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
Objective:To investigate whether the presence or absence of improvement in chronic severe functional constipation(CSFC)at the early stage of treatment with electroacupuncture predicts subsequent response or non-respon...Objective:To investigate whether the presence or absence of improvement in chronic severe functional constipation(CSFC)at the early stage of treatment with electroacupuncture predicts subsequent response or non-response,and to determine the optimal treatment duration for assessing subsequent responses to electroacupuncture.Methods:This is a post hoc analysis using data pooled from two large-scale randomized controlled trials.Patients with CSFC were recruited,and those in the electroacupuncture groups were included in the present study.Early improvement was defined as a weekly increase of≥1 complete spontaneous bowel movement(CSBM)compared to baseline.Three treatment response criteria were evaluated:≥3CSBMs per week,overall CSBM response,and sustained CSBM response.Predictive statistics,including sensitivity,specificity,positive predictive value,and negative predictive value,were calculated at weeks1–4.Receiver operating characteristic curves and accuracy rates were used to determine the optimal timepoint for differentiation between responders and non-responders.Results:Cases from a total of 813 participants who received electroacupuncture were analyzed.The proportion of improvers was 40.34%by week 1,increasing to 52.52%by week 4.After 8 weeks of treatment,the response rates were 30.14%,25.83%and 25.58%according to the three aforementioned criteria,respectively.Early improvement was a strong predictor of treatment response,with week 3 demonstrating the highest predictive accuracy.Conclusion:Early improvement with electroacupuncture,especially at week 3,can predict subsequent outcomes.Our findings suggest that acupuncturists may identify non-responders who might require adjustments to therapeutic strategies early in treatment.展开更多
Objective:While immunotherapy holds great potential for triple-negative breast cancer(TNBC),the lack of non-invasive biomarkers to identify beneficiaries limits the application.Methods:Paired baseline,on-treatment,and...Objective:While immunotherapy holds great potential for triple-negative breast cancer(TNBC),the lack of non-invasive biomarkers to identify beneficiaries limits the application.Methods:Paired baseline,on-treatment,and post-treatment plasma samples were collected from 195 TNBC patients receiving anti-PD-1 immunotherapy in this retrospective study conducted at the Fudan University Shanghai Cancer Center(FUSCC)for sequential high-precision proteomic profiling.Results:ARG1,NOS3,and CD28 were identified as plasma proteins significantly associated with the response to immunotherapy in neoadjuvant settings or in advanced stages of TNBC.Matched single-cell RNA sequencing data were incorporated to correlate peripheral plasma with the tumor microenvironment.Furthermore,the Plasma Immuno Prediction Score was developed to demonstrate significant predictive power for evaluating the efficacy and prognosis of patients undergoing neoadjuvant immunotherapy.Conclusions:The results underscore the importance of systemic immunity in the immunotherapy response and support the use of plasma protein profiles as a feasible tool for enhancing personalized management of immunotherapy in breast cancer.展开更多
The Zhejiang University(ZJU)index,which combines body mass index,fasting blood glucose,triglyceride level and alanine aminotransferase/aspartate aminotransferase ratio,can be used to predict metabolic dysfunction-asso...The Zhejiang University(ZJU)index,which combines body mass index,fasting blood glucose,triglyceride level and alanine aminotransferase/aspartate aminotransferase ratio,can be used to predict metabolic dysfunction-associated steatotic liver disease(MASLD)in patients with type 2 diabetes mellitus(T2DM).The ZJU index of 38.87 has been identified as the key threshold for diagnosing MASLD.The new model for predicting MASLD in T2DM based on ZJU index shows high diagnostic value.While the study is methodologically robust and offers a valuable clinical tool,it is limited by its cross-sectional design,inpatient cohort bias,unadjusted pharmacotherapy effects,and reliance on ultrasound for MASLD diagnosis.Future validation in outpatient settings,incorporating medication data and advanced fibrosis assessment,is crucial to translate this cost-effective biomarker into wide practice.展开更多
BACKGROUND Juvenile arthritis damage index(JADI)is a tool that measures the degree of aggressiveness of the juvenile idiopathic arthritis(JIA)course and assesses articular[JADI-articular damage(JADI-A)]and extraarticu...BACKGROUND Juvenile arthritis damage index(JADI)is a tool that measures the degree of aggressiveness of the juvenile idiopathic arthritis(JIA)course and assesses articular[JADI-articular damage(JADI-A)]and extraarticular[JADI-extraarticular damage(JADI-E)]damage.While aggressive JIA often requires early bio-logic disease-modified antirheumatic drugs(bDMARDs),the utility of JADI as a predictor of treatment response remains underexplored.AIM To evaluate the potential of JADI as a predictor of bDMARD treatment response in JIA patients.METHODS This prospective study included 112 highly active non-systemic JIA biologic-naïve patients with a mean age of 12.2±4.6 years and a median disease duration of 2.5(interquartile range:1-5)years.Their clinical and radiological assessment,juvenile arthritis disease activity score 71,JADI-A,and JADI-E,were evaluated twice:Before the biologic initiation(baseline)and 12 months after(end of study).At baseline,50%had any damage,with 43%with articular damage and 23%with extraarticular damage.RESULTS During the study,JADI-A/JADI-E improved(33.9%/9.8%),worsened(8.9%/5.4%),or remained unchanged(57.1%/84.8%).Patients with baseline damage had higher markers of JIA activity:Polyarticular course,earlier onset age,ANA-positivity,and more active joints.Patients without initial structural damage(JADI“-”)were more likely(odds ratio=3.8,95%confidence interval:1.6-9.0,P<0.004)to achieve a low degree of activity or remission(46.2%),while on biological therapy,their scores were comparable to JADI-positive(18.3%).Pre-biological joint damage according to the JADI-A index(P=0.003),wrist(P=0.035),elbow(P=0.027),cervical spine limitation of motion(P=0.051),and erosions confirmed by magnetic resonance imaging(P=0.002),were associated with poor response to biological treatment and follow-up JIA activity.CONCLUSION Baseline structural damage in JIA is associated with diminished bDMARDs efficacy,increased disability,and shorter remission duration.JADI enhances conventional clinical risk stratification by facilitating timely initiation of bDMARDs,adherence to treat-to-target strategy and tailored patient care.展开更多
Tian et al present a timely machine learning(ML)model integrating biochemical and novel traditional Chinese medicine(TCM)indicators(tongue edge redness,greasy coating)to predict hepatic steatosis in high metabolic ris...Tian et al present a timely machine learning(ML)model integrating biochemical and novel traditional Chinese medicine(TCM)indicators(tongue edge redness,greasy coating)to predict hepatic steatosis in high metabolic risk patients.Their prospective cohort design and dual-feature selection(LASSO+RFE)culminating in an interpretable XGBoost model(area under the curve:0.82)represent a significant methodological advance.The inclusion of TCM diagnostics addresses metabolic dysfunction-associated fatty liver disease(MAFLD’s)multisystem heterogeneity-a key strength that bridges holistic medicine with precision analytics and underscores potential cost savings over imaging-dependent screening.However,critical limitations impede clinical translation.First,the model’s singlecenter validation(n=711)lacks external/generalizability testing across diverse populations,risking bias from local demographics.Second,MAFLD subtyping(e.g.,lean MAFLD,diabetic MAFLD)was omitted despite acknowledged disease heterogeneity;this overlooks distinct pathophysiologies and may limit utility in stratified care.Third,while TCM features ranked among the top predictors in SHAP analysis,their clinical interpretability remains nebulous without mechanistic links to metabolic dysregulation.To resolve these gaps,we propose external validation in multiethnic cohorts using the published feature set(e.g.,aspartate aminotransferase/alanine aminotransferase,low-density lipoprotein cholesterol,TCM tongue markers)to assess robustness.Subtype-specific modeling to capture MAFLD heterogeneity,potentially enhancing accuracy in highrisk subgroups.Probing TCM microbiome/metabolomic correlations to ground tongue phenotypes in biological pathways,elevating model credibility.Despite shortcomings,this work pioneers a low-cost screening paradigm.Future iterations addressing these issues could revolutionize early MAFLD detection in resource-limited settings.展开更多
Rainfall event is the very specific, reliable unambiguous precursor for the earthquake event. Over the years scientists have hunted for some signal—a precursory sign, however faint—that would allow forecasters to pi...Rainfall event is the very specific, reliable unambiguous precursor for the earthquake event. Over the years scientists have hunted for some signal—a precursory sign, however faint—that would allow forecasters to pin-point exactly where and when the big ones will hit. After decades spent searching in vain, many seismologists now doubt whether such a signal even exists. But in a great surprise to everyone, from an ordinary lay man to eminent scientists, 100% earthquakes occur after rainfalls! Though I have the findings for the entire regions of the world, here E Turkey are the region for submission for the period Jan-November, 2012 to study the strong correlation and show the strong evidence to prove that the 100% earthquakes after rainfall in a consistence manner. Anyone can very easily verify the validity of the findings for any forthcoming earthquakes for any regions of E Turkey in just two weeks of period. Nature does not give two different results for the same phenomena, for two different observers. Though there exists a very strong relation between the rainfalls and the earthquakes, scientists and seismologists have not been able to detect and identify this rainfall precursory signal for hundreds of years that consistently occurs before earthquakes. The methodology of rainfall event before earthquakes, even works consistently for earthquake prediction purpose, especially in any regions of the world. Rainfall type precursor is the best approach to predict specific earthquakes, which provide the potential for estimating the epicenter and magnitude of any moderate to strong earthquakes. Earthquakes are more likely when there is rain than it is not. The magnitudes of a resulting individual earthquake depend on the severity of the weather changes. However, in a very few cases the time scales and magnitude do vary substantially as a consequence of local site geology and other factors.展开更多
"Global IT market will sustain increase in fluctuating in 2005. In varied merger, integration, adjustment, global IT industry moves ahead prudently. And China IT market will obtain enormous opportunities and ... "Global IT market will sustain increase in fluctuating in 2005. In varied merger, integration, adjustment, global IT industry moves ahead prudently. And China IT market will obtain enormous opportunities and challenges in this market." Mr. Xie Shihe,President of China of IDC company. This is the first time of IDC to deliver its point of view to media.……展开更多
BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking Univers...BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.展开更多
BACKGROUND Surgery is the primary curative option in patients with hepatocellular carcinoma(HCC).However,recurrence within 2 years is observed in 30%–50%of patients,being a major cause of mortality.AIM To construct a...BACKGROUND Surgery is the primary curative option in patients with hepatocellular carcinoma(HCC).However,recurrence within 2 years is observed in 30%–50%of patients,being a major cause of mortality.AIM To construct and verify a non-invasive prediction model combining contrastenhanced ultrasound(CEUS)with serology biomarkers to predict the early recurrence of HCC.METHODS Records of 744 consecutive patients undergoing first-line curative surgery for HCC in one institution from 2016–2018 were reviewed,and 292 local patients were selected for analysis.General characteristics including gender and age,CEUS liver imaging reporting and data system(LIRADS)parameters including wash-in time,wash-in type,wash-out time,and wash-out type,and serology biomarkers including alanine aminotransferase,aspartate aminotransferase,platelets,and alpha-fetoprotein(AFP)were collected.Univariate analysis and multivariate Cox proportional hazards regression model were used to evaluate the independent prognostic factors for tumor recurrence.Then a nomogram called CEUS model was constructed.The CEUS model was then used to predict recurrence at 6 mo,12 mo,and 24 mo,the cut-off value was calculate by X-tile,and each C-index was calculated.Then Kaplan-Meier curve was compared by logrank test.The calibration curves of each time were depicted.RESULTS A nomogram predicting early recurrence(ER),named CEUS model,was formulated based on the results of the multivariate Cox regression analysis.This nomogram incorporated tumor diameter,preoperative AFP level,and LIRADS,and the hazard ratio was 1.123(95%confidence interval[CI]:1.041-1.211),1.547(95%CI:1.245-1.922),and 1.428(95%CI:1.059-1.925),respectively.The cut-off value at 6 mo,12 mo,and 24 mo was 100,80,and 50,and the C-index was 0.748(95%CI:0.683-0.813),0.762(95%CI:0.704-0.820),and 0.762(95%CI:0.706-0.819),respectively.The model showed satisfactory results,and the calibration at 6 mo was desirable;however,the calibration at 12 and 24 mo should be improved.CONCLUSION The CEUS model enables the well-calibrated individualized prediction of ER before surgery and may represent a novel tool for biomarker research and individual counseling.展开更多
BACKGROUND Large-scale functional connectivity(LSFC)patterns in the brain have unique intrinsic characteristics.Abnormal LSFC patterns have been found in patients with dementia,as well as in those with mild cognitive ...BACKGROUND Large-scale functional connectivity(LSFC)patterns in the brain have unique intrinsic characteristics.Abnormal LSFC patterns have been found in patients with dementia,as well as in those with mild cognitive impairment(MCI),and these patterns predicted their cognitive performance.It has been reported that patients with type 2 diabetes mellitus(T2DM)may develop MCI that could progress to dementia.We investigated whether we could adopt LSFC patterns as discriminative features to predict the cognitive function of patients with T2DM,using connectome-based predictive modeling(CPM)and a support vector machine.AIM To investigate the utility of LSFC for predicting cognitive impairment related to T2DM more accurately and reliably.METHODS Resting-state functional magnetic resonance images were derived from 42 patients with T2DM and 24 healthy controls.Cognitive function was assessed using the Montreal Cognitive Assessment(MoCA).Patients with T2DM were divided into two groups,according to the presence(T2DM-C;n=16)or absence(T2DM-NC;n=26)of MCI.Brain regions were marked using Harvard Oxford(HOA-112),automated anatomical labeling(AAL-116),and 264-region functional(Power-264)atlases.LSFC biomarkers for predicting MoCA scores were identified using a new CPM technique.Subsequently,we used a support vector machine based on LSFC patterns for among-group differentiation.The area under the receiver operating characteristic curve determined the appearance of the classification.RESULTS CPM could predict the MoCA scores in patients with T2DM(Pearson’s correlation coefficient between predicted and actual MoCA scores,r=0.32,P=0.0066[HOA-112 atlas];r=0.32,P=0.0078[AAL-116 atlas];r=0.42,P=0.0038[Power-264 atlas]),indicating that LSFC patterns represent cognition-level measures in these patients.Positive(anti-correlated)LSFC networks based on the Power-264 atlas showed the best predictive performance;moreover,we observed new brain regions of interest associated with T2DM-related cognition.The area under the receiver operating characteristic curve values(T2DM-NC group vs.T2DM-C group)were 0.65-0.70,with LSFC matrices based on HOA-112 and Power-264 atlases having the highest value(0.70).Most discriminative and attractive LSFCs were related to the default mode network,limbic system,and basal ganglia.CONCLUSION LSFC provides neuroimaging-based information that may be useful in detecting MCI early and accurately in patients with T2DM.展开更多
Catheter ablation has been recommended as a treatment option for paroxysmal atrial fibrillation（PAF） patients complicated with type 2 diabetes mellitus（T2DM）. PAF patients with T2 DM have a higher recurrence rate ...Catheter ablation has been recommended as a treatment option for paroxysmal atrial fibrillation（PAF） patients complicated with type 2 diabetes mellitus（T2DM）. PAF patients with T2 DM have a higher recurrence rate after catheter ablation. Prolongation of corrected QT（QTc） interval has been linked to poor outcomes in T2 DM patients. Whether the abnormal QTc interval is associated with the ablation outcome in the PAF patients with T2 DM remains unknown. In this study, 134 PAF patients with T2 DM undergoing primary catheter ablation were retrospectively enrolled. Pre-procedural QTc interval was corrected by using the Bazett＇s formula. Cox proportional hazards models were constructed to assess the relationship between QTc interval and the recurrence of AF. After a 29.1-month follow-up period, 61 patients experienced atrial tachyarrhythmia recurrence. Recurrent patients had a longer QTc interval than non-recurrent patients（425.2±21.5 ms vs. 414.1±13.4 ms, P=0.002）. Multivariate Cox regression analysis revealed that QTc interval [hazard ratio（HR）=1.026, 95% confidence interval（CI） 1.012–1.040, P=0.005] and left atrial diameter（LAD）（HR=1.125, 95% CI 1.062–1.192, P=0.003） were independent predictors of recurrent atrial tachyarrhythmia. Receiver operating characteristic analysis demonstrated that the cut-off value of QTc（418 ms） predicted arrhythmia recurrence with a sensitivity of 55.7% and a specificity of 69.9%. A combination of LAD and QTc was more effective than LAD alone（P〈0.001） in predicting arrhythmia recurrence after the procedure. QTc interval could be used as an independent predictor of arrhythmia recurrence in T2 DM patients undergoing AF ablation, thus providing a simple method to identify those patients who likely have a better outcome following the procedure.展开更多
Drilling in any environment is challenging as it poses a challenge to drill reservoir targets without losses and minimum casing strings and is even challenging in HPHT (high pressure high temperature) environment. Sei...Drilling in any environment is challenging as it poses a challenge to drill reservoir targets without losses and minimum casing strings and is even challenging in HPHT (high pressure high temperature) environment. Seismic is the fundamental for pre-drill prognosis and completion design. The target depth prognosis is achieved through depth transformation by using seismic velocities or available velocity logs in the nearby field or block and often has varying degree of uncertainty in target depths depending upon the suitable of the velocity function used. The velocity function used could be affected due to available seismic bandwidth or structure. These uncertainties in target depths often lead to increased well costs as a result of wellbore stability issues & undesired casing strings. Most common issue faced by drillers is the target confirmation & distance to these targets ahead of bit. Vertical seismic profile (VSP) look-ahead at intermediate depths is one of the approaches to mitigate these uncertainties and drill wells safely. VSP help confirm the presence of drilling targets & also predict the depth to top of these targets. Additionally, the predicted interval velocity is used to predict the pre-pressure for next section drilling. In South China Sea, oil & gas operators face a significant risk while drilling over-pressured formations. It is therefore imperative to know the depth to top of these high pressured formations to avoid drilling directly into it and risking the well. It is also important to know the pore-pressure and mud weight for the next section to be drilled for safe drilling & with minimum casing strings [1] [2] [3]. It is more difficult to get this information in the HPHT environment due to the lack of high temperature tools [4]. Schlumberger’s proprietary QVSI*—High pressure, high temperature VSI* (Versatile Seismic Imager) has been successfully used to predict the target depth for casing landing and pore-pressure prediction in HPHT environment. QVSI is the latest generation of VSI* Versatile Seismic Imager tools developed by Schlumberger to acquire high quality tri-axial borehole seismic data in extreme environment wells. The QVSI* tool uses the Q-Technology* singlesensor hardware and software and advanced wireline telemetry for fast digital seismic data transmission from borehole to surface. QVSI is a high-temperature, high-pressure array tool design that focuses on tri-axial vector fidelity and efficient data acquisition, extending the limits in a 4-tool configuration to 500°F (260℃) and 30 kpsi (207 MPa). In this paper, a case study is presented for Well-XX for CNOOC from South China Sea. The well-xx is located in Yanyan Sag, Qiongdongnan Basin and the downhole temperature was 204℃. The main target layer is Lingshui III sandstone, which is controlled by Northwest fault. It is a gas well and critical for the client to land the casing at right depth and know the drilling parameters for the next section ahead. QVSI* predicted the target depth within ±2 m for decision on casing point. The predicted pore pressure was within ±0.1 ppg.展开更多
Background:Cholangiocarcinoma(CCA)is highly malignant and has a poor prognosis has a high malignant degree and poor prognosis.The purpose of this study is to develop a new prognostic model based on genes related to th...Background:Cholangiocarcinoma(CCA)is highly malignant and has a poor prognosis has a high malignant degree and poor prognosis.The purpose of this study is to develop a new prognostic model based on genes related to the tumor microenvironment(TME).Methods:Derived from the discerned differentially expressed genes within The Cancer Genome Atlas(TCGA)dataset,this investigation employed the methodology of weighted gene co-expression network analysis(WGCNA)to ascertain gene co-expressed modules intricately linked to the Tumor Microenvironment(TME)among Cholangiocarcinoma(CCA)patients.The genes associated with prognosis,as identified through Cox regression analysis,were employed in the formulation of a predictive model.This model underwent validation,leading to the development of a risk score formula and nomogram.Concurrently,we validated the model’s reliability using data from CCA patients in the Gene Expression Omnibus(GEO)database(accession:GSE107943).Results:6139 DEGs were divided into 10 co-expressed gene modules using WGCNA.Among these,two modules(blue module with 832 genes and brown module with 1379 genes)showed high correlation with the TME.Five prognostic genes(BNIP3,COL4A3,SPRED3,CEBPB,PLOD2)were identified through Cox regression analysis,and a prognostic model and risk score formula were developed based on these genes.Risk score formula:Risk score=BNIP3×1.70520-COL4A3×2.39815+SPRED3×1.17936+CEBPB×0.40456+PLOD2×0.24785.Kaplan-Meier survival analysis revealed that the survival probabilities of the low-risk group were significantly higher than those of the high-risk group.Furthermore,the related evaluation indexes suggested that the model exhibited strong predictive ability.Conclusion:The prognostic model,based on five TME-related genes(BNIP3,COL4A3,SPRED3,CEBPB,PLOD2),could accurately assess the prognosis of CCA patients to aid in guiding clinical decisions.展开更多
Cervical cancer(CC)is the second most common cancer of female reproductive system.However,satisfactory prognostic model for CC remains to be established.In this study,we perform whole-exome sequencing on formalin-fixe...Cervical cancer(CC)is the second most common cancer of female reproductive system.However,satisfactory prognostic model for CC remains to be established.In this study,we perform whole-exome sequencing on formalin-fixed and paraffin-embedded tumor specimens extracted from 67 recurrent and 28 matched non-recurrent CC patients.As a result,four core mutated genes(i.e.,DCHS2,DNAH10,RYR1,and WDFY4)that are differentially presented in recurrent and non-recurrent CC patients are screened out to construct a recurrence-free related score(RRS)model capable of predicting CC prognosis in our cohort,which is further confirmed in TCGA CESC cohort.Moreover,combining tumor mutational burden(TMB)and RRS into an integrated RRS/TMB model enables better stratification of CC patients with distinct prognosis in both cohorts.Increased infiltration of multiple immune cell types,enriched interferon signaling pathway,and elevated cytolytic activity are evident in tumors from patients with a higher RRS and/or a higher TMB.In summary,this study establishes a novel mutation-based prognostic model for CC,the predictive value of which can be attributable to immunological mechanisms.This study will provide insight into the utilization of mutational analysis in guiding therapeutic strategies for CC patients.展开更多
Background and Aims:T lymphocytes play a pivotal role in resolving hepatitis B virus infection.This study aimed to investigate the dynamics of peripheral blood T lymphocyte subsets during peginterferon alpha(peg-IFN-...Background and Aims:T lymphocytes play a pivotal role in resolving hepatitis B virus infection.This study aimed to investigate the dynamics of peripheral blood T lymphocyte subsets during peginterferon alpha(peg-IFN-α)therapy and their association with hepatitis B surface antigen(HBsAg)clearance in inactive HBsAg carriers(IHCs).Methods:This prospective observational study enrolled 197 IHCs treated with peg-IFNα-2a/2b for 48 weeks and followed for 24 weeks(treatment group),and 221 IHCs who were regularly monitored for 72 weeks without treatment(IHC control group).Peripheral blood T lymphocyte subsets were evaluated using flow cytometry at baseline,and at 12,24,48,and 72 weeks in both groups.At 72 weeks,IHCs in the treatment group were categorized into an HBsAg clearance group and an HBsAg persistence group.Differences in T lymphocyte subsets among these groups were compared,and correlations between T lymphocyte subsets and HBsAg clearance were analyzed.Results:At 72 weeks,intention-to-treat analysis showed significantly higher HBsAg clearance(46.7%)and seroconversion rates(34.5%)in the treatment group compared to the IHC control group(HBsAg clearance rate of 1.4%,seroconversion rate of 0.9%;both p<0.001).The median absolute counts of CD3^(+),CD4^(+),and CD8^(+)cells significantly decreased at 12,24,and 48 weeks in both the HBsAg clearance and persistence groups,returning to baseline at 72 weeks(all p<0.001).IHCs with HBsAg clearance had higher median percentages of CD3^(+)CD8^(+)cells and lower median percentages of CD3^(+)CD4^(+)cells and CD4^(+)/CD8^(+)ratios at 12,24,and 48 weeks compared to the HBsAg persistence and IHC control groups(all p<0.001).Baseline HBsAg levels(below 2.0 log10 IU/mL)and hepatitis B virus DNA levels(below 20 IU/mL),alanine aminotransferase elevation at 12 weeks(greater than 2×upper limit of normal),and CD4^(+)/CD8^(+)ratios(less than 1.5 at 12 weeks and below 1.4 at 24 weeks)were predictive of HBsAg clearance.Conclusions Peripheral blood CD4^(+)/CD8^(+)ratios at 12 and 24 weeks may serve as predictive markers for HBsAg clearance in IHCs treated with peg-IFN-α.展开更多
The treatment efficacy of anti-diabetic therapies is highly heterogeneous among patients with type 2 diabetes(T2D)(Ahmad et al.2022).Predictive biomarkers can be used to stratify patients into subgroups with varying e...The treatment efficacy of anti-diabetic therapies is highly heterogeneous among patients with type 2 diabetes(T2D)(Ahmad et al.2022).Predictive biomarkers can be used to stratify patients into subgroups with varying efficacy before receiving the treatment,and help advance the understanding of disease and treatment(Ahmad et al.2022).Thus,identifying predictive biomarkers is important for precision medicine of patients with T2D.Approved in China in October 2021 as an adjunct to diet and exercise for improving glycemic control in adult patients with T2D,chiglitazar is a non-thiazolidinedione agonist of theα,δandγsubtypes of the peroxisome proliferator-activated receptors(PPARs)(Deeks 2022).展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives ...Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.展开更多
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.
基金supported by High-Level Chinese Medical Hospital Promotion ProjectHLCMHPP2023089.
文摘Objective:To investigate whether the presence or absence of improvement in chronic severe functional constipation(CSFC)at the early stage of treatment with electroacupuncture predicts subsequent response or non-response,and to determine the optimal treatment duration for assessing subsequent responses to electroacupuncture.Methods:This is a post hoc analysis using data pooled from two large-scale randomized controlled trials.Patients with CSFC were recruited,and those in the electroacupuncture groups were included in the present study.Early improvement was defined as a weekly increase of≥1 complete spontaneous bowel movement(CSBM)compared to baseline.Three treatment response criteria were evaluated:≥3CSBMs per week,overall CSBM response,and sustained CSBM response.Predictive statistics,including sensitivity,specificity,positive predictive value,and negative predictive value,were calculated at weeks1–4.Receiver operating characteristic curves and accuracy rates were used to determine the optimal timepoint for differentiation between responders and non-responders.Results:Cases from a total of 813 participants who received electroacupuncture were analyzed.The proportion of improvers was 40.34%by week 1,increasing to 52.52%by week 4.After 8 weeks of treatment,the response rates were 30.14%,25.83%and 25.58%according to the three aforementioned criteria,respectively.Early improvement was a strong predictor of treatment response,with week 3 demonstrating the highest predictive accuracy.Conclusion:Early improvement with electroacupuncture,especially at week 3,can predict subsequent outcomes.Our findings suggest that acupuncturists may identify non-responders who might require adjustments to therapeutic strategies early in treatment.
基金supported by the National Key Research and Development Project of China(Grant No.2021YFF1201300 and 2021YFF1201302)the Shanghai Committee of Science and Technology(Grant No.24DX2800100)the Institutional Projects of SIBPT(Grant No.YZ2024-07)。
文摘Objective:While immunotherapy holds great potential for triple-negative breast cancer(TNBC),the lack of non-invasive biomarkers to identify beneficiaries limits the application.Methods:Paired baseline,on-treatment,and post-treatment plasma samples were collected from 195 TNBC patients receiving anti-PD-1 immunotherapy in this retrospective study conducted at the Fudan University Shanghai Cancer Center(FUSCC)for sequential high-precision proteomic profiling.Results:ARG1,NOS3,and CD28 were identified as plasma proteins significantly associated with the response to immunotherapy in neoadjuvant settings or in advanced stages of TNBC.Matched single-cell RNA sequencing data were incorporated to correlate peripheral plasma with the tumor microenvironment.Furthermore,the Plasma Immuno Prediction Score was developed to demonstrate significant predictive power for evaluating the efficacy and prognosis of patients undergoing neoadjuvant immunotherapy.Conclusions:The results underscore the importance of systemic immunity in the immunotherapy response and support the use of plasma protein profiles as a feasible tool for enhancing personalized management of immunotherapy in breast cancer.
文摘The Zhejiang University(ZJU)index,which combines body mass index,fasting blood glucose,triglyceride level and alanine aminotransferase/aspartate aminotransferase ratio,can be used to predict metabolic dysfunction-associated steatotic liver disease(MASLD)in patients with type 2 diabetes mellitus(T2DM).The ZJU index of 38.87 has been identified as the key threshold for diagnosing MASLD.The new model for predicting MASLD in T2DM based on ZJU index shows high diagnostic value.While the study is methodologically robust and offers a valuable clinical tool,it is limited by its cross-sectional design,inpatient cohort bias,unadjusted pharmacotherapy effects,and reliance on ultrasound for MASLD diagnosis.Future validation in outpatient settings,incorporating medication data and advanced fibrosis assessment,is crucial to translate this cost-effective biomarker into wide practice.
文摘BACKGROUND Juvenile arthritis damage index(JADI)is a tool that measures the degree of aggressiveness of the juvenile idiopathic arthritis(JIA)course and assesses articular[JADI-articular damage(JADI-A)]and extraarticular[JADI-extraarticular damage(JADI-E)]damage.While aggressive JIA often requires early bio-logic disease-modified antirheumatic drugs(bDMARDs),the utility of JADI as a predictor of treatment response remains underexplored.AIM To evaluate the potential of JADI as a predictor of bDMARD treatment response in JIA patients.METHODS This prospective study included 112 highly active non-systemic JIA biologic-naïve patients with a mean age of 12.2±4.6 years and a median disease duration of 2.5(interquartile range:1-5)years.Their clinical and radiological assessment,juvenile arthritis disease activity score 71,JADI-A,and JADI-E,were evaluated twice:Before the biologic initiation(baseline)and 12 months after(end of study).At baseline,50%had any damage,with 43%with articular damage and 23%with extraarticular damage.RESULTS During the study,JADI-A/JADI-E improved(33.9%/9.8%),worsened(8.9%/5.4%),or remained unchanged(57.1%/84.8%).Patients with baseline damage had higher markers of JIA activity:Polyarticular course,earlier onset age,ANA-positivity,and more active joints.Patients without initial structural damage(JADI“-”)were more likely(odds ratio=3.8,95%confidence interval:1.6-9.0,P<0.004)to achieve a low degree of activity or remission(46.2%),while on biological therapy,their scores were comparable to JADI-positive(18.3%).Pre-biological joint damage according to the JADI-A index(P=0.003),wrist(P=0.035),elbow(P=0.027),cervical spine limitation of motion(P=0.051),and erosions confirmed by magnetic resonance imaging(P=0.002),were associated with poor response to biological treatment and follow-up JIA activity.CONCLUSION Baseline structural damage in JIA is associated with diminished bDMARDs efficacy,increased disability,and shorter remission duration.JADI enhances conventional clinical risk stratification by facilitating timely initiation of bDMARDs,adherence to treat-to-target strategy and tailored patient care.
文摘Tian et al present a timely machine learning(ML)model integrating biochemical and novel traditional Chinese medicine(TCM)indicators(tongue edge redness,greasy coating)to predict hepatic steatosis in high metabolic risk patients.Their prospective cohort design and dual-feature selection(LASSO+RFE)culminating in an interpretable XGBoost model(area under the curve:0.82)represent a significant methodological advance.The inclusion of TCM diagnostics addresses metabolic dysfunction-associated fatty liver disease(MAFLD’s)multisystem heterogeneity-a key strength that bridges holistic medicine with precision analytics and underscores potential cost savings over imaging-dependent screening.However,critical limitations impede clinical translation.First,the model’s singlecenter validation(n=711)lacks external/generalizability testing across diverse populations,risking bias from local demographics.Second,MAFLD subtyping(e.g.,lean MAFLD,diabetic MAFLD)was omitted despite acknowledged disease heterogeneity;this overlooks distinct pathophysiologies and may limit utility in stratified care.Third,while TCM features ranked among the top predictors in SHAP analysis,their clinical interpretability remains nebulous without mechanistic links to metabolic dysregulation.To resolve these gaps,we propose external validation in multiethnic cohorts using the published feature set(e.g.,aspartate aminotransferase/alanine aminotransferase,low-density lipoprotein cholesterol,TCM tongue markers)to assess robustness.Subtype-specific modeling to capture MAFLD heterogeneity,potentially enhancing accuracy in highrisk subgroups.Probing TCM microbiome/metabolomic correlations to ground tongue phenotypes in biological pathways,elevating model credibility.Despite shortcomings,this work pioneers a low-cost screening paradigm.Future iterations addressing these issues could revolutionize early MAFLD detection in resource-limited settings.
文摘Rainfall event is the very specific, reliable unambiguous precursor for the earthquake event. Over the years scientists have hunted for some signal—a precursory sign, however faint—that would allow forecasters to pin-point exactly where and when the big ones will hit. After decades spent searching in vain, many seismologists now doubt whether such a signal even exists. But in a great surprise to everyone, from an ordinary lay man to eminent scientists, 100% earthquakes occur after rainfalls! Though I have the findings for the entire regions of the world, here E Turkey are the region for submission for the period Jan-November, 2012 to study the strong correlation and show the strong evidence to prove that the 100% earthquakes after rainfall in a consistence manner. Anyone can very easily verify the validity of the findings for any forthcoming earthquakes for any regions of E Turkey in just two weeks of period. Nature does not give two different results for the same phenomena, for two different observers. Though there exists a very strong relation between the rainfalls and the earthquakes, scientists and seismologists have not been able to detect and identify this rainfall precursory signal for hundreds of years that consistently occurs before earthquakes. The methodology of rainfall event before earthquakes, even works consistently for earthquake prediction purpose, especially in any regions of the world. Rainfall type precursor is the best approach to predict specific earthquakes, which provide the potential for estimating the epicenter and magnitude of any moderate to strong earthquakes. Earthquakes are more likely when there is rain than it is not. The magnitudes of a resulting individual earthquake depend on the severity of the weather changes. However, in a very few cases the time scales and magnitude do vary substantially as a consequence of local site geology and other factors.
文摘 "Global IT market will sustain increase in fluctuating in 2005. In varied merger, integration, adjustment, global IT industry moves ahead prudently. And China IT market will obtain enormous opportunities and challenges in this market." Mr. Xie Shihe,President of China of IDC company. This is the first time of IDC to deliver its point of view to media.……
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2020D01C236)
文摘BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.
基金Startup Fund for Scientific Research,Fujian Medical University,No.2019QH1302.
文摘BACKGROUND Surgery is the primary curative option in patients with hepatocellular carcinoma(HCC).However,recurrence within 2 years is observed in 30%–50%of patients,being a major cause of mortality.AIM To construct and verify a non-invasive prediction model combining contrastenhanced ultrasound(CEUS)with serology biomarkers to predict the early recurrence of HCC.METHODS Records of 744 consecutive patients undergoing first-line curative surgery for HCC in one institution from 2016–2018 were reviewed,and 292 local patients were selected for analysis.General characteristics including gender and age,CEUS liver imaging reporting and data system(LIRADS)parameters including wash-in time,wash-in type,wash-out time,and wash-out type,and serology biomarkers including alanine aminotransferase,aspartate aminotransferase,platelets,and alpha-fetoprotein(AFP)were collected.Univariate analysis and multivariate Cox proportional hazards regression model were used to evaluate the independent prognostic factors for tumor recurrence.Then a nomogram called CEUS model was constructed.The CEUS model was then used to predict recurrence at 6 mo,12 mo,and 24 mo,the cut-off value was calculate by X-tile,and each C-index was calculated.Then Kaplan-Meier curve was compared by logrank test.The calibration curves of each time were depicted.RESULTS A nomogram predicting early recurrence(ER),named CEUS model,was formulated based on the results of the multivariate Cox regression analysis.This nomogram incorporated tumor diameter,preoperative AFP level,and LIRADS,and the hazard ratio was 1.123(95%confidence interval[CI]:1.041-1.211),1.547(95%CI:1.245-1.922),and 1.428(95%CI:1.059-1.925),respectively.The cut-off value at 6 mo,12 mo,and 24 mo was 100,80,and 50,and the C-index was 0.748(95%CI:0.683-0.813),0.762(95%CI:0.704-0.820),and 0.762(95%CI:0.706-0.819),respectively.The model showed satisfactory results,and the calibration at 6 mo was desirable;however,the calibration at 12 and 24 mo should be improved.CONCLUSION The CEUS model enables the well-calibrated individualized prediction of ER before surgery and may represent a novel tool for biomarker research and individual counseling.
基金Supported by the National Natural Science Foundation of China,No.81771815.
文摘BACKGROUND Large-scale functional connectivity(LSFC)patterns in the brain have unique intrinsic characteristics.Abnormal LSFC patterns have been found in patients with dementia,as well as in those with mild cognitive impairment(MCI),and these patterns predicted their cognitive performance.It has been reported that patients with type 2 diabetes mellitus(T2DM)may develop MCI that could progress to dementia.We investigated whether we could adopt LSFC patterns as discriminative features to predict the cognitive function of patients with T2DM,using connectome-based predictive modeling(CPM)and a support vector machine.AIM To investigate the utility of LSFC for predicting cognitive impairment related to T2DM more accurately and reliably.METHODS Resting-state functional magnetic resonance images were derived from 42 patients with T2DM and 24 healthy controls.Cognitive function was assessed using the Montreal Cognitive Assessment(MoCA).Patients with T2DM were divided into two groups,according to the presence(T2DM-C;n=16)or absence(T2DM-NC;n=26)of MCI.Brain regions were marked using Harvard Oxford(HOA-112),automated anatomical labeling(AAL-116),and 264-region functional(Power-264)atlases.LSFC biomarkers for predicting MoCA scores were identified using a new CPM technique.Subsequently,we used a support vector machine based on LSFC patterns for among-group differentiation.The area under the receiver operating characteristic curve determined the appearance of the classification.RESULTS CPM could predict the MoCA scores in patients with T2DM(Pearson’s correlation coefficient between predicted and actual MoCA scores,r=0.32,P=0.0066[HOA-112 atlas];r=0.32,P=0.0078[AAL-116 atlas];r=0.42,P=0.0038[Power-264 atlas]),indicating that LSFC patterns represent cognition-level measures in these patients.Positive(anti-correlated)LSFC networks based on the Power-264 atlas showed the best predictive performance;moreover,we observed new brain regions of interest associated with T2DM-related cognition.The area under the receiver operating characteristic curve values(T2DM-NC group vs.T2DM-C group)were 0.65-0.70,with LSFC matrices based on HOA-112 and Power-264 atlases having the highest value(0.70).Most discriminative and attractive LSFCs were related to the default mode network,limbic system,and basal ganglia.CONCLUSION LSFC provides neuroimaging-based information that may be useful in detecting MCI early and accurately in patients with T2DM.
基金supported by grants from the Ministry of Science and Technology of the People’s Republic of China(No.2013BAI09B02 and No.2013DFB30310)Beijing Municipal Commission of Science and Technology(No.D131100002-313001)the National Science Foundation Council of China(Nos.81170168,81370290,81370292 and 81470465)
文摘Catheter ablation has been recommended as a treatment option for paroxysmal atrial fibrillation（PAF） patients complicated with type 2 diabetes mellitus（T2DM）. PAF patients with T2 DM have a higher recurrence rate after catheter ablation. Prolongation of corrected QT（QTc） interval has been linked to poor outcomes in T2 DM patients. Whether the abnormal QTc interval is associated with the ablation outcome in the PAF patients with T2 DM remains unknown. In this study, 134 PAF patients with T2 DM undergoing primary catheter ablation were retrospectively enrolled. Pre-procedural QTc interval was corrected by using the Bazett＇s formula. Cox proportional hazards models were constructed to assess the relationship between QTc interval and the recurrence of AF. After a 29.1-month follow-up period, 61 patients experienced atrial tachyarrhythmia recurrence. Recurrent patients had a longer QTc interval than non-recurrent patients（425.2±21.5 ms vs. 414.1±13.4 ms, P=0.002）. Multivariate Cox regression analysis revealed that QTc interval [hazard ratio（HR）=1.026, 95% confidence interval（CI） 1.012–1.040, P=0.005] and left atrial diameter（LAD）（HR=1.125, 95% CI 1.062–1.192, P=0.003） were independent predictors of recurrent atrial tachyarrhythmia. Receiver operating characteristic analysis demonstrated that the cut-off value of QTc（418 ms） predicted arrhythmia recurrence with a sensitivity of 55.7% and a specificity of 69.9%. A combination of LAD and QTc was more effective than LAD alone（P〈0.001） in predicting arrhythmia recurrence after the procedure. QTc interval could be used as an independent predictor of arrhythmia recurrence in T2 DM patients undergoing AF ablation, thus providing a simple method to identify those patients who likely have a better outcome following the procedure.
文摘Drilling in any environment is challenging as it poses a challenge to drill reservoir targets without losses and minimum casing strings and is even challenging in HPHT (high pressure high temperature) environment. Seismic is the fundamental for pre-drill prognosis and completion design. The target depth prognosis is achieved through depth transformation by using seismic velocities or available velocity logs in the nearby field or block and often has varying degree of uncertainty in target depths depending upon the suitable of the velocity function used. The velocity function used could be affected due to available seismic bandwidth or structure. These uncertainties in target depths often lead to increased well costs as a result of wellbore stability issues & undesired casing strings. Most common issue faced by drillers is the target confirmation & distance to these targets ahead of bit. Vertical seismic profile (VSP) look-ahead at intermediate depths is one of the approaches to mitigate these uncertainties and drill wells safely. VSP help confirm the presence of drilling targets & also predict the depth to top of these targets. Additionally, the predicted interval velocity is used to predict the pre-pressure for next section drilling. In South China Sea, oil & gas operators face a significant risk while drilling over-pressured formations. It is therefore imperative to know the depth to top of these high pressured formations to avoid drilling directly into it and risking the well. It is also important to know the pore-pressure and mud weight for the next section to be drilled for safe drilling & with minimum casing strings [1] [2] [3]. It is more difficult to get this information in the HPHT environment due to the lack of high temperature tools [4]. Schlumberger’s proprietary QVSI*—High pressure, high temperature VSI* (Versatile Seismic Imager) has been successfully used to predict the target depth for casing landing and pore-pressure prediction in HPHT environment. QVSI is the latest generation of VSI* Versatile Seismic Imager tools developed by Schlumberger to acquire high quality tri-axial borehole seismic data in extreme environment wells. The QVSI* tool uses the Q-Technology* singlesensor hardware and software and advanced wireline telemetry for fast digital seismic data transmission from borehole to surface. QVSI is a high-temperature, high-pressure array tool design that focuses on tri-axial vector fidelity and efficient data acquisition, extending the limits in a 4-tool configuration to 500°F (260℃) and 30 kpsi (207 MPa). In this paper, a case study is presented for Well-XX for CNOOC from South China Sea. The well-xx is located in Yanyan Sag, Qiongdongnan Basin and the downhole temperature was 204℃. The main target layer is Lingshui III sandstone, which is controlled by Northwest fault. It is a gas well and critical for the client to land the casing at right depth and know the drilling parameters for the next section ahead. QVSI* predicted the target depth within ±2 m for decision on casing point. The predicted pore pressure was within ±0.1 ppg.
基金supported by Medical Scientific Research Foundation of Chongqing of China(2022MSXM048).
文摘Background:Cholangiocarcinoma(CCA)is highly malignant and has a poor prognosis has a high malignant degree and poor prognosis.The purpose of this study is to develop a new prognostic model based on genes related to the tumor microenvironment(TME).Methods:Derived from the discerned differentially expressed genes within The Cancer Genome Atlas(TCGA)dataset,this investigation employed the methodology of weighted gene co-expression network analysis(WGCNA)to ascertain gene co-expressed modules intricately linked to the Tumor Microenvironment(TME)among Cholangiocarcinoma(CCA)patients.The genes associated with prognosis,as identified through Cox regression analysis,were employed in the formulation of a predictive model.This model underwent validation,leading to the development of a risk score formula and nomogram.Concurrently,we validated the model’s reliability using data from CCA patients in the Gene Expression Omnibus(GEO)database(accession:GSE107943).Results:6139 DEGs were divided into 10 co-expressed gene modules using WGCNA.Among these,two modules(blue module with 832 genes and brown module with 1379 genes)showed high correlation with the TME.Five prognostic genes(BNIP3,COL4A3,SPRED3,CEBPB,PLOD2)were identified through Cox regression analysis,and a prognostic model and risk score formula were developed based on these genes.Risk score formula:Risk score=BNIP3×1.70520-COL4A3×2.39815+SPRED3×1.17936+CEBPB×0.40456+PLOD2×0.24785.Kaplan-Meier survival analysis revealed that the survival probabilities of the low-risk group were significantly higher than those of the high-risk group.Furthermore,the related evaluation indexes suggested that the model exhibited strong predictive ability.Conclusion:The prognostic model,based on five TME-related genes(BNIP3,COL4A3,SPRED3,CEBPB,PLOD2),could accurately assess the prognosis of CCA patients to aid in guiding clinical decisions.
基金supported by the National Key Research and Development Program(2021YFC2701204 to H.W.)the"Jianbing"and"Lingyan"R&D programs of Zhejiang province(2022C03013 to H.W.)+3 种基金the National Natural Science Foundation of China(82373260 to H.W.and 82273211 to Y.H.)the Research Funds from Tongji Hospital(20185BJRC004 and 2019BJRC008 to H.W.)the Fundamental Research Funds for the Central Universities,HUST(2021GCRC073 to X.H.)the Nature Science Foundation of Hubei Province(2021CFB346 to Y.H.).
文摘Cervical cancer(CC)is the second most common cancer of female reproductive system.However,satisfactory prognostic model for CC remains to be established.In this study,we perform whole-exome sequencing on formalin-fixed and paraffin-embedded tumor specimens extracted from 67 recurrent and 28 matched non-recurrent CC patients.As a result,four core mutated genes(i.e.,DCHS2,DNAH10,RYR1,and WDFY4)that are differentially presented in recurrent and non-recurrent CC patients are screened out to construct a recurrence-free related score(RRS)model capable of predicting CC prognosis in our cohort,which is further confirmed in TCGA CESC cohort.Moreover,combining tumor mutational burden(TMB)and RRS into an integrated RRS/TMB model enables better stratification of CC patients with distinct prognosis in both cohorts.Increased infiltration of multiple immune cell types,enriched interferon signaling pathway,and elevated cytolytic activity are evident in tumors from patients with a higher RRS and/or a higher TMB.In summary,this study establishes a novel mutation-based prognostic model for CC,the predictive value of which can be attributable to immunological mechanisms.This study will provide insight into the utilization of mutational analysis in guiding therapeutic strategies for CC patients.
文摘Background and Aims:T lymphocytes play a pivotal role in resolving hepatitis B virus infection.This study aimed to investigate the dynamics of peripheral blood T lymphocyte subsets during peginterferon alpha(peg-IFN-α)therapy and their association with hepatitis B surface antigen(HBsAg)clearance in inactive HBsAg carriers(IHCs).Methods:This prospective observational study enrolled 197 IHCs treated with peg-IFNα-2a/2b for 48 weeks and followed for 24 weeks(treatment group),and 221 IHCs who were regularly monitored for 72 weeks without treatment(IHC control group).Peripheral blood T lymphocyte subsets were evaluated using flow cytometry at baseline,and at 12,24,48,and 72 weeks in both groups.At 72 weeks,IHCs in the treatment group were categorized into an HBsAg clearance group and an HBsAg persistence group.Differences in T lymphocyte subsets among these groups were compared,and correlations between T lymphocyte subsets and HBsAg clearance were analyzed.Results:At 72 weeks,intention-to-treat analysis showed significantly higher HBsAg clearance(46.7%)and seroconversion rates(34.5%)in the treatment group compared to the IHC control group(HBsAg clearance rate of 1.4%,seroconversion rate of 0.9%;both p<0.001).The median absolute counts of CD3^(+),CD4^(+),and CD8^(+)cells significantly decreased at 12,24,and 48 weeks in both the HBsAg clearance and persistence groups,returning to baseline at 72 weeks(all p<0.001).IHCs with HBsAg clearance had higher median percentages of CD3^(+)CD8^(+)cells and lower median percentages of CD3^(+)CD4^(+)cells and CD4^(+)/CD8^(+)ratios at 12,24,and 48 weeks compared to the HBsAg persistence and IHC control groups(all p<0.001).Baseline HBsAg levels(below 2.0 log10 IU/mL)and hepatitis B virus DNA levels(below 20 IU/mL),alanine aminotransferase elevation at 12 weeks(greater than 2×upper limit of normal),and CD4^(+)/CD8^(+)ratios(less than 1.5 at 12 weeks and below 1.4 at 24 weeks)were predictive of HBsAg clearance.Conclusions Peripheral blood CD4^(+)/CD8^(+)ratios at 12 and 24 weeks may serve as predictive markers for HBsAg clearance in IHCs treated with peg-IFN-α.
基金the National Natural Science Foundation of China(T2425013,32370701,32470692,32170657)the National Key R&D Project of China(2023YFC3402501)+1 种基金Shanghai Municipal Science and Technology Major Project,the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA12040104)the 111 Project(B13016).
文摘The treatment efficacy of anti-diabetic therapies is highly heterogeneous among patients with type 2 diabetes(T2D)(Ahmad et al.2022).Predictive biomarkers can be used to stratify patients into subgroups with varying efficacy before receiving the treatment,and help advance the understanding of disease and treatment(Ahmad et al.2022).Thus,identifying predictive biomarkers is important for precision medicine of patients with T2D.Approved in China in October 2021 as an adjunct to diet and exercise for improving glycemic control in adult patients with T2D,chiglitazar is a non-thiazolidinedione agonist of theα,δandγsubtypes of the peroxisome proliferator-activated receptors(PPARs)(Deeks 2022).
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
基金supported by the National Natural Science Foundation of China(Grant No.U2342208)support from NSF/Climate Dynamics Award#2025057。
文摘Predicting monsoon climate is one of the major endeavors in climate science and is becoming increasingly challenging due to global warming. The accuracy of monsoon seasonal predictions significantly impacts the lives of billions who depend on or are affected by monsoons, as it is essential for the water cycle, food security, ecology, disaster prevention, and the economy of monsoon regions. Given the extensive literature on Asian monsoon climate prediction, we limit our focus to reviewing the seasonal prediction and predictability of the Asian Summer Monsoon (ASM). However, much of this review is also relevant to monsoon predictions in other seasons and regions. Over the past two decades, considerable progress has been made in the seasonal forecasting of the ASM, driven by an enhanced understanding of the sources of predictability and the dynamics of seasonal variability, along with advanced development in sophisticated models and technologies. This review centers on advances in understanding the physical foundation for monsoon climate prediction (section 2), significant findings and insights into the primary and regional sources of predictability arising from feedback processes among various climate components (sections 3 and 4), the effects of global warming and external forcings on predictability (section 5), developments in seasonal prediction models and techniques (section 6), the challenges and limitations of monsoon climate prediction (section 7), and emerging research trends with suggestions for future directions (section 8). We hope this review will stimulate creative activities to enhance monsoon climate prediction.
