The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities...The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.展开更多
Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating th...Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.展开更多
Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience...Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.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
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
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
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
Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we...Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we perform systematic studies on the elastic properties of the Cu–6wt% Ag alloy wire, which is a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques, i.e., resonant ultrasound spectroscopy(RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu–6wt% Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this opportunity to test the availability of our newly-built ultrasound pulse-echo facility at the Wuhan National High Magnetic Field Center(WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu–6wt% Ag alloy wire remains excellent without anomalous softening under extreme conditions,e.g., in ultra-high magnetic field up to 50 T and nitrogen or helium cryogenic liquids.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 Backfat thickness(BFT)is a vital economic trait in pigs,reflecting subcutaneous fat levels that affect meat quality and production efficiency.As a complex trait shaped by multiple genetic factors,BFT has be...Background Backfat thickness(BFT)is a vital economic trait in pigs,reflecting subcutaneous fat levels that affect meat quality and production efficiency.As a complex trait shaped by multiple genetic factors,BFT has been studied using genome-wide association studies(GWAS)and linkage analyses to locate fat-related quantitative trait loci(QTLs),but pinpointing causal variants and genes is hindered by linkage disequilibrium and limited regulatory data.This study aimed to dissect the QTLs affecting BFT on Sus scrofa chromosome 1(SSC1),elucidating regulatory variants,effector genes,and the cell types involved.Results Using whole-genome genotyping data from 3,578 pigs and phenotypic data for five BFT traits,we identified a 630.6 kb QTL on SSC1 significantly associated with these traits via GWAS and fine-mapping,pinpointing 34 candidate causal variants.Using deep convolutional neural networks to predict regulatory activity from sequence data integrated with detailed pig epigenetic profiles,we identified five SNPs potentially affecting enhancer activity in specific tissues.Notably,rs342950505(SSC1:161,123,588)influences weak enhancer activity across multiple tissues,including the brain.High-throughput chromosome conformation capture(Hi-C)analysis identified that rs342950505 interacts with eight genes.Chromatin state annotations confirmed enhancer activity at this QTL in the cerebellum.Leveraging these insights,single-cell ATAC-seq revealed a chromatin accessibility peak encompassing rs342950505 that regulates PMAIP1 expression in inhibitory neurons via enhancer-mediated mechanisms,with an adjacent peak modulating CCBE1 expression in neuroblasts and granule cells.Transcriptome-wide association studies(TWAS)confirmed PMAIP1's role in the hypothalamus,and Mendelian randomization(MR)validated PMAIP1 and CCBE1 as key brain expression quantitative trait locus(eQTL)effectors.We propose that the variant rs342950505,located within a regulatory peak,modulates PMAIP1 expression in inhibitory neurons,potentially influencing energy homeostasis via hypothalamic regulation.Similarly,CCBE1 may contribute to this process.Conclusions Our results,through systematic dissection of pleiotropic BFT-associated loci,provide a framework to elucidate regulatory mechanisms of complex traits,offering insights into polygenic control through lipid metabolism and neural signaling pathways.展开更多
Osmanthus fragrans Lour.is a well-known aromatic plant widely used as a food ingredient due to its unique floral fragrance and bioactive compounds.To fully utilize O.fragrans resources,we established an O.fragrans mul...Osmanthus fragrans Lour.is a well-known aromatic plant widely used as a food ingredient due to its unique floral fragrance and bioactive compounds.To fully utilize O.fragrans resources,we established an O.fragrans multi-omics database called the O.fragrans Information Resource(OfIR:http://yanglab.hzau.edu.cn/OfIR/home/).OfIR is a convenient and comprehensive multi-omics database that efficiently integrates phenotype and genetic variation from 127 O.fragrans cultivars,and provides many easy-to-use analysis tools,including primer design,sequence extraction,multi-sequence alignment,GO and KEGG enrichment analysis,variation annotation,and electronic PCR.Two case studies were used to demonstrate its power to mine candidate genetic variation sites or genes associated with specific traits or regulatory networks.In summary,the multi-omics database OfIR provides a convenient and user-friendly platform for researchers in mining functional genes and contributes to the genetic breeding of O.fragrans.展开更多
Background As an indigenous livestock species on the Tibetan Plateau,Tibetan sheep exhibit remarkable adaptability to low temperatures and nutrient-scarce environments.During the cold season,Tibetan sheep are typicall...Background As an indigenous livestock species on the Tibetan Plateau,Tibetan sheep exhibit remarkable adaptability to low temperatures and nutrient-scarce environments.During the cold season,Tibetan sheep are typically managed under two feeding regimes:barn feeding(BF)and traditional grazing(TG).However,the molecular mechanisms underlying their adaptation to these distinct management strategies remain unclear.This study aimed to investigate the adaptive strategies of rumen function in Tibetan sheep to cold-season feeding regimes by integrating analyses of rumen morphology,microbiome,metabolome,and transcriptome.Twelve healthy Tibetan sheep with similar body weights were assigned into two groups(BF vs.TG).At the end of the experiment,rumen tissues were subjected to histological observation.Multi-omics techniques were employed to evaluate the effects of cold-season feeding regimes on rumen function in Tibetan sheep.Results The ruminal papilla height,width,and muscular thickness were significantly higher in BF group.The relative abundances of Actinobacteria and Succiniclasticum were significantly elevated in the rumen of BF group,whereas Rikenellaceae,Gracilibacteria,and Lachnospiraceae showed higher abundances in the TG group.Metabolomic analysis identified 19 differential metabolites between the two groups,including upregulated compounds in BF group(fumaric acid,maltose,L-phenylalanine,and L-alanine)and TG group(e.g.,phenylacetic acid,salicyluric acid and ferulic acid).These metabolites were predominantly enriched in phenylalanine metabolism,alanine,aspartate and glutamate metabolism,and phenylalanine,tyrosine and tryptophan biosynthesis pathways.Additionally,210 differentially expressed genes(DEGs)were identified in rumen epithelium:100 upregulated DEGs in the BF group were enriched in nutrient metabolism-related pathways(e.g.,fatty acid degradation and PPAR signaling pathway),while 110 upregulated DEGs in the TG group were associated with immune-related pathways(e.g.,p53 signaling pathway and glutathione metabolism).Conclusions Among these,we observed distinct rumen functional responses to different cold-season feeding regimes in Tibetan sheep and revealed energy allocation strategies mediated by host-microbe interactions.In the BF group,Tibetan sheep adopted a"metabolic efficiency-priority"strategy,driving rumen microbiota to maximize energy capture from high-nutrient diets to support host growth.In contrast,the TG group exhibited an"environmental adaptation-priority"strategy,where rumen microbiota prioritized cellulose degradation and anti-inflammatory functions,reallocating energy toward homeostasis maintenance at the expense of rumen development and growth performance.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
文摘The rapid growth of biomedical data,particularly multi-omics data including genomes,transcriptomics,proteomics,metabolomics,and epigenomics,medical research and clinical decision-making confront both new opportunities and obstacles.The huge and diversified nature of these datasets cannot always be managed using traditional data analysis methods.As a consequence,deep learning has emerged as a strong tool for analysing numerous omics data due to its ability to handle complex and non-linear relationships.This paper explores the fundamental concepts of deep learning and how they are used in multi-omics medical data mining.We demonstrate how autoencoders,variational autoencoders,multimodal models,attention mechanisms,transformers,and graph neural networks enable pattern analysis and recognition across all omics data.Deep learning has been found to be effective in illness classification,biomarker identification,gene network learning,and therapeutic efficacy prediction.We also consider critical problems like as data quality,model explainability,whether findings can be repeated,and computational power requirements.We now consider future elements of combining omics with clinical and imaging data,explainable AI,federated learning,and real-time diagnostics.Overall,this study emphasises the need of collaborating across disciplines to advance deep learning-based multi-omics research for precision medicine and comprehending complicated disorders.
基金supported by Healthy China initiative of Traditional Chinese Medicine(No.889042).
文摘Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.
基金supported by the National Natural Science Foundation of China,No.31760290,82160688the Key Development Areas Project of Ganzhou Science and Technology,No.2022B-SF9554(all to XL)。
文摘Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.
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.
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Project supported by the National Key R&D Program of China (Grant Nos. 2022YFA1602602 and 2023YFA1609600)the National Natural Science Foundation of China (Grant No. U23A20580)+3 种基金the open research fund of Songshan Lake Materials Laboratory (Grant No. 2022SLABFN27)Beijing National Laboratory for Condensed Matter Physics (Grant No. 2024BNLCMPKF004)Guangdong Basic and Applied Basic Research Foundation (Grant No. 2022B1515120020)the interdisciplinary program of Wuhan National High Magnetic Field Center at Huazhong University of Science and Technology (Grant No. WHMFC202132)。
文摘Conductor materials with good mechanical performance as well as high electrical and thermal conductivities are particularly important to break through the current bottle-neck limit(~ 100 T) of pulsed magnets. Here, we perform systematic studies on the elastic properties of the Cu–6wt% Ag alloy wire, which is a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques, i.e., resonant ultrasound spectroscopy(RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu–6wt% Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this opportunity to test the availability of our newly-built ultrasound pulse-echo facility at the Wuhan National High Magnetic Field Center(WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu–6wt% Ag alloy wire remains excellent without anomalous softening under extreme conditions,e.g., in ultra-high magnetic field up to 50 T and nitrogen or helium cryogenic liquids.
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.
基金supported by the China Postdoctoral Science Foundation[Grant Number BX20240146 and 2024M761230]Key Project of Research and Development Plan in Jiangxi Province[Grant Number 20243BCC31001].
文摘Background Backfat thickness(BFT)is a vital economic trait in pigs,reflecting subcutaneous fat levels that affect meat quality and production efficiency.As a complex trait shaped by multiple genetic factors,BFT has been studied using genome-wide association studies(GWAS)and linkage analyses to locate fat-related quantitative trait loci(QTLs),but pinpointing causal variants and genes is hindered by linkage disequilibrium and limited regulatory data.This study aimed to dissect the QTLs affecting BFT on Sus scrofa chromosome 1(SSC1),elucidating regulatory variants,effector genes,and the cell types involved.Results Using whole-genome genotyping data from 3,578 pigs and phenotypic data for five BFT traits,we identified a 630.6 kb QTL on SSC1 significantly associated with these traits via GWAS and fine-mapping,pinpointing 34 candidate causal variants.Using deep convolutional neural networks to predict regulatory activity from sequence data integrated with detailed pig epigenetic profiles,we identified five SNPs potentially affecting enhancer activity in specific tissues.Notably,rs342950505(SSC1:161,123,588)influences weak enhancer activity across multiple tissues,including the brain.High-throughput chromosome conformation capture(Hi-C)analysis identified that rs342950505 interacts with eight genes.Chromatin state annotations confirmed enhancer activity at this QTL in the cerebellum.Leveraging these insights,single-cell ATAC-seq revealed a chromatin accessibility peak encompassing rs342950505 that regulates PMAIP1 expression in inhibitory neurons via enhancer-mediated mechanisms,with an adjacent peak modulating CCBE1 expression in neuroblasts and granule cells.Transcriptome-wide association studies(TWAS)confirmed PMAIP1's role in the hypothalamus,and Mendelian randomization(MR)validated PMAIP1 and CCBE1 as key brain expression quantitative trait locus(eQTL)effectors.We propose that the variant rs342950505,located within a regulatory peak,modulates PMAIP1 expression in inhibitory neurons,potentially influencing energy homeostasis via hypothalamic regulation.Similarly,CCBE1 may contribute to this process.Conclusions Our results,through systematic dissection of pleiotropic BFT-associated loci,provide a framework to elucidate regulatory mechanisms of complex traits,offering insights into polygenic control through lipid metabolism and neural signaling pathways.
基金supported by research grants provided by the National Natural Science Foundation of China(Grant Nos.32101581,32271951,and 32372754)the Hubei Provincial Central Leading Local Special Project(Grant No.2022BGE263)+3 种基金the Key Research and Science and Technology Program of Hubei Province(Grant No.2021BBA098)the Hubei Province Natural Science Foundation(Grant Nos.2023AFB1063 and 2024AFB1057)the Innovation Team Project from Hubei University of Science and Technology(Grant No.2022T02)a PhD grant from the Hubei University of Science and Technology(Grant Nos.BK202002and BK202419).
文摘Osmanthus fragrans Lour.is a well-known aromatic plant widely used as a food ingredient due to its unique floral fragrance and bioactive compounds.To fully utilize O.fragrans resources,we established an O.fragrans multi-omics database called the O.fragrans Information Resource(OfIR:http://yanglab.hzau.edu.cn/OfIR/home/).OfIR is a convenient and comprehensive multi-omics database that efficiently integrates phenotype and genetic variation from 127 O.fragrans cultivars,and provides many easy-to-use analysis tools,including primer design,sequence extraction,multi-sequence alignment,GO and KEGG enrichment analysis,variation annotation,and electronic PCR.Two case studies were used to demonstrate its power to mine candidate genetic variation sites or genes associated with specific traits or regulatory networks.In summary,the multi-omics database OfIR provides a convenient and user-friendly platform for researchers in mining functional genes and contributes to the genetic breeding of O.fragrans.
基金funded by the Chief Scientist Program of Qinghai Province(2024-SF-102)the Joint Special Project of Sanjiangyuan National Park(LHZX-2023-02).
文摘Background As an indigenous livestock species on the Tibetan Plateau,Tibetan sheep exhibit remarkable adaptability to low temperatures and nutrient-scarce environments.During the cold season,Tibetan sheep are typically managed under two feeding regimes:barn feeding(BF)and traditional grazing(TG).However,the molecular mechanisms underlying their adaptation to these distinct management strategies remain unclear.This study aimed to investigate the adaptive strategies of rumen function in Tibetan sheep to cold-season feeding regimes by integrating analyses of rumen morphology,microbiome,metabolome,and transcriptome.Twelve healthy Tibetan sheep with similar body weights were assigned into two groups(BF vs.TG).At the end of the experiment,rumen tissues were subjected to histological observation.Multi-omics techniques were employed to evaluate the effects of cold-season feeding regimes on rumen function in Tibetan sheep.Results The ruminal papilla height,width,and muscular thickness were significantly higher in BF group.The relative abundances of Actinobacteria and Succiniclasticum were significantly elevated in the rumen of BF group,whereas Rikenellaceae,Gracilibacteria,and Lachnospiraceae showed higher abundances in the TG group.Metabolomic analysis identified 19 differential metabolites between the two groups,including upregulated compounds in BF group(fumaric acid,maltose,L-phenylalanine,and L-alanine)and TG group(e.g.,phenylacetic acid,salicyluric acid and ferulic acid).These metabolites were predominantly enriched in phenylalanine metabolism,alanine,aspartate and glutamate metabolism,and phenylalanine,tyrosine and tryptophan biosynthesis pathways.Additionally,210 differentially expressed genes(DEGs)were identified in rumen epithelium:100 upregulated DEGs in the BF group were enriched in nutrient metabolism-related pathways(e.g.,fatty acid degradation and PPAR signaling pathway),while 110 upregulated DEGs in the TG group were associated with immune-related pathways(e.g.,p53 signaling pathway and glutathione metabolism).Conclusions Among these,we observed distinct rumen functional responses to different cold-season feeding regimes in Tibetan sheep and revealed energy allocation strategies mediated by host-microbe interactions.In the BF group,Tibetan sheep adopted a"metabolic efficiency-priority"strategy,driving rumen microbiota to maximize energy capture from high-nutrient diets to support host growth.In contrast,the TG group exhibited an"environmental adaptation-priority"strategy,where rumen microbiota prioritized cellulose degradation and anti-inflammatory functions,reallocating energy toward homeostasis maintenance at the expense of rumen development and growth performance.
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.
