The recent proliferation of empirically-supported treatments(ESTs)into the private sector has led to more U.S.children and families receiving high quality treatments and improved treatment outcomes.However,there remai...The recent proliferation of empirically-supported treatments(ESTs)into the private sector has led to more U.S.children and families receiving high quality treatments and improved treatment outcomes.However,there remains a significant dearth of evidence-based clinics,service providers,and training programs nationally,particularly in more remote communities.The Child&Family Institute(CFI)was founded in 2011 as the world’s first Clinical Dissemination Practice and training institute,comprising five core unifying stages and initiatives:(1)Dissemination Through Training,(2)Dissemination Through Community Partnership,(3)Dissemination Through Integrated Behavioral Health,(4)Dissemination Through Technology,and(5)Dissemination Through Multi-State,Multi-Site Program Development and Implementation,all with a common goal of raising awareness and leveraging local and national resources to disseminate and implement accessible,affordable,evidence-based care to children,families,and communities across the United States,and beyond.Perhaps most central and unique to CFI’s five initiatives,and its overall core values and mission,is the accessibility and affordability of services for each and every child.Preliminary feedback from patients,students,collaborators,local politicians and stakeholders,partner organizations,and the broader communities in the regions served has been enthusiastic,and several grant submissions and research partnerships are underway,to test the effectiveness of CFI programming and evidence-based treatments in“real-world”clinics nationwide.展开更多
Kang et al published a study recently in the World Journal of Gastroenterology introducing an interpretable machine learning model to predict anastomotic leakage after rectal cancer surgery,highlighting postoperative ...Kang et al published a study recently in the World Journal of Gastroenterology introducing an interpretable machine learning model to predict anastomotic leakage after rectal cancer surgery,highlighting postoperative serum calcium as a key predictive feature.While this represents a significant advancement,we argue that reliance on a static calcium threshold may limit clinical applicability.We advocate for a dynamic,trajectory-based assessment of serum calcium levels across perioperative time points,using modeling approaches such as time-series regression or mixed-effects models.Furthermore,the model’s robustness could be improved by incorporating systemic inflammation and nutritional indices such as C-reactive protein,procalcitonin,the neutrophil-to-lymphocyte ratio,and the systemic immune-inflammation index,supported by recent prospective studies.Finally,generalizability remains a concern,warranting broader validation and clearer clinical deployment strategies.By addressing these aspects,the model’s clinical translation and decision-making impact could be substantially enhanced.展开更多
In 2025,Shi et al constructed a model utilizing machine learning techniques to predict the one-year recurrence of colorectal polyps following endoscopic mucosal resection,showing excellent discriminatory performance w...In 2025,Shi et al constructed a model utilizing machine learning techniques to predict the one-year recurrence of colorectal polyps following endoscopic mucosal resection,showing excellent discriminatory performance with an area under the curve exceeding 0.90.However,limitations exist regarding its narrow temporal scope,potential overestimation due to feature collinearity and imputation opacity,and limited generalizability due to single-center derivation and validation.Moreover,no clear clinical implementation strategy was outlined.Prospective multicenter validation and integration of endoscopist variability,longitudinal outcome data,and deployment mechanisms are warranted to ensure broader applicability and clinical utility.展开更多
Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagn...Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagnostic imaging,such as resolution,radiation efficiency,and real-time processing.Methods:This work used a mixed-methods strategy,including controlled phantom experiments,retrospective multi-center clinical data analysis,and quantum-classical hybrid processing to assess enhancements in resolution,dosage efficiency,and diagnostic confidence.Statistical validation included analysis of variance(ANOVA)and receiver-operating characteristic curve analysis,juxtaposing quantum-enhanced methodologies with conventional and deep learning approaches.Results:Quantum entanglement reconstruction enhanced magnetic resonance imaging spatial resolution by 33.2%(P<0.01),quantum noise suppression facilitated computed tomography scans with a 60%reduction in radiation,and quantum beamforming improved ultrasound contrast by 27%while preserving real-time processing(<2 ms delay).Inter-reader variability(12%in Diagnostic Confidence Scores)showed that systematic training is needed,even if the performance was better.The research presented(1)a reusable clinical quantum imaging framework,(2)enhanced hardware processes(field-programmable gate array/graphics processing unit acceleration),and(3)cost-benefit analyses demonstrating a 22-month return on investment breakeven point.Conclusion:Quantum-enhanced imaging has a lot of promise for use in medicine,especially in neurology and cancer.Future research should focus on multi-modal integration(e.g.,positron emission tomography–magnetic resonance imaging),cloud-based quantum simulations for enhanced accessibility,and extensive trials to confirm long-term diagnostic accuracy.This breakthrough gives healthcare systems a technology roadmap and a reason to spend money on quantum-enhanced diagnostics.展开更多
Tremendous advances in artificial intelligence(AI)in medical image analysis have been achieved in recent years.The integration of AI is expected to cause a revolution in various areas of medicine,including gastrointes...Tremendous advances in artificial intelligence(AI)in medical image analysis have been achieved in recent years.The integration of AI is expected to cause a revolution in various areas of medicine,including gastrointestinal(GI)pathology.Currently,deep learning algorithms have shown promising benefits in areas of diagnostic histopathology,such as tumor identification,classification,prognosis prediction,and biomarker/genetic alteration prediction.While AI cannot substitute pathologists,carefully constructed AI applications may increase workforce productivity and diagnostic accuracy in pathology practice.Regardless of these promising advances,unlike the areas of radiology or cardiology imaging,no histopathology-based AI application has been approved by a regulatory authority or for public reimbursement.Thus,implying that there are still some obstacles to be overcome before AI applications can be safely and effectively implemented in real-life pathology practice.The challenges have been identified at different stages of the development process,such as needs identification,data curation,model development,validation,regulation,modification of daily workflow,and cost-effectiveness balance.The aim of this review is to present challenges in the process of AI development,validation,and regulation that should be overcome for its implementation in real-life GI pathology practice.展开更多
Implementing clinical trials with large multicenter samples is an important way to scientifically evaluate and demonstrate the curative effect of moxibustion.At present,clinical trials on moxibustion with large multic...Implementing clinical trials with large multicenter samples is an important way to scientifically evaluate and demonstrate the curative effect of moxibustion.At present,clinical trials on moxibustion with large multicenter samples are prospering in China.It is necessary for research units to have good research professionals and technical platforms as well as a highly standardized and scientifically feasible methodology of research.Taking tasks in the ongoing national 973 project and in the sci-tech support program of the "11th 5-year plan",for example,this research captures the characteristics of moxibustion,carries out deep analysis and introduces specific methods and the important significance of clinical research tasks on moxibustion in designing multicenter plans,implementing experiments,supervising quality and strengthening compliance.展开更多
The aim of this work was to supply an overview of the germline Pharmacogenetics that can be already implemented in the oncology clinical practice.An explanation of the three pillars considered necessary for determinin...The aim of this work was to supply an overview of the germline Pharmacogenetics that can be already implemented in the oncology clinical practice.An explanation of the three pillars considered necessary for determining which genetic polymorphisms should be used has been provided.These are PharmGKB single nucleotide polymorphism(SNP)-Drug Clinical Annotations with levels of evidence 1 or 2;the genetic information provided in the drug labels by the drug regulatory main agencies(Food and Drug Administration and European Medicines Agency,mainly);and the guidelines elaborated by international expert consortia(mainly Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group).A summary of the relevant SNPs and the recommendations on how to apply their results has also been compiled.展开更多
Polychemotherapeutic protocols for the treatment of pediatric acute lymphoblastic leukemia(ALL)always include thiopurines.Specific approaches vary in terms of drugs,dosages and combinations.Such therapeutic schemes,in...Polychemotherapeutic protocols for the treatment of pediatric acute lymphoblastic leukemia(ALL)always include thiopurines.Specific approaches vary in terms of drugs,dosages and combinations.Such therapeutic schemes,including risk-adapted intensity,have been extremely successful for children with ALL who have reached an outstanding 5-year survival of greater than 90%in developed countries.Innovative drugs such as the proteasome inhibitor bortezomib and the bi-specific T cell engager blinatumomab are available to further improve therapeutic outcomes.Nevertheless,daily oral thiopurines remain the backbone maintenance or continuation therapy.Pharmacogenetics allows the personalization of thiopurine therapy in pediatric ALL and clinical guidelines to tailor therapy on the basis of genetic variants in TPMT and NUDT15 genes are already available.Other genes of interest,such as ITPA and PACSIN2,have been implicated in interindividual variability in thiopurines efficacy and adverse effects and need additional research to be implemented in clinical protocols.In this review we will discuss current literature and clinical guidelines available to implement pharmacogenetics for tailoring therapy with thiopurines in pediatric ALL.展开更多
文摘The recent proliferation of empirically-supported treatments(ESTs)into the private sector has led to more U.S.children and families receiving high quality treatments and improved treatment outcomes.However,there remains a significant dearth of evidence-based clinics,service providers,and training programs nationally,particularly in more remote communities.The Child&Family Institute(CFI)was founded in 2011 as the world’s first Clinical Dissemination Practice and training institute,comprising five core unifying stages and initiatives:(1)Dissemination Through Training,(2)Dissemination Through Community Partnership,(3)Dissemination Through Integrated Behavioral Health,(4)Dissemination Through Technology,and(5)Dissemination Through Multi-State,Multi-Site Program Development and Implementation,all with a common goal of raising awareness and leveraging local and national resources to disseminate and implement accessible,affordable,evidence-based care to children,families,and communities across the United States,and beyond.Perhaps most central and unique to CFI’s five initiatives,and its overall core values and mission,is the accessibility and affordability of services for each and every child.Preliminary feedback from patients,students,collaborators,local politicians and stakeholders,partner organizations,and the broader communities in the regions served has been enthusiastic,and several grant submissions and research partnerships are underway,to test the effectiveness of CFI programming and evidence-based treatments in“real-world”clinics nationwide.
基金Supported by Clinical Translational Medicine Project of the Department of Science and Technology of Anhui Province,No.202427b10020138.
文摘Kang et al published a study recently in the World Journal of Gastroenterology introducing an interpretable machine learning model to predict anastomotic leakage after rectal cancer surgery,highlighting postoperative serum calcium as a key predictive feature.While this represents a significant advancement,we argue that reliance on a static calcium threshold may limit clinical applicability.We advocate for a dynamic,trajectory-based assessment of serum calcium levels across perioperative time points,using modeling approaches such as time-series regression or mixed-effects models.Furthermore,the model’s robustness could be improved by incorporating systemic inflammation and nutritional indices such as C-reactive protein,procalcitonin,the neutrophil-to-lymphocyte ratio,and the systemic immune-inflammation index,supported by recent prospective studies.Finally,generalizability remains a concern,warranting broader validation and clearer clinical deployment strategies.By addressing these aspects,the model’s clinical translation and decision-making impact could be substantially enhanced.
基金Supported by the Wuhu Municipal Science and Technology Bureau Project,No.2024kj072.
文摘In 2025,Shi et al constructed a model utilizing machine learning techniques to predict the one-year recurrence of colorectal polyps following endoscopic mucosal resection,showing excellent discriminatory performance with an area under the curve exceeding 0.90.However,limitations exist regarding its narrow temporal scope,potential overestimation due to feature collinearity and imputation opacity,and limited generalizability due to single-center derivation and validation.Moreover,no clear clinical implementation strategy was outlined.Prospective multicenter validation and integration of endoscopist variability,longitudinal outcome data,and deployment mechanisms are warranted to ensure broader applicability and clinical utility.
文摘Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagnostic imaging,such as resolution,radiation efficiency,and real-time processing.Methods:This work used a mixed-methods strategy,including controlled phantom experiments,retrospective multi-center clinical data analysis,and quantum-classical hybrid processing to assess enhancements in resolution,dosage efficiency,and diagnostic confidence.Statistical validation included analysis of variance(ANOVA)and receiver-operating characteristic curve analysis,juxtaposing quantum-enhanced methodologies with conventional and deep learning approaches.Results:Quantum entanglement reconstruction enhanced magnetic resonance imaging spatial resolution by 33.2%(P<0.01),quantum noise suppression facilitated computed tomography scans with a 60%reduction in radiation,and quantum beamforming improved ultrasound contrast by 27%while preserving real-time processing(<2 ms delay).Inter-reader variability(12%in Diagnostic Confidence Scores)showed that systematic training is needed,even if the performance was better.The research presented(1)a reusable clinical quantum imaging framework,(2)enhanced hardware processes(field-programmable gate array/graphics processing unit acceleration),and(3)cost-benefit analyses demonstrating a 22-month return on investment breakeven point.Conclusion:Quantum-enhanced imaging has a lot of promise for use in medicine,especially in neurology and cancer.Future research should focus on multi-modal integration(e.g.,positron emission tomography–magnetic resonance imaging),cloud-based quantum simulations for enhanced accessibility,and extensive trials to confirm long-term diagnostic accuracy.This breakthrough gives healthcare systems a technology roadmap and a reason to spend money on quantum-enhanced diagnostics.
文摘Tremendous advances in artificial intelligence(AI)in medical image analysis have been achieved in recent years.The integration of AI is expected to cause a revolution in various areas of medicine,including gastrointestinal(GI)pathology.Currently,deep learning algorithms have shown promising benefits in areas of diagnostic histopathology,such as tumor identification,classification,prognosis prediction,and biomarker/genetic alteration prediction.While AI cannot substitute pathologists,carefully constructed AI applications may increase workforce productivity and diagnostic accuracy in pathology practice.Regardless of these promising advances,unlike the areas of radiology or cardiology imaging,no histopathology-based AI application has been approved by a regulatory authority or for public reimbursement.Thus,implying that there are still some obstacles to be overcome before AI applications can be safely and effectively implemented in real-life pathology practice.The challenges have been identified at different stages of the development process,such as needs identification,data curation,model development,validation,regulation,modification of daily workflow,and cost-effectiveness balance.The aim of this review is to present challenges in the process of AI development,validation,and regulation that should be overcome for its implementation in real-life GI pathology practice.
基金Supported by the National "11th 5-year Plan" (2006BAI12B04-2)National Plan on Developing Key Basic Researches(973 Plan)(2009CB522902)+1 种基金State Natural Science Fund(30760320)a project of Key Sci-tech Support Plan in Jiangxi
文摘Implementing clinical trials with large multicenter samples is an important way to scientifically evaluate and demonstrate the curative effect of moxibustion.At present,clinical trials on moxibustion with large multicenter samples are prospering in China.It is necessary for research units to have good research professionals and technical platforms as well as a highly standardized and scientifically feasible methodology of research.Taking tasks in the ongoing national 973 project and in the sci-tech support program of the "11th 5-year plan",for example,this research captures the characteristics of moxibustion,carries out deep analysis and introduces specific methods and the important significance of clinical research tasks on moxibustion in designing multicenter plans,implementing experiments,supervising quality and strengthening compliance.
文摘The aim of this work was to supply an overview of the germline Pharmacogenetics that can be already implemented in the oncology clinical practice.An explanation of the three pillars considered necessary for determining which genetic polymorphisms should be used has been provided.These are PharmGKB single nucleotide polymorphism(SNP)-Drug Clinical Annotations with levels of evidence 1 or 2;the genetic information provided in the drug labels by the drug regulatory main agencies(Food and Drug Administration and European Medicines Agency,mainly);and the guidelines elaborated by international expert consortia(mainly Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group).A summary of the relevant SNPs and the recommendations on how to apply their results has also been compiled.
基金This project is supported by the Italian Ministry of Health(Progetto Ricerca Corrente 5/2012).
文摘Polychemotherapeutic protocols for the treatment of pediatric acute lymphoblastic leukemia(ALL)always include thiopurines.Specific approaches vary in terms of drugs,dosages and combinations.Such therapeutic schemes,including risk-adapted intensity,have been extremely successful for children with ALL who have reached an outstanding 5-year survival of greater than 90%in developed countries.Innovative drugs such as the proteasome inhibitor bortezomib and the bi-specific T cell engager blinatumomab are available to further improve therapeutic outcomes.Nevertheless,daily oral thiopurines remain the backbone maintenance or continuation therapy.Pharmacogenetics allows the personalization of thiopurine therapy in pediatric ALL and clinical guidelines to tailor therapy on the basis of genetic variants in TPMT and NUDT15 genes are already available.Other genes of interest,such as ITPA and PACSIN2,have been implicated in interindividual variability in thiopurines efficacy and adverse effects and need additional research to be implemented in clinical protocols.In this review we will discuss current literature and clinical guidelines available to implement pharmacogenetics for tailoring therapy with thiopurines in pediatric ALL.
