST),resistance genes,and virulence genes.Two smooth-type of Salmonella Saintpaul ST50 were selected as comparative genomic reference strains from the Chinese local Salmonella genome database.The literature reviews of global Salmonella serotype of urinary tract infection were summarized.Specific serum agglutination confir-mation of isolate 2024JD5 failed due to characterization of the mucus type.The strain 2024JD5 was predicted as Salmonella Saintpaul(4,5,12:e,h:1,2)ST50 using WGS,and was resistant to ciprofloxacin,nalidixic acid,chloramphenicol and tetracy-cline with carrying aminoglycoside resistance genes aac(6')-Ⅰaa and aph(3)-Ⅱa,chloramphenicol resistance gene floR,tetra-cycline resistance gene tet,quinolone resistance gene qnrS1,and S83Y substitution in the gyrA gene was found in the quinolo-ne resistance determination region(QRDR).In addition,the strain 2024JD4 carried six types of non-plasmid-based mobile ge-netic elements and 144 virulence genes,including 71 secretion transporter genes and 58 fimbriae adhesion genes,respectively.Four types of fimbriae regulatory genes(csgB,csgC,fimW,fimY)were absent in comparison with smooth-type Salmonella Saintpaul.The literature reviews showed Salmonella Saintpaul was currently a rare Salmonella serotype in cases of urinary tract infections worldwide.Salmonella Saintpaul ST50 with mucoid-type is the pathogen of urinary tract infection with multi-drug resistant phenotypic and genotypic characteristics,and the high mucoid expression may be related to the compensatory mechanism of fimbriae regulatory genes absence in urinary tract colonization and adaptation.WGS combined with the Chinese local Salmonella genome database can effectively solve the diagnosis and biosafety assessments of rare Salmonella phenotypes.