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
Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geos...Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota （SD） U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit （PSU） level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service （NASS） ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency （FSA） Common Land Unit （CLU） and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.展开更多
Recent advancements in genome sequencing have enabled the estimation of genetic load through deleterious mutation profiling.However,Chinese populations remain underexplored in this context.We analyze whole-exome seque...Recent advancements in genome sequencing have enabled the estimation of genetic load through deleterious mutation profiling.However,Chinese populations remain underexplored in this context.We analyze whole-exome sequencing data from 5002 individuals,encompassing major Han subgroups―North Han(NHan),South Han(S-Han),and Guangxi Han(G-Han)―as well as 13 ethnic minorities.Notably,G-Han exhibits significant genetic affinity with the Zhuang population.Systematic curation of 2110 ClinVar pathogenic or likely pathogenic variants reveals 93.4%are ultra-rare.Exceptions include GJB2 rs72474224-A(hearing loss),which shows higher frequencies in Zhuang and G-Han,and β-thalassemia-associated HBB variants(rs33986703-A and rs33950507-T),which are elevated in G-Han compared to other Han subgroups.Among 96 autosomal dominant mutation carriers,LDLR variants are predominant(~25%),with comparable frequencies across Han subgroups.Adaptive signatures highlight gene-environment interactions:MTHFR rs1801133-A(UV adaptation)declines southward,while ALDH2 rs671-A(alcohol metabolism)displays the opposite trend.ABCC11 rs17822931-A,associated with cold adaptation,is particularly low frequency in G-Han.Gene-based rare-variant collapsing analyses identify an elevated risk of retinitis pigmentosa in S-Han(PRPF4,TUB).Our findings demonstrate that genetic load in Chinese populations is influenced by demographic history,population structure,and regional adaptation,emphasizing the importance of population-specific frameworks in precision medicine.展开更多
Space-filling designs with superior low-dimensional properties are highly required in computer experiments.Strong orthogonal arrays(SOAs)represent a class of such designs that outperform ordinary orthogonal arrays in ...Space-filling designs with superior low-dimensional properties are highly required in computer experiments.Strong orthogonal arrays(SOAs)represent a class of such designs that outperform ordinary orthogonal arrays in their stratification properties within low dimensions.Nevertheless,current methods for constructing high-strength SOAs are rare,and they typically rely on regular designs,thereby limiting the number of runs in the final arrays to prime powers.This study presents new construction methods for three types of SOAs:SOAs of strength three,column-orthogonal SOAs(OSOAs)of strength three and three minus.The resulting designs have run sizes of twice an odd prime power without replications,filling the gaps in run sizes left by existing constructions.The projection properties of Addelman–Kempthorne orthogonal arrays are instrumental in the development of these construction methods.展开更多
Radiopharmaceuticals deliver diagnostic or therapeutic radionuclides to disease sites with molecular precision.Over the past five years,clinical adoption has accelerated,led by U.S.Food and Drug Administration approva...Radiopharmaceuticals deliver diagnostic or therapeutic radionuclides to disease sites with molecular precision.Over the past five years,clinical adoption has accelerated,led by U.S.Food and Drug Administration approvals of 177Lu-DOTA-TATE and 177Lu-PSMA-617 and their complementary Positron Emission Tomography agents(68Ga-DOTA-TATE,68Ga-PSMA-11),which have established radiotheranostics as a pillar of oncology care.The new generation of agents couples optimized radionuclides(β-,α,and Auger emitters)to antibodies,peptides,and small-molecule vectors that improve tumor uptake,residence time,and clearance profiles,thereby enhancing efficacy and safety.Beyond neuroendocrine tumors and prostate cancer,radiotheranostic strategies are advancing for diverse malignancies by exploiting tumor-specific antigens,overexpressed receptors,and intracellular targets.Notably,α-emitters such as 225Ac and 211At—owing to high linear energy transfer and short path length—show potent cytotoxicity with limited off-target injury,while emergingβ/Auger emitters like 161Tb may surpass 177Lu in microdosimetric effectiveness.Concurrent innovations in patient selection and response prediction leverage diagnostic radiopharmaceuticals for image-guided stratification,individualized dosimetry,and adaptive treatment planning,supporting the broader paradigm of precision medicine.Although oncology remains the primary focus,applications are expanding to neurodegeneration,cardiovascular disease,and inflammatory conditions.This review synthesizes technological and clinical progress from 2021-2025,spanning FDA-approved and late-stage investigational agents;mechanisms of radiopharmaceutical-induced cell death;dosimetry methodologies;trial landscapes for expanding indications;and translational challenges,including supply chains,chelation chemistry,and toxicity management.Accordingly,this review focuses on the latest radiopharmaceutical diagnostic and therapeutic technologies,integrating advances in radionuclide platforms,targeting vectors,dosimetry,and clinical trial data from 2021-2025 to guide future development and clinical implementation of precision radiotheranostics.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
Background:Drug-coated balloons(DCBs)are receiving increasing attention in interventional therapy for coronary artery disease.However,evidence regarding their application in acute myocardial infarction(AMI),particular...Background:Drug-coated balloons(DCBs)are receiving increasing attention in interventional therapy for coronary artery disease.However,evidence regarding their application in acute myocardial infarction(AMI),particularly in high-risk AMI patients,is limited,leading to significant clinical concerns.This study aims to compare the efficacy and safety of DCBs versus standard drug-eluting stents(DESs)in AMI patients and explore their efficacy differences in patients with ST-segment elevation myocardial infarction(STEMI),non-ST-segment elevation myocardial infarction(NSTEMI),and different risk stratifications.Methods:A single-center,retrospective cohort study was conducted,involving 86 patients who underwent percutaneous coronary intervention(PCI)for AMI between January 2023 and July 2025.Patients were divided into a DCB group(n=26)and a DES group(n=60)based on the treatment modality.According to the Killip classification of myocardial infarction at admission,patients were categorized into a low-risk group(Killip Class I,n=68)and a high-risk group(Killip Classes II-IV,n=18).The primary efficacy endpoint was targeting lesion restenosis as shown by coronary angiography follow-up(6-12 months).Safety endpoints included acute in-stent thrombosis during hospitalization(ARC criteria)and long-term coronary slow flow.A multivariate logistic regression model was used to evaluate the associations between intervention modality,risk stratification,infarction type,and endpoint events,and to test for interactions.Results:The DCB and DES groups were generally balanced in terms of baseline traditional risk factors.During hospitalization,three cases(5.0%)of acute in-stent thrombosis occurred in the DES group,all requiring urgent re-intervention,while no such events occurred in the DCB group(0%).Acute in-stent thrombosis formation was significantly associated with high-risk stratification(χ2 test,p=0.047).The overall restenosis rate was 22.1%(19/86).Multivariate analysis showed no statistically significant difference in restenosis risk between the intervention modalities(DCB vs.DES)(adjusted odds ratio[OR]=1.07,95%confidence interval[CI]0.27-4.21,p=0.920),and no statistical differences were found in subgroups based on risk stratification(p=0.382)or infarction type(p=0.484).There was a trend toward increased restenosis risk in high-risk patients(OR=12.34),but the difference was not statistically significant(95%CI 0.28-542.75,p=0.193).The incidence of long-term coronary slow flow was significantly higher in the DES group than in the DCB group(16.7%vs.3.8%,Fisher’s exact test,p=0.048),with a statistically significant difference.Conclusion:For AMI patients,DCBs demonstrate similar efficacy to DESs in preventing restenosis.However,DESs are associated with a higher risk of acute thrombosis during hospitalization,especially in high-risk patients,and a higher risk of long-term slow coronary flow.DCBs exhibit superior perioperative and long-term safety compared to DESs.Given the limited sample size,particularly the small number of high-risk patients and those treated with DCBs,the conclusions require validation through larger-scale prospective studies.展开更多
Triple-negative breast cancer(TNBC)is the most challenging breast cancer subtype.Molecular stratification and target therapy bring clinical benefit for TNBC patients,but it is difficult to implement comprehensive mole...Triple-negative breast cancer(TNBC)is the most challenging breast cancer subtype.Molecular stratification and target therapy bring clinical benefit for TNBC patients,but it is difficult to implement comprehensive molecular testing in clinical practice.Here,using our multi-omics TNBC cohort(N=425),a deep learning-based framework was devised and validated for comprehensive predictions of molecular features,subtypes and prognosis from pathological whole slide images.The framework first incorporated a neural network to decompose the tissue on WSIs,followed by a second one which was trained based on certain tissue types for predicting different targets.Multi-omics molecular features were analyzed including somatic mutations,copy number alterations,germline mutations,biological pathway activities,metabolomics features and immunotherapy biomarkers.It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation,germline BRCA2 mutation and PD-L1 protein expression(area under the curve[AUC]:0.78,0.79 and 0.74 respectively).The molecular subtypes of TNBC can be identified(AUC:0.84,0.85,0.93 and 0.73 for the basal-like immune-suppressed,immunomodulatory,luminal androgen receptor,and mesenchymal-like subtypes respectively)and their distinctive morphological patterns were revealed,which provided novel insights into the heterogeneity of TNBC.A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes(log-rank P<0.001).Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA(N=143)and appeared robust to the changes in patient population.For potential clinical translation,we built a novel online platform,where we modularized and deployed our framework along with the validated models.It can realize real-time one-stop prediction for new cases.In summary,using only pathological WSIs,our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making.It had the potential to be clinically implemented and promote the personalized management of TNBC.展开更多
BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized p...BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized prognostic models that can effectively predict esophagogastric variceal rebleeding in patients with liver cirrhosis are lacking.AIM To construct and externally validate a reliable prognostic model for predicting the occurrence of esophagogastric variceal rebleeding.METHODS This study included 477 EGVB patients across 2 cohorts:The derivation cohort(n=322)and the validation cohort(n=155).The primary outcome was rebleeding events within 1 year.The least absolute shrinkage and selection operator was applied for predictor selection,and multivariate Cox regression analysis was used to construct the prognostic model.Internal validation was performed with bootstrap resampling.We assessed the discrimination,calibration and accuracy of the model,and performed patient risk stratification.RESULTS Six predictors,including albumin and aspartate aminotransferase concentrations,white blood cell count,and the presence of ascites,portal vein thrombosis,and bleeding signs,were selected for the rebleeding event prediction following endoscopic treatment(REPET)model.In predicting rebleeding within 1 year,the REPET model ex-hibited a concordance index of 0.775 and a Brier score of 0.143 in the derivation cohort,alongside 0.862 and 0.127 in the validation cohort.Furthermore,the REPET model revealed a significant difference in rebleeding rates(P<0.01)between low-risk patients and intermediate-to high-risk patients in both cohorts.CONCLUSION We constructed and validated a new prognostic model for variceal rebleeding with excellent predictive per-formance,which will improve the clinical management of rebleeding in EGVB patients.展开更多
As a crucial component of the Earth’s climate system,Antarctic sea ice has demonstrated significant variability over the satellite era.Here,we identify a remarkable decadal transition in the total Antarctic Sea Ice E...As a crucial component of the Earth’s climate system,Antarctic sea ice has demonstrated significant variability over the satellite era.Here,we identify a remarkable decadal transition in the total Antarctic Sea Ice Extent(SIE).The stage from 1979 to 2006 is characterized by high-frequency(i.e.,seasonal to interannual)temporal variability in SIE and zonal asymmetry in Sea Ice Concentration(SIC),which is primarily under the control of the Amundsen Sea Low(ASL).After 2007,however,sea ice changes exhibit a more spatially homogeneous pattern in SIC and a more temporally long-lasting mode in SIE.Further analysis reveals that sea ice-ocean interaction plays a major role in the low-frequency(i.e.,multiannual)variability of Antarctic sea ice from 2007−22.The related physical process is inferred to manifest as a strong coupling between the surface and the subsurface ocean layers,involving enhanced vertical convection and the downward delivery of the surface anomalies related to ice melting and freezing processes,thus maintaining the SIE anomalies for a longer time.Furthermore,this process mainly occurs in the Amundsen-Bellingshausen Sea(ABS)sector,and the weakened subsurface ocean stratification is the key factor triggering the coupling process in this region.We find that the Circumpolar Deep Water(CDW)over the ABS sector continued to shoal before 2007 and remained stable thereafter.It is speculated that the shoaling of the CDW may be a possible driver leading to the weakening of the subsurface stratification.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
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 are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with...Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with artificial intelligence(AI)playing a key role in analyzing complex data to improve diagnostic accuracy,predict outcomes,and optimize therapies.AI can identify patterns in imaging and biomarkers,facilitating the earlier detection of medical conditions.Wearable devices and health applications facilitate continuous monitoring and personalized care.Emerging fields such as digital Chinese medicine offer additional perspectives by integrating traditional diagnostic principles with modern digital tools,contributing to holistic and individualized cardiovascular care.This study examines the advancements and challenges in personalized cardiovascular medicine,highlighting the need to address issues such as data privacy,algorithmic bias,and accessibility to promote the equitable application of personalized medicine.展开更多
Prognostication of compensated advanced chronic liver disease(cACLD)is of paramount importance for the physician-and-patient communication and for rational clinical decisions.The paper published by Dallio et al report...Prognostication of compensated advanced chronic liver disease(cACLD)is of paramount importance for the physician-and-patient communication and for rational clinical decisions.The paper published by Dallio et al reports on red cell distribution width(RDW)/platelet ratio(RPR)as a non-invasive biomarker in predicting decompensation of metabolic dysfunction-associated steatotic liver disease(MASLD)-related cACLD.Differently from other biomarkers and algorithms,RPR is inexpensive and widely available,based on parameters which are included in a complete blood count.RPR is computed on the grounds of two different items,one of which,RDW,mirrors the host’s response to a variety of disease stimuli and is non-specific.The second parameter involved in RPR,platelet count,is more specific and has been used in the hepatological clinic to discriminate cirrhotic from non-cirrhotic chronic liver disease for decades.Cardiovascular disease is the primary cause of mortality among MASLD subjects,followed by extra-hepatic cancers and liver-related mortality.Therefore,MASLD biomarkers should be validated not only in terms of liver-related events but also in the prediction of major adverse cardiovascular events and cardiovascular mortality and extra-hepatic cancers.Adequately sized multi-ethnic confirmatory investigation is required to define the role and significance of RPR in the stratification of MASLD-cACLD.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
Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predi...Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predict NDMM patient outcomes. The Durie-Salmon (D-S) staging system reflects tumor burden and clinical progression staging with prognostic value.展开更多
Indonesia is an archipelago located in a tropical climate zone that is home to 17%of the world's creatures,buthuman disturbances still threaten the existence of bird species in Indonesia.This encourages bird conse...Indonesia is an archipelago located in a tropical climate zone that is home to 17%of the world's creatures,buthuman disturbances still threaten the existence of bird species in Indonesia.This encourages bird conservation effortsboth through conservation areas and community forests.This study aims to determine the diversity and interaction ofbirds with the vegetation stratum in the community forest of Gunungkelir Hamlet,Jatimulyo Village,Kulon ProgoRegency,Yogyakarta.This research was conducted from February to March 2024,using a combination of line transect,point count,and rapid assessment methods for bird observation.Data were analyzed using diversity index(H'),evenness(E),and relative abundance.Vegetation stratum data used in vegetation analysis through nested plot sampling to obtainthe Important Value Index(IVI).The results showed that there were 21 species from 13 bird families;the diversity valueobtained on the three lanes was 2.62 on lane 1,1.84 on lane 2,and 1.79 on lane 3.The Albizia chinensis species hadthe highest IVI value at the seedling and sapling levels,with(67%)and(76.4%),respectively;then cloves obtained thehighest IVI value at the pole and tree levels with(84.5%)and(81.3%).The majority of birds,comprising as many as15 species,were found in stratum C,followed by stratum D,which had as many as 8 species,stratum E with 3 species,stratum B with 2 species,and no birds were found in stratum A.The most common form of vegetation utilizationfound was resting.Birds utilized the stratum layer to rest,play,and find food.Understanding bird ecology also meansunderstanding human safety in wisely managing forest ecosystems.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
BACKGROUND Acute liver failure(ALF)with sepsis is associated with rapid disease progression and high mortality.Therefore,early detection of high-risk sepsis subgroups in patients with ALF is crucial.AIM To develop and...BACKGROUND Acute liver failure(ALF)with sepsis is associated with rapid disease progression and high mortality.Therefore,early detection of high-risk sepsis subgroups in patients with ALF is crucial.AIM To develop and validate an accurate nomogram model for predicting the risk of sepsis in patients with ALF.METHODS We retrieved data from the Medical Information Mart for Intensive Care(MIMIC)IV database and the Fifth Medical Center of Chinese PLA General Hospital(FMCPH).Univariate and multivariate logistic regression analysis were used to identify risk factors for sepsis in ALF and were subsequently incorporated to construct a nomogram model[sepsis in ALF(SIALF)].The discrimination ability,calibration,and clinical applicability of the SIALF model were evaluated by the area under receiver operating characteristic curve,calibration curves,and decision curve analysis,respectively.The Kaplan-Meier curves were used for robustness check.The SIALF model was internally validated using the bootstrapping method with the MIMIC validation cohort and externally validated by the FMCPH cohort.RESULTS A total of 738 patients with ALF patients were included in this study,with 510 from the MIMIC IV database and 228 from the FMCPH cohort.In the MIMIC IV cohort,387(75.89%)patients developed sepsis.Multivariate logistic regression analysis revealed that age[odds ratio(OR)=1.016,95%confidence interval(CI):1.003-1.028,P=0.017],total bilirubin(OR=1.047,95%CI:1.008-1.088,P=0.017),lactate dehydrogenase(OR=1.001,95%CI:1.000-1.001,P<0.001),albumin(OR=0.436,95%CI:0.274-0.692,P=0.003),and mechanical ventilation(OR=1.985,95%CI:1.269-3.105,P=0.003)were independent risk factors associated with sepsis in patients with ALF.The SIALF model demonstrated satisfactory accuracy and clinical utility with area under receiver operating characteristic curve values of 0.849,0.847,and 0.835 for the internal derivation,internal validation,and external validation cohort,respectively,which outperformed the Sequential Organ Failure Assessment scores of 0.733,0.746,and 0.721 and systemic inflammatory response syndrome scores of 0.578,0.653,and 0.615,respectively.The decision curve analysis and calibration curves indicated superior clinical utility and efficiency than other score systems.Based on the risk stratification score derived from the SIALF model,the Kaplan-Meier curves effectively discriminated the real high-risk subpopulation.To enhance the clinical utility,we constructed an online dynamic version,enabling physicians to evaluate patients’condition and track disease progression in real-time.CONCLUSION Based on easily identifiable clinical data,we developed the SIALF model to predict the risk of sepsis in patients with ALF.The model demonstrated robust predictive efficiency,outperformed Sequential Organ Failure Assessment and systemic inflammatory response syndrome scores,and was validated in an external cohort.The model-based risk stratification and online calculator might further facilitate the early detection and appropriate treatment for this subpopulation.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.
文摘Area Sampling Frames （ASFs） are the basis of many statistical programs around the world. To improve the accuracy, objectivity and efficiency of crop survey estimates, an automated stratification method based on geospatial crop planting frequency and cultivation data is proposed. This paper investigates using 2008-2013 geospatial corn, soybean and wheat planting frequency data layers to create three corresponding single crop specific and one multi-crop specific South Dakota （SD） U.S. ASF stratifications. Corn, soybeans and wheat are three major crops in South Dakota. The crop specific ASF stratifications are developed based on crop frequency statistics derived at the primary sampling unit （PSU） level based on the Crop Frequency Data Layers. The SD corn, soybean and wheat mean planting frequency strata of the single crop stratifications are substratified by percent cultivation based on the 2013 Cultivation Layer. The three newly derived ASF stratifications provide more crop specific information when compared to the current National Agricultural Statistics Service （NASS） ASF based on percent cultivation alone. Further, a multi-crop stratification is developed based on the individual corn, soybean and wheat planting frequency data layers. It is observed that all four crop frequency based ASF stratifications consistently predict corn, soybean and wheat planting patterns well as verified by the 2014 Farm Service Agency （FSA） Common Land Unit （CLU） and 578 administrative data. This demonstrates that the new stratifications based on crop planting frequency and cultivation are crop type independent and applicable to all major crops. Further, these results indicate that the new crop specific ASF stratifications have great potential to improve ASF accuracy, efficiency and crop estimates.
基金supported by the National Natural Science Foundation of China(NSFC)grants(32030020,32288101,32470649,323B2013,32300499,32270665)the National Key Research and Development Program of China(2023YFC2605400)+1 种基金the Shanghai Science and Technology Commission Program(25JS2810100,23JS1410100,QNKJ2024023)the Office of Global Partnerships(Key Projects Development Fund).
文摘Recent advancements in genome sequencing have enabled the estimation of genetic load through deleterious mutation profiling.However,Chinese populations remain underexplored in this context.We analyze whole-exome sequencing data from 5002 individuals,encompassing major Han subgroups―North Han(NHan),South Han(S-Han),and Guangxi Han(G-Han)―as well as 13 ethnic minorities.Notably,G-Han exhibits significant genetic affinity with the Zhuang population.Systematic curation of 2110 ClinVar pathogenic or likely pathogenic variants reveals 93.4%are ultra-rare.Exceptions include GJB2 rs72474224-A(hearing loss),which shows higher frequencies in Zhuang and G-Han,and β-thalassemia-associated HBB variants(rs33986703-A and rs33950507-T),which are elevated in G-Han compared to other Han subgroups.Among 96 autosomal dominant mutation carriers,LDLR variants are predominant(~25%),with comparable frequencies across Han subgroups.Adaptive signatures highlight gene-environment interactions:MTHFR rs1801133-A(UV adaptation)declines southward,while ALDH2 rs671-A(alcohol metabolism)displays the opposite trend.ABCC11 rs17822931-A,associated with cold adaptation,is particularly low frequency in G-Han.Gene-based rare-variant collapsing analyses identify an elevated risk of retinitis pigmentosa in S-Han(PRPF4,TUB).Our findings demonstrate that genetic load in Chinese populations is influenced by demographic history,population structure,and regional adaptation,emphasizing the importance of population-specific frameworks in precision medicine.
基金supported by the Fundamental Research Funds for the Central Universities[grant number 2025JBZX013]the National Natural Science Foundation of China[grant numbers 12001036,12271166,32030063]+1 种基金Young Elite Scientists Sponsorship Program by CAST[grant number 2022QNRC001]National Key Research and Development Program of China[grant number 2024YFA1016200].
文摘Space-filling designs with superior low-dimensional properties are highly required in computer experiments.Strong orthogonal arrays(SOAs)represent a class of such designs that outperform ordinary orthogonal arrays in their stratification properties within low dimensions.Nevertheless,current methods for constructing high-strength SOAs are rare,and they typically rely on regular designs,thereby limiting the number of runs in the final arrays to prime powers.This study presents new construction methods for three types of SOAs:SOAs of strength three,column-orthogonal SOAs(OSOAs)of strength three and three minus.The resulting designs have run sizes of twice an odd prime power without replications,filling the gaps in run sizes left by existing constructions.The projection properties of Addelman–Kempthorne orthogonal arrays are instrumental in the development of these construction methods.
基金supported by the NRF-2021R1C1 C1009541,2022R1FA1063012.
文摘Radiopharmaceuticals deliver diagnostic or therapeutic radionuclides to disease sites with molecular precision.Over the past five years,clinical adoption has accelerated,led by U.S.Food and Drug Administration approvals of 177Lu-DOTA-TATE and 177Lu-PSMA-617 and their complementary Positron Emission Tomography agents(68Ga-DOTA-TATE,68Ga-PSMA-11),which have established radiotheranostics as a pillar of oncology care.The new generation of agents couples optimized radionuclides(β-,α,and Auger emitters)to antibodies,peptides,and small-molecule vectors that improve tumor uptake,residence time,and clearance profiles,thereby enhancing efficacy and safety.Beyond neuroendocrine tumors and prostate cancer,radiotheranostic strategies are advancing for diverse malignancies by exploiting tumor-specific antigens,overexpressed receptors,and intracellular targets.Notably,α-emitters such as 225Ac and 211At—owing to high linear energy transfer and short path length—show potent cytotoxicity with limited off-target injury,while emergingβ/Auger emitters like 161Tb may surpass 177Lu in microdosimetric effectiveness.Concurrent innovations in patient selection and response prediction leverage diagnostic radiopharmaceuticals for image-guided stratification,individualized dosimetry,and adaptive treatment planning,supporting the broader paradigm of precision medicine.Although oncology remains the primary focus,applications are expanding to neurodegeneration,cardiovascular disease,and inflammatory conditions.This review synthesizes technological and clinical progress from 2021-2025,spanning FDA-approved and late-stage investigational agents;mechanisms of radiopharmaceutical-induced cell death;dosimetry methodologies;trial landscapes for expanding indications;and translational challenges,including supply chains,chelation chemistry,and toxicity management.Accordingly,this review focuses on the latest radiopharmaceutical diagnostic and therapeutic technologies,integrating advances in radionuclide platforms,targeting vectors,dosimetry,and clinical trial data from 2021-2025 to guide future development and clinical implementation of precision radiotheranostics.
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.
基金Social Development Science and Technology Project of Dongguan Science and Technology Bureau(Project No.:20221800905302)。
文摘Background:Drug-coated balloons(DCBs)are receiving increasing attention in interventional therapy for coronary artery disease.However,evidence regarding their application in acute myocardial infarction(AMI),particularly in high-risk AMI patients,is limited,leading to significant clinical concerns.This study aims to compare the efficacy and safety of DCBs versus standard drug-eluting stents(DESs)in AMI patients and explore their efficacy differences in patients with ST-segment elevation myocardial infarction(STEMI),non-ST-segment elevation myocardial infarction(NSTEMI),and different risk stratifications.Methods:A single-center,retrospective cohort study was conducted,involving 86 patients who underwent percutaneous coronary intervention(PCI)for AMI between January 2023 and July 2025.Patients were divided into a DCB group(n=26)and a DES group(n=60)based on the treatment modality.According to the Killip classification of myocardial infarction at admission,patients were categorized into a low-risk group(Killip Class I,n=68)and a high-risk group(Killip Classes II-IV,n=18).The primary efficacy endpoint was targeting lesion restenosis as shown by coronary angiography follow-up(6-12 months).Safety endpoints included acute in-stent thrombosis during hospitalization(ARC criteria)and long-term coronary slow flow.A multivariate logistic regression model was used to evaluate the associations between intervention modality,risk stratification,infarction type,and endpoint events,and to test for interactions.Results:The DCB and DES groups were generally balanced in terms of baseline traditional risk factors.During hospitalization,three cases(5.0%)of acute in-stent thrombosis occurred in the DES group,all requiring urgent re-intervention,while no such events occurred in the DCB group(0%).Acute in-stent thrombosis formation was significantly associated with high-risk stratification(χ2 test,p=0.047).The overall restenosis rate was 22.1%(19/86).Multivariate analysis showed no statistically significant difference in restenosis risk between the intervention modalities(DCB vs.DES)(adjusted odds ratio[OR]=1.07,95%confidence interval[CI]0.27-4.21,p=0.920),and no statistical differences were found in subgroups based on risk stratification(p=0.382)or infarction type(p=0.484).There was a trend toward increased restenosis risk in high-risk patients(OR=12.34),but the difference was not statistically significant(95%CI 0.28-542.75,p=0.193).The incidence of long-term coronary slow flow was significantly higher in the DES group than in the DCB group(16.7%vs.3.8%,Fisher’s exact test,p=0.048),with a statistically significant difference.Conclusion:For AMI patients,DCBs demonstrate similar efficacy to DESs in preventing restenosis.However,DESs are associated with a higher risk of acute thrombosis during hospitalization,especially in high-risk patients,and a higher risk of long-term slow coronary flow.DCBs exhibit superior perioperative and long-term safety compared to DESs.Given the limited sample size,particularly the small number of high-risk patients and those treated with DCBs,the conclusions require validation through larger-scale prospective studies.
基金supported by grants from the National Key Research and Development Program of China(2021YFF1201300 and 2021YFF1201305)the National Natural Science Foundation of China(82103039,81572583,81922048,91959207,U1809205,92159301,61771249 and 62171230)。
文摘Triple-negative breast cancer(TNBC)is the most challenging breast cancer subtype.Molecular stratification and target therapy bring clinical benefit for TNBC patients,but it is difficult to implement comprehensive molecular testing in clinical practice.Here,using our multi-omics TNBC cohort(N=425),a deep learning-based framework was devised and validated for comprehensive predictions of molecular features,subtypes and prognosis from pathological whole slide images.The framework first incorporated a neural network to decompose the tissue on WSIs,followed by a second one which was trained based on certain tissue types for predicting different targets.Multi-omics molecular features were analyzed including somatic mutations,copy number alterations,germline mutations,biological pathway activities,metabolomics features and immunotherapy biomarkers.It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation,germline BRCA2 mutation and PD-L1 protein expression(area under the curve[AUC]:0.78,0.79 and 0.74 respectively).The molecular subtypes of TNBC can be identified(AUC:0.84,0.85,0.93 and 0.73 for the basal-like immune-suppressed,immunomodulatory,luminal androgen receptor,and mesenchymal-like subtypes respectively)and their distinctive morphological patterns were revealed,which provided novel insights into the heterogeneity of TNBC.A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes(log-rank P<0.001).Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA(N=143)and appeared robust to the changes in patient population.For potential clinical translation,we built a novel online platform,where we modularized and deployed our framework along with the validated models.It can realize real-time one-stop prediction for new cases.In summary,using only pathological WSIs,our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making.It had the potential to be clinically implemented and promote the personalized management of TNBC.
基金Supported by National Natural Science Foundation of China,No.81874390 and No.81573948Shanghai Natural Science Foundation,No.21ZR1464100+1 种基金Science and Technology Innovation Action Plan of Shanghai Science and Technology Commission,No.22S11901700the Shanghai Key Specialty of Traditional Chinese Clinical Medicine,No.shslczdzk01201.
文摘BACKGROUND Rebleeding after recovery from esophagogastric variceal bleeding(EGVB)is a severe complication that is associated with high rates of both incidence and mortality.Despite its clinical importance,recognized prognostic models that can effectively predict esophagogastric variceal rebleeding in patients with liver cirrhosis are lacking.AIM To construct and externally validate a reliable prognostic model for predicting the occurrence of esophagogastric variceal rebleeding.METHODS This study included 477 EGVB patients across 2 cohorts:The derivation cohort(n=322)and the validation cohort(n=155).The primary outcome was rebleeding events within 1 year.The least absolute shrinkage and selection operator was applied for predictor selection,and multivariate Cox regression analysis was used to construct the prognostic model.Internal validation was performed with bootstrap resampling.We assessed the discrimination,calibration and accuracy of the model,and performed patient risk stratification.RESULTS Six predictors,including albumin and aspartate aminotransferase concentrations,white blood cell count,and the presence of ascites,portal vein thrombosis,and bleeding signs,were selected for the rebleeding event prediction following endoscopic treatment(REPET)model.In predicting rebleeding within 1 year,the REPET model ex-hibited a concordance index of 0.775 and a Brier score of 0.143 in the derivation cohort,alongside 0.862 and 0.127 in the validation cohort.Furthermore,the REPET model revealed a significant difference in rebleeding rates(P<0.01)between low-risk patients and intermediate-to high-risk patients in both cohorts.CONCLUSION We constructed and validated a new prognostic model for variceal rebleeding with excellent predictive per-formance,which will improve the clinical management of rebleeding in EGVB patients.
基金supported by the National Natural Science Foundation China(Grant No.42176222).
文摘As a crucial component of the Earth’s climate system,Antarctic sea ice has demonstrated significant variability over the satellite era.Here,we identify a remarkable decadal transition in the total Antarctic Sea Ice Extent(SIE).The stage from 1979 to 2006 is characterized by high-frequency(i.e.,seasonal to interannual)temporal variability in SIE and zonal asymmetry in Sea Ice Concentration(SIC),which is primarily under the control of the Amundsen Sea Low(ASL).After 2007,however,sea ice changes exhibit a more spatially homogeneous pattern in SIC and a more temporally long-lasting mode in SIE.Further analysis reveals that sea ice-ocean interaction plays a major role in the low-frequency(i.e.,multiannual)variability of Antarctic sea ice from 2007−22.The related physical process is inferred to manifest as a strong coupling between the surface and the subsurface ocean layers,involving enhanced vertical convection and the downward delivery of the surface anomalies related to ice melting and freezing processes,thus maintaining the SIE anomalies for a longer time.Furthermore,this process mainly occurs in the Amundsen-Bellingshausen Sea(ABS)sector,and the weakened subsurface ocean stratification is the key factor triggering the coupling process in this region.We find that the Circumpolar Deep Water(CDW)over the ABS sector continued to shoal before 2007 and remained stable thereafter.It is speculated that the shoaling of the CDW may be a possible driver leading to the weakening of the subsurface stratification.
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.
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 are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with artificial intelligence(AI)playing a key role in analyzing complex data to improve diagnostic accuracy,predict outcomes,and optimize therapies.AI can identify patterns in imaging and biomarkers,facilitating the earlier detection of medical conditions.Wearable devices and health applications facilitate continuous monitoring and personalized care.Emerging fields such as digital Chinese medicine offer additional perspectives by integrating traditional diagnostic principles with modern digital tools,contributing to holistic and individualized cardiovascular care.This study examines the advancements and challenges in personalized cardiovascular medicine,highlighting the need to address issues such as data privacy,algorithmic bias,and accessibility to promote the equitable application of personalized medicine.
文摘Prognostication of compensated advanced chronic liver disease(cACLD)is of paramount importance for the physician-and-patient communication and for rational clinical decisions.The paper published by Dallio et al reports on red cell distribution width(RDW)/platelet ratio(RPR)as a non-invasive biomarker in predicting decompensation of metabolic dysfunction-associated steatotic liver disease(MASLD)-related cACLD.Differently from other biomarkers and algorithms,RPR is inexpensive and widely available,based on parameters which are included in a complete blood count.RPR is computed on the grounds of two different items,one of which,RDW,mirrors the host’s response to a variety of disease stimuli and is non-specific.The second parameter involved in RPR,platelet count,is more specific and has been used in the hepatological clinic to discriminate cirrhotic from non-cirrhotic chronic liver disease for decades.Cardiovascular disease is the primary cause of mortality among MASLD subjects,followed by extra-hepatic cancers and liver-related mortality.Therefore,MASLD biomarkers should be validated not only in terms of liver-related events but also in the prediction of major adverse cardiovascular events and cardiovascular mortality and extra-hepatic cancers.Adequately sized multi-ethnic confirmatory investigation is required to define the role and significance of RPR in the stratification of MASLD-cACLD.
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.
基金supported by the National Natural Science Foundation of China (Grant nos. 82470209 and 82170141)the Jiaxing Key Discipiline of Medcine-Nephrology (Grant no. 2023-ZC-011)。
文摘Precise risk stratification is crucial for selecting the optimal risk-adapted treatment for newly diagnosed multiple myeloma (NDMM) patients. Various prognostic factors and staging systems have been developed to predict NDMM patient outcomes. The Durie-Salmon (D-S) staging system reflects tumor burden and clinical progression staging with prognostic value.
文摘Indonesia is an archipelago located in a tropical climate zone that is home to 17%of the world's creatures,buthuman disturbances still threaten the existence of bird species in Indonesia.This encourages bird conservation effortsboth through conservation areas and community forests.This study aims to determine the diversity and interaction ofbirds with the vegetation stratum in the community forest of Gunungkelir Hamlet,Jatimulyo Village,Kulon ProgoRegency,Yogyakarta.This research was conducted from February to March 2024,using a combination of line transect,point count,and rapid assessment methods for bird observation.Data were analyzed using diversity index(H'),evenness(E),and relative abundance.Vegetation stratum data used in vegetation analysis through nested plot sampling to obtainthe Important Value Index(IVI).The results showed that there were 21 species from 13 bird families;the diversity valueobtained on the three lanes was 2.62 on lane 1,1.84 on lane 2,and 1.79 on lane 3.The Albizia chinensis species hadthe highest IVI value at the seedling and sapling levels,with(67%)and(76.4%),respectively;then cloves obtained thehighest IVI value at the pole and tree levels with(84.5%)and(81.3%).The majority of birds,comprising as many as15 species,were found in stratum C,followed by stratum D,which had as many as 8 species,stratum E with 3 species,stratum B with 2 species,and no birds were found in stratum A.The most common form of vegetation utilizationfound was resting.Birds utilized the stratum layer to rest,play,and find food.Understanding bird ecology also meansunderstanding human safety in wisely managing forest ecosystems.
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 National Key Research and Development Program,No.2022YFA1103501。
文摘BACKGROUND Acute liver failure(ALF)with sepsis is associated with rapid disease progression and high mortality.Therefore,early detection of high-risk sepsis subgroups in patients with ALF is crucial.AIM To develop and validate an accurate nomogram model for predicting the risk of sepsis in patients with ALF.METHODS We retrieved data from the Medical Information Mart for Intensive Care(MIMIC)IV database and the Fifth Medical Center of Chinese PLA General Hospital(FMCPH).Univariate and multivariate logistic regression analysis were used to identify risk factors for sepsis in ALF and were subsequently incorporated to construct a nomogram model[sepsis in ALF(SIALF)].The discrimination ability,calibration,and clinical applicability of the SIALF model were evaluated by the area under receiver operating characteristic curve,calibration curves,and decision curve analysis,respectively.The Kaplan-Meier curves were used for robustness check.The SIALF model was internally validated using the bootstrapping method with the MIMIC validation cohort and externally validated by the FMCPH cohort.RESULTS A total of 738 patients with ALF patients were included in this study,with 510 from the MIMIC IV database and 228 from the FMCPH cohort.In the MIMIC IV cohort,387(75.89%)patients developed sepsis.Multivariate logistic regression analysis revealed that age[odds ratio(OR)=1.016,95%confidence interval(CI):1.003-1.028,P=0.017],total bilirubin(OR=1.047,95%CI:1.008-1.088,P=0.017),lactate dehydrogenase(OR=1.001,95%CI:1.000-1.001,P<0.001),albumin(OR=0.436,95%CI:0.274-0.692,P=0.003),and mechanical ventilation(OR=1.985,95%CI:1.269-3.105,P=0.003)were independent risk factors associated with sepsis in patients with ALF.The SIALF model demonstrated satisfactory accuracy and clinical utility with area under receiver operating characteristic curve values of 0.849,0.847,and 0.835 for the internal derivation,internal validation,and external validation cohort,respectively,which outperformed the Sequential Organ Failure Assessment scores of 0.733,0.746,and 0.721 and systemic inflammatory response syndrome scores of 0.578,0.653,and 0.615,respectively.The decision curve analysis and calibration curves indicated superior clinical utility and efficiency than other score systems.Based on the risk stratification score derived from the SIALF model,the Kaplan-Meier curves effectively discriminated the real high-risk subpopulation.To enhance the clinical utility,we constructed an online dynamic version,enabling physicians to evaluate patients’condition and track disease progression in real-time.CONCLUSION Based on easily identifiable clinical data,we developed the SIALF model to predict the risk of sepsis in patients with ALF.The model demonstrated robust predictive efficiency,outperformed Sequential Organ Failure Assessment and systemic inflammatory response syndrome scores,and was validated in an external cohort.The model-based risk stratification and online calculator might further facilitate the early detection and appropriate treatment for this subpopulation.
