ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

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.

Purpose To investigate the expression of Versican(VCAN)and thrombospondin 2(THBS2)and their relationship with cancer-associated fibroblast(CAFs)and clinicopathological significance in papillary thyroid car-cinoma(PTC).Methods Bioinformatics analyses were performed using PTC single-cell sequencing data from the GEO and TCGA database.Weighted correlation network analysis identified CAFs-related genes,and enrichment analy-sis highlighted pivotal genes associated with CAFs;the expression of VCAN,THBS2,and α-SMA in 130 PTC tissue samples were detected by immunohistochemistry EnVision method.Masson staining evaluated tumor stromal fibrosis.Relationships between these markers,clinicopathological parameters,and CAF proliferation were analyzed.Results Bioinformatics analysis identified VCAN and THBS2 as core genes significantly associated with CAFs,and extracellular matrix-related pathways.The proliferation rate of CAFs in PTC was 83.1％(108/130),with positivity rate of 96.9％(126/130)for VCAN and 75.4％(98/130)for THBS2.The median mesenchymal fibrosis index was 32.4(inter-quartile range:22.7-50.0).High CAF proliferation correlated positively with lymph node metastasis(P＜0.001),higher TNM stage(P＜0.05),and specific histologic subtypes of PTC.Similarly,VCAN expression,THBS2 expres-sion,and the degree of PTC stromal fibrosis were positively correlated with lymph node metastasis(P＜0.001,P＜0.05,and P＜0.001,respectively).Both THBS2 expression and the degree of PTC stromal fibrosis correlated with the histologic subtype of PTC.The percentage of tumor mesenchymal α-SMA-positive cells strongly correlated with the im-mune response score(IRS)of VCAN and THBS2(rs=0.713,P＜0.001;rs=0.646,P＜0.001).Additionally,the percentage of Masson-stained area was positively correlated with the percentage of tumor mesenchymal α-SMA-posi-tive cells,and the IRS of VCAN and THBS2(rs=0.892,P＜0.001;rs=0.729,P＜0.001;rs=0.616,P＜0.001).Conclusion VCAN and THBS2 serve as potential markers for assessing invasiveness and lymph node metas-tasis of PTC.Their strong association with CAFs provides a basis for further investigation of the malignant biological be-havior of PTC.

Purpose To investigate the expression of FAM134B in hepatocellular carcinoma(HCC)and its clini-cal significance.Methods Immunohistochemical EnVision two-step method was used to detect the expression of FAM134B in 60 cases of HCC tissue and adjacent non-tumor liver tissue.The relationship between FAM134B expres-sion and clinicopathological characteristics and prognosis of HCC was analyzed.Transwell assays,CCK-8 assays and clone formation assays were used to assess the effects of FAM134B knockdown on HCC cell migration,invasion and proliferation.Results FAM134B had a high expression rates of 70.0％(42/60)in HCC tissues and 40.0％(24/60)in adjacent normal tissues.Compared to adjacent non-tumor tissues,FAM134B expression was significantly higher in HCC tissues(P all＜0.001),and it was positively correlated with vascular invasion,tumor maximum diameter,and early recurrence(P all＜0.05).Survival analysis showed that high expression of FAM134B was an independent poor prognostic factor and a high recurrence risk factor for HCC patients(P all＜0.05).In vitro experiments demonstrated that knockdown FAM134B inhibited HCC cell migration,invasion and proliferation(P all＜0.05).GSEA analysis u-sing the TCGA database indicated that the expression of FAM134B was positively correlatied with the AKT/mTOR path-way.Conclusion High expression of FAM134B may be a marker of high recurrence risk and poor prognosis in HCC and holds potential as a therapeutic target for HCC.

AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85％ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.

AIM To investigate the stability of salvianolic acid B.METHODS HPLC was adopted in the content determination of salvianolic acid B,after which the chemical stability in different pH of buffer solutions,oxidation stability in different concentrations of H2O2,and biological stability in artificial gastric fluid,artificial intestinal fluid and biological matrices were analyzed,and its degradation kinetics was fitted.RESULTS Salvianolic acid B was stable in acidic and weakly acidic buffer solutions and artificial gastric fluid,which demonstrated poor stability in neutral and alkaline buffer solutions,artificial intestinal fluid,H2O2 and biological matrices.The degradation process of this constituent accorded with the first-order kinetic model in ileum homogenate,and the second-order kinetic model in pH 7.4 buffer solution,artificial intestinal fluid,H2O2 and stomach,duodenum,jejunum,colon homogenates.CONCLUSION Biological matrices,oxidants and alkaline environment can affect the stability of salvianolic acid B.This experimental exhibits important significance for the development and application of salvianolic acid B-related products.

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.

Purpose To investigate the expression of LAMB3 and ITGB4 in esophageal squamous cell carcinoma(ESCC)and analyze their associations with clinicopathological features.Methods Bioinformatics was used to assess the expression of LAMB3 and ITGB4 in pan-cancer and ESCC.Immunohistochemistry was performed to evaluate their expression and distribution in ESCC tissues,and correlations clinicopathological features were analyzed.Follow-up data were collected to construct Kaplan-Meier survival curves,and Cox regression analysis was proformed to determine their prognostic significance.Results Bioinformatics analysis showed that LAMB3 and ITGB4 were highly expressed in ES-CC tissues(P＜0.001).Immunohistochemistry confirmed that both proteins were localized in the cytoplasm and membrane of tumor cells.High LAMB3 expression was significantly associated with poor differentiation(P＜0.001),lymph node metastasis(P=0.015),and T staging(P＜0.001).High ITGB4 expression was significantly correlated with poor differentiation(P=0.004)and advanced T staging(P=0.004).Cox regression analysis identified high ex-pression of LAMB3 and ITGB4 as independent prognostic factors for overall survival[HR=4.97(95％CI:2.73-9.02);HR=2.33(95％CI:1.36-3.99)].Conclusion LAMB3 and ITGB4 are highly expressed in ESCC.High LAMB3 expression is associated with tumor differentiation,lymph node metastasis,and T staging,while high ITGB4 expression is correlated with tumor differentiation and T staging.Patients with high expression of LAMB3 or ITGB4 have poorer overall survival,suggesting that these proteins may serve as prognostic biomarkers for unfavorable outcome in ESCC.

Aim To investigate the anti-acute lung injury(ALI)effect of Sterculiae Lychnophorae Semen(SLS)and its mechanism.Methods The main ac-tive components of SLS and their core targets and path-ways of action against ALI were obtained by network pharmacology methods.Subsequently,molecular doc-king technology and in vitro cellular experiments were applied for validation.Results A total of 19 core tar-gets were obtained,including HSP90AA1,CASP3,TNF,MAPK8 and MAPK14.The mechanisms may in-volve signaling pathways such as cancer,PI3K/Akt and MAPK.Molecular docking confirmed that the key targets of SLS formed a better binding activity with the relevant active ingredients.The in vitro results showed that SLS was able to protect the PM2.5-contaminated BEAS-2B cells,inhibit their NO,IL-1β and TNF-αlevels,and reduce the expression of p-p38 MAPK and p-JNK proteins.Conclusions The study successfully predicts the active ingredients,targets and signaling pathways of SLS against ALI,and in vitro experiments demonstrate that SLS might protect BEAS-2B cells from PM2.5 stimulus-induced inflammation and apoptosis by inhibiting the over-activation of p38 MAPK and JNK signaling pathways.

Objective To investigate the changes of serum microRNA (miR)-138-5p and microRNA(miR)-574-5p expression levels and their clinical significance in newborns acute respiratory distress syndrome (nARDS). Methods A total of 112 infants with nARDS from September 2018 to August 2023 in the Neonatal Department of Xiaogan Hospital Affiliated to Wuhan University of Science and Technology were collected as the observation group. They were divided into good prognosis group (n=98) and the poor prognosis group (n=14). A total of 104 healthy full-term newborns born at the same time were selected as the control group. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of miR-138-5p and miR-574-5p in serum. ROC curve was used to analyze the diagnostic value of serum miR-574-5p and miR-138-5p levels for poor prognosis of infants with nARDS. Multivariate Logistic regression analysis of factors affecting the poor prognosis of infants with nARDS. Results Compared with the control group,the expression level of serum miR-574-5p in the observation group increased (1.72±0.23 vs 1.04±0.17),with the expression level of miR-138-5p decreased (0.55±0.08 vs 1.02±0.16),with statistically significant differences (t=24.557,25.597,all P<0.05). Compared with the good prognosis group,the serum miR-138-5p expression level in the poor prognosis group decreased (0.41±0.06 vs 0.57±0.08),with the miR-574-5p expression level increased (2.07±0.25 vs 1.67±0.19),with statistically significant differences (t=7.188,7.069,all P<0.05). The age,intrauterine distress,and proportion of abnormal amniotic fluid in the poor prognosis group were higher than those in the good prognosis group (t=5.359,4.257,6.577,all P<0.05). MiR-574-5p was an independent risk factor for poor prognosis with nARDS,and miR-138-5p was a protective factor (all P<0.05).The AUC (95％ CI) of serum miR-138-5p and miR-574-5p alone and combined diagnosis of nADRS were 0.793 (0.706～0.864),0.898 (0.826～0.947) and 0.931 (0.867～0.970),respectively. The combined prediction of miR-138-5p and miR-574-5p were better than that of miR-138-5p alone and miR-574-5p alone (Z=2.151,1.982,all P<0.05). Conclusion The expression levels of miR-138-5p in serum of infant with nARDS were lower and the expression levels of miR-574-5p were higher,both of which have certain diagnostic value for poor prognosis of infant with nARDS .