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.

Objective To analyze the global research literature on monkeypox from 2014 to 2024 through bibliometric analysis,and provide reference for monkeypox research in China.Methods Based on data from the Web of Science Core Collection database and utilizing the visualization analysis capabilities of VOSviewer software,we employed keyword co-occurrence analysis and national cooperative network analysis methods and examined the trends in monkeypox research publications,popular journals,high-yield institutions,international collaborations,and keywords.Results A total of 2 396 papers were published from 2014 to 2024,with a significant increase in publications after 2022.The United States had the highest number of publications(808 papers,accounting for 33.72%).The network of international scientific collaborations showed close cooperation between the United States and countries like the United Kingdom and Canada,frequent collaborations among developing countries such as China and India,and extensive cooperation among European countries like Italy and Spain,which also established partnerships with Brazil,Mexico,and others.Keywords co-occurrence clustering and essential science indicators(ESI)highly cited papers revealed that the monkeypox research hotspots after 2022 including the analysis of the virology,clinical,epidemiological characteristics of the global outbreak in 2022,uncovering the causes of the global outbreak and the differences from previous outbreaks.Studies on vaccines and antiviral drugs also gradually became focal points.Conclusion Since the outbreak of monkeypox in 2022,monkeypox research has developed rapidly.Papers focus on specific populations,and gradually shifting from virological,clinical and epidemiological characterization to the development of new drugs,vaccines,and clinical validation studies.

Objective To analyze the current status of malaria vaccine research from 2019 to 2024 by using bibliometric methods.Methods Based on the Web of Science core collection database,we used VOSviewer to conduct a visual analysis of the publishing trends,publishing journals,international cooperation status,institutions and research hotspots of malaria vaccine research.Results A total of 2 467 relevant articles were retrieved,and the annual number of publications showed a stable trend.The number of articles published by different countries/regions varied greatly,and the top effect was obvious.The United States published the most papers(1 032 articles,41.83%).The international cooperation network reflected the regional collaborative relationships in malaria vaccine research,predominantly involving the United States,the United Kingdom,Australia,India and China.Through keyword co-occurrence clustering,the current research hotspots in the field of malaria vaccines were basic research on key sites and mechanisms of potential vaccines,clinical research on new vaccines,epidemiological studies on the impact of malaria vaccines on malaria transmission,etc.Conclusion In recent years,malaria vaccine research has received sustained attention.The translation of clinical research on malaria vaccine was currently accelerating,and children and women were still the key groups of concern.

Medical engineering in TCM medical institutions in Guizhou Province was described in terms of its development status and problems in functional positioning,professional title appraisal,unbalanced staff composition and discipline foun-dation.Some suggestions were put forward including determining the functional positioning and management mode of medical engineering institutions,promoting the professional title system for medical engineering staffs,strengthening medical engineering team and enhancing medical engineering discipline.References were provided for the development of medical engineering in TCM medical institutions in Guizhou Province.[Chinese Medical Equipment Journal,2025,46(5):84-90]

Objective To explore the diagnostic value of electrocardiogram parameters combined with serum microRNA(miR)-322 and miR-568 levels in patients with chronic heart failure(CHF)complicated with ventricular arrhythmias(VA).Methods A total of 230 CHF patients admitted to Zhangjiakou First Hospital from April 2020 to April 2023 were selected as the study objects,including 120 VA patients(VA group)and 110 non VA patients(non VA group),and 110 patients who underwent health examinations in Zhangjiakou First Hospital during the same period as the control group.Compared three sets of general information,electrocardiogram parameters,left ventricular ejection fraction(LVEF),cardiac function grade and serum miR-322 and miR-568 levels.Logistic regression analyzed the influencing factors of VA in CHF patients.Receiver operating characteristic curve(ROC)analyzed electrocardiogram parameters combined with serum miR-322 and miR-568 for the diagnostic value of VA in CHF patients.Results The three groups showed statistically obvious differences in classification of nyha heart function(NYHA)and left ventricular ejection fraction(LVEF)(F=6.033,691.853,all P<0.05).The electrocardiogram parameters of CHF patients,including QT interval dispersion(QTD),QRS wave duration and corrected QT systolic time(QTc)were obviously higher than those in the control group(t=16.539,17.709,14.414),and the VA group were obviously higher than the non VA group(q=10.984,7.794,10.174),and the differences were statistically significan(all P<0.05).The serum levels of miR-322 and miR-568 were obviously lower than those in the control group(t=23.719,17.359).and the VA group were obviously lower than the non VA group(q=10.345,9.941),the differences were statistically significant(all P<0.05).Logistic regression analysis showed that NYHA grading,LVEF,QTD,QRS,wave duration,QTc,serum miR-322 and miR-568 levels were all influencing factors in the complication of VA in patients with CHF(Wald χ2=4.267～9.839,all P<0.05).The combination of electrocardiogram parameters and serum miR-322,miR-568 was better diagnosing CHF patients with concurrent VA that QTD,QRS duration,QTc and serum miR-332,miR-568 were measured separately.Conclusion Serum levels of miR-322 and miR-568 are obviously reduced,and the combination of electrocardiogram parameters with serum miR-322 and miR-568 has high diagnostic value for CHF patients with VA.

Glycoengineering was carried out in the mammalian cell line CHO for the production of pro-tein-based drugs.Firstly,the genome sequence of the Rosa26 locus of CHO cells was determined,the gRNA sequences were designed,and the landing pad was integrated into the Rosa26 locus of CHO cells by CRISPR/Cas9 technology.Three targeting vectors co-expressed by glycosyltransferases,which are β-1,4 galactosyltransferase(B4GALT1),α-2,6-sialyltransferase 1(ST6GAL1)and N-acetaminoglycosyl-transferase Ⅲ(GnT Ⅲ),were constructed by overlapping PCR and seamless ligation technology,and the three glycosyltransferase genes were integrated into the CHO Rosa26 locus by Cre enzyme-mediated cassette exchange technology.PCR confirmed that three glycosyltransferases had been successfully site-directed integrated into the Rosa26 site.The mRNA expression levels of the three glycosyltransferases were more than 50 000-fold by qRT-PCR,and the protein expression levels of the three glycosyltrans-ferases were more than 4-fold via western blotting(P＜0.001).A CHO-engineered cell line with three glycosyltransferases integrated into Rosa26 site was successfully constructed.

AIM To study the chemical constituents from Citri reticulatae Pericarpium Viride and their anti-triple negative breast cancer activities in vitro.METHODS The ethanolic extract of Citri reticulatae Pericarpium Viride was isolated and purified by silica gel,polyamide,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The anti-triple negative breast cancer activities were screened by SRB assay,and their effects on the proliferation of triple negative breast cancer cell lines HCC1806,HCC1937 and MDA-MB-231 in vitro were evaluated.RESULTS Twenty compounds were isolated and identified as nobiletin(1),tangeritin(2),5,4'-dihydroxy-7,8-dimethoxy flavonoid(3),naringenin(4),artemetin(5),5-demethynobiletin(6),3,5,6,7,8,3',4'-pentamethoxy flavonoid(7),5,4'-dihydroxy-3,6,7,8,3'-pentamethoxyflavone(8),xanthomicrol(9),p-hydroxycinnamic acid(10),5,4'-dihydroxy-6,7,8,3'-tetramethoxyflavone(11),pectolinarigenin(12),4'-dihydroxy-5,6,7-tetramethoxyflavone(13),hispidulin(14),4',5,6,7-tetramethoxy-flavone(15),1-methyl-4-(prop-1-en-2-yl)cyclohexane-1,2-diol(16),umbelliferone(17),5-hydroxymethyl furfural(18),hydroquinone(19),1H-indole-3-carbaldehyde(20).Compound 8 showed a significant inhibitory effect with the IC50 value of(5.36±0.24)μmol/L on HCC1806 cells.CONCLUSION Compound 20 is isolated from genus Citrus for the first time,8,12-13,16-17 are isolated from this plant for the first time.Compound 8 show inhibitory effects on the proliferation of HCC1806,HCC1937 and MDA-MB-231 cells in vitro and have the strongest activities.Compounds 3-4,11-12,15,17 and 19 show strong inhibitory effect on HCC1806 cells.Compounds 15,19 also inhibit the proliferation of HCC1937 cells in vitro.

Antibiotics are widely used in clinical treatment of bacterial infection diseases and in the breeding of livestock,poultry and aquatic products.However,the irrational and excessive use of antibiotics not only leads to the emergence of drug-resistant superbugs,but also the antibiotics discharged into the environment pose a significant threat to the environment and human health.Antibiotics have been included in the list of key new pollutants to be controlled.Therefore,the detection of residual antibiotics in environmental media and food is of vital importance for protecting the environment and public health.Among various antibiotic detection methods,electrochemical sensors have attracted extensive attention due to their high sensitivity,low cost,simplicity and rapidity.Appropriate modification of the electrode surface can enhance the sensitivity of electrochemical sensors,reduce interference and expand the detection range.Metal-organic frameworks(MOFs)materials have the advantages of rich types,adjustable structure and activity,high specific surface area and high porosity,and show great application potential in the field of electrochemical sensing.This paper first introduces the synthesis methods of MOFs,reviews the research progress of MOFs-modified electrodes for detection of common antibiotics by electrochemical sensors,and finally looks forward to their future development trends in the field of rapid antibiotic detection.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.