This paper studies consensus problems in weighted scale-free networks of asymmetrically coupled dynamical units, where the asymmetry in a given link is deter：mined by the relative degree of the involved nodes. It sho...This paper studies consensus problems in weighted scale-free networks of asymmetrically coupled dynamical units, where the asymmetry in a given link is deter：mined by the relative degree of the involved nodes. It shows that the asymmetry of interactions has a great effect on the consensus. Especially, when the interactions are dominant from higher- to lower-degree nodes, both the convergence speed and the robustness to communication delay are enhanced.展开更多
The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from com...The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from complex certificate management,inefficient consensus protocols,and poor resilience in high-frequency communication,resulting in high latency,poor scalability,and unstable network performance.To address these issues,this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9.First,this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9,enabling lightweight authentication and key negotiation,thereby reducing the complexity of key management.To ensure the traceability and global consistency of authentication data,this scheme also integrates blockchain technology,applying its inherent invariance.Then,this paper introduces a reputation-driven dynamic node grouping mechanism that transparently evaluates and groups’node behavior using smart contracts to enhance network stability.Furthermore,a new RBSFT(Reputation-Based SM9 Friendly-Tolerant)consensus mechanism is proposed for the first time to enhance consensus efficiency by optimizing the PBFT algorithm.RBSFT aims to write authentication information into the blockchain ledger to achieve multi-level optimization of trust management and decision-making efficiency,thereby significantly improving the responsiveness and robustness in high-frequency IoV scenarios.Experimental results show that it excels in authentication,communication efficiency,and computational cost control,making it a feasible solution for achieving IoV security and real-time performance.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
Colorectal cancer(CRC)is one of the most molecularly heterogeneous malignancies,with complexity that extends far beyond traditional histopathological classifications.The consensus molecular subtypes(CMS)established in...Colorectal cancer(CRC)is one of the most molecularly heterogeneous malignancies,with complexity that extends far beyond traditional histopathological classifications.The consensus molecular subtypes(CMS)established in 2015 brought a marked advancement in the taxonomy of CRC,consolidating six classification systems into four novel subtypes,which focus on vital gene expression patterns and clinical and prognostic outcomes.However,nearly a decade of clinical experience with CMS classification has revealed fundamental limitations that underscore the inadequacy of any single classification system for capturing the full spectrum of CRC biology.The inherent challenges of the current paradigm are multifaceted.In the CMS classification,mixed phenotypes that remain unclassifiable constitute 13%of CRC cases.This reflects the remarkable heterogeneity that CRC shows.The tumor budding regions reflect the molecular shift due to CMS 2 to CMS 4 switching,causing further heterogeneity.Moreover,the reliance on bulk RNA sequencing fails to capture the spatial organization of molecular signatures within tumors and the critical contributions of the tumor microenvironment.Recent technological advances in spatial transcriptomics,singlecell RNA sequencing,and multi-omic integration have revealed the limitations of transcriptome-only classifications.The emergence of CRC intrinsic subtypes that attempt to remove microenvironmental contributions,pathway-derived subtypes,and stem cell-based classifications demonstrates the field’s recognition that multiple complementary classification systems are necessary.These newer molecular subtypes are not discrete categories but biological continua,thus highlighting that the vast molecular landscape is a tapestry of interlinked features,not rigid subtypes.Multiple technical hurdles cause difficulty in implementing the clinical translation of these newer molecular subtypes,including gene signature complexity,platform-dependent variations,and the difficulty of getting and preserving fresh frozen tissue.CMS 4 shows a poor prognostic outcome among the CMS subtypes,while CMS 1 is associated with poor survival in metastatic cases.However,the predictive value for definitive therapy remains subdued.Looking forward,the integration of artificial intelligence,liquid biopsy approaches,and real-time molecular monitoring promises to enable dynamic,multi-dimensional tumor characterization.The temporal and spatial complexity can only be captured by complementary molecular taxonomies rather than a single,unified system of CRC classification.Such an approach recognizes that different clinical questions–prognosis,treatment selection,resistance prediction–may require different molecular lenses,each optimized for specific clinical applications.This editorial advocates for a revolutionary change from pursuing a single“best”classification system toward a diverse approach that welcomes the molecular mosaic of CRC.Only through such comprehensive molecular characterization can we hope to achieve the promise of precision oncology for the diverse spectrum of patients with CRC.展开更多
Objective:To characterize placental morphologic features in Moroccan women with adverse outcomes,across different clinical contexts,based on the Amsterdam consensus classification.Methods:A prospective analysis was co...Objective:To characterize placental morphologic features in Moroccan women with adverse outcomes,across different clinical contexts,based on the Amsterdam consensus classification.Methods:A prospective analysis was conducted on placentas with umbilical cords collected fresh between March 1,2024 and July 15,2024 from women with adverse pregnancy outcomes.Clinical data(age,parity,gravidity,complications)were retrieved.Macroscopic parameters(weight,dimensions,cord insertion,membranes,lesions)were assessed,followed by systematic sampling.Tissue was processed by standard histology(formalin fixation,paraffin embedding,hematoxylin and eosin staining),and lesions were classified per Amsterdam criteria.Results:16 placentas from patients with adverse pregnancy outcomes were included.The median maternal age was 30 years.Adverse conditions included placental abruption(50%),intrauterine growth restriction(IUGR,38%),intrauterine fetal death(IUFD,31%),pre-eclampsia/eclampsia(19%),premature rupture of membranes(13%),and oligohydramnios(13%).Several placentas were associated with more than one adverse condition.Histopathology revealed maternal vascular malperfusion lesions in 94%,particularly in pre-eclampsia,IUGR,and IUFD.Fetal vascular malperfusion was found in 88%,mainly in IUGR and IUFD.Inflammatory lesions,dominated by acute maternal and fetal responses stage 3(necrotizing chorioamnionitis and funisitis),were primarily linked to IUFD.Conclusions:Placental examination enhances understanding of the pathophysiology underlying adverse pregnancy outcomes,supports diagnostic confirmation,and guides preventive strategies for recurrence.This study highlights the prevalence of maternal vascular malperfusion in Moroccan women and emphasizes the importance of systematic placental histopathology in obstetric care.展开更多
Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.You...Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.展开更多
Kidney transplantation(KT)accounts for nearly three-fourths of organ transplants in India,with living donors contributing to 82%of cases.Induction immunosuppression is essential to optimize initial immunosuppression,r...Kidney transplantation(KT)accounts for nearly three-fourths of organ transplants in India,with living donors contributing to 82%of cases.Induction immunosuppression is essential to optimize initial immunosuppression,reduce acute rejections,and enable tailored use of maintenance agents.Rabbit anti-thymocyte globulin(rATG)and interleukin-2 receptor anatagonists(IL-2RA/IL-2RBs)are the most widely used induction therapies.However,data on induction practices across India are limited.To evaluate induction immunosuppression practices across KT centers in India and establish a consensus for different subsets of KT recipients.A nationwide online survey was conducted by the Indian Society of Organ Transplantation(ISOT)among its members(400 KT centers).Responses were analyzed to assess induction practices across diverse donor types,age groups,and immunological risk profiles.Heterogeneity in practices prompted consensus building using a modified Delphi process.Literature review and expert panel discussions(April 2024)were followed by structured voting,and 16 consensus statements were finalized.Of 400 centers approached,254 participated.rATG was the most commonly used induction therapy,followed by IL-2RBs;alemtuzumab was least used.Significant heterogeneity was observed in type,dose,and duration of induction therapy.Consensus recommendations were framed:rATG for high immunological risk recipients and deceased donor KTs;IL-2RB or low-dose rATG for low immunological risk;rituximab in ABOincompatible KTs;and tailoring based on age,diabetes,donor type,infection risk,and affordability.This first ISOT consensus provides 16 India-specific statements on induction therapy in KT.It emphasizes risk-stratified,evidenceinformed,and context-appropriate induction strategies,supporting standardization of care across the country.展开更多
The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three ...The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.展开更多
Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination...Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.展开更多
Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privac...Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.展开更多
The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and ...The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services.However,this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats.Consequently,innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed.Recently,the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions,commonly referred to as the Internet of Blockchained Things(IoBT).Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments.Within this context,consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems.The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential.This paper presents a comprehensive examination of lightweight,constraint-aware consensus algorithms tailored for IoBT.The study categorizes these consensus mechanisms based on their core operations,the security of the block validation process,the incorporation of AI techniques,and the specific applications they are designed to support.展开更多
Cooperative guidance is a method for achieving combat objectives through information sharing and cooperative effects,and has emerged as a significant research area in the fields of missile guidance and systematic warf...Cooperative guidance is a method for achieving combat objectives through information sharing and cooperative effects,and has emerged as a significant research area in the fields of missile guidance and systematic warfare.This study presents a systematic review and analysis of current research on cooperative guidance.First,a bibliometric analysis is conducted on 513 articles using the Scopus database and CiteSpace software to assess keyword clustering,keyword cooccurrence,and keyword burst,and to later visualize the results.Second,fundamental theories of cooperative guidance,including relative motion modeling methods,algebraic graph theory,and multi-agent consensus theory,are summarized.Subsequently,an overview of current cooperative laws and corresponding analysis methods is provided,with categorization based on the cooperative structure and convergence performance.Finally,we summarize current research developments based on five perspectives and propose a developmental framework based on five layers(cyber,physical,decision,information,and system),discussing potential future advancements in cooperative terminal guidance.This framework emphasizes five key areas of research:networked,heterogeneous,integrated,intelligent,and group cooperations,with the goal of offering trends and insights for futurework.展开更多
Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for ...Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for stakeholders and the entire community.Aims This study aims to establish a multidisciplinary consensus of principles for ethical governance of clinical BCI research for mental disorders and offer practical ethical guidance to stakeholders involved.Methods A systematic literature review,symposium and roundtable discussions,and a pre-Delphi(round 0)survey were conducted to form the questionnaire for the three-round modified Delphi study.Two rounds of surveys,followed by a third round of independent interviews of 25 experts from BCI-related research domains,were involved.We conducted quantitative analysis of responses and agreements among experts to reveal the consensus and differences regarding the ethical governance of mental BCI research from a multidisciplinary perspective.Results The Delphi panel emphasised important concerns of ethical review practices and ethical principles within the BCI context,identified qualified and highly influential institutions and personnel in conducting and advancing clinical BCI research,and recognised prioritised aspects in the risk-benefit evaluation.Experts expressed diverse opinions on specific ethical concerns,including concerns about invasive technology,its impact on humanity and potential social consequences.Agreement was reached that the practices of ethical governance of clinical BCI for mental disorders should focus on patient voluntariness,autonomy,long-term effects and related assessments of BCI interventions,as well as privacy protection,transparent reporting and ensuring that the research is conducted in qualified institutions with strong data security.Conclusions Ethical governance of clinical research on BCI for mental disorders should include interdisciplinary experts to balance various needs and incorporate the expertise of different stakeholders to avoid serious ethical issues.It requires scientifically grounded approaches,continuous monitoring and interdisciplinary collaboration to ensure evidence-based policies,comprehensive risk assessments and transparency,thereby promoting responsible innovations and protecting patient rights and well-being.展开更多
Establishing Consensus with Users of Research Irradiator Devices to Facilitate Source Type Replacement Danette R.Fennesy1,Janet M.Gutiérrez1,2,Scott J.Patlovich1,Robert J.Emery1(1.The University of Texas Health S...Establishing Consensus with Users of Research Irradiator Devices to Facilitate Source Type Replacement Danette R.Fennesy1,Janet M.Gutiérrez1,2,Scott J.Patlovich1,Robert J.Emery1(1.The University of Texas Health Science Center at Houston,Environmental Health&Safety,6431 Fannin St,CYF G.102,Houston,TX,77030;2.Corresponding author)Abstract:The ability to irradiate cells,tissues,and other biological materials with high-energy photons has been an essential tool in the discovery of numerous biomedical research advancements.展开更多
Dear Editor,This letter studies output consensus problem of heterogeneous linear multiagent systems over directed graphs. A novel adaptive dynamic event-triggered controller is presented based only on the feedback com...Dear Editor,This letter studies output consensus problem of heterogeneous linear multiagent systems over directed graphs. A novel adaptive dynamic event-triggered controller is presented based only on the feedback combination of the agent's own state and neighbors' output,which can achieve exponential output consensus through intermittent communication. The controller is obtained by solving two linear matrix equations, and Zeno behavior is excluded.展开更多
Dear Editor,This letter studies the bipartite consensus tracking problem for heterogeneous multi-agent systems with actuator faults and a leader's unknown time-varying control input. To handle such a problem, the ...Dear Editor,This letter studies the bipartite consensus tracking problem for heterogeneous multi-agent systems with actuator faults and a leader's unknown time-varying control input. To handle such a problem, the continuous fault-tolerant control protocol via observer design is developed. In addition, it is strictly proved that the multi-agent system driven by the designed controllers can still achieve bipartite consensus tracking after faults occur.展开更多
Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol ...Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).展开更多
This paper mainly focuses on the velocity-constrained consensus problem of discrete-time heterogeneous multi-agent systems with nonconvex constraints and arbitrarily switching topologies,where each agent has first-ord...This paper mainly focuses on the velocity-constrained consensus problem of discrete-time heterogeneous multi-agent systems with nonconvex constraints and arbitrarily switching topologies,where each agent has first-order or second-order dynamics.To solve this problem,a distributed algorithm is proposed based on a contraction operator.By employing the properties of the stochastic matrix,it is shown that all agents’position states could converge to a common point and second-order agents’velocity states could remain in corresponding nonconvex constraint sets and converge to zero as long as the joint communication topology has one directed spanning tree.Finally,the numerical simulation results are provided to verify the effectiveness of the proposed algorithms.展开更多
Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has bee...Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has been advocated for decentralized data management in a tamper-resistance,traceable,and transparent manner.However,a major issue that hinders the integration of blockchain and IoT lies in that,it is rather challenging for resource-constrained IoT devices to perform computation-intensive blockchain consensuses such as Proof-of-Work(PoW).Furthermore,the incentive mechanism of PoW pushes lightweight IoT nodes to aggregate their computing power to increase the possibility of successful block generation.Nevertheless,this eventually leads to the formation of computing power alliances,and significantly compromises the decentralization and security of BlockChain-aided IoT(BC-IoT)networks.To cope with these issues,we propose a lightweight consensus protocol for BC-IoT,called Proof-of-Trusted-Work(PoTW).The goal of the proposed consensus is to disincentivize the centralization of computing power and encourage the independent participation of lightweight IoT nodes in blockchain consensus.First,we put forth an on-chain reputation evaluation rule and a reputation chain for PoTW to enable the verifiability and traceability of nodes’reputations based on their contributions of computing power to the blockchain consensus,and we incorporate the multi-level block generation difficulty as a rewards for nodes to accumulate reputations.Second,we model the block generation process of PoTW and analyze the block throughput using the continuous time Markov chain.Additionally,we define and optimize the relative throughput gain to quantify and maximize the capability of PoTW that suppresses the computing power centralization(i.e.,centralization suppression).Furthermore,we investigate the impact of the computing power of the computing power alliance and the levels of block generation difficulty on the centralization suppression capability of PoTW.Finally,simulation results demonstrate the consistency of the analytical results in terms of block throughput.In particular,the results show that PoTW effectively reduces the block generation proportion of the computing power alliance compared with PoW,while simultaneously improving that of individual lightweight nodes.This indicates that PoTW is capable of suppressing the centralization of computing power to a certain degree.Moreover,as the levels of block generation difficulty in PoTW increase,its centralization suppression capability strengthens.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos 10775060 and 10805033)the Doctoral Education Foundation of National Education Committeethe Natural Science Foundation of Gansu Province
文摘This paper studies consensus problems in weighted scale-free networks of asymmetrically coupled dynamical units, where the asymmetry in a given link is deter：mined by the relative degree of the involved nodes. It shows that the asymmetry of interactions has a great effect on the consensus. Especially, when the interactions are dominant from higher- to lower-degree nodes, both the convergence speed and the robustness to communication delay are enhanced.
基金supported by the National Natural Science Foundation of China(Grant No.61762071,Grant No.61163025).
文摘The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from complex certificate management,inefficient consensus protocols,and poor resilience in high-frequency communication,resulting in high latency,poor scalability,and unstable network performance.To address these issues,this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9.First,this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9,enabling lightweight authentication and key negotiation,thereby reducing the complexity of key management.To ensure the traceability and global consistency of authentication data,this scheme also integrates blockchain technology,applying its inherent invariance.Then,this paper introduces a reputation-driven dynamic node grouping mechanism that transparently evaluates and groups’node behavior using smart contracts to enhance network stability.Furthermore,a new RBSFT(Reputation-Based SM9 Friendly-Tolerant)consensus mechanism is proposed for the first time to enhance consensus efficiency by optimizing the PBFT algorithm.RBSFT aims to write authentication information into the blockchain ledger to achieve multi-level optimization of trust management and decision-making efficiency,thereby significantly improving the responsiveness and robustness in high-frequency IoV scenarios.Experimental results show that it excels in authentication,communication efficiency,and computational cost control,making it a feasible solution for achieving IoV security and real-time performance.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
文摘Colorectal cancer(CRC)is one of the most molecularly heterogeneous malignancies,with complexity that extends far beyond traditional histopathological classifications.The consensus molecular subtypes(CMS)established in 2015 brought a marked advancement in the taxonomy of CRC,consolidating six classification systems into four novel subtypes,which focus on vital gene expression patterns and clinical and prognostic outcomes.However,nearly a decade of clinical experience with CMS classification has revealed fundamental limitations that underscore the inadequacy of any single classification system for capturing the full spectrum of CRC biology.The inherent challenges of the current paradigm are multifaceted.In the CMS classification,mixed phenotypes that remain unclassifiable constitute 13%of CRC cases.This reflects the remarkable heterogeneity that CRC shows.The tumor budding regions reflect the molecular shift due to CMS 2 to CMS 4 switching,causing further heterogeneity.Moreover,the reliance on bulk RNA sequencing fails to capture the spatial organization of molecular signatures within tumors and the critical contributions of the tumor microenvironment.Recent technological advances in spatial transcriptomics,singlecell RNA sequencing,and multi-omic integration have revealed the limitations of transcriptome-only classifications.The emergence of CRC intrinsic subtypes that attempt to remove microenvironmental contributions,pathway-derived subtypes,and stem cell-based classifications demonstrates the field’s recognition that multiple complementary classification systems are necessary.These newer molecular subtypes are not discrete categories but biological continua,thus highlighting that the vast molecular landscape is a tapestry of interlinked features,not rigid subtypes.Multiple technical hurdles cause difficulty in implementing the clinical translation of these newer molecular subtypes,including gene signature complexity,platform-dependent variations,and the difficulty of getting and preserving fresh frozen tissue.CMS 4 shows a poor prognostic outcome among the CMS subtypes,while CMS 1 is associated with poor survival in metastatic cases.However,the predictive value for definitive therapy remains subdued.Looking forward,the integration of artificial intelligence,liquid biopsy approaches,and real-time molecular monitoring promises to enable dynamic,multi-dimensional tumor characterization.The temporal and spatial complexity can only be captured by complementary molecular taxonomies rather than a single,unified system of CRC classification.Such an approach recognizes that different clinical questions–prognosis,treatment selection,resistance prediction–may require different molecular lenses,each optimized for specific clinical applications.This editorial advocates for a revolutionary change from pursuing a single“best”classification system toward a diverse approach that welcomes the molecular mosaic of CRC.Only through such comprehensive molecular characterization can we hope to achieve the promise of precision oncology for the diverse spectrum of patients with CRC.
文摘Objective:To characterize placental morphologic features in Moroccan women with adverse outcomes,across different clinical contexts,based on the Amsterdam consensus classification.Methods:A prospective analysis was conducted on placentas with umbilical cords collected fresh between March 1,2024 and July 15,2024 from women with adverse pregnancy outcomes.Clinical data(age,parity,gravidity,complications)were retrieved.Macroscopic parameters(weight,dimensions,cord insertion,membranes,lesions)were assessed,followed by systematic sampling.Tissue was processed by standard histology(formalin fixation,paraffin embedding,hematoxylin and eosin staining),and lesions were classified per Amsterdam criteria.Results:16 placentas from patients with adverse pregnancy outcomes were included.The median maternal age was 30 years.Adverse conditions included placental abruption(50%),intrauterine growth restriction(IUGR,38%),intrauterine fetal death(IUFD,31%),pre-eclampsia/eclampsia(19%),premature rupture of membranes(13%),and oligohydramnios(13%).Several placentas were associated with more than one adverse condition.Histopathology revealed maternal vascular malperfusion lesions in 94%,particularly in pre-eclampsia,IUGR,and IUFD.Fetal vascular malperfusion was found in 88%,mainly in IUGR and IUFD.Inflammatory lesions,dominated by acute maternal and fetal responses stage 3(necrotizing chorioamnionitis and funisitis),were primarily linked to IUFD.Conclusions:Placental examination enhances understanding of the pathophysiology underlying adverse pregnancy outcomes,supports diagnostic confirmation,and guides preventive strategies for recurrence.This study highlights the prevalence of maternal vascular malperfusion in Moroccan women and emphasizes the importance of systematic placental histopathology in obstetric care.
文摘Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.
文摘Kidney transplantation(KT)accounts for nearly three-fourths of organ transplants in India,with living donors contributing to 82%of cases.Induction immunosuppression is essential to optimize initial immunosuppression,reduce acute rejections,and enable tailored use of maintenance agents.Rabbit anti-thymocyte globulin(rATG)and interleukin-2 receptor anatagonists(IL-2RA/IL-2RBs)are the most widely used induction therapies.However,data on induction practices across India are limited.To evaluate induction immunosuppression practices across KT centers in India and establish a consensus for different subsets of KT recipients.A nationwide online survey was conducted by the Indian Society of Organ Transplantation(ISOT)among its members(400 KT centers).Responses were analyzed to assess induction practices across diverse donor types,age groups,and immunological risk profiles.Heterogeneity in practices prompted consensus building using a modified Delphi process.Literature review and expert panel discussions(April 2024)were followed by structured voting,and 16 consensus statements were finalized.Of 400 centers approached,254 participated.rATG was the most commonly used induction therapy,followed by IL-2RBs;alemtuzumab was least used.Significant heterogeneity was observed in type,dose,and duration of induction therapy.Consensus recommendations were framed:rATG for high immunological risk recipients and deceased donor KTs;IL-2RB or low-dose rATG for low immunological risk;rituximab in ABOincompatible KTs;and tailoring based on age,diabetes,donor type,infection risk,and affordability.This first ISOT consensus provides 16 India-specific statements on induction therapy in KT.It emphasizes risk-stratified,evidenceinformed,and context-appropriate induction strategies,supporting standardization of care across the country.
基金supported by the National Medical Products Administration Commissioned Research Project (No.20211440216)the National Administration of Traditional Chinese Medicine Science and Technology Project (No.GZY-KJS-2024-03)+3 种基金the State Key Laboratory of Drug Regulatory Science Project (No.2023SKLDRS0104)the Basic Research Program Natural Science Fund-Frontier Leading Technology Basic Research Special Project of Jiangsu Province (No.BK20232014)the Programs Foundation for Leading Talents in National Administration of Traditional Chinese Medicine of China“Qihuang scholars”Projectthe Tianjin Administration for Market Regulation Science and Technology Key Projects (No.2022-W35)。
文摘The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.
基金supports by the National Natural Science Foundation of China(Nos.82201135)"2015"Cultivation Program for Reserve Talents for Academic Leaders of Nanjing Stomatological School,Medical School of Nanjing University(No.0223A204).
文摘Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.
文摘Distributed Federated Learning(DFL)technology enables participants to cooperatively train a shared model while preserving the privacy of their local datasets,making it a desirable solution for decentralized and privacy-preserving Web3 scenarios.However,DFL faces incentive and security challenges in the decentralized framework.To address these issues,this paper presents a Hierarchical Blockchain-enabled DFL(HBDFL)system,which provides a generic solution framework for the DFL-related applications.The proposed system consists of four major components,including a model contribution-based reward mechanism,a Proof of Elapsed Time and Accuracy(PoETA)consensus algorithm,a Distributed Reputation-based Verification Mechanism(DRTM)and an Accuracy-Dependent Throughput Management(ADTM)mechanism.The model contribution-based rewarding mechanism incentivizes network nodes to train models with their local datasets,while the PoETA consensus algorithm optimizes the tradeoff between the shared model accuracy and system throughput.The DRTM improves the system efficiency in consensus,and the ADTM mechanism guarantees that the throughput performance remains within a predefined range while improving the shared model accuracy.The performance of the proposed HBDFL system is evaluated by numerical simulations,with the results showing that the system improves the accuracy of the shared model while maintaining high throughput and ensuring security.
文摘The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services.However,this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats.Consequently,innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed.Recently,the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions,commonly referred to as the Internet of Blockchained Things(IoBT).Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments.Within this context,consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems.The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential.This paper presents a comprehensive examination of lightweight,constraint-aware consensus algorithms tailored for IoBT.The study categorizes these consensus mechanisms based on their core operations,the security of the block validation process,the incorporation of AI techniques,and the specific applications they are designed to support.
基金supported by the National Natural Science Foundation of China(No.62173274)the National Key R&D Program of China(No.2019YFA0405300)+4 种基金the Natural Science Foundation of Hunan Province of China(Nos.2021JJ10045 and 2025JJ60072)the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-01)the Postdoctoral Fellowship Program of CPSF(No.GZB20240989)the China Postdoctoral Science Foundation(No.2024M754304)the Aeronautical Science Foundation of China(No.2023Z005030001).
文摘Cooperative guidance is a method for achieving combat objectives through information sharing and cooperative effects,and has emerged as a significant research area in the fields of missile guidance and systematic warfare.This study presents a systematic review and analysis of current research on cooperative guidance.First,a bibliometric analysis is conducted on 513 articles using the Scopus database and CiteSpace software to assess keyword clustering,keyword cooccurrence,and keyword burst,and to later visualize the results.Second,fundamental theories of cooperative guidance,including relative motion modeling methods,algebraic graph theory,and multi-agent consensus theory,are summarized.Subsequently,an overview of current cooperative laws and corresponding analysis methods is provided,with categorization based on the cooperative structure and convergence performance.Finally,we summarize current research developments based on five perspectives and propose a developmental framework based on five layers(cyber,physical,decision,information,and system),discussing potential future advancements in cooperative terminal guidance.This framework emphasizes five key areas of research:networked,heterogeneous,integrated,intelligent,and group cooperations,with the goal of offering trends and insights for futurework.
基金funded by the Shanghai Philosophy and Social Science Planning Project (2021BZX008)the National Social Science Foundation of China (23BZX110)the National Office for Philosophy and Social Science (20&ZD045).
文摘Background Clinical brain-computer interface(BCI)for mental disorders is an emerging interdisciplinary research field,posing new ethical concerns and challenges,yet lacking practical ethical governance guidelines for stakeholders and the entire community.Aims This study aims to establish a multidisciplinary consensus of principles for ethical governance of clinical BCI research for mental disorders and offer practical ethical guidance to stakeholders involved.Methods A systematic literature review,symposium and roundtable discussions,and a pre-Delphi(round 0)survey were conducted to form the questionnaire for the three-round modified Delphi study.Two rounds of surveys,followed by a third round of independent interviews of 25 experts from BCI-related research domains,were involved.We conducted quantitative analysis of responses and agreements among experts to reveal the consensus and differences regarding the ethical governance of mental BCI research from a multidisciplinary perspective.Results The Delphi panel emphasised important concerns of ethical review practices and ethical principles within the BCI context,identified qualified and highly influential institutions and personnel in conducting and advancing clinical BCI research,and recognised prioritised aspects in the risk-benefit evaluation.Experts expressed diverse opinions on specific ethical concerns,including concerns about invasive technology,its impact on humanity and potential social consequences.Agreement was reached that the practices of ethical governance of clinical BCI for mental disorders should focus on patient voluntariness,autonomy,long-term effects and related assessments of BCI interventions,as well as privacy protection,transparent reporting and ensuring that the research is conducted in qualified institutions with strong data security.Conclusions Ethical governance of clinical research on BCI for mental disorders should include interdisciplinary experts to balance various needs and incorporate the expertise of different stakeholders to avoid serious ethical issues.It requires scientifically grounded approaches,continuous monitoring and interdisciplinary collaboration to ensure evidence-based policies,comprehensive risk assessments and transparency,thereby promoting responsible innovations and protecting patient rights and well-being.
文摘Establishing Consensus with Users of Research Irradiator Devices to Facilitate Source Type Replacement Danette R.Fennesy1,Janet M.Gutiérrez1,2,Scott J.Patlovich1,Robert J.Emery1(1.The University of Texas Health Science Center at Houston,Environmental Health&Safety,6431 Fannin St,CYF G.102,Houston,TX,77030;2.Corresponding author)Abstract:The ability to irradiate cells,tissues,and other biological materials with high-energy photons has been an essential tool in the discovery of numerous biomedical research advancements.
基金supported by the National Science and Technology Innovation 2030-Major Program(2022ZD 0115403)the National Natural Science Foundation of China(61991414)+1 种基金Chongqing Natural Science Foundation(CSTB2023NSCQJQX0018)Beijing Natural Science Foundation(L221005)
文摘Dear Editor,This letter studies output consensus problem of heterogeneous linear multiagent systems over directed graphs. A novel adaptive dynamic event-triggered controller is presented based only on the feedback combination of the agent's own state and neighbors' output,which can achieve exponential output consensus through intermittent communication. The controller is obtained by solving two linear matrix equations, and Zeno behavior is excluded.
基金supported by the National Natural Science Foundation of China(62325304,U22B2046,62073079,62376029)the Jiangsu Provincial Scientific Research Center of Applied Mathematics(BK20233002)the China Postdoctoral Science Foundation(2023M730255,2024T171123)
文摘Dear Editor,This letter studies the bipartite consensus tracking problem for heterogeneous multi-agent systems with actuator faults and a leader's unknown time-varying control input. To handle such a problem, the continuous fault-tolerant control protocol via observer design is developed. In addition, it is strictly proved that the multi-agent system driven by the designed controllers can still achieve bipartite consensus tracking after faults occur.
基金supported by the National Nature Science Foundation of China(U21A20166)the Science and Technology Development Foundation of Jilin Province(20230508095RC)+2 种基金the Major Science and Technology Projects of Jilin Province and Changchun City(20220301033GX)the Development and Reform Commission Foundation of Jilin Province(2023C034-3)the Interdisciplinary Integration and Innovation Project of JLU(JLUXKJC2020202).
文摘Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).
基金2024 Jiangsu Province Youth Science and Technology Talent Support Project2024 Yancheng Key Research and Development Plan(Social Development)projects,“Research and Application of Multi Agent Offline Distributed Trust Perception Virtual Wireless Sensor Network Algorithm”and“Research and Application of a New Type of Fishery Ship Safety Production Monitoring Equipment”。
文摘This paper mainly focuses on the velocity-constrained consensus problem of discrete-time heterogeneous multi-agent systems with nonconvex constraints and arbitrarily switching topologies,where each agent has first-order or second-order dynamics.To solve this problem,a distributed algorithm is proposed based on a contraction operator.By employing the properties of the stochastic matrix,it is shown that all agents’position states could converge to a common point and second-order agents’velocity states could remain in corresponding nonconvex constraint sets and converge to zero as long as the joint communication topology has one directed spanning tree.Finally,the numerical simulation results are provided to verify the effectiveness of the proposed algorithms.
基金supported in part by National Key R&D Program of China(Grant No.2021YFB1714100)in part by the National Natural Science Foundation of China(NSFC)under Grant 62371239+5 种基金in part by the the Program of Science and Technology Cooperation of Nanjing with International/Hong Kong,Macao and Taiwan(Grant No.202401019)in part by the Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515012407)in part by the the Research Center for FinTech and Digital-Intelligent Management at Shenzhen University,in part by the National Natural Science Foundation of China under Grant 62271192in part by the Equipment Pre-Research Joint Research Program of Ministry of Education under Grant 8091B032129in part by the Major Science and Technology Projects of Longmen Laboratory under Grant 231100220300 and 231100220200in part by the Central Plains Leading Talent in Scientific and Technological Innovation Program under Grant 244200510048.
文摘Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has been advocated for decentralized data management in a tamper-resistance,traceable,and transparent manner.However,a major issue that hinders the integration of blockchain and IoT lies in that,it is rather challenging for resource-constrained IoT devices to perform computation-intensive blockchain consensuses such as Proof-of-Work(PoW).Furthermore,the incentive mechanism of PoW pushes lightweight IoT nodes to aggregate their computing power to increase the possibility of successful block generation.Nevertheless,this eventually leads to the formation of computing power alliances,and significantly compromises the decentralization and security of BlockChain-aided IoT(BC-IoT)networks.To cope with these issues,we propose a lightweight consensus protocol for BC-IoT,called Proof-of-Trusted-Work(PoTW).The goal of the proposed consensus is to disincentivize the centralization of computing power and encourage the independent participation of lightweight IoT nodes in blockchain consensus.First,we put forth an on-chain reputation evaluation rule and a reputation chain for PoTW to enable the verifiability and traceability of nodes’reputations based on their contributions of computing power to the blockchain consensus,and we incorporate the multi-level block generation difficulty as a rewards for nodes to accumulate reputations.Second,we model the block generation process of PoTW and analyze the block throughput using the continuous time Markov chain.Additionally,we define and optimize the relative throughput gain to quantify and maximize the capability of PoTW that suppresses the computing power centralization(i.e.,centralization suppression).Furthermore,we investigate the impact of the computing power of the computing power alliance and the levels of block generation difficulty on the centralization suppression capability of PoTW.Finally,simulation results demonstrate the consistency of the analytical results in terms of block throughput.In particular,the results show that PoTW effectively reduces the block generation proportion of the computing power alliance compared with PoW,while simultaneously improving that of individual lightweight nodes.This indicates that PoTW is capable of suppressing the centralization of computing power to a certain degree.Moreover,as the levels of block generation difficulty in PoTW increase,its centralization suppression capability strengthens.
