High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging ...High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).展开更多
Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging ...Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.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
In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics,...In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.展开更多
Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of ...Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.展开更多
Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,a...Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.展开更多
Soybean(Glycine max)is a vital foundation of global food security,providing a primary source of highquality protein and oil for human consumption and animal feed.The rising global population has significantly increase...Soybean(Glycine max)is a vital foundation of global food security,providing a primary source of highquality protein and oil for human consumption and animal feed.The rising global population has significantly increased the demand for soybeans,emphasizing the urgency of developing high-yield,stresstolerant,and nutritionally superior cultivars.The extensive collection of soybean germplasm resources—including wild relatives,landraces,and cultivars—represents a valuable reservoir of genetic diversity critical for breeding advancements.Recent breakthroughs in genomic technologies,particularly highthroughput sequencing and multi-omics approaches,have revolutionized the identification of key genes associated with essential agronomic traits within these resources.These innovations enable precise and strategic utilization of genetic diversity,empowering breeders to integrate traits that improve yield potential,resilience to biotic and abiotic stresses,and nutritional quality.This review highlights the critical role of genetic resources and omics-driven innovations in soybean breeding.It also offers insights into strategies for accelerating the development of elite soybean cultivars to meet the growing demands of global soybean production.展开更多
Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatmen...Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.展开更多
Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underly...Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood,limiting the development of precise and effective treatments.The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract.By mapping expression profiles across various molecular levels,these omics approaches enhance our understanding of the disease’s etiological mechanisms,aid in the identification of novel biomarkers and key pathways,and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies.In this review,we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade,encompassing genomics,transcriptomics,proteomics,and metabolomics.Furthermore,we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.展开更多
OBJECTIVE:To develop a safe and effective green therapy for triple-negative breast cancer,this study combines hydrogen-rich water with acupuncture point injection,and finds that it can prevent tumor growth and minimiz...OBJECTIVE:To develop a safe and effective green therapy for triple-negative breast cancer,this study combines hydrogen-rich water with acupuncture point injection,and finds that it can prevent tumor growth and minimize cancer metastasis.METHODS:After 21 d of hydrogen rich water injection treatment on 4T1(mouse breast cancer cells)xenograft mice,in order to systematically identify differentially expressed proteins in tumor samples between the model group and the Zusanli(ST36)group injected with hydrogen rich water at acupoints,with a focus on functional proteins or signaling pathways related to tumor occurrence and development,researchers conducted four-dimensional data independent acquisition(4D-DIA)proteomic analysis on tumor tissues.In order to further investigate the dynamic changes of metabolites after therapeutic intervention,researchers conducted liquid chromatography-tandem mass spectrometry untargeted metabolomics identification and analysis on mouse serum.The results of the joint proteomics–metabolomics analysis were validated using experimental methods such as immunofluorescence,Western blotting,and quantitative reverse transcription polymerase chain reaction detection.RESULTS:Injecting hydrogen-rich water into acupoints significantly inhibited tumor growth(P<0.05).4D-DIA proteomics and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses uncovered pathways such as T helper 1 cell(Th1)and T helper 2 cell(Th2)cell differentiation.The KEGG metabolic pathways identified in the metabolomics analysis included galactose metabolism along with fructose and mannose metabolism.Based on the combined proteomics and metabolomics analysis,the key pathways included the Ctype lectin receptor signaling pathway.The major cancerrelated differential proteins detected in Th1 and Th2 cell differentiation[interleukin 6 signal transducer,nuclear factor of activated T cells 4,recombinant mitogen activated protein kinase 10(MAPK10),and MAPK11]were upregulated after the injection of hydrogen-rich water into the Zusanli(ST36)acupoint,whereas Linker for activation of T cells(Lat),signal transducer and activator of transcription 1,and protein kinase C,theta were downregulated.CONCLUSION:The injection of hydrogen-rich water into the Zusanli(ST36)acupoint effectively inhibited the hyperplasia of 4T1 BC cells and enhanced their apoptosis,potentially exerting a therapeutic effect through multiple pathways and targeting various sites.展开更多
In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicin...In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicine(TCM)with the modern technology of network pharmacology(NP)and omics sequencing.GC is a heterogenous disease,as it incorporates several biochemical pathways that contribute to pathogenesis.TCM acknowledges the multifactorial,heterogenous nature of disease and utilizes an integrative approach to medicine.NP,a modern philosophy within drug development,integrates traditional knowledge of nutraceuticals and modern technologies to address the complex interactions of pathways within the body.Omics technologies,which is at the core of precision medicine,has allowed for this newfound principle of drug development.Metabolic pathways are better distinguished,leading to more targeted drug development.However,the use of omics technology needs to be employed to better characterize the subtypes of GC.This will allow TCM’s use of nutraceuticals in the application of NP to better target metabolic pathways that may aid in the prevention of GC as well as enhance treatment.展开更多
Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed...Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.Methods:To quantify CRD,the HCC CRD score(HCCcrds)was developed.Using machine learning algorithms,we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort(n=369),and the robustness of this method was validated.Furthermore,we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.Results:We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis.The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis,higher pathological grade,and advanced clinical stages,while the CRD-related subtype with low HCCcrds had better clinical outcomes.We also identified novel biomarkers for each subtype,such as nicotinamide nmethyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.Conclusion:We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers.Within these groups greater HCCcrds was associated with worse prognosis.This approach has the potential to improve prediction of an individual’s prognosis,guide precision treatments,and assist clinical decision making for HCC patients.展开更多
There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative...There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.展开更多
Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex inte...Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment(TIME).Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME.Furthermore,integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior.In this review,we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC,highlighting their utility in identifying metastasis dissemination,recurrence risk,and therapeutic resistance in patients treated with immunotherapeutic approaches.This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms.Additionally,an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.展开更多
Chronic uncontrolled inflammation is a major risk factor driving the occurrence of hepatocellular carcinoma(HCC),with over half of global cases attributed to hepatitis B virus(HBV)infection.Persistent inflammation fre...Chronic uncontrolled inflammation is a major risk factor driving the occurrence of hepatocellular carcinoma(HCC),with over half of global cases attributed to hepatitis B virus(HBV)infection.Persistent inflammation frequently progresses to cirrhosis and,ultimately,malignancy[1].Monitoring the key risk factors involved in the inflammatory-to-cancerous transformation in HCC is crucial for enabling timely intervention and improving patient survival rates.To address this challenge,we analyzed plasma samples collected from healthy volunteers and patients at various stages of HCC progression.展开更多
Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of prec...Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular,metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed： 1） the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2） the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.展开更多
Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visuali...Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.展开更多
Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to ...Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to quantify the mRNA expression of a large number of genes in the spatial context of tissues and cells.As a paradigm shift in biological research,spatial transcriptomics can provide both spatial location information and transcriptome-level cellular gene expression data,elucidating the interactions between cells and the microenvironment.From the understanding of the entire functional life cycle of RNA to the characterization of molecular mechanisms to the mapping of gene expression in various tissue regions,by choosing the appropriate spatial transcriptome technology,researchers can achieve a deeper exploration of biological developmental processes,disease pathogenesis,etc.In recent years,the field of spatial transcriptomics has ushered in several challenges along with its rapid development,such as the dependence on sample types,the resolution of visualized genes,the difficulty of commercialization,and the ability to obtain detailed single-cell information.In this paper,we summarize and review the four major categories of spatial transcriptome technologies and compare and analyze the technical advantages and major challenges of multiple research strategies to assist current experimental design and research analysis.Finally,the importance of spatial transcriptomics in the integration of multi-omics analysis and disease modeling as well as the future development prospects are summarized and outlined.展开更多
文摘High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).
基金supported by the grants from the Key Research and Development Program of Xinjiang Uygur autonomous region in China(Grant No.2023B02017)the National Key Research and Development Program of China(Grant No.2024YFD2300703)+1 种基金the financial support from the Beijing Rural Revitalization Agricultural Science and Technology Project(Grant No.NY2401080000),BAIC01-2025the 2115 Talent Development Program of China Agricultural University.
文摘Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.
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 Professor of Chang Jiang Scholars Program,NSFC(No.81230090)Shanghai Leading Academic Discipline Project(B906)+3 种基金Key laboratory of drug research for special environments,PLA,Shanghai Engineering Research Center for the Preparation of Bioactive Natural Products(No.10DZ2251300)the Scientific Foundation of Shanghai,China(Nos.12401900801,13401900 101)National Major Project of China(No.2011ZX09307-002-03)the National Key Technology R&D Program of China(No.2012BAI29B06)
文摘In the post-genomic era, biological studies are characterized by the rapid development and wide application of a series of "omics" technologies, including genomics, proteomics, metabolomics, transcriptomics, lipidomics, cytomics, metallomics, ionomics, interactomics, and phenomics. These "omics" are often based on global analyses of biological samples using high through-put analytical approaches and bioinformatics and may provide new insights into biological phenomena. In this paper, the development and advances in these omics made in the past decades are reviewed, especially genomics, transcriptomics, proteomics and metabolomics; the applications of omics technologies in pharmaceutical research are then summarized in the fields of drug target discovery, toxicity evaluation, personalized medicine, and traditional Chinese medicine; and finally, the limitations of omics are discussed, along with the future challenges associated with the multi-omics data processing, dynamics omics analysis, and analytical approaches, as well as amenable solutions and future prospects.
基金supported by two DoD grants(HT94252310534 to R.J.T.and HT94252310519 to C.M.K.)the following NIH/NIAMS grants:R01 grants(AR078035 and AR076900 to C.L.+10 种基金AG069401 and AG067698 to L.Q.AI186118,HD112474,and HD107034 to R.J.T.AR076325 and AR071967 to C.M.K.AR080902 and AR072999 to F.G.AR074441 and AR077678 to S.Y.T.AR082667 and AR077527 to A.E.L.AR083900,AR075860 and AR077616 to J.S.),R21 grants(AR077226 to J.S.AR083217 to A.E.L.AR081517 to S.Y.T.)a T32 grant(HD007434 to D.R.K.)P30 center grants(AR074992 and AR073752).
文摘Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.
基金supported by the National Natural Science Foundation of China(82302757)Shenzhen Science and Technology Program(JCY20240813145204006,SGDX20201103095600002,JCYJ20220818103417037,KJZD20230923115200002)+1 种基金Shenzhen Key Laboratory of Digital Surgical Printing Project(ZDSYS201707311542415)Shenzhen Development and Reform Program(XMHT20220106001).
文摘Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.
基金supported by the National Key Research and Development Program of China(2022YFF1003301,2023YFF1000101,2022YFE0130200)the Taishan Scholars Program。
文摘Soybean(Glycine max)is a vital foundation of global food security,providing a primary source of highquality protein and oil for human consumption and animal feed.The rising global population has significantly increased the demand for soybeans,emphasizing the urgency of developing high-yield,stresstolerant,and nutritionally superior cultivars.The extensive collection of soybean germplasm resources—including wild relatives,landraces,and cultivars—represents a valuable reservoir of genetic diversity critical for breeding advancements.Recent breakthroughs in genomic technologies,particularly highthroughput sequencing and multi-omics approaches,have revolutionized the identification of key genes associated with essential agronomic traits within these resources.These innovations enable precise and strategic utilization of genetic diversity,empowering breeders to integrate traits that improve yield potential,resilience to biotic and abiotic stresses,and nutritional quality.This review highlights the critical role of genetic resources and omics-driven innovations in soybean breeding.It also offers insights into strategies for accelerating the development of elite soybean cultivars to meet the growing demands of global soybean production.
基金College Students Innovation and Entrepreneurship Training Program(X202511049398)College Students Innovation and Entrepreneurship Training Program(X202511049201)+1 种基金College Students Innovation and Entrepreneurship Training Program(X202511258005S)University-Level Research Funding Program of Hainan Science and Technology Vocational University(HKKY2024-87)。
文摘Sandfly fever is a viral infectious disease transmitted by sand flies that is widely prevalent in tropical and subtropical regions.Previous studies on its infection mechanism,immune response and diagnosis and treatment methods were lack of systematic.This study applied spatio-temporal omics technology to comprehensively explain the dynamic changes of immunity in the incubation period,exacerbation period,peak period and recovery period of Sandfl y fever,and integrated with diff erent coping strategies.To provide new research ideas for its overall research.
基金supported by the General Program of Natural Science Foundation of Guangdong Province(2023A1515011102).
文摘Pediatric cataract,a leading cause of blindness in children globally,imposing a significant financial burden on both families and society.The extensive phenotypic heterogeneity of this condition means that the underlying mechanisms remain poorly understood,limiting the development of precise and effective treatments.The advent of omics technologies has provided potent tools for unraveling the pathogenesis of pediatric cataract.By mapping expression profiles across various molecular levels,these omics approaches enhance our understanding of the disease’s etiological mechanisms,aid in the identification of novel biomarkers and key pathways,and offer researchers new insights for the innovative strategies in disease diagnosis and targeted therapies.In this review,we summarize the application of omics approaches in clinical and basic research on pediatric cataract over the past decade,encompassing genomics,transcriptomics,proteomics,and metabolomics.Furthermore,we discuss the current challenges and future prospects of omics analyses in pediatric cataract studies.
基金the National Natural Science Foundation of China:Exploring the Advantages of Micro-needle System Therapy for Specific Diseases and the Patterns of Acupoint Selection through Data Mining Techniques(No.81473773)Key Project of Hebei Provincial Education Department:Exploring the Molecular Mechanism behind How Hydrogen Mitigates the Aging of Vascular Endothelial Cells Induced by Chronic Intermittent Hypoxia,Utilizing the Keap1-Nuclear factor erythroid 2-related factor 2 Signaling Pathway(No.ZD2020142)Hebei University of Traditional Chinese Medicine 2024 Graduate Student Innovation Funding Project:Study on the Inhibitory Effect and Mechanism of Hydrogen-rich Water Acupoint Injection on Tumors in Mice with Triple-negative Breast Cancer(No.CXZZBS2024154)。
文摘OBJECTIVE:To develop a safe and effective green therapy for triple-negative breast cancer,this study combines hydrogen-rich water with acupuncture point injection,and finds that it can prevent tumor growth and minimize cancer metastasis.METHODS:After 21 d of hydrogen rich water injection treatment on 4T1(mouse breast cancer cells)xenograft mice,in order to systematically identify differentially expressed proteins in tumor samples between the model group and the Zusanli(ST36)group injected with hydrogen rich water at acupoints,with a focus on functional proteins or signaling pathways related to tumor occurrence and development,researchers conducted four-dimensional data independent acquisition(4D-DIA)proteomic analysis on tumor tissues.In order to further investigate the dynamic changes of metabolites after therapeutic intervention,researchers conducted liquid chromatography-tandem mass spectrometry untargeted metabolomics identification and analysis on mouse serum.The results of the joint proteomics–metabolomics analysis were validated using experimental methods such as immunofluorescence,Western blotting,and quantitative reverse transcription polymerase chain reaction detection.RESULTS:Injecting hydrogen-rich water into acupoints significantly inhibited tumor growth(P<0.05).4D-DIA proteomics and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses uncovered pathways such as T helper 1 cell(Th1)and T helper 2 cell(Th2)cell differentiation.The KEGG metabolic pathways identified in the metabolomics analysis included galactose metabolism along with fructose and mannose metabolism.Based on the combined proteomics and metabolomics analysis,the key pathways included the Ctype lectin receptor signaling pathway.The major cancerrelated differential proteins detected in Th1 and Th2 cell differentiation[interleukin 6 signal transducer,nuclear factor of activated T cells 4,recombinant mitogen activated protein kinase 10(MAPK10),and MAPK11]were upregulated after the injection of hydrogen-rich water into the Zusanli(ST36)acupoint,whereas Linker for activation of T cells(Lat),signal transducer and activator of transcription 1,and protein kinase C,theta were downregulated.CONCLUSION:The injection of hydrogen-rich water into the Zusanli(ST36)acupoint effectively inhibited the hyperplasia of 4T1 BC cells and enhanced their apoptosis,potentially exerting a therapeutic effect through multiple pathways and targeting various sites.
文摘In this editorial,we comment on the article by Micucci et al published in the recent issue.We focus on the heterogenous nature of gastric cancer(GC)and the potential benefits of integrating traditional Chinese medicine(TCM)with the modern technology of network pharmacology(NP)and omics sequencing.GC is a heterogenous disease,as it incorporates several biochemical pathways that contribute to pathogenesis.TCM acknowledges the multifactorial,heterogenous nature of disease and utilizes an integrative approach to medicine.NP,a modern philosophy within drug development,integrates traditional knowledge of nutraceuticals and modern technologies to address the complex interactions of pathways within the body.Omics technologies,which is at the core of precision medicine,has allowed for this newfound principle of drug development.Metabolic pathways are better distinguished,leading to more targeted drug development.However,the use of omics technology needs to be employed to better characterize the subtypes of GC.This will allow TCM’s use of nutraceuticals in the application of NP to better target metabolic pathways that may aid in the prevention of GC as well as enhance treatment.
基金supported by Tianjian advanced biomedical laboratory key research and development projectHenan Province Natural Science Foundation(grant number:242300421283)+1 种基金Henan Province Science and Technology Research and Development(grant number:242102311176)Henan Province medical science and technology research project(grant number:SBGJ202403038)。
文摘Objective:Circadian rhythm disruption(CRD)is a risk factor that correlates with poor prognosis across multiple tumor types,including hepatocellular carcinoma(HCC).However,its mechanism remains unclear.This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity.Methods:To quantify CRD,the HCC CRD score(HCCcrds)was developed.Using machine learning algorithms,we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort(n=369),and the robustness of this method was validated.Furthermore,we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes.Results:We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis.The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis,higher pathological grade,and advanced clinical stages,while the CRD-related subtype with low HCCcrds had better clinical outcomes.We also identified novel biomarkers for each subtype,such as nicotinamide nmethyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1.Conclusion:We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers.Within these groups greater HCCcrds was associated with worse prognosis.This approach has the potential to improve prediction of an individual’s prognosis,guide precision treatments,and assist clinical decision making for HCC patients.
基金supported by the China Science and Technology Innovation 2030-Major Project(Nos.2022ZD0211701,2021ZD0200700)the National Natural Science Foundation of China(Nos.82130042,81830040,22176195,82127801)+3 种基金Shenzhen Science and Technology Serial Funds(Nos.GJHZ20210705141400002,KCXFZ20211020164543006,JCYJ20220818101615033,ZDSYS20220606100606014,KQTD 20221101093608028)the National Key R&D Program of China(No.2022YFF0705003)Guangdong Province Zhu Jiang Talents Plan(No.2021QN02Y028)the Guangdong Science and Technology Department(No.2021B1212030004)。
文摘There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.
基金supported by the Zhejiang Province Traditional Chinese Medicine Science and Technology Project(GZY-ZJ-KJ-24063)the Natural Science Foundation of Zhejiang Province(Q24H290031)the Key Laboratory for Molecular Medicine and Chinese Medicine Preparations(No.GZY-ZJ-SY-2303).
文摘Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer(CC).However,the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment(TIME).Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME.Furthermore,integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior.In this review,we present advanced omics technologies that utilize various clinical samples to address scientific inquiries related to immunotherapies for CC,highlighting their utility in identifying metastasis dissemination,recurrence risk,and therapeutic resistance in patients treated with immunotherapeutic approaches.This review elaborates on the strategy for integrating multi-omics data through artificial intelligence algorithms.Additionally,an analysis of the obstacles encountered in the multi-omics analysis process and potential avenues for future research in this domain are presented.
基金supported by Liaoning Province Science and Technology Plan Project,China(Grant No.:2022JH2/101300038)Liaoning Provincial Applied Basic Research Project,China(Grant No.:2022020255-JH2/1013)+5 种基金the National Natural Science Foundation of China of China(Grant Nos.:82104379/H3203 and 82104126/H3410)Liaoning Distinguished Professor Project(2017)Liaoning BaiQianWan Talents Program in 2019(A-37)China,Liaoning key Research and Development Program(2018),China,the Natural Science Funds of Liaoning Province,China(Grant No.:2021JH2/10300068)the Basic Scientific Research Project of Higher Education Department of Liaoning Province,China(Grant No.:LJ212410163036)Educational Commission of Liaoning Province of China,China(Grant No.:LJ212410163026).
文摘Chronic uncontrolled inflammation is a major risk factor driving the occurrence of hepatocellular carcinoma(HCC),with over half of global cases attributed to hepatitis B virus(HBV)infection.Persistent inflammation frequently progresses to cirrhosis and,ultimately,malignancy[1].Monitoring the key risk factors involved in the inflammatory-to-cancerous transformation in HCC is crucial for enabling timely intervention and improving patient survival rates.To address this challenge,we analyzed plasma samples collected from healthy volunteers and patients at various stages of HCC progression.
基金financially supported by grants from the National Natural Science Foundation of China (Nos.31371515 and 3150040263)the Special Financial Grant awarded to S.M. Lam from the China Postdoctoral Science Foundation (No.2014T70137)
文摘Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular,metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed： 1） the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2） the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.
基金supported by Basic and Applied Basic Research Foundation of Guangdong Province(No.2022A1111220217)Medical Scientific Research Foundation of Guangdong Province(Nos.A2023216,A2022124)+3 种基金Science and Technology Program of Guangzhou(Nos.202201010840,202201010810,202102080132,202002030032,202002020023)Health Commission Program of Guangzhou(20212A010021,20201A010081,20211A011116)Science and Technology Project of Panyu,Guangzhou(2022-Z04-009,2022-Z04-090,2022-Z04-072,2021-Z04-013,2020-Z04-026,2019-Z04-02)Scientific Research Project of Guangzhou Panyu Central Hospital(Nos.2022Y002,2021Y004,2021Y002).
文摘Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.
基金supported by the National Natural Science Foundation of China(Grant No.22275071)
文摘Spatial transcriptomics is an organizational study done on tissue sections that preserves the spatial information of the sample.Spatial transcriptomics aims to combine spatial information with gene expression data to quantify the mRNA expression of a large number of genes in the spatial context of tissues and cells.As a paradigm shift in biological research,spatial transcriptomics can provide both spatial location information and transcriptome-level cellular gene expression data,elucidating the interactions between cells and the microenvironment.From the understanding of the entire functional life cycle of RNA to the characterization of molecular mechanisms to the mapping of gene expression in various tissue regions,by choosing the appropriate spatial transcriptome technology,researchers can achieve a deeper exploration of biological developmental processes,disease pathogenesis,etc.In recent years,the field of spatial transcriptomics has ushered in several challenges along with its rapid development,such as the dependence on sample types,the resolution of visualized genes,the difficulty of commercialization,and the ability to obtain detailed single-cell information.In this paper,we summarize and review the four major categories of spatial transcriptome technologies and compare and analyze the technical advantages and major challenges of multiple research strategies to assist current experimental design and research analysis.Finally,the importance of spatial transcriptomics in the integration of multi-omics analysis and disease modeling as well as the future development prospects are summarized and outlined.
