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.

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.

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.

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.

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 investigate the changes and predictive value of Omentin-1 levels in patients with type 2 diabetes mellitus(T2DM)under different bone metabolic status.Methods A total of 120 T2DM pa-tients admitted to a hospital from June 2021 to December 2022 were selected and divided into group A(normal bone mass,T-value-1.0,36 cases),Group B(bone loss,-2.5＜T-value＜-1.0,49 cases)and group C(osteoporosis,T-value-2.5,35 cases)according to different bone mineral density.Another 50 healthy sub-jects who underwent physical examination in a hospital during the same period were selected as the healthy control group.Basic data,serum Omentin-1 and bone metabolism levels of the 4 groups were compared,and the correlation between serum Omentin-1 and bone metabolism and blood glucose levels was analyzed by Pear-son correlation analysis.Multiple stepwise regression analysis was conducted to analyze the factors affecting bone mineral density in T2DM patients.Receiver operating characteristic(ROC)curve was drawn to analyze the predictive value of serum Omentin-1 level in T2DM with osteoporosis.Results The fasting blood glucose(FBG)level of groups A,B and C was higher than that of healthy control group,and the hemoglobin A1c(HbA1c)and homeostasis model assessment of insulin resistance(HOMA-IR)of healthy control group,group A and group B were lower than that of group C,with statistical significance(P＜0.05).Omentin-1,type Ⅰ procollagen N-terminal propeptide(P Ⅰ NP)and osteocalcin(BGP)in healthy control group,group A and group B were higher than those in group C,while the β-CTX sequence of type Ⅰ collagen in healthy con-trol group,group A and group B was lower than that in group C,and the difference was statistically signifi-cant(P＜0.05).Pearson correlation analysis showed that the serum Omentin-1 level in T2DM patients was negatively correlated with the levels of HbA1c,HOMA-IR and β-CTX(r=-0.770,-0.807,-0.759,P＜0.05),and positively correlated with the levels of P Ⅰ NP and BGP(r=0.868,0.879,P＜0.05),but no sig-nificant correlation with FBG level(r=-0.085,P=0.152).Omentin-1,P Ⅰ NP,β-CTX,BGP,HbA1c and HOMA-IR were independent influencing factors of BMD in T2DM patients(P＜0.05).ROC curve analysis showed that the area under the curve of serum Omentin-1 level predicting T2DM with osteoporosis was 0.835(95％CI:0.764-0.906),and when the cut-off value was 50.325 ng/mL,the sensitivity was 0.854,the speci-ficity was 0.801,and the Youden index was 0.655.Conclusion Serum Omentin-1 expression is low in T2DM patients,and its expression is closely related to bone mineral density,bone metabolism and insulin resistance in T2DM patients,and can effectively predict the occurrence of T2DM with osteoporosis.

Fatigue-related traffic accidents and fatalities have been extensively studied by scholars globally.Specialized vehicles,due to their unique mission profiles,are more likely to cause driving-related fatigue and serious consequences.This paper reviews the current research of fatigue driving by using an inductive analysis method to summarize the mechanisms,risk factors,and monitoring methods.This paper also offers a vision of priorities and methodologies for research in the future.It is recommended that the mechanisms of driving fatigue be explored at the molecular biological level and that fatigue monitoring systems be made more feasible via the combined application of non-intrusive monitoring in order to reduce the toll on life and property taken by driving fatigue.

Objective To observe the value of intratumoral and peritumoral radiomics features of apparent diffusion coefficient(ADC)for predicting prognosis of children with medulloblastoma(MB).Methods Data of 74 children with MB were retrospectively analyzed.The children were divided into progression group(n=29)or non-progression group(n=45)according to results of 2-year follow-up,also into training set(n=44)or validation set(n=30)at the ratio of 6∶4.The intratumoral and peritumoral radiomics features were extracted and screened based on ADC images.The intratumoral,peritumoralas well as intratumoral+peritumoral radiomics models were established,and 3 combination models were constructed combining with clinical and conventional imaging features.The predictive efficiency were compared between each 2 combination models.Results In training set,the area under the curve(AUC)of clinical-conventional imaging-peritumoral radiomics model and clinical-conventional imaging-intratumoral+peritumoral radiomics model were both larger than that of peritumoral radiomics models(both P＜0.05).In validation set,AUC of clinical-conventional imaging-intratumoral+peritumoral radiomics model was the largest,but no significant difference of AUC was found among 3 combination models(all P＞0.05).Conclusion The intratumoral and peritumoral ADC radiomics features could be used to predict prognosis of MB children.Combining with clinical and conventional imaging features might improve the efficiency of prediction.

Objective To understand the current status and influencing factors of patient perception for humanistic care in China hospitals,and to provide a basis for developing nursing humanistic care measures and improving the quality of nursing humanistic care services.Methods A total of 30,099 outpatients and inpatients from 107 hospitals in 30 provinces(autonomous regions and municipalities)from July to August 2022 as survey subjects.A general information questionnaire and the Relational Caring Questionnaire-Patient Form were used for a cross-sectional survey,and a single-factor analysis was used to analyze the influencing factors of patient relationship care.Results Finally,29 108 valid questionnaires were collected,and the effective questionnaire recovery rate was 96.7％.The patient evaluation of relationship care was(65.72±8.61)points.Single-factor analysis showed that gender,age,marital status,children's situation,education level,occupation,place of residence,average family income,medical insurance type,visiting department,and location of the visiting hospital,and whether or not surgery were influencing factors of patient relationship care(P＜0.05).Conclusion The evaluation score of caregiver-patient relationship care among Chinese hospital patients is above average,but there is still room for improvement in western and rural regions,seriously ill and outpatient patients,low-income and low-medical insurance reimbursement populations,and non-surgical patients.Medical institutions at all levels should optimize and improve nursing humanistic care services based on influencing factors,and further enhance patients'perception of nursing humanistic care.