Objective:Triple-negative breast cancer(TNBC)is a highly aggressive subtype that lacks targeted therapies,leading to a poorer prognosis.However,some patients achieve long-term recurrence-free survival(RFS),offering va...Objective:Triple-negative breast cancer(TNBC)is a highly aggressive subtype that lacks targeted therapies,leading to a poorer prognosis.However,some patients achieve long-term recurrence-free survival(RFS),offering valuable insights into tumor biology and potential treatment strategies.Methods:We conducted a comprehensive multi-omics analysis of 132 patients with American Joint Committee on Cancer(AJCC)stage III TNBC,comprising 36 long-term survivors(RFS≥8 years),62 moderate-term survivors(RFS:3-8 years),and 34 short-term survivors(RFS<3 years).Analyses investigated clinicopathological factors,whole-exome sequencing,germline mutations,copy number alterations(CNAs),RNA sequences,and metabolomic profiles.Results:Long-term survivors exhibited fewer metastatic regional lymph nodes,along with tumors showing reduced stromal fibrosis and lower Ki67 index.Molecularly,these tumors exhibited multiple alterations in genes related to homologous recombination repair,with higher frequencies of germline mutations and somatic CNAs.Additionally,tumors from long-term survivors demonstrated significant downregulation of the RTK-RAS signaling pathway.Metabolomic profiling revealed decreased levels of lipids and carbohydrate,particularly those involved in glycerophospholipid,fructose,and mannose metabolism,in long-term survival group.Multivariate Cox analysis identified fibrosis[hazard ratio(HR):12.70,95%confidence interval(95%CI):2.19-73.54,P=0.005]and RAC1copy number loss/deletion(HR:0.22,95%CI:0.06-0.83,P=0.026)as independent predictors of RFS.Higher fructose/mannose metabolism was associated with worse overall survival(HR:1.30,95%CI:1.01-1.68,P=0.045).Our findings emphasize the association between biological determinants and prolonged survival in patients with TNBC.Conclusions:Our study systematically identified the key molecular and metabolic features associated with prolonged survival in AJCC stage III TNBC,suggesting potential therapeutic targets to improve patient outcomes.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scannin...Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.展开更多
This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,includin...This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.展开更多
One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physio...Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physiological processes.To achieve a targeted improvement of their adaptability to various environments,a detail analysis of their evolutionary physiological processes is required.While several studies have been carried out in the past by using single-omics techniques to investigate their response to environmental stress,most researchers are now using a multi-omics approach to explore more detail in the biological regulatory networks and molecular mechanisms of lactic acid bacteria in response to environmental stress,thereby overcoming the limitations of single-omics analysis.In this review,we describe the various single-omics approaches that have been used to study environmental stress in lactic acid bacteria,present the advantages of various multi-omics combined analysis approaches,and discuss the potential and practicality of applying emerging single-cell transcriptomics and single-cell metabolomics techniques to the molecular mechanism study of microbes response to environmental stress.Multi-omics approaches enable the accurate identification of complex microbial physiological processes in different environments,allow people to comprehensively reveal the molecular mechanisms of microbes response to stress from different perspectives.Single-cell omics techniques,analyze the targeted regulation of microbial functions in a multi-dimensional space,provides a new perspective on understanding microbes responses environment stress.展开更多
BACKGROUND Autoimmune liver diseases,including primary biliary cholangitis(PBC),autoi-mmune hepatitis(AIH),and their overlap syndrome(OS),involve immune-mediated liver injury,with OS occurring in 1.2%-25%of PBC patien...BACKGROUND Autoimmune liver diseases,including primary biliary cholangitis(PBC),autoi-mmune hepatitis(AIH),and their overlap syndrome(OS),involve immune-mediated liver injury,with OS occurring in 1.2%-25%of PBC patients.OS carries a higher risk of cirrhosis,hepatocellular carcinoma,and reduced survival.While its pathogenesis remains unclear,gut microbiota dysbiosis and serum metabolite alterations may play key roles.This study uses 16S rRNA sequencing and liquid chromatography-mass spec-trometry(LC-MS)metabolomics to compare gut microbiota and serum metabolites among PBC,AIH,and OS patients,and explores their associations with liver function.AIM To differentiate OS from PBC and AIH based on gut microbiota,serum metabolites,and liver function.METHODS Gut microbiota profiles were analyzed using 16S rRNA sequencing,while untargeted serum metabolomics was conducted via LC-MS.Comparative analyses were performed to identify differences in microbial composition and serum metabolite levels among PBC,AIH,and OS groups.Correlation analyses and network visualization tech-niques were applied to elucidate the interactions among liver function parameters,gut microbiota,and serum metabolites in OS patients.RESULTS Compared to patients with PBC or AIH,OS patients demonstrated significantly reduced microbial diversity and richness.Notable taxonomic shifts included decreased abundances of Firmicutes,Bacteroidetes,and Actinobacteria,alongside increased levels of Proteobacteria and Verrucomicrobia.Distinct serum metabolites,such as pentadecanoic acid and aminoimidazole carboxamide ribonucleotide,were identified in OS patients.Correlation analysis revealed that aspartate aminotransferase(AST)levels were negatively associated with the bacterial genus Fusicatenibacter and the metabolite L-Tyrosine.A microbial-metabolite network diagram further confirmed a strong association between Fusicatenibacter and L-Tyrosine in OS patients.CONCLUSION OS patients show decreased gut microbiota diversity and unique serum metabolites.Multi-omics linked AST,Fusicatenibacter,and L-Tyrosine,revealing OS mechanisms and diagnostic potential.展开更多
Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We dis...Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.展开更多
Objective To map the research hotspots,developmental trends,and existing challenges in the integration of artificial intelligence(AI)with multi-omics in traditional Chinese medicine(TCM)through comprehensive bibliomet...Objective To map the research hotspots,developmental trends,and existing challenges in the integration of artificial intelligence(AI)with multi-omics in traditional Chinese medicine(TCM)through comprehensive bibliometric analysis.Methods China National Knowledge Infrastructure(CNKI),Wanfang Data,China Science and Technology Journal Database(VIP),Chaoxing Journal Database,PubMed,and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31,2024.Eligible records were required to simultaneously address AI,TCM,and multi-omics.Quantitative and visual analyses of publication growth,core authorship networks,institutional collaboration patterns,and keyword co-occurrence were performed using Microsoft Excel 2021,NoteExpress v4.0.0,and Cite-Space 6.3.R1.AI application modes in TCM multi-omics research were also categorized and summarized.Results A total of 1106 articles were enrolled(932 Chinese and 174 English).Publication output has increased continuously since 2010 and accelerated after 2016.Region-specific collaboration clusters were identified,dominated by Beijing University of Chinese Medicine,China Academy of Chinese Medical Sciences,Shanghai University of Traditional Chinese Medicine,and Nanjing University of Chinese Medicine.Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining.Research foci mainly ranked as follows:single herbs,herbal formulae,and disease-syndrome differentiation.Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present,utilized for processing omics data and uncovering latent patterns therein.The domain of TCM,in addition to investigating omics information procured through high-throughput technologies,also integrates data on traditional Chinese medicinal substances and clinical phenotypes,progressing towards joint analysis of multi-omics,high-dimensionality of data,and multi-modality of information.Deep learning approaches represent an emerging trend in the field.展开更多
BACKGROUND Gastrointestinal(GI)malignancies,including gastric and colorectal cancers,remain one of the primary contributors to cancer-related illness and death globally.Despite the availability of conventional diagnos...BACKGROUND Gastrointestinal(GI)malignancies,including gastric and colorectal cancers,remain one of the primary contributors to cancer-related illness and death globally.Despite the availability of conventional diagnostic tools,early detection and personalized treatment remain significant clinical challenges.Integrated multi-omics methods encompassing genomic,transcriptomic,proteomic,metabolomic,and microbiome profiles have emerged as powerful tools for advancing precision oncology,improving diagnostic accuracy,and informing therapeutic strategies.AIM To investigate the application of multi-omics approaches in the early detection,risk stratification,treatment optimization,and biomarker discovery of GI malignancies.METHODS The systematic review process was conducted in accordance with the PRISMA 2020 guidelines.Five databases,PubMed,ScienceDirect,Scopus,ProQuest,and Web of Science,were searched for studies published in English from 2015 onwards.Eligible studies involved human subjects and focused on multi-omics integration in GI cancers,including biomarker identification,tumor microenvironment analysis,tumor heterogeneity,organoid modeling,and artificial intelligence(AI)-driven analytics.Data extraction included study characteristics,omics modalities,clinical applications,and evaluation of study quality conducted with the Cochrane risk of bias 2.0 instrument.RESULTS A total of 17196 initially identified articles,20 met the inclusion criteria.The findings highlight the superiority of multi-omics platforms over traditional biomarkers(e.g.,carcinoembryonic antigen and carbohydrate antigen 19-9 in detecting early stage GI cancers.Key applications include the identification of circulating tumor DNA,extracellular vesicles,lipidomic and proteomic signatures,and the adoption of AI algorithms to enhance diagnostic precision.Multi-omics analysis has also revealed the mechanisms of immune modulation,tumor microenvironment regulation,metastatic behavior,and drug resistance.Organoid models and microbiota profiling have contributed to personalized therapeutic strategies and immunotherapy optimization.CONCLUSION Multi-omics approaches offer significant advancements in the early diagnosis,prognostic evaluation,and personalized treatment of GI malignancies.Their integration with AI analytics,organoid biobanking,and microbiota modulation provides a pathway for precision oncology research.展开更多
In this editorial,we discuss the findings reported by Wang et al in the latest issue of the World Journal of Gastrointestinal Oncology.Various research methodologies,including microbiome analysis,assert that the Tzu-C...In this editorial,we discuss the findings reported by Wang et al in the latest issue of the World Journal of Gastrointestinal Oncology.Various research methodologies,including microbiome analysis,assert that the Tzu-Chi Cancer-Antagonizing and Life-Protecting II Decoction of Chinese herbal compounds mitigates inflammatory responses by inhibiting the NF-κB signaling pathway.This action helps maintain the dynamic equilibrium of the intestinal microecology and lessens chemotherapy-induced gastrointestinal damage.The efficacy of these compounds is intimately linked to the composition of intestinal microbes.These compounds regulate intestinal microecology by virtue of their specific compatibility and effectiveness,thereby enhancing the overall therapeutic outcomes of cancer chemotherapy.Nonetheless,the exact mechanisms underlying these effects warrant further investigation.Multi-omics technologies offer a systematic approach to elucidate the mechanisms and effectiveness of Chinese herbal compounds in vivo.This manuscript reviews the application of multi-omics technologies to Chinese herbal compounds and explores their potential role in modulating the gastrointestinal microenvironment following cancer chemotherapy,thus providing a theoretical foundation for their continued use in adjunct cancer treatment.展开更多
Objective Pneumoconiosis,a lung disease caused by irreversible fibrosis,represents a significant public health burden.This study investigates the causal relationships between gut microbiota,gene methylation,gene expre...Objective Pneumoconiosis,a lung disease caused by irreversible fibrosis,represents a significant public health burden.This study investigates the causal relationships between gut microbiota,gene methylation,gene expression,protein levels,and pneumoconiosis using a multi-omics approach and Mendelian randomization(MR).Methods We analyzed gut microbiota data from MiBioGen and Esteban et al.to assess their potential causal effects on pneumoconiosis subtypes(asbestosis,silicosis,and inorganic pneumoconiosis)using conventional and summary-data-based MR(SMR).Gene methylation and expression data from Genotype-Tissue Expression and eQTLGen,along with protein level data from deCODE and UK Biobank Pharma Proteomics Project,were examined in relation to pneumoconiosis data from FinnGen.To validate our findings,we assessed self-measured gut flora from a pneumoconiosis cohort and performed fine mapping,drug prediction,molecular docking,and Phenome-Wide Association Studies to explore relevant phenotypes of key genes.Results Three core gut microorganisms were identified:Romboutsia(OR=0.249)as a protective factor against silicosis,Pasteurellaceae(OR=3.207)and Haemophilus parainfluenzae(OR=2.343)as risk factors for inorganic pneumoconiosis.Additionally,mapping and quantitative trait loci analyses revealed that the genes VIM,STX8,and MIF were significantly associated with pneumoconiosis risk.Conclusions This multi-omics study highlights the associations between gut microbiota and key genes(VIM,STX8,MIF)with pneumoconiosis,offering insights into potential therapeutic targets and personalized treatment strategies.展开更多
Cancer rates are increasing globally,making it more urgent than ever to enhance research and treatment strategies.This study aims to investigate how innovative technology and integrated multi-omics techniques could he...Cancer rates are increasing globally,making it more urgent than ever to enhance research and treatment strategies.This study aims to investigate how innovative technology and integrated multi-omics techniques could help improve cancer diagnosis,knowledge,and therapy.A complete literature search was undertaken using PubMed,Elsevier,Google Scholar,ScienceDirect,Embase,and NCBI.This review examined the articles published from 2010 to 2025.Relevant articles were found using keywords and selected using inclusion criteria New sequencing methods,like next-generation sequencing and single-cell analysis,have transformed our ability to study tumor complexity and genetic mutations,paving the way for more precise,personalized treatments.At the same time,imaging technologies such as Positron Emission Tomography(PET)and Magnetic Resonance Imaging(MRI)have made detecting tumors early and tracking treatment progress easier,all while improving patient comfort.Artificial intelligence(AI)and machine learning(ML)are having a significant impact by helping to analyze large volumes of data more efficiently and enhancing diagnostic accuracy.Meanwhile,Clustered Regulatory Interspaced Short Palindromic Repeats(CRISPR/Cas9)gene editing is emerging as a promising tool for directly targeting genes related to cancer,providing new possibilities for treatment.By integrating genomic,transcriptomic,proteomic,and metabolomic data,multi-omics approaches provide researchers with a more comprehensive understanding of the molecular mechanisms driving cancer,thereby facilitating the discovery of novel biomarkers and therapeutic targets.Despite these advancements,additional challenges persist,such as data integration,elevated costs,standardisation concerns,and the intricacies of translating findings into clinical practice,which might prevent wider implementation.Research needs to concentrate on improving these developments and encouraging multidisciplinary cooperation going forward to maximize their possibilities.Personalized cancer therapies will become more successful with ongoing developments,therefore enhancing patient outcomes and quality of life.展开更多
Cold tumors,defined by insufficient immune cell infiltration and a highly immunosuppressive tumor microenvironment(TME),exhibit limited responsiveness to conventional immunotherapies.This reviewsystematically summariz...Cold tumors,defined by insufficient immune cell infiltration and a highly immunosuppressive tumor microenvironment(TME),exhibit limited responsiveness to conventional immunotherapies.This reviewsystematically summarizes the mechanisms of immune evasion and the therapeutic strategies for cold tumors as revealed by multiomics technologies.By integrating genomic,transcriptomic,proteomic,metabolomic,and spatialmulti-omics data,the review elucidates key immune evasionmechanisms,including activation of the WNT/β-catenin pathway,transforming growth factor-β(TGF-β)–mediated immunosuppression,metabolic reprogramming(e.g.,lactate accumulation),and aberrant expression of immune checkpoint molecules.Furthermore,this review proposes multi-dimensional therapeutic strategies,such as targeting immunosuppressive pathways(e.g.,programmed death-1(PD-1)/programmed death-ligand 1(PD-L1)inhibitors combined with TGF-βblockade),reshaping the TME through chemokine-based therapies,oncolytic viruses,and vascular normalization,and metabolic interventions(e.g.,inhibition of lactate dehydrogenase A(LDHA)or glutaminase(GLS)).In addition,personalized neoantigen vaccines and engineered cell therapies(e.g.,T cell receptor-engineered T(TCR-T)and natural killer(NK)cells)show promising potential.Emerging evidence also highlights the role of epigenetic regulation(e.g.,histone deacetylase(HDAC)inhibitors)and N6-Methyladenosine(m6A)RNA modifications in reversing immune evasion.Despite the promising insights offered by multi-omics integration in guiding precision immunotherapy,challenges remain in clinical translation,including data heterogeneity,target-specific toxicity,and limitations in preclinical models.Future efforts should focus on coupling dynamic multi-omics technologies with intelligent therapeutic design to convert cold tumors into immunologically active(“hot”)microenvironments,ultimately facilitating breakthroughs in personalized immunotherapy.展开更多
Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategie...Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategies often fall short in addressing the complex,multifactorial nature of DM.This review ex-plores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches.We consolidated genomic,transcriptomic,proteomic,metabolomic,and microbiomic data from major databases and peer-reviewed publications(2015-2025),with an emphasis on clinical relevance.Multi-omics investigations have identified convergent mole-cular networks underlyingβ-cell dysfunction,insulin resistance,and diabetic complications.The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis.Novel biomarkers facilitate early detection of DM and its complications,while single-cell multi-omics and machine learning further refine risk stratification.By dissecting DM heterogeneity more precisely,multi-omics integration enables targeted in-terventions and preventive strategies.Future efforts should focus on data har-monization,ethical considerations,and real-world validation to fully leverage multi-omics in addressing the global DM burden.展开更多
Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single ...Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.展开更多
Short process forming techniques for brazing and soldering materials can shorten the process,improve product quality,and increase production efficiency,which has received much attention from welding researchers.This r...Short process forming techniques for brazing and soldering materials can shorten the process,improve product quality,and increase production efficiency,which has received much attention from welding researchers.This review mainly summarized the research reports on short process forming techniques for brazing and soldering materials.Firstly,the traditional process and its shortcomings were presented.Secondly,the latest research of short process forming technologies,such as continuous casting technique,atomization powder technique,solder ball forming technique,and rapid solidification technique,was summarized,and the traditional forming performance of several brazing and soldering materials was introduced.Finally,the current restrictions and research trends of short process forming technique for brazing and solder materials were put forward,providing theoretical guidance and reference for related research and technique development in brazing and soldering field.展开更多
Aging and regeneration represent complex biological phenomena that have long captivated the scientific community.To fully comprehend these processes,it is essential to investigate molecular dynamics through a lens tha...Aging and regeneration represent complex biological phenomena that have long captivated the scientific community.To fully comprehend these processes,it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions.Conventional omics methodologies,such as genomics and transcriptomics,have been instrumental in identifying critical molecular facets of aging and regeneration.However,these methods are somewhat limited,constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations.The advent of emerging spatiotemporal multi-omics approaches,encompassing transcriptomics,proteomics,metabolomics,and epigenomics,furnishes comprehensive insights into these intricate molecular dynamics.These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells,tissues,and organs,thereby offering an in-depth understanding of the fundamental mechanisms at play.This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research.It underscores how these methodologies augment our comprehension of molecular dynamics,cellular interactions,and signaling pathways.Initially,the review delineates the foundational principles underpinning these methods,followed by an evaluation of their recent applications within the field.The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field.Indubitably,spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration,thus charting a course toward potential therapeutic innovations.展开更多
Increasing evidence implicates disruptions in testicular fatty acid metabolism as a contributing factor in nonobstructive azoospermia(NOA),a severe form of male infertility.However,the precise mechanisms linking fatty...Increasing evidence implicates disruptions in testicular fatty acid metabolism as a contributing factor in nonobstructive azoospermia(NOA),a severe form of male infertility.However,the precise mechanisms linking fatty acid metabolism to NOA pathogenesis have not yet been fully elucidated.Multi-omics analyses,including microarray analysis,single-cell RNA sequencing(scRNA-seq),and metabolomics,were utilized to investigate disruptions in fatty acid metabolism associated with NOA using data from public databases.Results identified ACSL6,ACSBG2,and OLAH as key genes linked to fatty acid metabolism dysregulation,suggesting their potential causative roles in NOA.A marked reduction in omega-3 polyunsaturated fatty acids,especially docosahexaenoic acid(DHA),was observed,potentially contributing to the pathological process of NOA.Sertoli cells in NOA patients exhibited apparent fatty acid metabolic dysfunction,with PPARG identified as a key transcription factor(TF)regulating this process.Functional analyses demonstrated that PPARG is crucial for maintaining blood-testis barrier(BTB)integrity and promoting spermatogenesis via regulation of fatty acid metabolism.These findings reveal the pivotal role of fatty acid metabolism in NOA and identify PPARG as a potential therapeutic target.展开更多
基金supported by grants from the Medical Engineering Jiont Fund of the Fudan University(No.IDH2310117)。
文摘Objective:Triple-negative breast cancer(TNBC)is a highly aggressive subtype that lacks targeted therapies,leading to a poorer prognosis.However,some patients achieve long-term recurrence-free survival(RFS),offering valuable insights into tumor biology and potential treatment strategies.Methods:We conducted a comprehensive multi-omics analysis of 132 patients with American Joint Committee on Cancer(AJCC)stage III TNBC,comprising 36 long-term survivors(RFS≥8 years),62 moderate-term survivors(RFS:3-8 years),and 34 short-term survivors(RFS<3 years).Analyses investigated clinicopathological factors,whole-exome sequencing,germline mutations,copy number alterations(CNAs),RNA sequences,and metabolomic profiles.Results:Long-term survivors exhibited fewer metastatic regional lymph nodes,along with tumors showing reduced stromal fibrosis and lower Ki67 index.Molecularly,these tumors exhibited multiple alterations in genes related to homologous recombination repair,with higher frequencies of germline mutations and somatic CNAs.Additionally,tumors from long-term survivors demonstrated significant downregulation of the RTK-RAS signaling pathway.Metabolomic profiling revealed decreased levels of lipids and carbohydrate,particularly those involved in glycerophospholipid,fructose,and mannose metabolism,in long-term survival group.Multivariate Cox analysis identified fibrosis[hazard ratio(HR):12.70,95%confidence interval(95%CI):2.19-73.54,P=0.005]and RAC1copy number loss/deletion(HR:0.22,95%CI:0.06-0.83,P=0.026)as independent predictors of RFS.Higher fructose/mannose metabolism was associated with worse overall survival(HR:1.30,95%CI:1.01-1.68,P=0.045).Our findings emphasize the association between biological determinants and prolonged survival in patients with TNBC.Conclusions:Our study systematically identified the key molecular and metabolic features associated with prolonged survival in AJCC stage III TNBC,suggesting potential therapeutic targets to improve patient outcomes.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金supported by the National Natural Science Foundation of China(Nos.12341501 and 11905074)。
文摘Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.
文摘This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
基金supported by the National Natural Science Foundation of China(32160578)the Ningxia Hui Autonomous Region Key Research and Develoment Program(2023BCF01027).
文摘Lactic acid bacteria and the fermentation environment interact to form an intertwined system.Lactic acid bacteria are constantly evolving to adapt to different fermentation environments,causing changes in their physiological processes.To achieve a targeted improvement of their adaptability to various environments,a detail analysis of their evolutionary physiological processes is required.While several studies have been carried out in the past by using single-omics techniques to investigate their response to environmental stress,most researchers are now using a multi-omics approach to explore more detail in the biological regulatory networks and molecular mechanisms of lactic acid bacteria in response to environmental stress,thereby overcoming the limitations of single-omics analysis.In this review,we describe the various single-omics approaches that have been used to study environmental stress in lactic acid bacteria,present the advantages of various multi-omics combined analysis approaches,and discuss the potential and practicality of applying emerging single-cell transcriptomics and single-cell metabolomics techniques to the molecular mechanism study of microbes response to environmental stress.Multi-omics approaches enable the accurate identification of complex microbial physiological processes in different environments,allow people to comprehensively reveal the molecular mechanisms of microbes response to stress from different perspectives.Single-cell omics techniques,analyze the targeted regulation of microbial functions in a multi-dimensional space,provides a new perspective on understanding microbes responses environment stress.
基金Supported by WBE Liver Foundation,No.WBE20220182022 Young and Middle-aged Talents Incubation Project(Youth Innovation)of Beijing Youan Hospital,Capital Medical University,No.BJYAYY-YN-2022-092023 Young and Middle-aged Talents Incubation Project(Youth Innovation)of Beijing Youan Hospital,Capital Medical University,No.BJYAYYYN2023-14.
文摘BACKGROUND Autoimmune liver diseases,including primary biliary cholangitis(PBC),autoi-mmune hepatitis(AIH),and their overlap syndrome(OS),involve immune-mediated liver injury,with OS occurring in 1.2%-25%of PBC patients.OS carries a higher risk of cirrhosis,hepatocellular carcinoma,and reduced survival.While its pathogenesis remains unclear,gut microbiota dysbiosis and serum metabolite alterations may play key roles.This study uses 16S rRNA sequencing and liquid chromatography-mass spec-trometry(LC-MS)metabolomics to compare gut microbiota and serum metabolites among PBC,AIH,and OS patients,and explores their associations with liver function.AIM To differentiate OS from PBC and AIH based on gut microbiota,serum metabolites,and liver function.METHODS Gut microbiota profiles were analyzed using 16S rRNA sequencing,while untargeted serum metabolomics was conducted via LC-MS.Comparative analyses were performed to identify differences in microbial composition and serum metabolite levels among PBC,AIH,and OS groups.Correlation analyses and network visualization tech-niques were applied to elucidate the interactions among liver function parameters,gut microbiota,and serum metabolites in OS patients.RESULTS Compared to patients with PBC or AIH,OS patients demonstrated significantly reduced microbial diversity and richness.Notable taxonomic shifts included decreased abundances of Firmicutes,Bacteroidetes,and Actinobacteria,alongside increased levels of Proteobacteria and Verrucomicrobia.Distinct serum metabolites,such as pentadecanoic acid and aminoimidazole carboxamide ribonucleotide,were identified in OS patients.Correlation analysis revealed that aspartate aminotransferase(AST)levels were negatively associated with the bacterial genus Fusicatenibacter and the metabolite L-Tyrosine.A microbial-metabolite network diagram further confirmed a strong association between Fusicatenibacter and L-Tyrosine in OS patients.CONCLUSION OS patients show decreased gut microbiota diversity and unique serum metabolites.Multi-omics linked AST,Fusicatenibacter,and L-Tyrosine,revealing OS mechanisms and diagnostic potential.
文摘Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.
基金General Project of Scientific Research of Hunan Provincial Education Department (22C0191)General Project of University-level Scientific Research of Hunan University of Chinese Medicine (Z2023XJYB21)Hunan Provincial Degree and Graduate Education Reform Research Project(2024JGYB157)。
文摘Objective To map the research hotspots,developmental trends,and existing challenges in the integration of artificial intelligence(AI)with multi-omics in traditional Chinese medicine(TCM)through comprehensive bibliometric analysis.Methods China National Knowledge Infrastructure(CNKI),Wanfang Data,China Science and Technology Journal Database(VIP),Chaoxing Journal Database,PubMed,and Web of Science were searched to collect literature on the theme of AI in TCM multi-omics research from the inception of each database to December 31,2024.Eligible records were required to simultaneously address AI,TCM,and multi-omics.Quantitative and visual analyses of publication growth,core authorship networks,institutional collaboration patterns,and keyword co-occurrence were performed using Microsoft Excel 2021,NoteExpress v4.0.0,and Cite-Space 6.3.R1.AI application modes in TCM multi-omics research were also categorized and summarized.Results A total of 1106 articles were enrolled(932 Chinese and 174 English).Publication output has increased continuously since 2010 and accelerated after 2016.Region-specific collaboration clusters were identified,dominated by Beijing University of Chinese Medicine,China Academy of Chinese Medical Sciences,Shanghai University of Traditional Chinese Medicine,and Nanjing University of Chinese Medicine.Keyword co-occurrence analysis revealed that current AI applications predominantly centered on metabolomics and algorithms such as cluster analysis and data mining.Research foci mainly ranked as follows:single herbs,herbal formulae,and disease-syndrome differentiation.Conclusion Machine learning methods are the predominant integrative modality of AI in the realm of TCM multi-omics research at present,utilized for processing omics data and uncovering latent patterns therein.The domain of TCM,in addition to investigating omics information procured through high-throughput technologies,also integrates data on traditional Chinese medicinal substances and clinical phenotypes,progressing towards joint analysis of multi-omics,high-dimensionality of data,and multi-modality of information.Deep learning approaches represent an emerging trend in the field.
文摘BACKGROUND Gastrointestinal(GI)malignancies,including gastric and colorectal cancers,remain one of the primary contributors to cancer-related illness and death globally.Despite the availability of conventional diagnostic tools,early detection and personalized treatment remain significant clinical challenges.Integrated multi-omics methods encompassing genomic,transcriptomic,proteomic,metabolomic,and microbiome profiles have emerged as powerful tools for advancing precision oncology,improving diagnostic accuracy,and informing therapeutic strategies.AIM To investigate the application of multi-omics approaches in the early detection,risk stratification,treatment optimization,and biomarker discovery of GI malignancies.METHODS The systematic review process was conducted in accordance with the PRISMA 2020 guidelines.Five databases,PubMed,ScienceDirect,Scopus,ProQuest,and Web of Science,were searched for studies published in English from 2015 onwards.Eligible studies involved human subjects and focused on multi-omics integration in GI cancers,including biomarker identification,tumor microenvironment analysis,tumor heterogeneity,organoid modeling,and artificial intelligence(AI)-driven analytics.Data extraction included study characteristics,omics modalities,clinical applications,and evaluation of study quality conducted with the Cochrane risk of bias 2.0 instrument.RESULTS A total of 17196 initially identified articles,20 met the inclusion criteria.The findings highlight the superiority of multi-omics platforms over traditional biomarkers(e.g.,carcinoembryonic antigen and carbohydrate antigen 19-9 in detecting early stage GI cancers.Key applications include the identification of circulating tumor DNA,extracellular vesicles,lipidomic and proteomic signatures,and the adoption of AI algorithms to enhance diagnostic precision.Multi-omics analysis has also revealed the mechanisms of immune modulation,tumor microenvironment regulation,metastatic behavior,and drug resistance.Organoid models and microbiota profiling have contributed to personalized therapeutic strategies and immunotherapy optimization.CONCLUSION Multi-omics approaches offer significant advancements in the early diagnosis,prognostic evaluation,and personalized treatment of GI malignancies.Their integration with AI analytics,organoid biobanking,and microbiota modulation provides a pathway for precision oncology research.
基金Supported by 2023 Government-funded Project of the Outstanding Talents Training Program in Clinical Medicine,No.ZF2023165Key Research and Development Projects of Hebei Province,No.18277731DNatural Science Foundation of Hebei Province,No.H202423105.
文摘In this editorial,we discuss the findings reported by Wang et al in the latest issue of the World Journal of Gastrointestinal Oncology.Various research methodologies,including microbiome analysis,assert that the Tzu-Chi Cancer-Antagonizing and Life-Protecting II Decoction of Chinese herbal compounds mitigates inflammatory responses by inhibiting the NF-κB signaling pathway.This action helps maintain the dynamic equilibrium of the intestinal microecology and lessens chemotherapy-induced gastrointestinal damage.The efficacy of these compounds is intimately linked to the composition of intestinal microbes.These compounds regulate intestinal microecology by virtue of their specific compatibility and effectiveness,thereby enhancing the overall therapeutic outcomes of cancer chemotherapy.Nonetheless,the exact mechanisms underlying these effects warrant further investigation.Multi-omics technologies offer a systematic approach to elucidate the mechanisms and effectiveness of Chinese herbal compounds in vivo.This manuscript reviews the application of multi-omics technologies to Chinese herbal compounds and explores their potential role in modulating the gastrointestinal microenvironment following cancer chemotherapy,thus providing a theoretical foundation for their continued use in adjunct cancer treatment.
基金the Central Guidance for Regional Science and Technology Development Projects(YDZJSX2024B010)Research project of Shanxi Provincial Health Commission(2024067)。
文摘Objective Pneumoconiosis,a lung disease caused by irreversible fibrosis,represents a significant public health burden.This study investigates the causal relationships between gut microbiota,gene methylation,gene expression,protein levels,and pneumoconiosis using a multi-omics approach and Mendelian randomization(MR).Methods We analyzed gut microbiota data from MiBioGen and Esteban et al.to assess their potential causal effects on pneumoconiosis subtypes(asbestosis,silicosis,and inorganic pneumoconiosis)using conventional and summary-data-based MR(SMR).Gene methylation and expression data from Genotype-Tissue Expression and eQTLGen,along with protein level data from deCODE and UK Biobank Pharma Proteomics Project,were examined in relation to pneumoconiosis data from FinnGen.To validate our findings,we assessed self-measured gut flora from a pneumoconiosis cohort and performed fine mapping,drug prediction,molecular docking,and Phenome-Wide Association Studies to explore relevant phenotypes of key genes.Results Three core gut microorganisms were identified:Romboutsia(OR=0.249)as a protective factor against silicosis,Pasteurellaceae(OR=3.207)and Haemophilus parainfluenzae(OR=2.343)as risk factors for inorganic pneumoconiosis.Additionally,mapping and quantitative trait loci analyses revealed that the genes VIM,STX8,and MIF were significantly associated with pneumoconiosis risk.Conclusions This multi-omics study highlights the associations between gut microbiota and key genes(VIM,STX8,MIF)with pneumoconiosis,offering insights into potential therapeutic targets and personalized treatment strategies.
文摘Cancer rates are increasing globally,making it more urgent than ever to enhance research and treatment strategies.This study aims to investigate how innovative technology and integrated multi-omics techniques could help improve cancer diagnosis,knowledge,and therapy.A complete literature search was undertaken using PubMed,Elsevier,Google Scholar,ScienceDirect,Embase,and NCBI.This review examined the articles published from 2010 to 2025.Relevant articles were found using keywords and selected using inclusion criteria New sequencing methods,like next-generation sequencing and single-cell analysis,have transformed our ability to study tumor complexity and genetic mutations,paving the way for more precise,personalized treatments.At the same time,imaging technologies such as Positron Emission Tomography(PET)and Magnetic Resonance Imaging(MRI)have made detecting tumors early and tracking treatment progress easier,all while improving patient comfort.Artificial intelligence(AI)and machine learning(ML)are having a significant impact by helping to analyze large volumes of data more efficiently and enhancing diagnostic accuracy.Meanwhile,Clustered Regulatory Interspaced Short Palindromic Repeats(CRISPR/Cas9)gene editing is emerging as a promising tool for directly targeting genes related to cancer,providing new possibilities for treatment.By integrating genomic,transcriptomic,proteomic,and metabolomic data,multi-omics approaches provide researchers with a more comprehensive understanding of the molecular mechanisms driving cancer,thereby facilitating the discovery of novel biomarkers and therapeutic targets.Despite these advancements,additional challenges persist,such as data integration,elevated costs,standardisation concerns,and the intricacies of translating findings into clinical practice,which might prevent wider implementation.Research needs to concentrate on improving these developments and encouraging multidisciplinary cooperation going forward to maximize their possibilities.Personalized cancer therapies will become more successful with ongoing developments,therefore enhancing patient outcomes and quality of life.
基金The 75th Batch of China Postdoctoral Science Foundation projects(No.2024M754279)Natural Science Foundation of Jiangsu Province(No.BK20240738)+2 种基金Basic Science(Natural Science)Research Project in Universities of Jiangsu Province(No.24KJB360004)Jiangsu Province Chinese Medicine Science and Technology Development Plan Youth Talent Project(No.QN202206)Nanjing University of ChineseMedicine Luo Linxiu Teacher Development Fund Project(No.LLX202310).
文摘Cold tumors,defined by insufficient immune cell infiltration and a highly immunosuppressive tumor microenvironment(TME),exhibit limited responsiveness to conventional immunotherapies.This reviewsystematically summarizes the mechanisms of immune evasion and the therapeutic strategies for cold tumors as revealed by multiomics technologies.By integrating genomic,transcriptomic,proteomic,metabolomic,and spatialmulti-omics data,the review elucidates key immune evasionmechanisms,including activation of the WNT/β-catenin pathway,transforming growth factor-β(TGF-β)–mediated immunosuppression,metabolic reprogramming(e.g.,lactate accumulation),and aberrant expression of immune checkpoint molecules.Furthermore,this review proposes multi-dimensional therapeutic strategies,such as targeting immunosuppressive pathways(e.g.,programmed death-1(PD-1)/programmed death-ligand 1(PD-L1)inhibitors combined with TGF-βblockade),reshaping the TME through chemokine-based therapies,oncolytic viruses,and vascular normalization,and metabolic interventions(e.g.,inhibition of lactate dehydrogenase A(LDHA)or glutaminase(GLS)).In addition,personalized neoantigen vaccines and engineered cell therapies(e.g.,T cell receptor-engineered T(TCR-T)and natural killer(NK)cells)show promising potential.Emerging evidence also highlights the role of epigenetic regulation(e.g.,histone deacetylase(HDAC)inhibitors)and N6-Methyladenosine(m6A)RNA modifications in reversing immune evasion.Despite the promising insights offered by multi-omics integration in guiding precision immunotherapy,challenges remain in clinical translation,including data heterogeneity,target-specific toxicity,and limitations in preclinical models.Future efforts should focus on coupling dynamic multi-omics technologies with intelligent therapeutic design to convert cold tumors into immunologically active(“hot”)microenvironments,ultimately facilitating breakthroughs in personalized immunotherapy.
文摘Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategies often fall short in addressing the complex,multifactorial nature of DM.This review ex-plores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches.We consolidated genomic,transcriptomic,proteomic,metabolomic,and microbiomic data from major databases and peer-reviewed publications(2015-2025),with an emphasis on clinical relevance.Multi-omics investigations have identified convergent mole-cular networks underlyingβ-cell dysfunction,insulin resistance,and diabetic complications.The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis.Novel biomarkers facilitate early detection of DM and its complications,while single-cell multi-omics and machine learning further refine risk stratification.By dissecting DM heterogeneity more precisely,multi-omics integration enables targeted in-terventions and preventive strategies.Future efforts should focus on data har-monization,ethical considerations,and real-world validation to fully leverage multi-omics in addressing the global DM burden.
文摘Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
基金National Key Research and Development Program(2021YFB3401101)。
文摘Short process forming techniques for brazing and soldering materials can shorten the process,improve product quality,and increase production efficiency,which has received much attention from welding researchers.This review mainly summarized the research reports on short process forming techniques for brazing and soldering materials.Firstly,the traditional process and its shortcomings were presented.Secondly,the latest research of short process forming technologies,such as continuous casting technique,atomization powder technique,solder ball forming technique,and rapid solidification technique,was summarized,and the traditional forming performance of several brazing and soldering materials was introduced.Finally,the current restrictions and research trends of short process forming technique for brazing and solder materials were put forward,providing theoretical guidance and reference for related research and technique development in brazing and soldering field.
基金supported by the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang(2023R01002)the National Natural Science Foundation of China(82271629,82301790)。
文摘Aging and regeneration represent complex biological phenomena that have long captivated the scientific community.To fully comprehend these processes,it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions.Conventional omics methodologies,such as genomics and transcriptomics,have been instrumental in identifying critical molecular facets of aging and regeneration.However,these methods are somewhat limited,constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations.The advent of emerging spatiotemporal multi-omics approaches,encompassing transcriptomics,proteomics,metabolomics,and epigenomics,furnishes comprehensive insights into these intricate molecular dynamics.These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells,tissues,and organs,thereby offering an in-depth understanding of the fundamental mechanisms at play.This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research.It underscores how these methodologies augment our comprehension of molecular dynamics,cellular interactions,and signaling pathways.Initially,the review delineates the foundational principles underpinning these methods,followed by an evaluation of their recent applications within the field.The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field.Indubitably,spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration,thus charting a course toward potential therapeutic innovations.
基金supported by the National Natural Science Foundation of China (U22A20277,81971373)Jiangsu Provincial Medical Key Discipline Cultivation Unit (JSDW202215)+1 种基金333 High-level Personnel Training Project of Jiangsu Province (BRA2019109)Postgraduate Research&Practice Innovation Program of Jiangsu Province (KYCX22_1826)。
文摘Increasing evidence implicates disruptions in testicular fatty acid metabolism as a contributing factor in nonobstructive azoospermia(NOA),a severe form of male infertility.However,the precise mechanisms linking fatty acid metabolism to NOA pathogenesis have not yet been fully elucidated.Multi-omics analyses,including microarray analysis,single-cell RNA sequencing(scRNA-seq),and metabolomics,were utilized to investigate disruptions in fatty acid metabolism associated with NOA using data from public databases.Results identified ACSL6,ACSBG2,and OLAH as key genes linked to fatty acid metabolism dysregulation,suggesting their potential causative roles in NOA.A marked reduction in omega-3 polyunsaturated fatty acids,especially docosahexaenoic acid(DHA),was observed,potentially contributing to the pathological process of NOA.Sertoli cells in NOA patients exhibited apparent fatty acid metabolic dysfunction,with PPARG identified as a key transcription factor(TF)regulating this process.Functional analyses demonstrated that PPARG is crucial for maintaining blood-testis barrier(BTB)integrity and promoting spermatogenesis via regulation of fatty acid metabolism.These findings reveal the pivotal role of fatty acid metabolism in NOA and identify PPARG as a potential therapeutic target.
