ObjectiveTo explore the typical syndromes and their characteristic of symptoms and signs with high diagnostic value in patients with metabolic syndrome （MS）. MethodsTraditional Chinese medicine （TCM） diagnostic information was collected from 135 MS patients. Syndrome element differentiation and latent class analysis （LCA） were applied to identify the major TCM syndromes in MS patients. Symptoms were analyzed based on the differentiated syndromes， and a binary logistic regression model was constructed to determine symptoms and signs with high diagnostic value. ResultsA total of 135 MS patients were included， involving 163 symptoms and signs with a total frequency of 1749； twenty-three syndrome elements were extracted， 367 times frequency in total， among which 8 syndrome elements occurred ≥10 times with 323 frequencies （88.01% of the total）. These included location-related elements such as kidney （48 times）， spleen （14 times）， and stomach （14 times）， and nature-related elements such as phlegm （71 times）， yin deficiency （64 times）， dampness （57 times）， heat （42 times）， and qi deficiency （13 times）. Based on LCA， the 135 patients were categorized into two groups distinguished by the syndrome elements of dampness and phlegm， forming the "phlegm-dampness syndrome" as the major syndrome type. Nine high-frequency symptoms and signs associated with the phlegm-dampness syndrome were identified，i.e. obesity （39 times）， greasy coating （38 times）， slippery pulse （33 times）， white coating （31 times）， preference for fatty and heavy foods （30 times）， excessive urination （30 times）， fatigue and lack of strength （29 times）， wiry pulse （25 times）， and dark red tongue （25 times）. A binary logistic regression model was constructed combining these nine symptoms and signs with the LCA classification results， ultimately identifying obesity， greasy coating， fatigue and lack of strength， and white coating as independent factors associated with the phlegm-dampness syndrome in MS patients （P＜0.05）. ConclusionThe major TCM syndrome in MS patients is phlegm-dampness syndrome， and obesity， greasy coating， fatigue and lack of strength， and white coating are the typical symptoms and signs for diagnosing phlegm-dampness syndrome in MS patients.

BACKGROUND:Ferroptosis is closely associated with the pathogenesis of ischemic stroke,and targeting ferroptosis is a promising regimen for the treatment of ischemic stroke,but the specific regulatory targets are unclear. OBJECTIVE:To screen ferroptosis-related characterized genes in ischemic stroke by bioinformatics and machine learning methods and validate them by cellular experiments to investigate the role of ferroptosis in ischemic stroke. METHODS:Eligible ischemic stroke-related datasets and ferroptosis expression datasets were selected based on GEO database and FerrDb database,and ferroptosis-related differential genes were screened by t-test.GO functional enrichment analysis with KEGG signaling pathway enrichment analysis was performed for ferroptosis-related differential genes.Characterized genes for ferroptosis in ischemic stroke were screened by PPI network analysis and machine learning.The reliability and biological functions of the characterized genes were explored using ROC analysis and GSEA analysis,followed by cell experiment.HT22 cells were divided into control and ischemic stroke groups.No intervention was made in the control group,and 0.1 mM H2O2 was added to the ischemic stroke group for 24 hours to simulate cellular oxidative stress injury and ferroptosis.The ferroptosis and the expression of characterized genes were verified by real-time fluorescence quantitative polymerase chain reaction(RT-PCR)and western blot assay. RESULTS AND CONCLUSION:(1)Forty-five ferroptosis-associated differential genes were obtained,and GO and KEGG enrichment analyses revealed that the differential genes were closely associated with oxidative stress,autophagy,ferroptosis,adipocytokine signaling pathway,and mitochondrial metabolism.(2)A total of one ferroptosis characterized gene,nuclear factor erythroid 2-related factor 2(NFE2L2),was identified by the MCODE plugin and cytoHubba plugin in the PPI network with the LASSO algorithm and SVM-RFE algorithm in machine learning.(3)Receiver operating characteristic curve analysis of NFE2L2 revealed that the diagnostic prediction models constructed in the training and validation sets had good accuracy and specificity.GSEA analysis of NFE2L2 revealed that the characterized gene was involved in the regulation of ischemic stroke pathogenesis through immunity,inflammatory response,amino acid metabolism,and neurofactor regulation.(4)RT-PCR and western blot analyses showed that the acyl coenzyme A synthetase long chain family,member 4(ACSL4)mRNA and protein expression levels were significantly higher in the ischemic stroke group compared with the control group(P<0.05),and the glutathione peroxidase 4(GPX4)mRNA and protein expression levels were significantly lower in the ischemic stroke group(P<0.05).Compared with the control group,the mRNA and protein expression levels of the characterized gene NFE2L2 were significantly higher in the ischemic stroke group(P<0.05).(5)It suggests that ischemic stroke is closely related to ferroptosis,and targeting the characterized gene NFE2L2 may provide certain ideas and directions for the study and treatment of ischemic stroke.

The N-methyl-D-aspartate receptor (NMDA-R) subunit GluN2B is abundantly expressed in brain regions critical for synaptic plasticity and cognitive processes. This study investigated the structure-activity relationships (SAR) of NMDA-R ligands using GluN2B as a molecular target. Thirty potential NMDA-R antagonists were categorized into two structural classes: 1-(1-phenylcyclohexyl) amines (series A) and α-amino-2-phenylcyclohexanone derivatives (series B). In series A compounds, the phenyl ring and R1 substituents were positioned at the carbon center of the cyclohexyl ring, with R2 substituents at the para- or meta-positions of the phenyl ring. SAR analysis revealed optimal binding affinity when R1 was carbonyl (C=O) and R2 was 4-methoxy (4-OMe). Series B compounds featured a cyclohexanone scaffold with NH-R1 at the α-position and a phenyl ring bearing R2 substituents at ortho-, meta-, or para-positions. Maximum binding affinity was achieved with R1 as hydrogen (H) and R2 as hydroxyl (OH). Compounds were assessed for GluN2B-mediated ERK activation to evaluate potential metabotropic signaling properties. Approximately 50% of the compounds demonstrated ERK activation through a non-ionotropic signaling cascade involving Src, phosphatidylinositol 3-kinase, and protein kinase C. This study elucidated key structural determinants for NMDA-R binding and characterized a novel metabotropic signaling pathway. Notably, our findings suggest that compounds acting as antagonists at the ionotropic site may simultaneously function as agonists through non-ionotropic mechanisms.

ObjectiveTo explore the current situation and influencing factors of humanistic care experience among patients visiting traditional Chinese medicine （TCM） outpatient clinics in China， and to provide a basis for optimizing TCM-characterized services in both TCM and Western medicine hospitals. MethodsA multi-center cross-sectional study was conducted using convenience sampling to select 35 hospitals across 13 provinces in China （including 3 TCM hospitals and 32 TCM outpatient clinics in general hospitals）. A total of 3，430 patients were surveyed using the general information questionnaire and the Outpatient Humanistic Care Experience Questionnaire， with data collected via Questionnaire Star. Univariate analysis and multiple linear regression were employed to examine the impacts of patient characteristics， visit characteristics， hospital type （TCM hospital/general hospital）， and geographic region （eastern/central/western） on humanistic care experience. ResultsThe total score of humanistic care experience was 194 （188， 233）. Univariate analysis showed that gender， educational level， current residence， per capita monthly household income， location attribute of medical institutions， number of previous visits to this hospital， payment method of medical expenses， previous hospitalization history in this hospital， frequency of outpatient visits within the past 12 months， self-rated disease severity， familiarity with the outpatient procedures， implementation of the follow-up service provided by the hospital， satisfaction with follow-up services， the grade of the hospital visited， geographical region of the hospital visited， and the department visited had an impact on the humanistic care experience during outpatient visits （P<0.05）. Multivariate analysis demonstrated that educational level （β=0.609， P=0.011）， self-rated disease severity （β=-0.646， P=0.047）， familiarity with outpatient procedures （β=4.784， P<0.001）， satisfaction with follow-up services （β=6.365， P<0.001）， and the grade of the hospital visited （β=-5.487， P<0.001） affected the humanistic care experience in outpatient medical treatment， explaining 24.4% of the total variation. ConclusionHumanistic care experience in TCM outpatient clinics is influenced by multiple factors. It is recommended to optimize the medical treatment process， strengthen doctor-patient communication training， and establish a precise follow-up mechanism， with a focus on improving care perceptions among patients with lower education levels and those attending primary-level hospitals， to refine the TCM-characterized service system.

Objective To investigate the value of artificial intelligence-assisted compressed sensing (ACS) technology for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear using three-dimensional fluid-attenuated inversion recovery (3D-FLAIR) sequence. Methods The patients received gadolinium contrast-enhanced magnetic resonance imaging using ACS and united compressed sensing (uCS) 3D-FLAIR at Zhongshan Hospital, Fudan University from January to November 2024 were prospectively enrolled. The repetition time was 16 000 ms, and acquisition time was 6 min 40 s and 10 min 24 s in ACS 3D-FLAIR and uCS 3D-FLAIR, respectively. The images on the two sequences were evaluated independently by two radiologists. The image quality of the two sequences was subjectively evaluated and compared. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the two sequences. The grading consistencies using two sequences and between the two doctors were analyzed. Results There was no statistically difference in subjective score of image quality between the two sequences. SNR and CNR of the ACS 3D-FLAIR sequence were significantly higher than those of the uCS 3D-FLAIR sequence (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops were 0.942 and 0.888 using two sequences (P＜0.001). The kappa values of grades of cochlear and vestibular endolymphatic hydrops using the ACS 3D-FLAIR sequence between the two doctors were 0.784 and 0.831, respectively (P＜0.001); the kappa values of grades of cochlear and vestibular endolymphatic hydrops using uCS 3D-FLAIR sequence between the two doctors were 0.725 and 0.756, respectively (P＜0.001). Conclusions ACS 3D-FLAIR could provide higher SNR and CNR than uCS 3D-FLAIR, and is more suitable for intravenous gadolinium contrast-enhanced magnetic resonance imaging of the inner ear; the endolymphatic hydrops grades using ACS 3D-FLAIR is similar to use uCS 3D-FLAIR.

Objective:To analyze the genetic characteristics of varicella-zoster virus（VZV）in Anhui province from 2022 to 2023.Methods:Vesicle fluid and throat swab samples were collected from suspected varicella patients in Anhui province during 2022—2023. Fresh vesicle fluid samples were selected for VZV isolation，and real-time PCR was used for VZV nucleic acid detection. For positive samples，the region containing five single nucleotide polymorphism（SNP）sites in the open reading frame 22（ORF22）fragment was amplified，and PCR products were sequenced to identify viral genotypes. Reference sequences of VZV genotypes were downloaded from GenBank，sequence alignment and phylogenetic tree analysis were performed using Sequencher and MEGA5.0 software. Additionally，four SNP sites in ORF38 and ORF62 fragments were detected to distinguish vaccine strains from wild strains.Results:Among 96 samples from suspected varicella cases，55 of 61 vesicle fluid samples and 21 of 35 throat swab samples were positive for VZV nucleic acid. The virus isolation rate for vesicle fluid samples was 14.75%. Genetic sequencing was successful for 51 strains，all of which were wild strains belonging to the clade 2 genetic branch. Compared with the reference strain of clade 2，the nucleotide and amino acid homologies of the ORF22 fragment were 99.46%~100% and 98.39%~100%，respectively. One strain（2023VZVCZ45）exhibited an A→G mutation at site 37916.Conclusion:The prevalent VZV strains detected in Anhui province during 2022—2023 were all wild strains of clade 2，with no vaccine-associated cases identified.

The N-methyl-D-aspartate receptor (NMDA-R) subunit GluN2B is abundantly expressed in brain regions critical for synaptic plasticity and cognitive processes. This study investigated the structure-activity relationships (SAR) of NMDA-R ligands using GluN2B as a molecular target. Thirty potential NMDA-R antagonists were categorized into two structural classes: 1-(1-phenylcyclohexyl) amines (series A) and α-amino-2-phenylcyclohexanone derivatives (series B). In series A compounds, the phenyl ring and R1 substituents were positioned at the carbon center of the cyclohexyl ring, with R2 substituents at the para- or meta-positions of the phenyl ring. SAR analysis revealed optimal binding affinity when R1 was carbonyl (C=O) and R2 was 4-methoxy (4-OMe). Series B compounds featured a cyclohexanone scaffold with NH-R1 at the α-position and a phenyl ring bearing R2 substituents at ortho-, meta-, or para-positions. Maximum binding affinity was achieved with R1 as hydrogen (H) and R2 as hydroxyl (OH). Compounds were assessed for GluN2B-mediated ERK activation to evaluate potential metabotropic signaling properties. Approximately 50% of the compounds demonstrated ERK activation through a non-ionotropic signaling cascade involving Src, phosphatidylinositol 3-kinase, and protein kinase C. This study elucidated key structural determinants for NMDA-R binding and characterized a novel metabotropic signaling pathway. Notably, our findings suggest that compounds acting as antagonists at the ionotropic site may simultaneously function as agonists through non-ionotropic mechanisms.

The N-methyl-D-aspartate receptor (NMDA-R) subunit GluN2B is abundantly expressed in brain regions critical for synaptic plasticity and cognitive processes. This study investigated the structure-activity relationships (SAR) of NMDA-R ligands using GluN2B as a molecular target. Thirty potential NMDA-R antagonists were categorized into two structural classes: 1-(1-phenylcyclohexyl) amines (series A) and α-amino-2-phenylcyclohexanone derivatives (series B). In series A compounds, the phenyl ring and R1 substituents were positioned at the carbon center of the cyclohexyl ring, with R2 substituents at the para- or meta-positions of the phenyl ring. SAR analysis revealed optimal binding affinity when R1 was carbonyl (C=O) and R2 was 4-methoxy (4-OMe). Series B compounds featured a cyclohexanone scaffold with NH-R1 at the α-position and a phenyl ring bearing R2 substituents at ortho-, meta-, or para-positions. Maximum binding affinity was achieved with R1 as hydrogen (H) and R2 as hydroxyl (OH). Compounds were assessed for GluN2B-mediated ERK activation to evaluate potential metabotropic signaling properties. Approximately 50% of the compounds demonstrated ERK activation through a non-ionotropic signaling cascade involving Src, phosphatidylinositol 3-kinase, and protein kinase C. This study elucidated key structural determinants for NMDA-R binding and characterized a novel metabotropic signaling pathway. Notably, our findings suggest that compounds acting as antagonists at the ionotropic site may simultaneously function as agonists through non-ionotropic mechanisms.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.