This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor gro...This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.展开更多
The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed patho...The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.展开更多
This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal disease...This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.展开更多
Metabolomics utilizes advanced analytical profiling techniques to comprehensively measure small molecules in cells,tissues,and biological fluids.Nutritional metabolomics studies in pigs have reported changes in hundre...Metabolomics utilizes advanced analytical profiling techniques to comprehensively measure small molecules in cells,tissues,and biological fluids.Nutritional metabolomics studies in pigs have reported changes in hundreds of metabolites across various sample types,including plasma,serum,urine,digesta,and feces,following dietary interventions.These findings can help identify biomarkers of gastrointestinal functionality and beyond,as well as investigate mechanistic interactions between diet,host,microbiome,and metabolites.This review aims to summarize the current literature on nutritional metabolomics in pigs and its use to investigate how different dietary approaches impact the gut health of pigs.Here,we critically assessed and categorized the impact of the main macronutrients-carbohydrates,proteins,and fats—along with feed additives such as amino acids,bile acids,and probiotics,as well as feeding strategies like creep feeding,milk replacer introduction,and time-restricted feeding,on the pig metabolome.Additionally,we discuss the potential modes of action of the key affected metabolites on pig gut health.展开更多
Pelvic fractures are rare but severe injuries that severely affect patients’quality of life.Treatment of these fractures often involves invasive approaches with high risk of injuries to nervous structures,particularl...Pelvic fractures are rare but severe injuries that severely affect patients’quality of life.Treatment of these fractures often involves invasive approaches with high risk of injuries to nervous structures,particularly lumbosacral plexus.The introduction of minimally invasive surgical approaches,such as the lateral rectus approach,not only contributes to preserving lumbar plexus integrity in operated patients but also positively impacts their psychological well-being.Patients treated by surgical reduction of pelvic fractures with lumbosacral plexus injury often experience states of anxiety and depression.The lateral rectus approach is associated with lower levels of anxiety and depression compared to more invasive surgical techniques used for similar fractures.展开更多
Approximately 5%of patients with renal cancer present with synchronous bilateral renal masses(SBRM).1,2 Bilateral renal tumors associated with hereditary syndromes often exhibit more aggressive biological behaviors co...Approximately 5%of patients with renal cancer present with synchronous bilateral renal masses(SBRM).1,2 Bilateral renal tumors associated with hereditary syndromes often exhibit more aggressive biological behaviors compared to sporadic SBRM cases.3,4 Notably,the prognosis for sporadic cases,in terms of cancerspecific and distant metastasis-free survival,is comparable to that of unilateral renal masses.展开更多
The theory of new quality productive forces provides a foundational framework for cultivating pre-service English teachers.There is a high degree of consistency between the development of new quality productive forces...The theory of new quality productive forces provides a foundational framework for cultivating pre-service English teachers.There is a high degree of consistency between the development of new quality productive forces and the cultivation of pre-service English teachers.The development of new quality productive forces has put forward new requirements for the cultivation of pre-service English teachers,while the cultivation of pre-service English teachers will also promote the development of new quality productive forces and provide talent support for it.Currently,the cultivation of pre-service English teachers faces numerous challenges,which requires strengthening top-level program design,reconstructing the curriculum system,expanding cultivation fields for pre-service English teachers,improving the digital literacy of pre-service English teachers,deepening international exchanges and cooperation,and building an evidence-based evaluation system as a guarantee to achieve new breakthroughs in the cultivation of pre-service English teachers and promote the development of new quality productive forces.展开更多
Stroke is one of the leading causes of death and long-term disability worldwide,severely affecting patients'quality of life and socio-economic development.In recent years,with advancements in neuroscience,research...Stroke is one of the leading causes of death and long-term disability worldwide,severely affecting patients'quality of life and socio-economic development.In recent years,with advancements in neuroscience,researchers have gradually recognized that neuroinflammation plays critical roles in the neurorestoration after stroke.1 Understanding the molecular mechanisms of these processes helps reveal the complex pathophysiological changes following stroke and provides new perspectives for developing effective therapeutic strategies.2 This editorial aims to explore the molecular mechanisms of neuroinflammation and neurorestoration after stroke and review current therapeutic strategies to provide theoretical support for clinical interventions.展开更多
With the rapid development of information technology and the advancement of educational modernization,the teaching mode of vocal music in colleges and universities is undergoing a new transformation,which complies wit...With the rapid development of information technology and the advancement of educational modernization,the teaching mode of vocal music in colleges and universities is undergoing a new transformation,which complies with the trend of digital age and brings new challenges.This paper explores the specific implementation path of artificial intelligence technology,virtual reality technology,big data technology and intelligent interaction technology in vocal music teaching in colleges and universities,aiming to inject new vitality into the traditional teaching mode and improve teaching quality and efficiency.展开更多
The rising prevalence of chronic multimorbidity poses substantial challenges to healthcare systems,necessitating the development of innovative management strategies to optimize patient care and system efficiency.The s...The rising prevalence of chronic multimorbidity poses substantial challenges to healthcare systems,necessitating the development of innovative management strategies to optimize patient care and system efficiency.The study by Fontalba-Navas et al investigates the implementation of a novel high complexity unit(HCU)specifically designed to improve the management of patients with chronic complex conditions.By adopting a multidisciplinary approach,the HCU aims to provide comprehensive,patient-centered care that enhances health outcomes and alleviates the strain on traditional hospital services.Utilizing a longitudinal analysis of data from the Basic Minimum Data Set,this study compares hospitalization metrics among the HCU,Internal Medicine,and other departments within a regional hospital throughout 2022.The findings reveal that the HCU's integrated care model significantly reduces readmission rates and boosts patient satisfaction compared to conventional care practices.The study highlights the HCU's potential as a replicable model for managing chronic multimorbidity,emphasizing its effectiveness in minimizing unnecessary hospitalizations and enhancing the overall quality of patient care.This innovative approach not only addresses the complexities associated with chronic multimorbid conditions but also offers a sustainable framework for healthcare systems confronting similar challenges.展开更多
Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands...Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands on its control performance.The model predictive control(MPC)algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints.For the MPC used in the PMSM control process,there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object,which causes the prediction error and thus affects the dynamic stability of the control system.This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance.The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility.Compared with the classical MPC strategy,the superiority of the algorithm has also been verified.展开更多
Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensem...Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions.With the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data.Ensemble deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning algorithms.Although ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble learning.Ensemble deep learning has been successfully used in several areas,such as bioinformatics,finance,and health care.In this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug discovery.We cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also demonstrated.Furthermore,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and explored.Finally,future directions and opportunities for enhancing healthcare model performance are discussed.展开更多
Long COVID(also called post-COVID condition"or"post-COVID-19 syndrome")was first defined in adults by WHO in October,2021[1,2].Usually,it occurs 3 months after the onset of COVID-19.It is a series of co...Long COVID(also called post-COVID condition"or"post-COVID-19 syndrome")was first defined in adults by WHO in October,2021[1,2].Usually,it occurs 3 months after the onset of COVID-19.It is a series of complex symptoms that last for at least 2 months and cannot be explained by an alternative diagnosis in individuals with a history of probable or confirmed SARS-CoV-2 infection[3,4].At least 65 million individuals globally are estimated to have long COVID,mostly are hospitalized cases(50%70%),and others are non-hospitalized and vaccinated cases[5].展开更多
Oral submucous fibrosis(OSF),characterized by excessive deposition of extracellular matrix(ECM)that causes oral mucosal tissue sclerosis,and even cancer transformation,is a chronic,progressive fibrosis disease.However...Oral submucous fibrosis(OSF),characterized by excessive deposition of extracellular matrix(ECM)that causes oral mucosal tissue sclerosis,and even cancer transformation,is a chronic,progressive fibrosis disease.However,despite some advancements in recent years,no targeted antifibrotic strategies for OSF have been approved;likely because the complicated mechanisms that initiate and drive fibrosis remain to be determined.In this review,we briefly introduce the epidemiology and etiology of OSF.Then,we highlight how cell-intrinsic changes in significant structural cells can drive fibrotic response by regulating biological behaviors,secretion function,and activation of ECM-producing myofibroblasts.In addition,we also discuss the role of innate and adaptive immune cells and how they contribute to the pathogenesis of OSF.Finally,we summarize strategies to interrupt key mechanisms that cause OSF,including modulation of the ECM,inhibition of inflammation,improvement of vascular disturbance.This review will provide potential routes for developing novel anti-OSF therapeutics.展开更多
In May 2025,the Fuding White Tea Culture System in southeast China’s Fujian Province was officially recognized by the UN Food and Agriculture Organization(FAO)as a Globally Important Agricultural Heritage System(GIAH...In May 2025,the Fuding White Tea Culture System in southeast China’s Fujian Province was officially recognized by the UN Food and Agriculture Organization(FAO)as a Globally Important Agricultural Heritage System(GIAHS).It mainly includes national-level superior varieties-Fuding Dabai Tea,Fuding Dahao Tea,and Fuding Cai Tea(group variety)which retains tradition and uses tea seeds for sexual reproduction-providing abundant germplasm resources for cultivating new tea varieties.展开更多
The world’s increasing population requires the process industry to produce food,fuels,chemicals,and consumer products in a more efficient and sustainable way.Functional process materials lie at the heart of this chal...The world’s increasing population requires the process industry to produce food,fuels,chemicals,and consumer products in a more efficient and sustainable way.Functional process materials lie at the heart of this challenge.Traditionally,new advanced materials are found empirically or through trial-and-error approaches.As theoretical methods and associated tools are being continuously improved and computer power has reached a high level,it is now efficient and popular to use computational methods to guide material selection and design.Due to the strong interaction between material selection and the operation of the process in which the material is used,it is essential to perform material and process design simultaneously.Despite this significant connection,the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required.Hybrid modeling provides a promising option to tackle such complex design problems.In hybrid modeling,the material properties,which are computationally expensive to obtain,are described by data-driven models,while the well-known process-related principles are represented by mechanistic models.This article highlights the significance of hybrid modeling in multiscale material and process design.The generic design methodology is first introduced.Six important application areas are then selected:four from the chemical engineering field and two from the energy systems engineering domain.For each selected area,state-ofthe-art work using hybrid modeling for multiscale material and process design is discussed.Concluding remarks are provided at the end,and current limitations and future opportunities are pointed out.展开更多
Non-learning based motion and path planning of an Unmanned Aerial Vehicle(UAV)is faced with low computation efficiency,mapping memory occupation and local optimization problems.This article investigates the challenge ...Non-learning based motion and path planning of an Unmanned Aerial Vehicle(UAV)is faced with low computation efficiency,mapping memory occupation and local optimization problems.This article investigates the challenge of quadrotor control using offline reinforcement learning.By establishing a data-driven learning paradigm that operates without real-environment interaction,the proposed workflow offers a safer approach than traditional reinforcement learning,making it particularly suited for UAV control in industrial scenarios.The introduced algorithm evaluates dataset uncertainty and employs a pessimistic estimation to foster offline deep reinforcement learning.Experiments highlight the algorithm's superiority over traditional online reinforcement learning methods,especially when learning from offline datasets.Furthermore,the article emphasizes the importance of a more general behavior policy.In evaluations,the trained policy demonstrated versatility by adeptly navigating diverse obstacles,underscoring its real-world applicability.展开更多
A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis ca...A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.展开更多
Background: Cutaneous oncology encompasses a broad range of skin malignancies, including melanoma, cutaneous squamous cell carcinoma (SCC), and basal cell carcinoma (BCC), all of which pose significant global health c...Background: Cutaneous oncology encompasses a broad range of skin malignancies, including melanoma, cutaneous squamous cell carcinoma (SCC), and basal cell carcinoma (BCC), all of which pose significant global health challenges. The World Health Organization (WHO) estimates that melanoma incidence has increased by approximately 50% over the past three decades. While SCC and BCC are generally less aggressive than melanoma, they contribute significantly to the overall burden of skin cancer due to their high prevalence. Traditional treatment modalities for these malignancies, such as surgery, radiation, and chemotherapy, have shown limitations in achieving durable responses and minimizing systemic toxicity. As a result, there is an increasing need for more effective and less toxic treatment options. Immunotherapeutic strategies have emerged as a promising avenue in oncology, with the potential to revolutionize treatment approaches for cutaneous malignancies. Objectives: This literature review aims to undertake an in-depth examination of immunotherapeutic strategies for melanoma, SCC, and BCC. Specifically, the review focuses on the role of immune checkpoint inhibitors, adoptive cell therapies, and emerging immunotherapies, assessing their impact on treatment outcomes, survival rates, and patient quality of life. Methods: A literature search was conducted using databases such as PubMed, Google Scholar, and Scopus. The search terms included “cutaneous oncology”, “immunotherapy”, “immune checkpoint inhibitors”, “adoptive cell therapy”, “melanoma”, “cutaneous squamous cell carcinoma”, and “basal cell carcinoma”. Peer-reviewed articles published in the last 10 years that reported clinical outcomes from immunotherapy-based treatments for cutaneous malignancies were included. The studies were reviewed and analyzed based on their reported clinical outcomes, including survival rates, adverse events, and quality of life metrics. Results: Our review identified significant advancements in immunotherapeutic strategies for cutaneous oncology. Immune checkpoint inhibitors, such as pembrolizumab and nivolumab, demonstrated improved overall survival rates, particularly in melanoma patients. In addition, adoptive cell therapies, including tumor-infiltrating lymphocyte (TIL) therapies, showed promise in managing both cutaneous SCC and BCC, with reported reductions in tumor burden and durable responses. Emerging immunotherapies, such as cancer vaccines and oncolytic viruses, are in early clinical trials but exhibit potential in enhancing antitumor immunity and expanding treatment options. Conclusions: Immunotherapeutic strategies represent a critical advancement in the management of cutaneous malignancies, offering improved outcomes compared to traditional therapies. Immune checkpoint inhibitors and adoptive cell therapies are already reshaping clinical practice, while emerging immunotherapies provide exciting avenues for future research. These therapies not only enhance survival rates but also reduce systemic toxicities, representing a transformative approach to treating skin cancer. Further research and clinical trials are needed to refine these strategies and expand their applicability to a broader patient population.展开更多
One Health is an integrative approach that emphasizes the interconnectedness of human,animal,and environmental health,advocating for collaborative,multidisciplinary efforts to address health challenges,particularly am...One Health is an integrative approach that emphasizes the interconnectedness of human,animal,and environmental health,advocating for collaborative,multidisciplinary efforts to address health challenges,particularly amid globalization and emerging threats.This paper examines the integration of One Health principles into global health education,highlighting the importance of interdisciplinary collaboration and innovative pedagogical approaches.It evaluates various teaching methods,including problem-based learning(PBL),team-based learning(TBL),simulation-based education(SBE),case-based learning(CBL),interdisciplinary workshops and seminars(IWS),and service-learning(SL),analyzing their strengths and weaknesses in fostering interdisciplinary understanding and practical application of One Health concepts.While these methods enhance learning by promoting critical thinking,collaboration,and real-world application,they also face challenges such as resource constraints,variability in group dynamics,and the complexity of assessing long-term learning outcomes.The paper also discusses the role of global partnerships,such as the Global One Health Research Partnership(GOHRP),in advancing One Health education through collaborative research and educational initiatives.Addressing challenges in curriculum integration and interdisciplinary collaboration is crucial for the effective implementation of One Health education,ensuring that future health professionals are equipped to tackle complex global health challenges.展开更多
基金National Natural Science Foundation of China(Project No.:12371428)Projects of the Provincial College Students’Innovation and Training Program in 2024(Project No.:S202413023106,S202413023110)。
文摘This paper focuses on the numerical solution of a tumor growth model under a data-driven approach.Based on the inherent laws of the data and reasonable assumptions,an ordinary differential equation model for tumor growth is established.Nonlinear fitting is employed to obtain the optimal parameter estimation of the mathematical model,and the numerical solution is carried out using the Matlab software.By comparing the clinical data with the simulation results,a good agreement is achieved,which verifies the rationality and feasibility of the model.
基金supported by Singapore National Medical Research Council(NMRC)grants,including CS-IRG,HLCA2022(to ZDZ),STaR,OF LCG 000207(to EKT)a Clinical Translational Research Programme in Parkinson's DiseaseDuke-Duke-NUS collaboration pilot grant(to ZDZ)。
文摘The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.
基金Supported by National Research Foundation of Korea,No.NRF-2021S1A5A8062526.
文摘This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.
基金the PIG-PARADIGM project,funded by the Novo Nordisk Foundation(Grant No.NNFSA210073688).
文摘Metabolomics utilizes advanced analytical profiling techniques to comprehensively measure small molecules in cells,tissues,and biological fluids.Nutritional metabolomics studies in pigs have reported changes in hundreds of metabolites across various sample types,including plasma,serum,urine,digesta,and feces,following dietary interventions.These findings can help identify biomarkers of gastrointestinal functionality and beyond,as well as investigate mechanistic interactions between diet,host,microbiome,and metabolites.This review aims to summarize the current literature on nutritional metabolomics in pigs and its use to investigate how different dietary approaches impact the gut health of pigs.Here,we critically assessed and categorized the impact of the main macronutrients-carbohydrates,proteins,and fats—along with feed additives such as amino acids,bile acids,and probiotics,as well as feeding strategies like creep feeding,milk replacer introduction,and time-restricted feeding,on the pig metabolome.Additionally,we discuss the potential modes of action of the key affected metabolites on pig gut health.
文摘Pelvic fractures are rare but severe injuries that severely affect patients’quality of life.Treatment of these fractures often involves invasive approaches with high risk of injuries to nervous structures,particularly lumbosacral plexus.The introduction of minimally invasive surgical approaches,such as the lateral rectus approach,not only contributes to preserving lumbar plexus integrity in operated patients but also positively impacts their psychological well-being.Patients treated by surgical reduction of pelvic fractures with lumbosacral plexus injury often experience states of anxiety and depression.The lateral rectus approach is associated with lower levels of anxiety and depression compared to more invasive surgical techniques used for similar fractures.
文摘Approximately 5%of patients with renal cancer present with synchronous bilateral renal masses(SBRM).1,2 Bilateral renal tumors associated with hereditary syndromes often exhibit more aggressive biological behaviors compared to sporadic SBRM cases.3,4 Notably,the prognosis for sporadic cases,in terms of cancerspecific and distant metastasis-free survival,is comparable to that of unilateral renal masses.
基金supported by the National Education Sciences Planning Program of China through the National Office for Education Sciences Planning(Grant No.DIA220376).
文摘The theory of new quality productive forces provides a foundational framework for cultivating pre-service English teachers.There is a high degree of consistency between the development of new quality productive forces and the cultivation of pre-service English teachers.The development of new quality productive forces has put forward new requirements for the cultivation of pre-service English teachers,while the cultivation of pre-service English teachers will also promote the development of new quality productive forces and provide talent support for it.Currently,the cultivation of pre-service English teachers faces numerous challenges,which requires strengthening top-level program design,reconstructing the curriculum system,expanding cultivation fields for pre-service English teachers,improving the digital literacy of pre-service English teachers,deepening international exchanges and cooperation,and building an evidence-based evaluation system as a guarantee to achieve new breakthroughs in the cultivation of pre-service English teachers and promote the development of new quality productive forces.
基金supported by grants from the National Natural Science Foundation of China(81960234,82071331)National Key Research and Development Program of China(2018YFC1312200)+3 种基金Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20232401)Henan Province Medical Science and Technology Research Program(SBGJ202403031)Hunan Provincial Natural Science Foundation(2023JJ40572)Canadian Institutes of Health Research(VWY)。
文摘Stroke is one of the leading causes of death and long-term disability worldwide,severely affecting patients'quality of life and socio-economic development.In recent years,with advancements in neuroscience,researchers have gradually recognized that neuroinflammation plays critical roles in the neurorestoration after stroke.1 Understanding the molecular mechanisms of these processes helps reveal the complex pathophysiological changes following stroke and provides new perspectives for developing effective therapeutic strategies.2 This editorial aims to explore the molecular mechanisms of neuroinflammation and neurorestoration after stroke and review current therapeutic strategies to provide theoretical support for clinical interventions.
基金Education Department of Hainan Province(Project No.:Hnjg2024-112&Hnjg2025ZC-80)。
文摘With the rapid development of information technology and the advancement of educational modernization,the teaching mode of vocal music in colleges and universities is undergoing a new transformation,which complies with the trend of digital age and brings new challenges.This paper explores the specific implementation path of artificial intelligence technology,virtual reality technology,big data technology and intelligent interaction technology in vocal music teaching in colleges and universities,aiming to inject new vitality into the traditional teaching mode and improve teaching quality and efficiency.
基金Supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,No.NRF-RS-2023-00237287.
文摘The rising prevalence of chronic multimorbidity poses substantial challenges to healthcare systems,necessitating the development of innovative management strategies to optimize patient care and system efficiency.The study by Fontalba-Navas et al investigates the implementation of a novel high complexity unit(HCU)specifically designed to improve the management of patients with chronic complex conditions.By adopting a multidisciplinary approach,the HCU aims to provide comprehensive,patient-centered care that enhances health outcomes and alleviates the strain on traditional hospital services.Utilizing a longitudinal analysis of data from the Basic Minimum Data Set,this study compares hospitalization metrics among the HCU,Internal Medicine,and other departments within a regional hospital throughout 2022.The findings reveal that the HCU's integrated care model significantly reduces readmission rates and boosts patient satisfaction compared to conventional care practices.The study highlights the HCU's potential as a replicable model for managing chronic multimorbidity,emphasizing its effectiveness in minimizing unnecessary hospitalizations and enhancing the overall quality of patient care.This innovative approach not only addresses the complexities associated with chronic multimorbid conditions but also offers a sustainable framework for healthcare systems confronting similar challenges.
文摘Permanent magnet synchronous motor(PMSM)is widely used in alternating current servo systems as it provides high eficiency,high power density,and a wide speed regulation range.The servo system is placing higher demands on its control performance.The model predictive control(MPC)algorithm is emerging as a potential high-performance motor control algorithm due to its capability of handling multiple-input and multipleoutput variables and imposed constraints.For the MPC used in the PMSM control process,there is a nonlinear disturbance caused by the change of electromagnetic parameters or load disturbance that may lead to a mismatch between the nominal model and the controlled object,which causes the prediction error and thus affects the dynamic stability of the control system.This paper proposes a data-driven MPC strategy in which the historical data in an appropriate range are utilized to eliminate the impact of parameter mismatch and further improve the control performance.The stability of the proposed algorithm is proved as the simulation demonstrates the feasibility.Compared with the classical MPC strategy,the superiority of the algorithm has also been verified.
基金funded by Taif University,Saudi Arabia,project No.(TU-DSPP-2024-263).
文摘Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data.Recently,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions.With the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data.Ensemble deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning algorithms.Although ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble learning.Ensemble deep learning has been successfully used in several areas,such as bioinformatics,finance,and health care.In this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug discovery.We cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also demonstrated.Furthermore,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and explored.Finally,future directions and opportunities for enhancing healthcare model performance are discussed.
基金supported by the National Key Research and Development Program of China(No.2024YFC3044400)Shanghai Targeted Biomedical Emergency Project(No.23DX1900300).
文摘Long COVID(also called post-COVID condition"or"post-COVID-19 syndrome")was first defined in adults by WHO in October,2021[1,2].Usually,it occurs 3 months after the onset of COVID-19.It is a series of complex symptoms that last for at least 2 months and cannot be explained by an alternative diagnosis in individuals with a history of probable or confirmed SARS-CoV-2 infection[3,4].At least 65 million individuals globally are estimated to have long COVID,mostly are hospitalized cases(50%70%),and others are non-hospitalized and vaccinated cases[5].
基金study was supported by the National Key Research and Development Program of China(2022YFC2402900)National Natural Science Foundation of China(82470989,52103327)+3 种基金The Joint Funds of the Hunan Provincial Natural Science Foundation(2023JJ60509)The Science and Technology Talent Support Project of the Hunan Provincial Science Popularization Special Project(2023TJ-Z08)Hunan Provincial Innovation Foundation for Postgraduate(2023ZZTS0218)The Postgraduate Inde-pendent Exploration Innovation Fund of the Central South University(2023ZZTS0987)。
文摘Oral submucous fibrosis(OSF),characterized by excessive deposition of extracellular matrix(ECM)that causes oral mucosal tissue sclerosis,and even cancer transformation,is a chronic,progressive fibrosis disease.However,despite some advancements in recent years,no targeted antifibrotic strategies for OSF have been approved;likely because the complicated mechanisms that initiate and drive fibrosis remain to be determined.In this review,we briefly introduce the epidemiology and etiology of OSF.Then,we highlight how cell-intrinsic changes in significant structural cells can drive fibrotic response by regulating biological behaviors,secretion function,and activation of ECM-producing myofibroblasts.In addition,we also discuss the role of innate and adaptive immune cells and how they contribute to the pathogenesis of OSF.Finally,we summarize strategies to interrupt key mechanisms that cause OSF,including modulation of the ECM,inhibition of inflammation,improvement of vascular disturbance.This review will provide potential routes for developing novel anti-OSF therapeutics.
文摘In May 2025,the Fuding White Tea Culture System in southeast China’s Fujian Province was officially recognized by the UN Food and Agriculture Organization(FAO)as a Globally Important Agricultural Heritage System(GIAHS).It mainly includes national-level superior varieties-Fuding Dabai Tea,Fuding Dahao Tea,and Fuding Cai Tea(group variety)which retains tradition and uses tea seeds for sexual reproduction-providing abundant germplasm resources for cultivating new tea varieties.
文摘The world’s increasing population requires the process industry to produce food,fuels,chemicals,and consumer products in a more efficient and sustainable way.Functional process materials lie at the heart of this challenge.Traditionally,new advanced materials are found empirically or through trial-and-error approaches.As theoretical methods and associated tools are being continuously improved and computer power has reached a high level,it is now efficient and popular to use computational methods to guide material selection and design.Due to the strong interaction between material selection and the operation of the process in which the material is used,it is essential to perform material and process design simultaneously.Despite this significant connection,the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required.Hybrid modeling provides a promising option to tackle such complex design problems.In hybrid modeling,the material properties,which are computationally expensive to obtain,are described by data-driven models,while the well-known process-related principles are represented by mechanistic models.This article highlights the significance of hybrid modeling in multiscale material and process design.The generic design methodology is first introduced.Six important application areas are then selected:four from the chemical engineering field and two from the energy systems engineering domain.For each selected area,state-ofthe-art work using hybrid modeling for multiscale material and process design is discussed.Concluding remarks are provided at the end,and current limitations and future opportunities are pointed out.
基金supported by the National Natural Science Foundation of China(No.52272382)the Aeronautical Science Foundation of China(No.20200017051001)the Fundamental Research Funds for the Central Universities,China。
文摘Non-learning based motion and path planning of an Unmanned Aerial Vehicle(UAV)is faced with low computation efficiency,mapping memory occupation and local optimization problems.This article investigates the challenge of quadrotor control using offline reinforcement learning.By establishing a data-driven learning paradigm that operates without real-environment interaction,the proposed workflow offers a safer approach than traditional reinforcement learning,making it particularly suited for UAV control in industrial scenarios.The introduced algorithm evaluates dataset uncertainty and employs a pessimistic estimation to foster offline deep reinforcement learning.Experiments highlight the algorithm's superiority over traditional online reinforcement learning methods,especially when learning from offline datasets.Furthermore,the article emphasizes the importance of a more general behavior policy.In evaluations,the trained policy demonstrated versatility by adeptly navigating diverse obstacles,underscoring its real-world applicability.
基金This work was supported by the National Natural Science Foundation of China(Grant No.42050104)the Science Foundation of SINOPEC Group(Grant No.P20030).
文摘A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.
文摘Background: Cutaneous oncology encompasses a broad range of skin malignancies, including melanoma, cutaneous squamous cell carcinoma (SCC), and basal cell carcinoma (BCC), all of which pose significant global health challenges. The World Health Organization (WHO) estimates that melanoma incidence has increased by approximately 50% over the past three decades. While SCC and BCC are generally less aggressive than melanoma, they contribute significantly to the overall burden of skin cancer due to their high prevalence. Traditional treatment modalities for these malignancies, such as surgery, radiation, and chemotherapy, have shown limitations in achieving durable responses and minimizing systemic toxicity. As a result, there is an increasing need for more effective and less toxic treatment options. Immunotherapeutic strategies have emerged as a promising avenue in oncology, with the potential to revolutionize treatment approaches for cutaneous malignancies. Objectives: This literature review aims to undertake an in-depth examination of immunotherapeutic strategies for melanoma, SCC, and BCC. Specifically, the review focuses on the role of immune checkpoint inhibitors, adoptive cell therapies, and emerging immunotherapies, assessing their impact on treatment outcomes, survival rates, and patient quality of life. Methods: A literature search was conducted using databases such as PubMed, Google Scholar, and Scopus. The search terms included “cutaneous oncology”, “immunotherapy”, “immune checkpoint inhibitors”, “adoptive cell therapy”, “melanoma”, “cutaneous squamous cell carcinoma”, and “basal cell carcinoma”. Peer-reviewed articles published in the last 10 years that reported clinical outcomes from immunotherapy-based treatments for cutaneous malignancies were included. The studies were reviewed and analyzed based on their reported clinical outcomes, including survival rates, adverse events, and quality of life metrics. Results: Our review identified significant advancements in immunotherapeutic strategies for cutaneous oncology. Immune checkpoint inhibitors, such as pembrolizumab and nivolumab, demonstrated improved overall survival rates, particularly in melanoma patients. In addition, adoptive cell therapies, including tumor-infiltrating lymphocyte (TIL) therapies, showed promise in managing both cutaneous SCC and BCC, with reported reductions in tumor burden and durable responses. Emerging immunotherapies, such as cancer vaccines and oncolytic viruses, are in early clinical trials but exhibit potential in enhancing antitumor immunity and expanding treatment options. Conclusions: Immunotherapeutic strategies represent a critical advancement in the management of cutaneous malignancies, offering improved outcomes compared to traditional therapies. Immune checkpoint inhibitors and adoptive cell therapies are already reshaping clinical practice, while emerging immunotherapies provide exciting avenues for future research. These therapies not only enhance survival rates but also reduce systemic toxicities, representing a transformative approach to treating skin cancer. Further research and clinical trials are needed to refine these strategies and expand their applicability to a broader patient population.
文摘One Health is an integrative approach that emphasizes the interconnectedness of human,animal,and environmental health,advocating for collaborative,multidisciplinary efforts to address health challenges,particularly amid globalization and emerging threats.This paper examines the integration of One Health principles into global health education,highlighting the importance of interdisciplinary collaboration and innovative pedagogical approaches.It evaluates various teaching methods,including problem-based learning(PBL),team-based learning(TBL),simulation-based education(SBE),case-based learning(CBL),interdisciplinary workshops and seminars(IWS),and service-learning(SL),analyzing their strengths and weaknesses in fostering interdisciplinary understanding and practical application of One Health concepts.While these methods enhance learning by promoting critical thinking,collaboration,and real-world application,they also face challenges such as resource constraints,variability in group dynamics,and the complexity of assessing long-term learning outcomes.The paper also discusses the role of global partnerships,such as the Global One Health Research Partnership(GOHRP),in advancing One Health education through collaborative research and educational initiatives.Addressing challenges in curriculum integration and interdisciplinary collaboration is crucial for the effective implementation of One Health education,ensuring that future health professionals are equipped to tackle complex global health challenges.
