ObjectiveTo investigate the epigenetic mechanism of Diwu Yanggan Capsule in improving liver regeneration microenvironment in a rat model of liver cancer by regulating DNA methylation， and to provide a basis for scientific clinical medication. MethodsA total of 48 specific pathogen-free Sprague-Dawley rats were divided into normal group， model group， and Diwu Yanggan Capsule group using a random number table， with 16 rats in each group. The Solt-Farber two-step method was used to establish a rat model of liver cancer. The rats in the Diwu Yanggan Capsule group were given Diwu Yanggan Capsule at a dose of 750 mg/kg/d by gavage， and those in the normal group and the model group were given an equal volume of normal saline by gavage. Liver tissue samples were collected from each group of rats after 16 weeks of continuous intervention； DNA methylation chips were used to analyze the change in DNA methylation in liver tissue， and gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were used for data analysis. In addition， the MeDIP-PCR technique was used to detect the changes in candidate differentially methylated genes such as YWHAB， ADCK2， ERLIN2， SEMA3B， and TPH2 in the liver tissue of rats， and Western blot and RT-qPCR were used to verify the expression of key methylated genes. The independent-samples t test was used for comparison of continuous data between two groups， and a one-way analysis of variance was used for comparison between multiple groups， while the least significant difference t-test was used for further comparison between two groups. ResultsThe DNA methylation chip analysis showed that compared with the normal group， the model group had significant methylation changes in the promoter region of 2 422 genes in liver tissue of rats. The GO functional enrichment analysis and the KEGG pathway enrichment analysis showed that these differentially methylated genes were significantly enriched in metabolic pathways such as steroid hormone biosynthesis and drug metabolism-cytochrome P450. Compared with the model group， the Diwu Yanggan Capsule group had significant reversal of promoter methylation in 1 650 genes， and the KEGG enrichment analysis showed that these genes were mainly involved in the pathways closely associated with cell proliferation， apoptosis， and microenvironment regulation， such as the calcium ion signaling pathway， the cAMP signaling pathway， and the extracellular factor signaling pathway. Compared with the model group， the Diwu Yanggan Capsule group had a significant increase in the promoter methylation level of the ADCK2 gene （P<0.05） and significant reductions in the promoter methylation levels of the ERLIN2 and TPH2 genes （all P<0.05）. Compared with the model group， the Diwu Yanggan Capsule group had significant reductions in the mRNA expression levels and the protein expression levels of the ADCK2 （all P<0.05）. ConclusionAbnormal DNA methylation in liver tissue participates in the development and progression of liver cancer. The effect of Diwu Yanggan Capsule on DNA methylation level is an important epigenetic mechanism for its effect in the prevention and treatment of liver cancer.

ObjectiveThe frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state. MethodsWe designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses. ResultsThe comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions. ConclusionThis study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

AIM To study the chemical constituents from the branches and leaves of Michelia yunnanensis Franch.ex Finet & Gagnep.and their anti-inflammatory activities.METHODS The methanol extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Twenty compounds were isolated and identified as dihydrodehydrodiconifenyl alcohol(1),8-hydroxypinoresinol(2),lariciresinol(3),isolariciresinol(4),(7S,8R)-4-hydroxy-3,3',5'-trimethoxy-8',9'-dinor-8,4'-oxyneoligna-7,9-diol-7'-aldehyde(5),thero-2,3-bis-(4-hydroxy-3-methoxypheyl)-3-methoxy-propanol(6),evofolin B(7),(E)-p-coumaryl alcohol γ-O-methyl ether(8),ω-hydroxypropioguaiacone(9),sinapaldehyde(10),isoscopoletin(11),6-hydroxy-5,7-dimethoxycoumarin(12),2α,3α-dihydroxy-2-methylbutyrolactone(13),6-hydroxy-3(1-hydroxy-1-methylethyl)-6-methyl-2-cyclohexen-1-one(14),benzofuran-2-carboxaldehyde(15),3,4-dihydroxy-5-methoxybenzaldehyde(16),3,5-dimethoxy-4-hydroxybenzaldehyde(17),3,4-dihydroxybenzaldehyde(18),3,4-dihydroxybenzoic methyl ester(19),vanillic acid(20).The inhibition rate of compound 1 on NO was 45.39％±0.32％.CONCLUSION Compounds 1-16,18-20 are first isolated from this plant.Compound 1 has anti-inflammatory activity.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

This study aims to investigate the effect of Lactiplantibacillus plantarum LP12 on obe-sity prevention.In our study,Lactiplantibacillus plantarum LP12 was added to the diet for feed-ing,and the blood biochemistry status of rabbit,as well as the antioxidant effect of serum and liver samples were analyzed by determining the body weight change and feed intake of Japanese White rabbits.The changes in colony structure and abundance were also analyzed by 16S rDNA sequen-cing.The results showed that supplementation of Lactiplantibacillus plantarum LP12 inhibits weight gain,decreases serum glucose and ALT levels,and increases SOD activity in the liver.16S RNA gene sequencing analysis showed that the addition of Lactiplantibacillus plantarum LP12 increases the abundance of Bacteroidetes and Desulfovibrioides at the phylum level,and the supple-mentation of Lactiplantibacillus plantarum LP12 increases the abundance of Muribaculaceae at the genus level.Predictive analysis of microbiota function revealed that the supplementation of Lactiplantibacillus plantarum LP12 positively regulated iron-sulfur clusters and Zn-dependent proteases.In conclusion,the addition of Lactiplantibacillus plantarum effectively inhibits weight gain in Japanese White rabbits,enhances the antioxidative activity of the liver,and induces altera-tions in the gut microbiota composition of these rabbits.These findings lay an experimental foun-dation for further exploring the mechanisms by which Lactobacillus plantarum LP12 exerts its preventive effects against obesity and promotes metabolic health.

Objective To explore the relationship between triglyceride-glucose(TyG)index and hypertension in patients with cerebral hemorrhage.Methods A total of 1718 patients with cere-bral hemorrhage admitted to our hospital from January,2013 to May,2023 were enrolled in this study.According to the TyG index quartile,437 cases were assigned into Q1 group(≤8.375),424 cases into Q2 group(TyG index 8.376～8.737),429 cases into Q3 group(TyG index 8.738～9.087),and 428 cases into Q4 group(≥9.088).The general clinical data were compared in the four groups.Logistic regression analysis was used to study the correlation between TyG index and hy-pertension.Results There were significant differences among the four groups in terms of age,hy-pertension,diabetes,SBP,DBP,TC,TG,HDL-C,LDL-C,FBG,glycated hemoglobin and TyG in-dex(P＜0.05,P＜0.01).Logistic regression analysis showed that when the TyG index was a con-tinuous variable,it was significantly correlated with the risk of hypertension(OR=1.999,95％CI:1.393-2.869,P=0.001).When the index was used as a categorical variable,with Q1as a ref-erence,TyG index in Q3 and Q4 was associated with an increase in OR of hypertension(OR=1.869,95％CI:1.220-2.865,P=0.004;OR=1.844,95％CI:1.125-3.020,P=0.015).After ad-justing cofounders,the association of TyG index and risk of hypertension was stronger in the fe-males(OR=2.618,95％CI:1.312-5.221,P=0.006)than the males(OR=1.783,95％CI:1.151-2.761,P=0.010),and in the patients ≥65 years old(OR=3.277,95％CI:1.600-6.741,P=0.001)than those＜65 years old(OR=1.782,95％CI:1.076-2.949,P=0.025).Conclusion TyG index is closely associated with hypertension in patients with cerebral hemorrhage,especially in women and elderly.

AIM To study the chemical constituents from the branches and leaves of Michelia yunnanensis Franch.ex Finet & Gagnep.and their anti-inflammatory activities.METHODS The methanol extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Twenty compounds were isolated and identified as dihydrodehydrodiconifenyl alcohol(1),8-hydroxypinoresinol(2),lariciresinol(3),isolariciresinol(4),(7S,8R)-4-hydroxy-3,3',5'-trimethoxy-8',9'-dinor-8,4'-oxyneoligna-7,9-diol-7'-aldehyde(5),thero-2,3-bis-(4-hydroxy-3-methoxypheyl)-3-methoxy-propanol(6),evofolin B(7),(E)-p-coumaryl alcohol γ-O-methyl ether(8),ω-hydroxypropioguaiacone(9),sinapaldehyde(10),isoscopoletin(11),6-hydroxy-5,7-dimethoxycoumarin(12),2α,3α-dihydroxy-2-methylbutyrolactone(13),6-hydroxy-3(1-hydroxy-1-methylethyl)-6-methyl-2-cyclohexen-1-one(14),benzofuran-2-carboxaldehyde(15),3,4-dihydroxy-5-methoxybenzaldehyde(16),3,5-dimethoxy-4-hydroxybenzaldehyde(17),3,4-dihydroxybenzaldehyde(18),3,4-dihydroxybenzoic methyl ester(19),vanillic acid(20).The inhibition rate of compound 1 on NO was 45.39％±0.32％.CONCLUSION Compounds 1-16,18-20 are first isolated from this plant.Compound 1 has anti-inflammatory activity.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To systematically investigate the ac-tive components,targets,and regulatory pathways of Po-lygonum capitatum in intervening atherosclerosis(AS)through network pharmacology,molecular docking and animal experiments.Methods Active components of Polygonum capitatum and AS-related targets were screened and identified through database searches.Protein-protein interaction(PPI)network analysis was performed using the STRING database,followed by GO and KEGG enrichment analyses via the David plat-form.Molecular docking validation was conducted with AutoDock.An AS model was established in Syrian golden hamsters fed a high-fat diet.Predicted pathways and targets were validated using qPCR,ELISA,and histopathological assessment of aortic and hepatic tis-sues via HE staining.Results Network pharmacology identified 27 potential active components of Polygonum capitatum(primarily flavonoids such as quercetin and luteolin)and 110 drug-disease intersection targets,in-cluding core targets MMP-9,ALB,and AKT1.GO and KEGG analyses enriched 593 and 125 pathways,re-spectively,with the NF-κB inflammatory pathway,TNF signaling pathway and lipid metabolism/atherosclerosis pathways highlighted as key mechanisms.Animal ex-periments demonstrated that Polygonum capitatum im-proved serum lipid profiles(reduced TC,TG,LDL-C)in AS hamsters,suppressed the MMP-9/NF-κB signa-ling pathway(downregulated MMP-9,p65 phosphoryla-tion,TNF-α,and IL-6),and inhibited VSMC synthetic phenotypic transformation(upregulated α-SMA and myocardin)by downregulating MCPIP1.Additionally,Polygonum capitatum ameliorated aortic lesions and he-patic lipid deposition in AS hamsters.Conclusions Polygonum capitatum alleviates AS by synergistically regulating the MMP-9/NF-κB/MCPIP1 axis through flavonoid components,suppressing vascular inflammato-ry cascades and maintaining VSMC contractile pheno-types.This reflects Polygonum capitatum's multi-com-ponent,multi-pathway,and multi-target characteristics in combating AS.

Isoflavones which mainly distributed in leguminous plants have plenty of health benefits.Isoflavone synthase(IFS)is a membrane-associated cytochrome P450 enzyme(CYP450)which carries out the unique aryl-ring migration and hydroxylation.So far,few crystal structures of plant P450s have been obtained.We determined the crystal structure of IFS from Medicago truncatula at 1.9 ? by MAD method using a selenomethionine substituted crystal and conducted molecular docking and mutagenesis study.The structure of IFS complexed with imidazole exhibits the helix Ⅰa-loop-helix Ⅰβ motif which cor-responds to helix Ⅰ of other P450s.Compared with structures of common P450s,IFS/imidazole structure contains an extra domain,i.e.,the γ-domain.The structure reveals a homodimer in which the γ-domain of one molecule interacts with the β-domain of another.The plane of heme group makes an angle of ap-proximately 40° with the helix Ⅰa-loop-helix Ⅰβ motif.Molecular docking combined with mutagenesis study suggested that Trp-128 and Asp-300 might play important roles in substrate binding and recogni-tion.Phe-301,Ser-303 and Gly-305 from the helix Ⅰa-loop-helix Ⅰβ motif may play important roles in the aryl-ring migration.These novel structural features reveal insights into the unique reaction mechanism of IFS and provide a basis for engineering IFS in leguminous crops for health purpose.