Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing can...Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.展开更多
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
Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal ce...Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal cells(MSCs)exhibited greater therapeutic efficacy than CD146-MSCs.These cells enhance epithelial repair through nuclear factor kappa B/cyclooxygenase-2-associated paracrine signaling and secretion of pro-angiogenic factors.We concur that MSCs hold significant promise for ARDS treatment;however,the heterogeneity of cell products is a translational barrier.Phenotype-aware strategies,such as CD146 enrichment,standardized potency assays,and extracellular vesicle profiling,are essential for improving the consistency of these studies.Further-more,advanced preclinical models,such as lung-on-a-chip systems,may provide more predictive insights into the therapeutic mechanisms.This article underscores the importance of CD146+MSCs in ARDS,emphasizes the need for precision in defining cell products,and discusses how integrating subset selection into translational pipelines could enhance the clinical impact of MSC-based therapies.展开更多
Nanofertilizers increase efficiency and sustainability of agricultural crop production.Due to their nanosize properties,they have been shown to increase productivity through target delivery or slow release of nutrient...Nanofertilizers increase efficiency and sustainability of agricultural crop production.Due to their nanosize properties,they have been shown to increase productivity through target delivery or slow release of nutrients,thereby limiting the rate of fertilizer application required.Nanofertilizers can be synthesized via different approaches ranging from physical and chemical to green(biological)synthesis.The green approach is preferable because it makes use of less chemicals,thereby producing less chemical contamination and it is safer in comparison to physicochemical approaches.Hence,discussion on the use of green synthesized nanoparticles as nanofertilizers is pertinent for a sustainable approach in agriculture.This review discusses recent developments and applications of biologically synthesized metallic nanoparticles that can also be used as nanofertilizers,as well as their uptake mechanisms for plant growth.Toxicity concerns of nanoparticle applications in agriculture are also discussed.展开更多
Based on Vacuum Differential Pressure Casting (VDPC) precision forming technology and the Selective Laser Sintering (SLS) Rapid Prototyping (RP) technology, a rapid manufacturing method called Rapid Precision Casting ...Based on Vacuum Differential Pressure Casting (VDPC) precision forming technology and the Selective Laser Sintering (SLS) Rapid Prototyping (RP) technology, a rapid manufacturing method called Rapid Precision Casting (RPC) process from computer three-dimensional solid models to metallic parts was investigated. The experimental results showed that the main advantage of RPC was not only its ability to cast higher internal quality and more accurate complex thin-walled aluminum alloy parts, but also the greatly-reduced lead time cycle from Selective Laser Sintering (SLS) plastic prototyping to metallic parts. The key forming technology of RPC for complex thin-walled metallic parts has been developed for new casting production and Rapid Tooling (RT), and it is possible to rapidly manufacture high-quality and accurate metallic parts by means of RP in foundry industry.展开更多
Preparation method of magnetic nanoparticles with core-shell structure was introduced,especially focusing on the preparation principle of sol-gel method,microemulsion method,and self-assembly technique.The application...Preparation method of magnetic nanoparticles with core-shell structure was introduced,especially focusing on the preparation principle of sol-gel method,microemulsion method,and self-assembly technique.The application of core-shell nanoparticles in precision machining was discussed.The Fe_(3)O_(4)@SiO_(2)composite particles were prepared by sol-gel method and were applied to the magnetorheological polishing of titanium alloy plates.Results show that core-shell nanoparticles with higher surface quality can be obtained after processing,compared with those after conventional abrasives.After polishing for 20 min,the surface roughness of the workpiece reaches 23 nm and the scratches are effectively reduced.Finally,the preparation and application of coreshell nanoparticles are summarized and prospected to provide a reference for further research on core-shell nanoparticles.展开更多
Extracorporeal liver surgery(ELS), also known as liver autotransplantation, is a hybrid(cross-fertilized) surgery incorporating the technical knowledge from extreme liver and transplant liver surgeries, and recently b...Extracorporeal liver surgery(ELS), also known as liver autotransplantation, is a hybrid(cross-fertilized) surgery incorporating the technical knowledge from extreme liver and transplant liver surgeries, and recently became more embraced and popularized among leading centers. ELS could be summarized into three major categories, namely, ex-situ liver resection and autotransplantation(ELRA), ante-situm liver resection and autotransplantation(ALRA) and auxiliary partial liver autotransplantation(APLA). The successful development of ELS during the past 37 years is definitely inseparable from continuous effort s done by Chinese surgeons and researchers. Especially, the precision liver surgery paradigm has allowed to transform ELS into a modularized, more simplified, and standardized surgery, to upgrade surgical skills, to improve peri-operative outcome and long-term survival, to increase the capability of surgeons to select more complex diseases and to expand the level of medical service to the population. This review highlights the Chinese contributions to the field of ELS, focusing thereby on features of different surgical types, technical innovations, disease selection and surgical indication, patient prognosis and future perspectives.展开更多
In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper...In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper“From digits towards digitization:the past,present,and future of traditional Chinese medicine”by Academician&TCM National Master Qi WANG(王琦).展开更多
Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,rad...Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,radiomics,and multimodal data integration,AI has achieved diagnostic parity with expert cli-nicians in endoscopic image analysis(e.g.,early gastric cancer detection,colorectal polyp identification)and non-invasive assessment of liver pathologies(e.g.,fibrosis staging,fatty liver typing)while demonstrating utility in personalized care scenarios such as predicting hepatocellular carcinoma recurrence and opti-mizing inflammatory bowel disease treatment responses.Despite these advance-ments challenges persist including limited model generalization due to frag-mented datasets,algorithmic limitations in rare conditions(e.g.,pediatric liver diseases)caused by insufficient training data,and unresolved ethical issues related to bias,accountability,and patient privacy.Mitigation strategies involve constructing standardized multicenter databases,validating AI tools through prospective trials,leveraging federated learning to address data scarcity,and de-veloping interpretable systems(e.g.,attention heatmap visualization)to enhance clinical trust.Integrating generative AI,digital twin technologies,and establishing unified ethical/regulatory frameworks will accelerate AI adoption in primary care and foster equitable healthcare access while interdisciplinary collaboration and evidence-based implementation remain critical for realizing AI’s potential to redefine precision care for digestive disorders,improve global health outcomes,and reshape healthcare equity.展开更多
Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models.Organoids pres...Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models.Organoids preserve the complex tissue architecture and cellular diversity of human cancers,enabling more accurate predictions of tumor growth,metastasis,and drug responses.Integration with microfluidic platforms,such as organ-on-a-chip systems,further enhances the ability to model tumor-environment interactions in real-time.Organoids facilitate in-depth exploration of tumor heterogeneity,molecular mechanisms,and the development of personalized treatment strategies when coupled with multi-omics technologies.Organoids provide a platform for investigating tumor-immune cell interactions,which aid in the design and testing of immune-based therapies and vaccines.Taken together,these features position organoids as a transformative tool in advancing cancer research and precision medicine.展开更多
Artificial intelligence(AI)and machine learning(ML)are transforming spine care by addressing diagnostics,treatment planning,and rehabilitation challenges.This study highlights advancements in precision medicine for sp...Artificial intelligence(AI)and machine learning(ML)are transforming spine care by addressing diagnostics,treatment planning,and rehabilitation challenges.This study highlights advancements in precision medicine for spinal pathologies,leveraging AI and ML to enhance diagnostic accuracy through deep learning algorithms,enabling faster and more accurate detection of abnormalities.AIpowered robotics and surgical navigation systems improve implant placement precision and reduce complications in complex spine surgeries.Wearable devices and virtual platforms,designed with AI,offer personalized,adaptive therapies that improve treatment adherence and recovery outcomes.AI also enables preventive interventions by assessing spine condition risks early.Despite progress,challenges remain,including limited healthcare datasets,algorithmic biases,ethical concerns,and integration into existing systems.Interdisciplinary collaboration and explainable AI frameworks are essential to unlock AI’s full potential in spine care.Future developments include multimodal AI systems integrating imaging,clinical,and genetic data for holistic treatment approaches.AI and ML promise significant improvements in diagnostic accuracy,treatment personalization,service accessibility,and cost efficiency,paving the way for more streamlined and effective spine care,ultimately enhancing patient outcomes.展开更多
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
Nanotechnology in cancer therapy has significantly advanced treatment precision,effectiveness,and safety,improving patient outcomes and personalized care.Engineered smart nanoparticles and cell-based therapies are des...Nanotechnology in cancer therapy has significantly advanced treatment precision,effectiveness,and safety,improving patient outcomes and personalized care.Engineered smart nanoparticles and cell-based therapies are designed to target tumor cells,precisely sensing the tumor microenvironment(TME)and sparing normal cells.These nanoparticles enhance drug accumulation in tumors by solubilizing insoluble compounds or preventing their degradation,and they can also overcome therapy resistance and deliver multiple drugs simultaneously.Despite these benefits,challenges remain in patient-specific responses and regulatory approvals for cell-based or nanoparticle therapies.Cell-based drug delivery systems(DDSs)that primarily utilize the immune-recognition principle between ligands and receptors have shown promise in selectively targeting and destroying cancer cells.This review aims to provide a comprehensive overview of various nanoparticle and cell-based drug delivery system types used in cancer research.It covers approved and experimental nanoparticle therapies,including liposomes,micelles,protein-based and polymeric nanoparticles,as well as cell-based DDSs like macrophages,T-lymphocytes,dendritic cells,viruses,bacterial ghosts,minicells,SimCells,and outer membrane vesicles(OMVs).The review also explains the role of TME and its impact on developing smart DDSs in combination therapies and integrating nanoparticles with cell-based systems for targeting cancer cells.By detailing DDSs at different stages of development,from laboratory research to clinical trials and approved treatments,this review provides the latest insights and a collection of valuable citations of the innovative strategies that can be improved for the precise treatment of cancer.展开更多
Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecis...Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.展开更多
For special-shaped parts, the clamping and processing are very difficult. Based on this, a part with high precision and special shape is selected as a case. In-depth analysis of its structure and accuracy, scientific ...For special-shaped parts, the clamping and processing are very difficult. Based on this, a part with high precision and special shape is selected as a case. In-depth analysis of its structure and accuracy, scientific and reasonable formulation of the processing technology, at the same time, the complete involvement of special tooling and fixtures, so as to ensure the simplification of parts processing, and thus ensure the processing progress. At the same time, in order to effectively control the quality based on the accuracy and shape requirements of the parts themselves, if ordinary inspection equipment is applied, the purpose of inspection cannot be achieved. Therefore, according to the actual situation, special inspection tools should be designed to ensure the reliability and efficiency of the inspection. Based on this, this paper mainly analyzes and discusses the NC machining process analysis and testing of precision special-shaped parts.展开更多
In the era of precision medicine,the breast cancer surgical treatment field is gradually moving toward a de-escalation model.Through precise preoperative assessments and multidisciplinary decision-making,surgical trau...In the era of precision medicine,the breast cancer surgical treatment field is gradually moving toward a de-escalation model.Through precise preoperative assessments and multidisciplinary decision-making,surgical trauma can be decreased,and patients’quality of life can be improved by ensuring safety.Herein,we explore the axillary de-escalation surgery model for breast cancer.展开更多
Lynch syndrome(LS)is the most common hereditary colorectal cancer(CRC)predisposition syndrome,characterized by a high mutational burden and microsatellite instability-high(MSI-H)tumors.Immunology of LS-associated CRC(...Lynch syndrome(LS)is the most common hereditary colorectal cancer(CRC)predisposition syndrome,characterized by a high mutational burden and microsatellite instability-high(MSI-H)tumors.Immunology of LS-associated CRC(LS-CRC)is unique,with significant implications for treatment.Despite well-established knowledge of LS immunology,immunotherapy dose and treatment response can vary significantly based on local tumor immunity and specific germline pathogenic variant of LS genes.This variability necessitates tailored surveillance strategies and new personalised immunotherapy approaches for LS patients.LS-CRC often benefits from immunotherapy due to the distinct tumor microenvironment(TME)and the variety of tumor infiltrating lymphocytes(TILs).This perspective discusses a novel approach of analysing spatial TILs at a single-cell level using tumor whole slide images(WSIs)that accounts for the distinct TME of LS-CRC.By emphasizing the necessity of personalized medicine in hereditary cancer syndromes,the future research and clinical practices that enhance patient outcomes through precision oncology is inspired.展开更多
Approximately 2.5%of the global population experience allergic reactions to seafood,making it one of the most prevalent and life-threatening allergies.Seafood allergy can lead to the disruption of the intestinal barri...Approximately 2.5%of the global population experience allergic reactions to seafood,making it one of the most prevalent and life-threatening allergies.Seafood allergy can lead to the disruption of the intestinal barrier,possibly due to aberrant intestinal glycosylation.In this study,the mechanisms underlying seafood allergy were explored through the lens of intestinal glycobiology.Mice were sensitized with tropomyosin,resulting in significant increases in allergy symptom scores,specific antibody and T helper 2 cytokine levels.Intestinal damage was confirmed by histopathology,as well as by assessments and levels of diamine oxidase and claudin-1.Moreover,alterations in glycosylated proteins within the jejunum were analyzed using highthroughput mass spectrometry and the pGlyco3.0 search engine.Precision N-glycoproteomics analysis yielded 2283 glycosylation peptides corresponding to 655 unique glycosylation sites on 399 proteins.Differential expression and enrichment analyses revealed that differentially expressed glycoproteins were significantly enriched in the extracellular matrix(ECM)-receptor interaction pathway and focal adhesion pathway.In conclusion,tropomyosin sensitization leads to intestinal glycome changes,accompanied by remodeling of the intestinal ECM.Our research establishes an essential theoretical basis for targeting the intestinal glycome and ECM remodeling in a precise and fine-tuned manner for the treatment of food allergies.展开更多
Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria sti...Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria still grapples with wide acceptance,key translational research and implementation of PM.This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.Methods:A cross‐sectional study was conducted in selected tertiary hospitals across the country.A 21‐item semi‐structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25.Descriptive statistics were used to summarize the data.A chi‐square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.Results:A total of 167 hospital pharmacists participated in the study.A high proportion of the participants are familiar with artificial intelligence(91.75%),Pharmacogenomics(84.5%),and precision medicine(61%).Overall,38.9%of the pharmacists had a good knowledge while 13.2%had a poor knowledge of PM and associated terms.The level of knowledge did not correlate significantly with gender(X^(2)=3.21,p=0.201),age(X^(2)=5,p=0.27),marital status(X^(2)=3.21,p=0.201),and professional level(X^(2)=6.85,p=0.144).The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine(49%)while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.Conclusions:There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria.Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM.Also,more research aimed at translating PM knowledge into clinical practice is recommended.展开更多
The management of breast cancer,one of the most common and heterogeneous malignancies,has transformed with the advent of precision medicine.This review explores current developments in genetic profiling,molecular diag...The management of breast cancer,one of the most common and heterogeneous malignancies,has transformed with the advent of precision medicine.This review explores current developments in genetic profiling,molecular diagnostics,and targeted therapies that have revolutionized breast cancer treatment.Key innovations,such as cyclin-dependent kinases 4/6(CDK4/6)inhibitors,antibodydrug conjugates(ADCs),and immune checkpoint inhibitors(ICIs),have improved outcomes for hormone receptor-positive(HR+),HER2-positive(HER2+),and triple-negative breast cancer(TNBC)subtypes remarkably.Additionally,emerging treatments,such as PI3K inhibitors,poly(ADP-ribose)polymerase(PARP)inhibitors,and m RNA-based therapies,offer new avenues for targeting specific genetic mutations and improving treatment response,particularly in difficult-to-treat breast cancer subtypes.The integration of liquid biopsy technologies provides a non-invasive approach for real-time monitoring of tumor evolution and treatment response,thus enabling dynamic adjustments to therapy.Molecular imaging and artificial intelligence(AI)are increasingly crucial in enhancing diagnostic precision,personalizing treatment plans,and predicting therapeutic outcomes.As precision medicine continues to evolve,it has the potential to significantly improve survival rates,decrease recurrence,and enhance quality of life for patients with breast cancer.By combining cutting-edge diagnostics,personalized therapies,and emerging treatments,precision medicine can transform breast cancer care by offering more effective,individualized,and less invasive treatment options.展开更多
文摘Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.
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the Scientific and Technological Research Council of Türkiye(TÜBİTAK)Under the International Postdoctoral Research Fellowship Program(2219),No.1059B192400980the National Postdoctoral Research Fellowship Program(2218),No.122C158.
文摘Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal cells(MSCs)exhibited greater therapeutic efficacy than CD146-MSCs.These cells enhance epithelial repair through nuclear factor kappa B/cyclooxygenase-2-associated paracrine signaling and secretion of pro-angiogenic factors.We concur that MSCs hold significant promise for ARDS treatment;however,the heterogeneity of cell products is a translational barrier.Phenotype-aware strategies,such as CD146 enrichment,standardized potency assays,and extracellular vesicle profiling,are essential for improving the consistency of these studies.Further-more,advanced preclinical models,such as lung-on-a-chip systems,may provide more predictive insights into the therapeutic mechanisms.This article underscores the importance of CD146+MSCs in ARDS,emphasizes the need for precision in defining cell products,and discusses how integrating subset selection into translational pipelines could enhance the clinical impact of MSC-based therapies.
基金supported by the L’Oréal-UNESCO for women in Science Programmethe National Research Foundation(129651)of South Africa。
文摘Nanofertilizers increase efficiency and sustainability of agricultural crop production.Due to their nanosize properties,they have been shown to increase productivity through target delivery or slow release of nutrients,thereby limiting the rate of fertilizer application required.Nanofertilizers can be synthesized via different approaches ranging from physical and chemical to green(biological)synthesis.The green approach is preferable because it makes use of less chemicals,thereby producing less chemical contamination and it is safer in comparison to physicochemical approaches.Hence,discussion on the use of green synthesized nanoparticles as nanofertilizers is pertinent for a sustainable approach in agriculture.This review discusses recent developments and applications of biologically synthesized metallic nanoparticles that can also be used as nanofertilizers,as well as their uptake mechanisms for plant growth.Toxicity concerns of nanoparticle applications in agriculture are also discussed.
文摘Based on Vacuum Differential Pressure Casting (VDPC) precision forming technology and the Selective Laser Sintering (SLS) Rapid Prototyping (RP) technology, a rapid manufacturing method called Rapid Precision Casting (RPC) process from computer three-dimensional solid models to metallic parts was investigated. The experimental results showed that the main advantage of RPC was not only its ability to cast higher internal quality and more accurate complex thin-walled aluminum alloy parts, but also the greatly-reduced lead time cycle from Selective Laser Sintering (SLS) plastic prototyping to metallic parts. The key forming technology of RPC for complex thin-walled metallic parts has been developed for new casting production and Rapid Tooling (RT), and it is possible to rapidly manufacture high-quality and accurate metallic parts by means of RP in foundry industry.
基金National Natural Science Foundation of China(52265056)Lanzhou Youth Talent Project(2023-QN-38)Hongliu Youth Fund of Lanzhou University of Technology(07/062004)。
文摘Preparation method of magnetic nanoparticles with core-shell structure was introduced,especially focusing on the preparation principle of sol-gel method,microemulsion method,and self-assembly technique.The application of core-shell nanoparticles in precision machining was discussed.The Fe_(3)O_(4)@SiO_(2)composite particles were prepared by sol-gel method and were applied to the magnetorheological polishing of titanium alloy plates.Results show that core-shell nanoparticles with higher surface quality can be obtained after processing,compared with those after conventional abrasives.After polishing for 20 min,the surface roughness of the workpiece reaches 23 nm and the scratches are effectively reduced.Finally,the preparation and application of coreshell nanoparticles are summarized and prospected to provide a reference for further research on core-shell nanoparticles.
基金supported by grants from the Beijing Hospitals Authority Youth Program (12022B4010)BTCH Young Talent En-lightenment Program (2024QMRC24)CAMS Innovation Fund for Medical Sciences (2019-I2M-5–056)。
文摘Extracorporeal liver surgery(ELS), also known as liver autotransplantation, is a hybrid(cross-fertilized) surgery incorporating the technical knowledge from extreme liver and transplant liver surgeries, and recently became more embraced and popularized among leading centers. ELS could be summarized into three major categories, namely, ex-situ liver resection and autotransplantation(ELRA), ante-situm liver resection and autotransplantation(ALRA) and auxiliary partial liver autotransplantation(APLA). The successful development of ELS during the past 37 years is definitely inseparable from continuous effort s done by Chinese surgeons and researchers. Especially, the precision liver surgery paradigm has allowed to transform ELS into a modularized, more simplified, and standardized surgery, to upgrade surgical skills, to improve peri-operative outcome and long-term survival, to increase the capability of surgeons to select more complex diseases and to expand the level of medical service to the population. This review highlights the Chinese contributions to the field of ELS, focusing thereby on features of different surgical types, technical innovations, disease selection and surgical indication, patient prognosis and future perspectives.
文摘In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper“From digits towards digitization:the past,present,and future of traditional Chinese medicine”by Academician&TCM National Master Qi WANG(王琦).
基金Supported by the Natural Science Foundation of Jilin Province,No.YDZJ202401182ZYTSJilin Provincial Key Laboratory of Precision Infectious Diseases,No.20200601011JCJilin Provincial Engineering Laboratory of Precision Prevention and Control for Common Diseases,Jilin Province Development and Reform Commission,No.2022C036.
文摘Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,radiomics,and multimodal data integration,AI has achieved diagnostic parity with expert cli-nicians in endoscopic image analysis(e.g.,early gastric cancer detection,colorectal polyp identification)and non-invasive assessment of liver pathologies(e.g.,fibrosis staging,fatty liver typing)while demonstrating utility in personalized care scenarios such as predicting hepatocellular carcinoma recurrence and opti-mizing inflammatory bowel disease treatment responses.Despite these advance-ments challenges persist including limited model generalization due to frag-mented datasets,algorithmic limitations in rare conditions(e.g.,pediatric liver diseases)caused by insufficient training data,and unresolved ethical issues related to bias,accountability,and patient privacy.Mitigation strategies involve constructing standardized multicenter databases,validating AI tools through prospective trials,leveraging federated learning to address data scarcity,and de-veloping interpretable systems(e.g.,attention heatmap visualization)to enhance clinical trust.Integrating generative AI,digital twin technologies,and establishing unified ethical/regulatory frameworks will accelerate AI adoption in primary care and foster equitable healthcare access while interdisciplinary collaboration and evidence-based implementation remain critical for realizing AI’s potential to redefine precision care for digestive disorders,improve global health outcomes,and reshape healthcare equity.
基金supported by the Chinese Academy of Medical Sciences(Grant No.2021RU002)Beijing Natural Science Foundation(Grant No.Z240013)+2 种基金National Natural Science Foundation of China(Grant Nos.82450111,82388102,82373416,and 92259303)Beijing Research Ward Excellence Program(Grant Nos.BRWEP2024W034080200 and BRWEP2024W034080204)Peking University People’s Hospital Research and Development Funds(Grant No.RZG2024-02).
文摘Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models.Organoids preserve the complex tissue architecture and cellular diversity of human cancers,enabling more accurate predictions of tumor growth,metastasis,and drug responses.Integration with microfluidic platforms,such as organ-on-a-chip systems,further enhances the ability to model tumor-environment interactions in real-time.Organoids facilitate in-depth exploration of tumor heterogeneity,molecular mechanisms,and the development of personalized treatment strategies when coupled with multi-omics technologies.Organoids provide a platform for investigating tumor-immune cell interactions,which aid in the design and testing of immune-based therapies and vaccines.Taken together,these features position organoids as a transformative tool in advancing cancer research and precision medicine.
文摘Artificial intelligence(AI)and machine learning(ML)are transforming spine care by addressing diagnostics,treatment planning,and rehabilitation challenges.This study highlights advancements in precision medicine for spinal pathologies,leveraging AI and ML to enhance diagnostic accuracy through deep learning algorithms,enabling faster and more accurate detection of abnormalities.AIpowered robotics and surgical navigation systems improve implant placement precision and reduce complications in complex spine surgeries.Wearable devices and virtual platforms,designed with AI,offer personalized,adaptive therapies that improve treatment adherence and recovery outcomes.AI also enables preventive interventions by assessing spine condition risks early.Despite progress,challenges remain,including limited healthcare datasets,algorithmic biases,ethical concerns,and integration into existing systems.Interdisciplinary collaboration and explainable AI frameworks are essential to unlock AI’s full potential in spine care.Future developments include multimodal AI systems integrating imaging,clinical,and genetic data for holistic treatment approaches.AI and ML promise significant improvements in diagnostic accuracy,treatment personalization,service accessibility,and cost efficiency,paving the way for more streamlined and effective spine care,ultimately enhancing patient outcomes.
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
文摘Nanotechnology in cancer therapy has significantly advanced treatment precision,effectiveness,and safety,improving patient outcomes and personalized care.Engineered smart nanoparticles and cell-based therapies are designed to target tumor cells,precisely sensing the tumor microenvironment(TME)and sparing normal cells.These nanoparticles enhance drug accumulation in tumors by solubilizing insoluble compounds or preventing their degradation,and they can also overcome therapy resistance and deliver multiple drugs simultaneously.Despite these benefits,challenges remain in patient-specific responses and regulatory approvals for cell-based or nanoparticle therapies.Cell-based drug delivery systems(DDSs)that primarily utilize the immune-recognition principle between ligands and receptors have shown promise in selectively targeting and destroying cancer cells.This review aims to provide a comprehensive overview of various nanoparticle and cell-based drug delivery system types used in cancer research.It covers approved and experimental nanoparticle therapies,including liposomes,micelles,protein-based and polymeric nanoparticles,as well as cell-based DDSs like macrophages,T-lymphocytes,dendritic cells,viruses,bacterial ghosts,minicells,SimCells,and outer membrane vesicles(OMVs).The review also explains the role of TME and its impact on developing smart DDSs in combination therapies and integrating nanoparticles with cell-based systems for targeting cancer cells.By detailing DDSs at different stages of development,from laboratory research to clinical trials and approved treatments,this review provides the latest insights and a collection of valuable citations of the innovative strategies that can be improved for the precise treatment of cancer.
基金supported by the National Natural Science Foundation of China(42274039)Shaanxi Provincial Innovation Capacity Support Plan Project(2023KJXX-050)+2 种基金The Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B18)Scientific and technological research projects for major issues in military medicine and aviation medicine(2022ZZXM012)Local special scientific research plan project of Shaanxi Provincial Department of Education(22JE012)。
文摘Zenith Tropospheric Delay(ZTD)is an important factor that restricts the high-precision positioning of global navigation satellite system(GNSS),and it is of great significance in establishing a real-time and highprecision ZTD model.However,existing ZTD models only consider the impact of linear terms on ZTD estimation,whereas the nonlinear factors have rarely been investigated before and thus become the focus of this study.A real-time and high-precision ZTD model for large height difference area is proposed by considering the linear and nonlinear characteristics of ZTD spatiotemporal variations and is called the realtime linear and nonlinearity ZTD(RLNZ)model.This model uses the ZTD estimated from the Global Pressure and Temperature 3(GPT3)model as the initial value.The linear impacts of periodic term and height on the estimation of ZTD difference between GNSS and GPT3 model are first considered.In addition,nonlinear factors such as geographical location and time are further used to fit the remaining nonlinear ZTD residuals using the general regression neural network method.Finally,the RLNZ-derived ZTD is obtained at an arbitrary location.The western United States,with height difference ranging from-500 to 4000 m,is selected,and the hourly ZTD of 484 GNSS stations provided by the Nevada Geodetic Laboratory(NGL)and the data of 9 radiosonde(RS)stations in the year 2021 are used.Experiment results show that a better performance of ZTD estimation can be retrieved from the proposed RLNZ model when compared with the GPT3 model.Statistical results show the averaged root mean square(RMS),Bias,and mean absolute error(MAE)of ZTD from GPT3 and RLNZ models are 33.7/0.8/25.7 mm and 22.6/0.1/17.4 mm,respectively.The average improvement rate of the RLNZ model is 33% when compared to the GPT3 model.Finally,the application of the proposed RLNZ model in simulated real-time Precise Point Positioning(PPP)indicates that the accuracy of PPP in N,E and U components is improved by 8%,2%,and 6% when compared with that from the GPT3-based PPP.Meanwhile,the convergence time in N and U components is improved by 23% and 7%,respectively.Such results verify the superiority of the proposed RLNZ model in retrieving realtime ZTD maps for GNSS positioning and navigation applications.
文摘For special-shaped parts, the clamping and processing are very difficult. Based on this, a part with high precision and special shape is selected as a case. In-depth analysis of its structure and accuracy, scientific and reasonable formulation of the processing technology, at the same time, the complete involvement of special tooling and fixtures, so as to ensure the simplification of parts processing, and thus ensure the processing progress. At the same time, in order to effectively control the quality based on the accuracy and shape requirements of the parts themselves, if ordinary inspection equipment is applied, the purpose of inspection cannot be achieved. Therefore, according to the actual situation, special inspection tools should be designed to ensure the reliability and efficiency of the inspection. Based on this, this paper mainly analyzes and discusses the NC machining process analysis and testing of precision special-shaped parts.
基金supported by grants from the Natural Science Foundation of Shandong Province(Grant No.ZR2024QH058).
文摘In the era of precision medicine,the breast cancer surgical treatment field is gradually moving toward a de-escalation model.Through precise preoperative assessments and multidisciplinary decision-making,surgical trauma can be decreased,and patients’quality of life can be improved by ensuring safety.Herein,we explore the axillary de-escalation surgery model for breast cancer.
文摘Lynch syndrome(LS)is the most common hereditary colorectal cancer(CRC)predisposition syndrome,characterized by a high mutational burden and microsatellite instability-high(MSI-H)tumors.Immunology of LS-associated CRC(LS-CRC)is unique,with significant implications for treatment.Despite well-established knowledge of LS immunology,immunotherapy dose and treatment response can vary significantly based on local tumor immunity and specific germline pathogenic variant of LS genes.This variability necessitates tailored surveillance strategies and new personalised immunotherapy approaches for LS patients.LS-CRC often benefits from immunotherapy due to the distinct tumor microenvironment(TME)and the variety of tumor infiltrating lymphocytes(TILs).This perspective discusses a novel approach of analysing spatial TILs at a single-cell level using tumor whole slide images(WSIs)that accounts for the distinct TME of LS-CRC.By emphasizing the necessity of personalized medicine in hereditary cancer syndromes,the future research and clinical practices that enhance patient outcomes through precision oncology is inspired.
基金funded by the Tianfu Emei Plan(a talent program of Sichuan Province,China),awarded to Huilian Che。
文摘Approximately 2.5%of the global population experience allergic reactions to seafood,making it one of the most prevalent and life-threatening allergies.Seafood allergy can lead to the disruption of the intestinal barrier,possibly due to aberrant intestinal glycosylation.In this study,the mechanisms underlying seafood allergy were explored through the lens of intestinal glycobiology.Mice were sensitized with tropomyosin,resulting in significant increases in allergy symptom scores,specific antibody and T helper 2 cytokine levels.Intestinal damage was confirmed by histopathology,as well as by assessments and levels of diamine oxidase and claudin-1.Moreover,alterations in glycosylated proteins within the jejunum were analyzed using highthroughput mass spectrometry and the pGlyco3.0 search engine.Precision N-glycoproteomics analysis yielded 2283 glycosylation peptides corresponding to 655 unique glycosylation sites on 399 proteins.Differential expression and enrichment analyses revealed that differentially expressed glycoproteins were significantly enriched in the extracellular matrix(ECM)-receptor interaction pathway and focal adhesion pathway.In conclusion,tropomyosin sensitization leads to intestinal glycome changes,accompanied by remodeling of the intestinal ECM.Our research establishes an essential theoretical basis for targeting the intestinal glycome and ECM remodeling in a precise and fine-tuned manner for the treatment of food allergies.
文摘Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria still grapples with wide acceptance,key translational research and implementation of PM.This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.Methods:A cross‐sectional study was conducted in selected tertiary hospitals across the country.A 21‐item semi‐structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25.Descriptive statistics were used to summarize the data.A chi‐square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.Results:A total of 167 hospital pharmacists participated in the study.A high proportion of the participants are familiar with artificial intelligence(91.75%),Pharmacogenomics(84.5%),and precision medicine(61%).Overall,38.9%of the pharmacists had a good knowledge while 13.2%had a poor knowledge of PM and associated terms.The level of knowledge did not correlate significantly with gender(X^(2)=3.21,p=0.201),age(X^(2)=5,p=0.27),marital status(X^(2)=3.21,p=0.201),and professional level(X^(2)=6.85,p=0.144).The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine(49%)while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.Conclusions:There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria.Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM.Also,more research aimed at translating PM knowledge into clinical practice is recommended.
基金supported by grants from the National Natural Science Foundation of China(Grant Nos.82103614 and 32171363)Natural Science Foundation of Fujian Province of China(Grant No.2021J05007)+4 种基金funding from the start-up fund for Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast CancerXiamen’s Key Laboratory of Precision Medicine for Endocrine-Related Cancersstart-up and supporting funds from the Third Affiliated Hospital of Kunming Medical University,Yunnan Cancer Hospital for Guo-Jun Zhang and Jing-Wen BaiKey Research and development program for social development of Yunnan Science and Technology Department(Grant No.202403AC100014-2)horizontal project funding from the Third Affiliated Hospital of Kunming Medical University(Grant Nos.20233160A0866 and 20243160A0511)。
文摘The management of breast cancer,one of the most common and heterogeneous malignancies,has transformed with the advent of precision medicine.This review explores current developments in genetic profiling,molecular diagnostics,and targeted therapies that have revolutionized breast cancer treatment.Key innovations,such as cyclin-dependent kinases 4/6(CDK4/6)inhibitors,antibodydrug conjugates(ADCs),and immune checkpoint inhibitors(ICIs),have improved outcomes for hormone receptor-positive(HR+),HER2-positive(HER2+),and triple-negative breast cancer(TNBC)subtypes remarkably.Additionally,emerging treatments,such as PI3K inhibitors,poly(ADP-ribose)polymerase(PARP)inhibitors,and m RNA-based therapies,offer new avenues for targeting specific genetic mutations and improving treatment response,particularly in difficult-to-treat breast cancer subtypes.The integration of liquid biopsy technologies provides a non-invasive approach for real-time monitoring of tumor evolution and treatment response,thus enabling dynamic adjustments to therapy.Molecular imaging and artificial intelligence(AI)are increasingly crucial in enhancing diagnostic precision,personalizing treatment plans,and predicting therapeutic outcomes.As precision medicine continues to evolve,it has the potential to significantly improve survival rates,decrease recurrence,and enhance quality of life for patients with breast cancer.By combining cutting-edge diagnostics,personalized therapies,and emerging treatments,precision medicine can transform breast cancer care by offering more effective,individualized,and less invasive treatment options.
