This study investigates the relationship between atmospheric stratification (i.e., static stability given by N^(2)) and the vertical energy transfer of stationary planetary waves, and further illustrates the underlyin...This study investigates the relationship between atmospheric stratification (i.e., static stability given by N^(2)) and the vertical energy transfer of stationary planetary waves, and further illustrates the underlying physical mechanism. Specifically, for the simplified case of constant stratospheric N^(2), the refractive index square of planetary waves has a theoretical tendency to increase first and then decrease with an increased N^(2), whereas the group velocity weakens. Mechanistically, this behavior can be understood as an intensified suppression of vertical isentropic surface displacement caused by meridional heat transport of planetary waves under strong N^(2) conditions. Observational analysis corroborates this finding, demonstrating a reduction in the vertical-propagation velocity of waves with increased N^(2). A linear, quasi- geostrophic, mid-latitude beta-plane model with a constant background westerly wind and a prescribed N^(2) applicable to the stratosphere is used to obtain analytic solutions. In this model, the planetary waves are initiated by steady energy influx from the lower boundary. The analysis indicates that under strong N^(2) conditions, the amplitude of planetary waves can be sufficiently increased by the effective energy convergence due to the slowing vertical energy transfer, resulting in a streamfunction response in this model that contains more energy. For N^(2) with a quasi-linear vertical variation, the results bear a resemblance to the constant case, except that the wave amplitude and oscillating frequency show some vertical variations.展开更多
Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diver...Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.展开更多
Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamm...Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamma-carboxy prothrombin(DCP),lack specificity,limiting their utility in risk strati-fication.YKL-40,a glycoprotein involved in extracellular matrix remodeling,hepatic stellate cell activation,and immune modulation,has emerged as a promising biomarker for post-LT surveillance.Elevated serum levels of YKL-40 are associated with advanced liver disease,tumor progression,and poorer post-LT outcomes,highlighting its potential to address gaps in early detection and personalized management of HCC recurrence.This manuscript synthesizes clinical and mechanistic evidence to evaluate YKL-40’s predictive utility in post-LT care.While preliminary findings demonstrate its specificity for liver-related pathologies,challenges remain,including assay standardization,lack of pro-spective validation,and the need to distinguish between malignant and non-malignant causes of elevated levels.Integrating YKL-40 into multi-biomarker panels with AFP and DCP could enhance predictive accuracy and enable tailored therapeutic strategies.Future research should focus on multicenter studies to validate YKL-40’s clinical utility,address confounding factors like graft rejection and systemic inflammation,and explore its role in predictive models driven by emerging technologies such as artificial intelligence.YKL-40 holds transformative potential in reshaping post-LT care through precision medicine,providing a pathway for better outcomes and improved management of high-risk LT recipients.展开更多
Cardiovascular diseases(CVDs)remain the leading cause of morbidity and mortality worldwide,necessitating innovative diagnostic and prognostic strategies.Traditional biomarkers like C-reactive protein,uric acid,troponi...Cardiovascular diseases(CVDs)remain the leading cause of morbidity and mortality worldwide,necessitating innovative diagnostic and prognostic strategies.Traditional biomarkers like C-reactive protein,uric acid,troponin,and natriuretic peptides play crucial roles in CVD management,yet they are often limited by sensitivity and specificity constraints.This narrative review critically examines the emerging landscape of cardiac biomarkers and advocates for a multiple-marker approach to enhance early detection,prognosis,and risk stratification of CVD.In recent years,several novel biomarkers have shown promise in revolutionizing CVD diagnostics.Gamma-glutamyltransferase,microRNAs,endothelial microparticles,placental growth factor,trimethylamine N-oxide,retinol-binding protein 4,copeptin,heart-type fatty acid-binding protein,galectin-3,growth differentiation factor-15,soluble suppression of tumorigenicity 2,fibroblast growth factor 23,and adrenomedullin have emerged as significant indicators of CV health.These biomarkers provide insights into various pathophysiological processes,such as oxidative stress,endothelial dysfunction,inflammation,metabolic disturbances,and myocardial injury.The integration of these novel biomarkers with traditional ones offers a more comprehensive understanding of CVD mechanisms.This multiple-marker approach can improve diagnostic accuracy,allowing for better risk stratification and more personalized treatment strategies.This review underscores the need for continued research to validate the clinical utility of these biomarkers and their potential incorporation into routine clinical practice.By leveraging the strengths of both traditional and novel biomarkers,precise therapeutic plans can be developed,thereby improving the management and prognosis of patients with CVDs.The ongoing exploration and validation of these biomarkers are crucial for advancing CV care and addressing the limitations of current diagnostic tools.展开更多
BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery ...BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.展开更多
Patients admitted with prediabetes and atrial fibrillation are at high risk for major adverse cardiac or cerebrovascular events independent of confounding variables.The shared pathophysiology between these three serio...Patients admitted with prediabetes and atrial fibrillation are at high risk for major adverse cardiac or cerebrovascular events independent of confounding variables.The shared pathophysiology between these three serious but common diseases and their association with atherosclerotic cardiovascular risk factors establish a vicious circle culminating in high atherogenicity.Because of that,it is of paramount importance to perform risk stratification of patients with prediabetes to define phenotypes that benefit from various interventions.Furthermore,stress hyperglycemia assessment of hospitalized patients and consensus on the definition of prediabetes is vital.The roles lifestyle and metformin play in prediabetes are well established.However,the role of glucagon-like peptide agonists and metabolic surgery is less clear.Prediabetes is considered an intermediate between normoglycemia and diabetes along the blood glucose continuum.One billion people are expected to suffer from prediabetes by the year 2045.Therefore,realworld randomized controlled trials to assess major adverse cardiac or cerebrovascular event risk reduction and reversal/prevention of type 2 diabetes among patients are needed to determine the proper interventions.展开更多
Unheralded cardiac arrest among previously healthy young people without antecedent illness,months or years after coronavirus disease 2019(COVID-19)vaccination,highlights the urgent need for risk stratification.The mos...Unheralded cardiac arrest among previously healthy young people without antecedent illness,months or years after coronavirus disease 2019(COVID-19)vaccination,highlights the urgent need for risk stratification.The most likely underlying pathophysiology is subclinical myopericarditis and reentrant ventri-cular tachycardia or spontaneous ventricular fibrillation that is commonly preci-pitated after a surge in catecholamines during exercise or the waking hours of terminal sleep.Small patches of inflammation and/or edema can be missed on cardiac imaging and autopsy,and the heart can appear grossly normal.This paper reviews evidence linking COVID-19 vaccines to cardiac arrest where unfortu-nately the majority of victims have had no antecedent clinical evaluation.We propose a comprehensive strategy for evaluating cardiovascular risk post-vaccination,incorporating detailed patient history,antibody testing,and cardiac diagnostics in the best attempt to detect abnormalities before sudden cardiac death.This approach aims to identify individuals at higher risk of cardiac events after COVID-19 vaccination and guide appropriate clinical management.It is prudent for each primary care physician to have a pre-established plan when addressing this issue in their practice.展开更多
A recent single-center retrospective study proposed novel combinations of hematological parameters and scoring systems for predicting severe acute pancre-atitis.While these combinations showed promising predictive per...A recent single-center retrospective study proposed novel combinations of hematological parameters and scoring systems for predicting severe acute pancre-atitis.While these combinations showed promising predictive performance,several limitations warrant consideration,including the lack of calibration,the absence of key inflammatory markers such as procalcitonin,and practical challenges in integrating these models into routine clinical workflows.To improve predictive accuracy and clinical applicability,prospective validation and the inclusion of additional variables are recommended.展开更多
1.Introduction With an estimate of 19,976,499 newly diagnosed cases and 9,743,832 deaths occurred in 2022 worldwide,cancer continues to impose a significant health and economic burden worldwide.1 The development of ca...1.Introduction With an estimate of 19,976,499 newly diagnosed cases and 9,743,832 deaths occurred in 2022 worldwide,cancer continues to impose a significant health and economic burden worldwide.1 The development of cancer is a complex interplay between genetic and environmental factors.2 In addition to genetic modifications,there is a growing body of evidence suggesting that epigenetic changes,which influence gene expression without modifying the DNA sequence,are playing an increasingly significant role in the development of cancer.DNA methylation,a key epigenetic mechanism,has been notably implicated in the early stages of cancer development,positioning it as a potential biomarker for cancer risk assessment.3 Studies have identified a diverse array of DNA methylation biomarkers for the early detection and diagnosis of cancer,utilizing DNA extracted from tissues,blood,stool,urine,and bowel lavage fluid.4 Research of DNA methylation has focused on two primary sources:peripheral blood mononuclear cell or white blood cell(WBC)DNA methylation,5 linked to cancer susceptibility and tumor-derived cell-free DNA(cfDNA)methylation,6 which has gained significant attention in recent years as a promising biomarker for cancer screening and diagnosis.展开更多
The variable salinity in stored reservoirs connected by a long channel attracts the attention of scientists worldwide,having applications in environmental and geophysical engineering.This study explores the impact of ...The variable salinity in stored reservoirs connected by a long channel attracts the attention of scientists worldwide,having applications in environmental and geophysical engineering.This study explores the impact of Navier slip conditions on exchange flows within a long channel connecting two large reservoirs of differing salinity.These horizontal density gradients drive the flow.We modify the recent one-dimensional theory,developed to avoid runaway stratification,to account for the presence of uniform slip walls.By adjusting the parameters of the horizontal density gradient based on the slip factor,we resolve analytically various flow regimes ranging from high diffusion to transitional high advection.These regimes are governed by physical parameters like channel aspect ratio,slip factor,Schmidt number,and gravitational Reynolds number.Our solutions align perfectly with ones in the no-slip limit.More importantly,under the conditions of no net flow across the channel and high Schmidt number(where stratification is concentrated near the channel’s mid-layer),we derive a closed-form solution for the slip parameter,aspect ratio,and gravitational Reynolds number that describes the interface’s behavior as a sharp interface separating two distinct zones.This interface,arising from hydrostatic wall gradients,ultimately detaches the low-and high-density regimes throughout the channel when the gravitational Reynolds number is inversely proportional to the aspect ratio for a fixed slip parameter.This phenomenon,observed previously in 2D numerical simulations with no-slip walls in the literature,is thus confirmed by our theoretical results.Our findings further demonstrate that wall slip leads to distinct and diverse flow regimes.展开更多
Background:Spontaneous intracerebral hemorrhage(ICH)is a severe neurological emergency with high morbidity and mortality.The effectiveness of surgical intervention remains controversial,partly due to significant heter...Background:Spontaneous intracerebral hemorrhage(ICH)is a severe neurological emergency with high morbidity and mortality.The effectiveness of surgical intervention remains controversial,partly due to significant heterogeneity among patients.Traditional clinical criteria often fail to identify those most likely to benefit from surgery.Methods:This nationwide retrospective study in China included 2,167 ICH patients from 31 hospitals.Using machine learning techniques,we integrated clinical and radiomic data to perform unsupervised clustering and identify distinct phenogroups.Dimensionality reduction and cross-validation were applied to minimize overfitting.External validation was conducted using data from the INTERACT3 trial,and a prospective cohort was used to assess real-world applicability.Results:Three phenogroups were identified.Among them,only Phenogroup 1-characterized by older age,moderate hematoma volume,and intermediate Glasgow Coma Scale scores-showed significant benefit from early surgical intervention,with a 42%reduction in 3-month mortality and improved functional outcomes.In contrast,surgery did not significantly affect outcomes in Phenogroups 0 and 2.These findings were consistent across multiple machine learning models and validated externally.Conclusion:Machine learning-driven phenotypic stratification can effectively identify ICH patients who are most likely to benefit from surgical treatment.This approach supports personalized treatment strategies and may improve clinical decision-making in ICH management.Further validation in diverse populations is warranted.展开更多
BACKGROUND Acute pancreatitis(AP)is an emergency gastrointestinal disease that requires immediate diagnosis and urgent clinical treatment.An accurate assessment and precise staging of severity are essential in initial...BACKGROUND Acute pancreatitis(AP)is an emergency gastrointestinal disease that requires immediate diagnosis and urgent clinical treatment.An accurate assessment and precise staging of severity are essential in initial intensive therapy.AIM To explore the prognostic value of inflammatory markers and several scoring systems[Acute Physiology and Chronic Health Evaluation II,the bedside index of severity in AP(BISAP),Ranson’s score,the computed tomography severity index(CTSI)and sequential organ failure assessment]in severity stratification of earlyphase AP.METHODS A total of 463 patients with AP admitted to our hospital between 1 January 2021 and 30 June 2024 were retrospectively enrolled in this study.Inflammation marker and scoring system levels were calculated and compared between different severity groups.Relationships between severity and several predictors were evaluated using univariate and multivariate logistic regression models.Predictive ability was estimated using receiver operating characteristic curves.RESULTS Of the 463 patients,50(10.80%)were classified as having severe AP(SAP).The results revealed that the white cell count significantly increased,whereas the prognostic nutritional index measured within 48 hours(PNI48)and calcium(Ca^(2+))were decreased as the severity of AP increased(P<0.001).According to multivariate logistic regression,C-reactive protein measured within 48 hours(CRP_(48)),Ca^(2+)levels,and PNI48 were independent risk factors for predicting SAP.The area under the curve(AUC)values for the CRP_(48),Ca^(2+),PNI48,Acute Physiology and Chronic Health Evaluation II,sequential organ failure assessment,BISAP,CTSI,and Ranson scores for the prediction of SAP were 0.802,0.736,0.871,0.799,0.783,0.895,0.931 and 0.914,respectively.The AUC for the combined CRP_(48)+Ca^(2+)+PNI48 model was 0.892.The combination of PNI48 and Ranson achieved an AUC of 0.936.CONCLUSION Independent risk factors for developing SAP include CRP_(48),Ca^(2+),and PNI48.CTSI,BISAP,and the combination of PNI48 and the Ranson score can act as reliable predictors of SAP.展开更多
This editorial comments on the study by Tao et al,emphasizing the scalable diagnostic tool for metabolic dysfunction-associated steatotic liver disease(MASLD)in type 2 diabetes mellitus(T2DM).Classical indices such as...This editorial comments on the study by Tao et al,emphasizing the scalable diagnostic tool for metabolic dysfunction-associated steatotic liver disease(MASLD)in type 2 diabetes mellitus(T2DM).Classical indices such as the fatty liver index(FLI),hepatic steatosis index(HSI),and non-alcoholic fatty liver disease-liver fat score have provided valuable insights.Still,their predictive accuracy often varies across populations and clinical settings.In Western cohorts,FLI and HSI are widely applied,yet they depend heavily on anthropometric or categorical variables,which limits their sensitivity in Asian populations.The Zhejiang University index(ZJU index),developed in China,integrates fasting glucose,triglycerides,hepatic enzyme ratios,and body mass index into a composite score of insulin resistance.Recent studies show that the ZJU index outperforms FLI and HSI in predicting MASLD among Chinese patients,particularly those with T2DM,where it demonstrates a nonlinear association with disease risk and identifies a critical threshold of 38.87.The ZJU index links to conditions like sarcopenia,sleep apnea,and gallstones,showing its versatility in metabolic health.This editorial compares its performance with other indices and emphasizes the ZJU index as a nextgeneration tool for MASLD risk stratification globally.展开更多
Pulmonary embolism(PE)represents the third leading cause of cardiovascular death,despite the implementation of European Society of Cardiology guidelines,the establishment of PE response teams and advances in diagnosis...Pulmonary embolism(PE)represents the third leading cause of cardiovascular death,despite the implementation of European Society of Cardiology guidelines,the establishment of PE response teams and advances in diagnosis and treatment modalities.Unfavorable prognosis may be attributed to the increasing incidence of the disease and pitfalls in risk stratification using the established risk stratification tools that fail to recognize patients with intermediate-high risk PE at normotensive shock in order to prevent further deterioration.In this light,research has been focused to identify novel risk stratification tools,based on the hemodynamic impact of PE on right ventricular function.Furthermore,a growing body of evidence has demonstrated that novel interventional treatments for PE,including catheter directed thrombolysis,mechanical thrombectomy and computer-assisted aspiration,are promising solutions in terms of efficacy and safety,when targeted at specific populations of the intermediate-high-and high-risk spectrum.Various therapeutic protocols have been suggested worldwide,regarding the indications and proper timing for interventional strategies.A STelevation myocardial infarction-like timing approach has been suggested in highrisk PE with contraindications for fibrinolysis,while optimal timing of the procedure in intermediate-high risk patients is still a matter of debate;however,early interventions,within 24-48 hours of presentation,are associated with more favorable outcomes.展开更多
Gastrointestinal(GI)cancers exact a staggering global toll through high incidence,mortality,and treatment costs,yet clinical research continues to be hampered by inadequate patient stratification,challenging recruitme...Gastrointestinal(GI)cancers exact a staggering global toll through high incidence,mortality,and treatment costs,yet clinical research continues to be hampered by inadequate patient stratification,challenging recruitment,suboptimal adherence,and time-consuming endpoint confirmations.Against this backdrop,artificial intelligence(AI)emerges as a powerful game-changer,offering streamlined trial design,predictive enrollment matching,dynamic endpoint assessment,and realworld data integration.This review synthesizes AI-driven advancements across the GI cancer research continuum.It covers precise patient stratification,automated efficacy evaluations,and remote compliance management.The analysis also addresses persistent challenges in data standardization,privacy protection,and regulatory oversight.We underscore the need for synergistic clinician–AI collaboration,alongside robust frameworks that ensure interpretability and ethical deployment.By illuminating the potential of AI to accelerate trial timelines,refine patient selection,and enhance outcome measurement,we aim to inspire new strategies that can significantly reduce the global burden of GI malignancies.Ultimately,this work provides a blueprint for stakeholders seeking to harness AI’s transformative capabilities,fostering a future in which GI cancer clinical research becomes more agile,personalized,and impactful for patients and healthcare systems alike.展开更多
To the editor,The article by Vrancken Peeters and colleagues,1 showing updated five-year conditional relative survival(5-year CRS)for young breast cancer patients by relevant prognostic factors and longer follow-up th...To the editor,The article by Vrancken Peeters and colleagues,1 showing updated five-year conditional relative survival(5-year CRS)for young breast cancer patients by relevant prognostic factors and longer follow-up than previous European studies,2,3 has filled an important gap in knowledge for the most common cancer among young women.展开更多
The mathematical model for non-Newtonian magnetohydrodynamics flows across a vertically stretched surface with non-linear thermal radiation,mass and heat transfer rates,thermophoretic and Brownian movements,bio-convec...The mathematical model for non-Newtonian magnetohydrodynamics flows across a vertically stretched surface with non-linear thermal radiation,mass and heat transfer rates,thermophoretic and Brownian movements,bio-convection,and motile microbes considered in the present work.It is possible to regulate the nanomaterial suspension in the nanofluid using the growth of microbes.With the use of boundary layer approximation,highly nonlinear partial differential equations were derived for the present flow model.The nonlinear partial differential equations are converted into ordinary differential equations by utilizing similarity transmutations,which simplify them.Numerical elixirs for ordinary differential equations are found through bvp4c.This guarantees accurate results for profiles of temperature,concentration,velocity,and motile density.There is a good match between the numerical values shown graphically and the existing data.As the thermal radiation parameter rises,the flow temperature grows.Increasing Lewis number values is a sharp drop in the nanoparticle volume fraction.Bioconvection Lewis number reduces microorganism profiles.The research work focused on electrical systems,heat transfer,acoustics,chemical processing,rigid body dynamics,fluid mechanics,and solid mechanics,among others.展开更多
Background:Primary small cell carcinoma of the oesophagus(PSCCE)is a gastrointestinal tumour of rare onset.The current study was to investigate the role of a novel risk stratification system(RSS)for PSCCE.Methods:The ...Background:Primary small cell carcinoma of the oesophagus(PSCCE)is a gastrointestinal tumour of rare onset.The current study was to investigate the role of a novel risk stratification system(RSS)for PSCCE.Methods:The study included patients with PSCCE attending any of five medical institutions in China in 2008-2021,four of which served as a training set(n=422)for construction of the RSS while the other served as a separate cohort(n=256)for validation of the model.The RSS was established based on covariates associated with overall survival(OS)with a two-sided P-value of<0.05 in multivariable regression.Survival discrimination of RSS was assessed.Results:In the training cohort,multivariate regression analysis revealed age,Eastern Cooperative Oncology Group score,and initial lymph node metastasis to be independent prognostic factors for OS in non-distant metastatic PESCC;concurrent hepatic metastasis was the only significant predictor of distant metastatic PESCC.Accordingly,the RSS was developed and could classify patients into four subgroups:low-risk localized disease(LLD,defined as non-distant metastasis PESCC without risk factors,n=58);high-risk localized disease(HLD,defined as non-distant metastasis PESCC with≥1 risk factor,n=199);low-risk metastatic disease(LMD,defined as metastatic PESCC without concomitant liver metastases,n=103);and high-risk metastatic disease(HMD,definded as metastatic disease with synchronous liver metastases,n=63).Three-year OS rates were 52.5%,29.5%,14.4%,and 5.7%for LLD,HLD,LMD,and HMD,respectively.When compared with the tumor-node-metastasis(TNM)system,RSS showed a consistently superior ability to predict OS in both the training and validation cohorts.Conclusion:The RSS is a reliable stratification model that could be used to optimize treatment for PESCC.展开更多
The rapid evolution of cardiovascular(CV)research demands innovative strategies to enhance risk stratification,diagnosis,and management.While traditional biomarkers,such as natriuretic peptides and troponins,remain es...The rapid evolution of cardiovascular(CV)research demands innovative strategies to enhance risk stratification,diagnosis,and management.While traditional biomarkers,such as natriuretic peptides and troponins,remain essential,they often fall short due to suboptimal sensitivity and specificity,particularly in complex or early-stage cases.Emerging biomarkers are central to advancing personalized medicine by enabling earlier,more accurate detection of CV diseases and enhancing predictive algorithms,including those powered by artificial intelligence and machine learning.Among these novel biomarkers,dipeptidyl peptidase 3(DPP3)has recently garnered attention as a highly specific indicator of cardiogenic shock,offering both prognostic value and therapeutic target potential.Released during cellular stress,circulating DPP3(cDPP3)plays a mechanistic role in myocardial depression and blood pressure regulation,positioning it as a compelling candidate for inclusion in multi-marker panels.Its integration into predictive models could further refine therapeutic decision-making and patient stratification in acute cardiac care.This editorial discusses the clinical value of incorporating cDPP3 into CV biomarker research and advocates its inclusion in next-generation predictive algorithms and real-time decision-support tools.Continued exploration of such biomarkers may enable tailored interventions and improve outcomes in complex CV cases.展开更多
Metabolic dysfunction-associated steatotic liver disease(MASLD),formerly known as non-alcoholic fatty liver disease,represents a growing global health burden,contributing significantly to liver-related morbidity and m...Metabolic dysfunction-associated steatotic liver disease(MASLD),formerly known as non-alcoholic fatty liver disease,represents a growing global health burden,contributing significantly to liver-related morbidity and mortality.Early detection and timely intervention are essential to prevent disease progression.Conventional diagnostic methods,which rely on specialized imaging and invasive liver biopsies,underscore the need for non-invasive,cost-effective alternatives.Artificial intelligence—particularly machine learning and deep learning—has emerged as a transformative tool in MASLD diagnostics,offering improved accuracy in risk prediction,imaging interpretation,and disease stratification.This review synthesizes recent advancements in AI-based MASLD diagnostics,highlighting key models,performance metrics,and clinical applications,while addressing ongoing challenges such as data standardization,interpretability,and clinical validation.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42261134532,42405059,and U2342212)。
文摘This study investigates the relationship between atmospheric stratification (i.e., static stability given by N^(2)) and the vertical energy transfer of stationary planetary waves, and further illustrates the underlying physical mechanism. Specifically, for the simplified case of constant stratospheric N^(2), the refractive index square of planetary waves has a theoretical tendency to increase first and then decrease with an increased N^(2), whereas the group velocity weakens. Mechanistically, this behavior can be understood as an intensified suppression of vertical isentropic surface displacement caused by meridional heat transport of planetary waves under strong N^(2) conditions. Observational analysis corroborates this finding, demonstrating a reduction in the vertical-propagation velocity of waves with increased N^(2). A linear, quasi- geostrophic, mid-latitude beta-plane model with a constant background westerly wind and a prescribed N^(2) applicable to the stratosphere is used to obtain analytic solutions. In this model, the planetary waves are initiated by steady energy influx from the lower boundary. The analysis indicates that under strong N^(2) conditions, the amplitude of planetary waves can be sufficiently increased by the effective energy convergence due to the slowing vertical energy transfer, resulting in a streamfunction response in this model that contains more energy. For N^(2) with a quasi-linear vertical variation, the results bear a resemblance to the constant case, except that the wave amplitude and oscillating frequency show some vertical variations.
基金supported by the Laoshan Laboratory[grant number LSKJ202202403]the National Natural Science Foundation of China[grant number 42030410]+1 种基金additionally supported by the Startup Foundation for Introducing Talent of NUISTJiangsu Innovation Research Group[grant number JSSCTD202346]。
文摘Global warming induced by increased CO_(2) has caused marked changes in the ocean.Previous estimates of ocean salinity change in response to global warming have considerable ambiguity,largely attributable to the diverse sensitivities of surface fluxes.This study utilizes data from the Flux-Anomaly-Forced Model Intercomparison Project to investigate how ocean salinity responds to perturbations of surface fluxes.The findings indicate the emergence of a sea surface salinity(SSS)dipole pattern predominantly in the North Atlantic and Pacific fresh pools,driven by surface flux perturbations.This results in an intensification of the“salty gets saltier and fresh gets fresher”SSS pattern across the global ocean.The spatial pattern amplification(PA)of SSS under global warming is estimated to be approximately 11.5%,with surface water flux perturbations being the most significant contributor to salinity PA,accounting for 8.1% of the change after 70 years in experiments since pre-industrial control(piControl).Notably,the zonal-depth distribution of salinity in the upper ocean exhibits lighter seawater above the denser water,with bowed isopycnals in the upper 400 m.This stable stratification inhibits vertical mixing of salinity and temperature.In response to the flux perturbations,there is a strong positive feedback due to consequent freshening.It is hypothesized that under global warming,an SSS amplification of 7.2%/℃ and a mixed-layer depth amplification of 12.5%/℃ will occur in the global ocean.It suggests that the salinity effect can exert a more stable ocean to hinder the downward transfer of heat,which provides positive feedback to future global warming.
文摘Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamma-carboxy prothrombin(DCP),lack specificity,limiting their utility in risk strati-fication.YKL-40,a glycoprotein involved in extracellular matrix remodeling,hepatic stellate cell activation,and immune modulation,has emerged as a promising biomarker for post-LT surveillance.Elevated serum levels of YKL-40 are associated with advanced liver disease,tumor progression,and poorer post-LT outcomes,highlighting its potential to address gaps in early detection and personalized management of HCC recurrence.This manuscript synthesizes clinical and mechanistic evidence to evaluate YKL-40’s predictive utility in post-LT care.While preliminary findings demonstrate its specificity for liver-related pathologies,challenges remain,including assay standardization,lack of pro-spective validation,and the need to distinguish between malignant and non-malignant causes of elevated levels.Integrating YKL-40 into multi-biomarker panels with AFP and DCP could enhance predictive accuracy and enable tailored therapeutic strategies.Future research should focus on multicenter studies to validate YKL-40’s clinical utility,address confounding factors like graft rejection and systemic inflammation,and explore its role in predictive models driven by emerging technologies such as artificial intelligence.YKL-40 holds transformative potential in reshaping post-LT care through precision medicine,providing a pathway for better outcomes and improved management of high-risk LT recipients.
文摘Cardiovascular diseases(CVDs)remain the leading cause of morbidity and mortality worldwide,necessitating innovative diagnostic and prognostic strategies.Traditional biomarkers like C-reactive protein,uric acid,troponin,and natriuretic peptides play crucial roles in CVD management,yet they are often limited by sensitivity and specificity constraints.This narrative review critically examines the emerging landscape of cardiac biomarkers and advocates for a multiple-marker approach to enhance early detection,prognosis,and risk stratification of CVD.In recent years,several novel biomarkers have shown promise in revolutionizing CVD diagnostics.Gamma-glutamyltransferase,microRNAs,endothelial microparticles,placental growth factor,trimethylamine N-oxide,retinol-binding protein 4,copeptin,heart-type fatty acid-binding protein,galectin-3,growth differentiation factor-15,soluble suppression of tumorigenicity 2,fibroblast growth factor 23,and adrenomedullin have emerged as significant indicators of CV health.These biomarkers provide insights into various pathophysiological processes,such as oxidative stress,endothelial dysfunction,inflammation,metabolic disturbances,and myocardial injury.The integration of these novel biomarkers with traditional ones offers a more comprehensive understanding of CVD mechanisms.This multiple-marker approach can improve diagnostic accuracy,allowing for better risk stratification and more personalized treatment strategies.This review underscores the need for continued research to validate the clinical utility of these biomarkers and their potential incorporation into routine clinical practice.By leveraging the strengths of both traditional and novel biomarkers,precise therapeutic plans can be developed,thereby improving the management and prognosis of patients with CVDs.The ongoing exploration and validation of these biomarkers are crucial for advancing CV care and addressing the limitations of current diagnostic tools.
基金Supported by Joint Funds for the Innovation of Science and Technology,Fujian Province,No.2023Y9187 and No.2021Y9057.
文摘BACKGROUND Minimally invasive esophagectomy(MIE)is a widely accepted treatment for esophageal cancer,yet it is associated with a significant risk of surgical adverse events(SAEs),which can compromise patient recovery and long-term survival.Accurate preoperative identification of high-risk patients is critical for improving outcomes.AIM To establish and validate a risk prediction and stratification model for the risk of SAEs in patients with MIE.METHODS This retrospective study included 747 patients who underwent MIE at two centers from January 2019 to February 2024.Patients were separated into a train set(n=549)and a validation set(n=198).After screening by least absolute shrinkage and selection operator regression,multivariate logistic regression analyzed clinical and intraoperative variables to identify independent risk factors for SAEs.A risk stratification model was constructed and validated to predict the probability of SAEs.RESULTS SAEs occurred in 10.2%of patients in train set and 13.6%in the validation set.Patients with SAE had significantly higher complication rate and a longer hospital stay after surgery.The key independent risk factors identified included chronic obstructive pulmonary disease,a history of alcohol consumption,low forced expiratory volume in the first second,and low albumin levels.The stratification model has excellent prediction accuracy,with an area under the curve of 0.889 for the training set and an area under the curve of 0.793 for the validation set.CONCLUSION The developed risk stratification model effectively predicts the risk of SAEs in patients undergoing MIE,facilitating targeted preoperative interventions and improving perioperative management.
文摘Patients admitted with prediabetes and atrial fibrillation are at high risk for major adverse cardiac or cerebrovascular events independent of confounding variables.The shared pathophysiology between these three serious but common diseases and their association with atherosclerotic cardiovascular risk factors establish a vicious circle culminating in high atherogenicity.Because of that,it is of paramount importance to perform risk stratification of patients with prediabetes to define phenotypes that benefit from various interventions.Furthermore,stress hyperglycemia assessment of hospitalized patients and consensus on the definition of prediabetes is vital.The roles lifestyle and metformin play in prediabetes are well established.However,the role of glucagon-like peptide agonists and metabolic surgery is less clear.Prediabetes is considered an intermediate between normoglycemia and diabetes along the blood glucose continuum.One billion people are expected to suffer from prediabetes by the year 2045.Therefore,realworld randomized controlled trials to assess major adverse cardiac or cerebrovascular event risk reduction and reversal/prevention of type 2 diabetes among patients are needed to determine the proper interventions.
文摘Unheralded cardiac arrest among previously healthy young people without antecedent illness,months or years after coronavirus disease 2019(COVID-19)vaccination,highlights the urgent need for risk stratification.The most likely underlying pathophysiology is subclinical myopericarditis and reentrant ventri-cular tachycardia or spontaneous ventricular fibrillation that is commonly preci-pitated after a surge in catecholamines during exercise or the waking hours of terminal sleep.Small patches of inflammation and/or edema can be missed on cardiac imaging and autopsy,and the heart can appear grossly normal.This paper reviews evidence linking COVID-19 vaccines to cardiac arrest where unfortu-nately the majority of victims have had no antecedent clinical evaluation.We propose a comprehensive strategy for evaluating cardiovascular risk post-vaccination,incorporating detailed patient history,antibody testing,and cardiac diagnostics in the best attempt to detect abnormalities before sudden cardiac death.This approach aims to identify individuals at higher risk of cardiac events after COVID-19 vaccination and guide appropriate clinical management.It is prudent for each primary care physician to have a pre-established plan when addressing this issue in their practice.
文摘A recent single-center retrospective study proposed novel combinations of hematological parameters and scoring systems for predicting severe acute pancre-atitis.While these combinations showed promising predictive performance,several limitations warrant consideration,including the lack of calibration,the absence of key inflammatory markers such as procalcitonin,and practical challenges in integrating these models into routine clinical workflows.To improve predictive accuracy and clinical applicability,prospective validation and the inclusion of additional variables are recommended.
基金supported by the Beijing Nova Program of Science and Technology(grant number:20230484397)the National Natural Science Foundation of China(grant number:82273726).
文摘1.Introduction With an estimate of 19,976,499 newly diagnosed cases and 9,743,832 deaths occurred in 2022 worldwide,cancer continues to impose a significant health and economic burden worldwide.1 The development of cancer is a complex interplay between genetic and environmental factors.2 In addition to genetic modifications,there is a growing body of evidence suggesting that epigenetic changes,which influence gene expression without modifying the DNA sequence,are playing an increasingly significant role in the development of cancer.DNA methylation,a key epigenetic mechanism,has been notably implicated in the early stages of cancer development,positioning it as a potential biomarker for cancer risk assessment.3 Studies have identified a diverse array of DNA methylation biomarkers for the early detection and diagnosis of cancer,utilizing DNA extracted from tissues,blood,stool,urine,and bowel lavage fluid.4 Research of DNA methylation has focused on two primary sources:peripheral blood mononuclear cell or white blood cell(WBC)DNA methylation,5 linked to cancer susceptibility and tumor-derived cell-free DNA(cfDNA)methylation,6 which has gained significant attention in recent years as a promising biomarker for cancer screening and diagnosis.
文摘The variable salinity in stored reservoirs connected by a long channel attracts the attention of scientists worldwide,having applications in environmental and geophysical engineering.This study explores the impact of Navier slip conditions on exchange flows within a long channel connecting two large reservoirs of differing salinity.These horizontal density gradients drive the flow.We modify the recent one-dimensional theory,developed to avoid runaway stratification,to account for the presence of uniform slip walls.By adjusting the parameters of the horizontal density gradient based on the slip factor,we resolve analytically various flow regimes ranging from high diffusion to transitional high advection.These regimes are governed by physical parameters like channel aspect ratio,slip factor,Schmidt number,and gravitational Reynolds number.Our solutions align perfectly with ones in the no-slip limit.More importantly,under the conditions of no net flow across the channel and high Schmidt number(where stratification is concentrated near the channel’s mid-layer),we derive a closed-form solution for the slip parameter,aspect ratio,and gravitational Reynolds number that describes the interface’s behavior as a sharp interface separating two distinct zones.This interface,arising from hydrostatic wall gradients,ultimately detaches the low-and high-density regimes throughout the channel when the gravitational Reynolds number is inversely proportional to the aspect ratio for a fixed slip parameter.This phenomenon,observed previously in 2D numerical simulations with no-slip walls in the literature,is thus confirmed by our theoretical results.Our findings further demonstrate that wall slip leads to distinct and diverse flow regimes.
基金supported by the Shanghai Municipal Health Commission(201840063,201801075)the Science and Technology Commission of Shanghai Municipality(18441903300).
文摘Background:Spontaneous intracerebral hemorrhage(ICH)is a severe neurological emergency with high morbidity and mortality.The effectiveness of surgical intervention remains controversial,partly due to significant heterogeneity among patients.Traditional clinical criteria often fail to identify those most likely to benefit from surgery.Methods:This nationwide retrospective study in China included 2,167 ICH patients from 31 hospitals.Using machine learning techniques,we integrated clinical and radiomic data to perform unsupervised clustering and identify distinct phenogroups.Dimensionality reduction and cross-validation were applied to minimize overfitting.External validation was conducted using data from the INTERACT3 trial,and a prospective cohort was used to assess real-world applicability.Results:Three phenogroups were identified.Among them,only Phenogroup 1-characterized by older age,moderate hematoma volume,and intermediate Glasgow Coma Scale scores-showed significant benefit from early surgical intervention,with a 42%reduction in 3-month mortality and improved functional outcomes.In contrast,surgery did not significantly affect outcomes in Phenogroups 0 and 2.These findings were consistent across multiple machine learning models and validated externally.Conclusion:Machine learning-driven phenotypic stratification can effectively identify ICH patients who are most likely to benefit from surgical treatment.This approach supports personalized treatment strategies and may improve clinical decision-making in ICH management.Further validation in diverse populations is warranted.
文摘BACKGROUND Acute pancreatitis(AP)is an emergency gastrointestinal disease that requires immediate diagnosis and urgent clinical treatment.An accurate assessment and precise staging of severity are essential in initial intensive therapy.AIM To explore the prognostic value of inflammatory markers and several scoring systems[Acute Physiology and Chronic Health Evaluation II,the bedside index of severity in AP(BISAP),Ranson’s score,the computed tomography severity index(CTSI)and sequential organ failure assessment]in severity stratification of earlyphase AP.METHODS A total of 463 patients with AP admitted to our hospital between 1 January 2021 and 30 June 2024 were retrospectively enrolled in this study.Inflammation marker and scoring system levels were calculated and compared between different severity groups.Relationships between severity and several predictors were evaluated using univariate and multivariate logistic regression models.Predictive ability was estimated using receiver operating characteristic curves.RESULTS Of the 463 patients,50(10.80%)were classified as having severe AP(SAP).The results revealed that the white cell count significantly increased,whereas the prognostic nutritional index measured within 48 hours(PNI48)and calcium(Ca^(2+))were decreased as the severity of AP increased(P<0.001).According to multivariate logistic regression,C-reactive protein measured within 48 hours(CRP_(48)),Ca^(2+)levels,and PNI48 were independent risk factors for predicting SAP.The area under the curve(AUC)values for the CRP_(48),Ca^(2+),PNI48,Acute Physiology and Chronic Health Evaluation II,sequential organ failure assessment,BISAP,CTSI,and Ranson scores for the prediction of SAP were 0.802,0.736,0.871,0.799,0.783,0.895,0.931 and 0.914,respectively.The AUC for the combined CRP_(48)+Ca^(2+)+PNI48 model was 0.892.The combination of PNI48 and Ranson achieved an AUC of 0.936.CONCLUSION Independent risk factors for developing SAP include CRP_(48),Ca^(2+),and PNI48.CTSI,BISAP,and the combination of PNI48 and the Ranson score can act as reliable predictors of SAP.
文摘This editorial comments on the study by Tao et al,emphasizing the scalable diagnostic tool for metabolic dysfunction-associated steatotic liver disease(MASLD)in type 2 diabetes mellitus(T2DM).Classical indices such as the fatty liver index(FLI),hepatic steatosis index(HSI),and non-alcoholic fatty liver disease-liver fat score have provided valuable insights.Still,their predictive accuracy often varies across populations and clinical settings.In Western cohorts,FLI and HSI are widely applied,yet they depend heavily on anthropometric or categorical variables,which limits their sensitivity in Asian populations.The Zhejiang University index(ZJU index),developed in China,integrates fasting glucose,triglycerides,hepatic enzyme ratios,and body mass index into a composite score of insulin resistance.Recent studies show that the ZJU index outperforms FLI and HSI in predicting MASLD among Chinese patients,particularly those with T2DM,where it demonstrates a nonlinear association with disease risk and identifies a critical threshold of 38.87.The ZJU index links to conditions like sarcopenia,sleep apnea,and gallstones,showing its versatility in metabolic health.This editorial compares its performance with other indices and emphasizes the ZJU index as a nextgeneration tool for MASLD risk stratification globally.
文摘Pulmonary embolism(PE)represents the third leading cause of cardiovascular death,despite the implementation of European Society of Cardiology guidelines,the establishment of PE response teams and advances in diagnosis and treatment modalities.Unfavorable prognosis may be attributed to the increasing incidence of the disease and pitfalls in risk stratification using the established risk stratification tools that fail to recognize patients with intermediate-high risk PE at normotensive shock in order to prevent further deterioration.In this light,research has been focused to identify novel risk stratification tools,based on the hemodynamic impact of PE on right ventricular function.Furthermore,a growing body of evidence has demonstrated that novel interventional treatments for PE,including catheter directed thrombolysis,mechanical thrombectomy and computer-assisted aspiration,are promising solutions in terms of efficacy and safety,when targeted at specific populations of the intermediate-high-and high-risk spectrum.Various therapeutic protocols have been suggested worldwide,regarding the indications and proper timing for interventional strategies.A STelevation myocardial infarction-like timing approach has been suggested in highrisk PE with contraindications for fibrinolysis,while optimal timing of the procedure in intermediate-high risk patients is still a matter of debate;however,early interventions,within 24-48 hours of presentation,are associated with more favorable outcomes.
文摘Gastrointestinal(GI)cancers exact a staggering global toll through high incidence,mortality,and treatment costs,yet clinical research continues to be hampered by inadequate patient stratification,challenging recruitment,suboptimal adherence,and time-consuming endpoint confirmations.Against this backdrop,artificial intelligence(AI)emerges as a powerful game-changer,offering streamlined trial design,predictive enrollment matching,dynamic endpoint assessment,and realworld data integration.This review synthesizes AI-driven advancements across the GI cancer research continuum.It covers precise patient stratification,automated efficacy evaluations,and remote compliance management.The analysis also addresses persistent challenges in data standardization,privacy protection,and regulatory oversight.We underscore the need for synergistic clinician–AI collaboration,alongside robust frameworks that ensure interpretability and ethical deployment.By illuminating the potential of AI to accelerate trial timelines,refine patient selection,and enhance outcome measurement,we aim to inspire new strategies that can significantly reduce the global burden of GI malignancies.Ultimately,this work provides a blueprint for stakeholders seeking to harness AI’s transformative capabilities,fostering a future in which GI cancer clinical research becomes more agile,personalized,and impactful for patients and healthcare systems alike.
基金supported by the Italian Association for Cancer Re-search(AIRC)(grant number:28893)the Italian Ministry of Health(Ricerca Corrente)(no grant number).
文摘To the editor,The article by Vrancken Peeters and colleagues,1 showing updated five-year conditional relative survival(5-year CRS)for young breast cancer patients by relevant prognostic factors and longer follow-up than previous European studies,2,3 has filled an important gap in knowledge for the most common cancer among young women.
基金U.F.-G.was supported by the Mobility Lab Foundation,a governmental organization of the Provincial Council of Araba,and the local council of Vitoria-Gasteiz.S.Noeiaghdam was supported by the Henan Academy of Sciences(Project No.241819246).
文摘The mathematical model for non-Newtonian magnetohydrodynamics flows across a vertically stretched surface with non-linear thermal radiation,mass and heat transfer rates,thermophoretic and Brownian movements,bio-convection,and motile microbes considered in the present work.It is possible to regulate the nanomaterial suspension in the nanofluid using the growth of microbes.With the use of boundary layer approximation,highly nonlinear partial differential equations were derived for the present flow model.The nonlinear partial differential equations are converted into ordinary differential equations by utilizing similarity transmutations,which simplify them.Numerical elixirs for ordinary differential equations are found through bvp4c.This guarantees accurate results for profiles of temperature,concentration,velocity,and motile density.There is a good match between the numerical values shown graphically and the existing data.As the thermal radiation parameter rises,the flow temperature grows.Increasing Lewis number values is a sharp drop in the nanoparticle volume fraction.Bioconvection Lewis number reduces microorganism profiles.The research work focused on electrical systems,heat transfer,acoustics,chemical processing,rigid body dynamics,fluid mechanics,and solid mechanics,among others.
基金supported by the Fujian Key Laboratory of Intelligent Imaging and Precision Radiother-apy for Tumors(Fujian Medical University)the Clinical Research Center for Radiology and Radiotherapy of Fujian Province(Digestive,Hematological and Breast Malignancies).
文摘Background:Primary small cell carcinoma of the oesophagus(PSCCE)is a gastrointestinal tumour of rare onset.The current study was to investigate the role of a novel risk stratification system(RSS)for PSCCE.Methods:The study included patients with PSCCE attending any of five medical institutions in China in 2008-2021,four of which served as a training set(n=422)for construction of the RSS while the other served as a separate cohort(n=256)for validation of the model.The RSS was established based on covariates associated with overall survival(OS)with a two-sided P-value of<0.05 in multivariable regression.Survival discrimination of RSS was assessed.Results:In the training cohort,multivariate regression analysis revealed age,Eastern Cooperative Oncology Group score,and initial lymph node metastasis to be independent prognostic factors for OS in non-distant metastatic PESCC;concurrent hepatic metastasis was the only significant predictor of distant metastatic PESCC.Accordingly,the RSS was developed and could classify patients into four subgroups:low-risk localized disease(LLD,defined as non-distant metastasis PESCC without risk factors,n=58);high-risk localized disease(HLD,defined as non-distant metastasis PESCC with≥1 risk factor,n=199);low-risk metastatic disease(LMD,defined as metastatic PESCC without concomitant liver metastases,n=103);and high-risk metastatic disease(HMD,definded as metastatic disease with synchronous liver metastases,n=63).Three-year OS rates were 52.5%,29.5%,14.4%,and 5.7%for LLD,HLD,LMD,and HMD,respectively.When compared with the tumor-node-metastasis(TNM)system,RSS showed a consistently superior ability to predict OS in both the training and validation cohorts.Conclusion:The RSS is a reliable stratification model that could be used to optimize treatment for PESCC.
文摘The rapid evolution of cardiovascular(CV)research demands innovative strategies to enhance risk stratification,diagnosis,and management.While traditional biomarkers,such as natriuretic peptides and troponins,remain essential,they often fall short due to suboptimal sensitivity and specificity,particularly in complex or early-stage cases.Emerging biomarkers are central to advancing personalized medicine by enabling earlier,more accurate detection of CV diseases and enhancing predictive algorithms,including those powered by artificial intelligence and machine learning.Among these novel biomarkers,dipeptidyl peptidase 3(DPP3)has recently garnered attention as a highly specific indicator of cardiogenic shock,offering both prognostic value and therapeutic target potential.Released during cellular stress,circulating DPP3(cDPP3)plays a mechanistic role in myocardial depression and blood pressure regulation,positioning it as a compelling candidate for inclusion in multi-marker panels.Its integration into predictive models could further refine therapeutic decision-making and patient stratification in acute cardiac care.This editorial discusses the clinical value of incorporating cDPP3 into CV biomarker research and advocates its inclusion in next-generation predictive algorithms and real-time decision-support tools.Continued exploration of such biomarkers may enable tailored interventions and improve outcomes in complex CV cases.
文摘Metabolic dysfunction-associated steatotic liver disease(MASLD),formerly known as non-alcoholic fatty liver disease,represents a growing global health burden,contributing significantly to liver-related morbidity and mortality.Early detection and timely intervention are essential to prevent disease progression.Conventional diagnostic methods,which rely on specialized imaging and invasive liver biopsies,underscore the need for non-invasive,cost-effective alternatives.Artificial intelligence—particularly machine learning and deep learning—has emerged as a transformative tool in MASLD diagnostics,offering improved accuracy in risk prediction,imaging interpretation,and disease stratification.This review synthesizes recent advancements in AI-based MASLD diagnostics,highlighting key models,performance metrics,and clinical applications,while addressing ongoing challenges such as data standardization,interpretability,and clinical validation.
