Objective:This study employs a combination of single-cell sequencing and Mendelian randomization to explore the genetic associations and molecular mechanisms of Eomes in RCC.Methods:In this study,single-cell transcriptomic data from RCC tissues and adjacent normal tissues were extracted from the GEO database.The data were analyzed using R language and various packages such as Seurat,limma,and CellChat for cell cluster annotation,intercellular communication analysis,and differential expression analysis.Additionally,eQTL data related to differentially expressed genes were retrieved from the GWAS database as exposure variables,with RCC used as the outcome variable in Mendelian randomization analysis to identify the role of Eomes in RCC.Finally,GO functional enrichment and KEGG pathway analyses were conducted to explore the potential molecular mechanisms of Eomes.Results:Single-cell RNA sequencing revealed that B cells play a significant role in the heterogeneity of RCC.Mendelian randomization analysis indicated that Eomes is an important risk factor for RCC(P＜0.05).Furthermore,seven highly correlated specific SNPs were identified,including rs 17021298,rs2247056,rs2617170,rs3806624,rs55908509,rs6590334,and rs9420589.GO and KEGG enrichment analyses suggest that Eomes may be involved in early cell fate determination in renal cell carcinoma and participate in the regulation of Th1 and Th2 cell differentiation,HPV infection,and the Notch signaling pathway.Conclusions:This study is the first to combine single-cell sequencing and Mendelian randomization analysis in RCC,confirming a strong positive causal relationship between Eomes and RCC(OR＞1).Our findings offer new insights into the pathogenesis of RCC,suggesting that Eomes could serve as a novel target for early diagnosis and personalized treatment of RCC.

A novel epileptic seizure prediction prediction model based on multichannel temporal and spatial feature extractions is presented.The model applies Stockwell transform to the original multichannel electroencephalogram(EEG)signals for extracting time-frequency components.To address the issue of insignificant difference between preseizure and interseizure time-frequency features,an adaptive feature module composing of ConvNeXt,SENet and pyramid pooling module is designed to enhance the ability of capturing key time-frequency features in each EEG channel.Meanwhile,a prediction model based on Bi-NLSTM is constructed to improve the spatiotemporal dependence between the time-frequency features of multichannel high-order EEG for further promoting the epilepsy classification performance.On the CHB-MIT dataset,the model has an accuracy,sensitivity,specificity and AUC of 96.0%,97.8%,96.8%and 0.987,respectively,and the false positive rate per hour decreased to 0.038,outperforming the existing mainstream methods.In addition,the effect of each component on the model performance is verified by ablation study.The proposed method improves the overall performance for seizure prediction effectively by optimizing local time-frequency feature extraction and enhancing multichannel spatiotemporal dependence.

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Objective:This study employs a combination of single-cell sequencing and Mendelian randomization to explore the genetic associations and molecular mechanisms of Eomes in RCC.Methods:In this study,single-cell transcriptomic data from RCC tissues and adjacent normal tissues were extracted from the GEO database.The data were analyzed using R language and various packages such as Seurat,limma,and CellChat for cell cluster annotation,intercellular communication analysis,and differential expression analysis.Additionally,eQTL data related to differentially expressed genes were retrieved from the GWAS database as exposure variables,with RCC used as the outcome variable in Mendelian randomization analysis to identify the role of Eomes in RCC.Finally,GO functional enrichment and KEGG pathway analyses were conducted to explore the potential molecular mechanisms of Eomes.Results:Single-cell RNA sequencing revealed that B cells play a significant role in the heterogeneity of RCC.Mendelian randomization analysis indicated that Eomes is an important risk factor for RCC(P＜0.05).Furthermore,seven highly correlated specific SNPs were identified,including rs 17021298,rs2247056,rs2617170,rs3806624,rs55908509,rs6590334,and rs9420589.GO and KEGG enrichment analyses suggest that Eomes may be involved in early cell fate determination in renal cell carcinoma and participate in the regulation of Th1 and Th2 cell differentiation,HPV infection,and the Notch signaling pathway.Conclusions:This study is the first to combine single-cell sequencing and Mendelian randomization analysis in RCC,confirming a strong positive causal relationship between Eomes and RCC(OR＞1).Our findings offer new insights into the pathogenesis of RCC,suggesting that Eomes could serve as a novel target for early diagnosis and personalized treatment of RCC.

Three typical failures of large-aperture 16-slice spiral Siemens SOMATOM Sensation Open CT were introduced in terms of phenomenon,cause and treatment method.References were provided for medical engineers to treat similar failures.

Under the guidance of five-viscus correlation theory,and with reference to the clinical practice,this paper discusses the pathogenesis of cardiogenic asthma,i.e.long illness of the heart resulting in asthma,from the perspective of physiological characteristics of heart,which belongs to yin in essence and yang in function.And this paper also introduces the correlation between five zang-organs and cardiogenic asthma:asthma induced by heart failure involves the lung,has close relation with middle energizer(spleen and stomach),results from the comorbidity of heart and liver,and contributes to the disorders of kidney.It is believed that cardiogenic asthma injures the heart,results in internal blockage of blood stasis,so the original pathogenesis of cardiogenic asthma is due to the heart;unsmoothed blood circulation causes fluid retention in the chest and lung,and then the lung is involved.The failure of spleen and stomach in generation and transportation will cause the unsmoothed circulation of qi and blood,liver qi stagnation will result in the failure of liver blood in nourishment,and the intense kidney yin-fire will stir upward and attack heart yang.The factors mentioned above all are prone to result in the aggravation of cardiogenic asthma.Therefore,the treatment of cardiogenic asthma with traditional Chinese medicine should be focused on heart,and methods of replenishing qi,activating blood circulation,and inducing diuresis are used as the primary therapeutic approaches.Moreover,according to the organs involved in cardiogenic asthma,therapies of regulating the five viscera and restoring the balance of yin and yang are used for precise treatment,and the therapeutic effect will be enhanced.

Three typical failures of large-aperture 16-slice spiral Siemens SOMATOM Sensation Open CT were introduced in terms of phenomenon,cause and treatment method.References were provided for medical engineers to treat similar failures.

Objective To design a night vision simulation training system to provide pilots with practical training on ground night vision goggles.Methods The system had its hardware composed of a control stick,a throttle lever,rudder pedals,a head-up display(HUD),a control box,a computer,a projector and a screen.The HUD and control box were designed using night vision-compatible lighting technology to simulate the ambient light conditions pilots experienced when flying with night vision goggles.The software of the system consisted of five ones developed with C++programming languge for visual scene simulation,instrument simulation,flight performance simulation,integrated management control and cockpit manage-ment.Night vision images and computer-rendered images of typical scenes with varying brightness levels were collected.Objective image evaluation metrics such as contrast and brightness were used as inputs,while subjective evaluation data served as outputs to construct and train a support vector machine(SVM)model.Totally 30 typical night vision training scenarios were selected based on model validation and optimization to evaluate the system's optical fidelity.Results The average fidelity score for the 30 typical night vision training scenarios was 8.05,indicating that the system could realistically simulate terrain and landscapes under various lighting and weather conditions during night flights and static and dynamic targets in the air,on the ground and at sea.Conclusion The system meets the desired requirements and effectively facilitates night vision training for pilots.[Chinese Medical Equipment Journal,2025,46(3):21-26]

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.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis