BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

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.

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 .

Background: Aristolochic acid II (AAII), a major nephrotoxic and carcinogenic component of aristolochic acids (AAs), has been less studied compared with its well-characterized analog, aristolochic acid I (AAI). Although AAs are known to induce carcinogenesis via DNA adduct formation, the toxicity mechanisms, environmental prevalence, and long-term health impacts of AAII remain poorly understood. Objective: This study aimed to systematically evaluate AAII’s acute and chronic toxicity, carcinogenic mechanisms, and environmental exposure patterns using integrated murine models and phytochemical analyses to clarify its toxicological profile and associated health risks. Methods: C57BL/6J mice were used in the following experiments: (1) determination of AAII content in 3 commonly used Aristolochia medicinal materials via liquid chromatography-mass spectrometry/mass spectrometry; (2) acute toxicity testing with single doses of 10, 20, or 40 mg/kg; and (3) chronic exposure with 1 or 10 mg/kg administered every other day for 24 weeks, followed by 21 to 40 weeks of postexposure monitoring. Histopathological examination, whole-exome sequencing, biochemical assays, and micronucleus tests were performed to assess multi-organ damage, tumorigenesis, genomic mutation signatures, and direct clastogenicity. Phytochemical analyses were used to evaluate environmental distribution. Results: (1) A single 40 mg/kg dose of AAII induced dose-dependent renal tubular degeneration without hepatotoxicity; (2) the 10 mg/kg group showed significant mortality (20%), tumor incidence (33.3%, primarily forestomach and bladder transitional cell carcinomas), persistent renal interstitial fibrosis, and subclinical hepatic injury. Chronic exposure to 1 mg/kg still induced 13.3% mortality and 15.5% tumor incidence over a 64-week period; (3) whole-exome sequencing revealed a predominance of C>T mutations and pathway enrichment in chemical carcinogenesis and cytochrome P450-mediated metabolism, indicating reactive metabolite-driven mechanisms distinct from classical AA-DNA adducts; and (4) no histopathological changes were observed in nontarget organs (brain, heart, and testes), and micronucleus assays confirmed the absence of direct clastogenicity. Conclusion: This study highlights the delayed carcinogenic risks of low-dose chronic AAII exposure and emphasizes the need to update regulatory frameworks to ensure the safe use of aristolochiaceae-containing herbal products.

Aim To investigate the effects of Congrong San(CRS)on learning and memory ability,hippocam-pal neuronal injury,and ferroptosis in rats with Alzhei-mer's disease(AD)and to explore the related mecha-nisms.Methods AD rat models were established and divided into Sham,Model,CRS low-dose,CRS medium-dose,CRS high-dose,and memantine groups.After treatment,Morris water maze,HE and Nissl staining,transmission electron microscopy,immunofluorescence staining,Western blot,and kit assays were performed to assess learning and memory ability,hippocampal neuro-nal injury,ferroptosis-related indicatorsand glucose reg-ulated protein 78 ku(GRP78)-(proteinkinaseR-li-keERkinase)PERK-(activating transcription factor 4)ATF4 pathway protein expression.Results Com-pared with the model group,rats in the CRS medium-and high-dose groups and the memantine group showed significant improvement in learning and memory abili-ty,reduced hippocampal neuronal injury,increased number of Nissl bodies,and ameliorated endoplasmic reticulum swelling and mitochondrial damage.In addi-tion,the expressions of GRP78,p-PERK/PERK,and ATF4 were downregulated,while GPX4 expression was upregulated in the CRS medium-and high-dose groups and the memantine group.Moreover,MDA content de-creased,and SOD and GSH-PX levels increased in these groups.Conclusions CRS can improve the learning and memory ability in AD rats,reduce hipp-ocampal neuronal injury and ferroptosis,and its mecha-nism may be related to the inhibition of the GRP78-PERK-ATF4 pathway,enhancement of GPX4 expres-sion,and reduction of oxidative stress levels,providing a new approach for the clinical treatment of AD.

Solid-phase extraction(SPE)combined with surface-enhanced Raman spectroscopy(SERS)has emerged as a promising analytical technique for detection and analysis of trace components in complex sample matrices.SPE enriches analytes through selective adsorption and solvent elution,effectively increasing the concentration and signal intensity.SERS enables ultra-sensitive and highly selective molecular analysis through the use of SERS-active substrates engineered to amplify Raman signals.The integration of these two techniques overcomes the limitations of conventional Raman spectroscopy in low-concentration detection field,while significantly improving sample preparation efficiency and analytical accuracy.This review provided a comprehensive overview of the characteristics of three SPE-SERS coupling modes,including two-step,one-step,and online integration.Special emphasis was placed on recent advancements in one-step SPE-SERS approaches based on novel functional adsorbent materials such as graphene,metal-organic frameworks,covalent organic frameworks,and molecularly imprinted polymers.Furthermore,future directions and development prospects of SPE-SERS technology were discussed.

Radiopharmaceuticals operate by combining radionuclides with carriers. The radiation energy emitted by radionuclides is utilized to selectively irradiate diseased tissues while minimizing damage to healthy tissues. In comparison to external beam radiation therapy, radionuclide drugs demonstrate research potential due to their biological targeting capabilities and reduced normal tissue toxicity. This article reviews the applications and research progress of radiopharmaceuticals in cancer treatment. Several key radionuclides are examined, including ²²³Ra, ⁹⁰Y, Lutetium-177 (¹⁷⁷Lu), ²¹²Pb, and Actinium-225 (²²⁵Ac). It also explores the current development trends of radiopharmaceuticals, encompassing the introduction of novel radionuclides, advancements in imaging technologies, integrated diagnosis and treatment approaches, and equipment-medication combinations. We review the progress in the development of new treatments, such as neutron capture therapy, proton therapy, and heavy ion therapy. Furthermore, we examine the challenges and breakthroughs associated with the clinical translation of radiopharmaceuticals and provide recommendations for the research and development of novel radionuclide drugs.
Humans ; Radiopharmaceuticals/therapeutic use* ; Neoplasms/radiotherapy* ; Radioisotopes/therapeutic use* ; Animals

Objective:To investigate the clinical characteristics and genetic etiology of Duchenne muscular dystrophy (DMD) with myogenic tumors.Methods:The clinical data of 2 children with DMD combined with myogenic tumors diagnosed in Children′s Hospital Affiliated to Zhengzhou University in July 2021 and February 2022 were collected. The relevant literature was reviewed to summarize the clinical characteristics and explore the mechanism of the dystrophin ( DMD) gene in myogenic tumors. Results:A 6-year and 10-month-old boy with DMD (deletion of exon 45) and a 12-year-old boy with DMD (deletion of exon 51) were diagnosed with tumors. They were diagnosed with DMD for delayed motor development in the Department of Neurology of Children′s Hospital Affiliated to Zhengzhou University. They presented with painless masses in the waist. Postoperative pathological diagnosis: the pathology and immunohistochemistry of case 1 showed an alveolar rhabdomyosarcoma (ARMS) and both myogenin and myogenic differentiation 1 positive; the pathology and immunohistochemistry of case 2 showed an alveolar soft part sarcoma(ASPS) and transcription factor enhancer 3 positive; both cases were myogenic tumors. Literature review (including this paper) showed that there were in total 14 cases with DMD combined with myogenic tumors including 13 cases of rhabdomyosarcoma (RMS) and 1 case of ASPS. All of them are male, and the age of onset of the tumors was 4-17 years. Pathological subtypes were described in 6 cases of ARMS and 5 cases of embryonal RMS, and were not described in 2 cases. The 9 cases described all had large deletions in the DMD gene which can change the reading frame of the DMD gene, and all gene mutations did not exceed exon 62. Conclusions:DMD gene with deletion may increase the risk of having myogenic tumors, and RMS is more common, which is manifested as painless mass in early stage. All DMD gene deletions do not exceed exon 62 and lead to change of the gene reading frame with severe clinical phenotype and degenerative changes in muscle function.