To address the challenge of identifying the primary causes of energy consumption fluctuations and accurately assessing the influence of various factors in the converter unit of an iron and steel plant,the focus is pla...To address the challenge of identifying the primary causes of energy consumption fluctuations and accurately assessing the influence of various factors in the converter unit of an iron and steel plant,the focus is placed on the critical components of material and heat balance.Through a thorough analysis of the interactions between various components and energy consumptions,six pivotal factors have been identified—raw material composition,steel type,steel temperature,slag temperature,recycling practices,and operational parameters.Utilizing a framework based on an equivalent energy consumption model,an integrated intelligent diagnostic model has been developed that encapsulates these factors,providing a comprehensive assessment tool for converter energy consumption.Employing the K-means clustering algorithm,historical operational data from the converter have been meticulously analyzed to determine baseline values for essential variables such as energy consumption and recovery rates.Building upon this data-driven foundation,an innovative online system for the intelligent diagnosis of converter energy consumption has been crafted and implemented,enhancing the precision and efficiency of energy management.Upon implementation with energy consumption data at a steel plant in 2023,the diagnostic analysis performed by the system exposed significant variations in energy usage across different converter units.The analysis revealed that the most significant factor influencing the variation in energy consumption for both furnaces was the steel grade,with contributions of−0.550 and 0.379.展开更多
We established a diagnostic model to predict acute Mycoplasma pneumoniae （M. pneumonia） infection in elderly Community-acquired pneumonia （CAP） patients. We divided 456 patients into acute and non-acute M. pneumon...We established a diagnostic model to predict acute Mycoplasma pneumoniae （M. pneumonia） infection in elderly Community-acquired pneumonia （CAP） patients. We divided 456 patients into acute and non-acute M. pneumoniae infection groups. Binary logistic regression and receiver operating characteristic （ROC） curves were used to establish a predictive model. The following independent factors were identified： age 〉 70 years; serum cTNT level 〉 0.0S ng/mL; lobar consolidation; mediastinal lymphadenopathy; and antibody titer in the acute phase 〉 1：40. The area under the ROC curve of the model was 0.923 and a score of 2 7 score predicted acute M. pneumoniae infection in elderly patients with CAP. The predictive model developed in this study has high diagnostic accuracy for the identification of elderly acute M. pneumoniae infection.展开更多
A high resolved two-dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate velocity field in the South China Sea(SCS). The study of model results shows that eddy diffu...A high resolved two-dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate velocity field in the South China Sea(SCS). The study of model results shows that eddy diffusion does not change basic structure of circulation in the SCS and does not change the direction of invasive water, but changes the value of transport considerably especially in straits. The velocity field is not changed whether the wind stress is considered or not. This result shows the circulation is largely determined by a density field which well records most of the important contribution of the wind stress effect. Potential vorticity is calculated to testify the dynamics of the model results. The result shows that a good conservation of the nonlinear PV. This indicates most effects of the important nonlinear processes are well recorded in density and the nonlinear term is negligible so that the simplified model is reliable. The model results show the water exchanges between the SCS and open ocean or surrounding seas. Cold deep water invades through Luzon Strait and Warm shallow water is pushed out mainly through Karimata Straits. The model results also reveal the structure of the circulation in the SCS basin. In two circulations of upper and middle layers, a cyclonic one in the north and an anti-cyclonic one in the south, reflect the climatologic average of the circulation driven by monsoon. In the deep or bottom layer, these two circulations reflect the topography of the basin. Above the middle layer, invasive water enters westward in the north but the way of invasion of Kuroshio is not clear. Below the deep layer, a current goes down south near the east basin ,and invasive water enters in the basin from the west Pacific.展开更多
Presently, research is lacking regarding the diagnosis and evaluation of habitat degradation in enclosed bay systems. We established a diagnostic model for enclosed bay habitat degradation(EBHD model) using a multi-ap...Presently, research is lacking regarding the diagnosis and evaluation of habitat degradation in enclosed bay systems. We established a diagnostic model for enclosed bay habitat degradation(EBHD model) using a multi-approach integrated diagnostic method in consideration of driving force-pressurestate-infl uence-response. The model optimizes the indicator standardization with annual average change rate of habitat degradation as the basic element, to refl ect accurately the impact of the change and speed of degradation on the diagnostic results, to quantify reasonably the contribution of individual diagnostic indicator to habitat degradation, and to solve the issue regarding the infl uence of subjective factors on the evaluation results during indicator scoring. We then applied the EBHD model for the Sansha Bay in Fujian Province, China, evaluated comprehensively the situation of habitat degradation in the bay, and screened out the major controlling factors in the study area. Results show that the diagnostic results are consistent in overall with the real situation of the study area. Therefore, the EBHD model is advantageous in terms of objectivity and accuracy, making a breakthrough in diagnosis and evaluation for habitat degradation in enclosed bay systems.展开更多
AIM： To build a clinical diagnostic model of primary open angle glaucoma （POAG） using the normal probability chart of frequency-domain optical coherence tomography （FD-OCT）. METHODS： This is a cross-sectional ...AIM： To build a clinical diagnostic model of primary open angle glaucoma （POAG） using the normal probability chart of frequency-domain optical coherence tomography （FD-OCT）. METHODS： This is a cross-sectional study. Total 133 eyes from 133 healthy subjects and 99 eyes from 99 early POAG patients were included in the study. The retinal nerve fibre layer （RNFL） thickness parameters of optic nerve head （ONH） and RNFL3.45 scan were measured in one randomly selected eye of each subject using RTVue-100 FD-OCT. Then, we used these parameters to establish the diagnostic models. Four different diagnostic models based on two different area partition strategies on ONH and RNFL3.45 parameters, including ONH traditional area partition model （ONH-T）, ONH new area partition model （ONH-N）, RNFL3.45 traditional area partition model （RNFL3.45-T） and RNFL3.45 new area partition model （RNFL3.45-N）, were built and tested by cross-validation. RESULTS： The new area partition models had higher area under the receiver operating characteristic （AROC; ONH-N： 0.990; RNFL3.45-N： 0.939） than corresponding traditional area partition models （ONH-T： 0.979; RNFL3.45-T： 0.881）. There was no statistical difference among AROC of ONH-T, ONH-N, and RNFL3.45-N. Nevertheless, ONH-N was the simplest model. CONCLUSION： The new area partition models had higher diagnostic accuracy than corresponding traditional area partition models, which can improve the diagnostic ability of early POAG. In particular, the simplest ONH-N diagnostic model may be convenient for clinical application.展开更多
Mining rich semantic information hidden in heterogeneous information network is one of the important tasks of data mining. Generally, a nuclear medicine text consists of the description of disease (<i>i.e.</i...Mining rich semantic information hidden in heterogeneous information network is one of the important tasks of data mining. Generally, a nuclear medicine text consists of the description of disease (<i>i.e.</i>, lesions) and diagnostic results. However, how to construct a computer-aided diagnostic model with a large number of medical texts is a challenging task. To automatically diagnose diseases with SPECT imaging, in this work, we create a knowledge-based diagnostic model by exploring the association between a disease and its properties. Firstly, an overview of nuclear medicine and data mining is presented. Second, the method of preprocessing textual nuclear medicine diagnostic reports is proposed. Last, the created diagnostic modes based on random forest and SVM are proposed. Experimental evaluation conducted real-world data of diagnostic reports of SPECT imaging demonstrates that our diagnostic models are workable and effective to automatically identify diseases with textual diagnostic reports.展开更多
Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin(FUO) hospitalized in Xiangya Hospital C...Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin(FUO) hospitalized in Xiangya Hospital Central South University, from January, 2006 to April, 2011 were retrospectively analyzed. Patients enrolled were divided into two groups. The first group was used to develop a diagnostic model: independent variables were recorded and considered in a logistic regression analysis to identify infectious and non-infectious diseases(αin = 0.05, αout = 0.10). The second group was used to evaluate the diagnostic model and make ROC analysis.Results The diagnostic rate of 143 patients in the first group was 87.4%, the diagnosis included infectious disease(52.4%), connective tissue diseases(16.8%), neoplastic disease(16.1%) and miscellaneous(2.1%). The diagnostic rate of 168 patients in the second group was 88.4%, and the diagnosis was similar to the first group. Logistic regression analysis showed that decreased white blood cell count(WBC < 4.0×109/L), higher lactate dehydrogenase level(LDH > 320 U/L) and lymphadenectasis were independent risk factors associated with non-infectious diseases. The odds ratios were 14.74, 5.84 and 5.11(P ≤ 0.01), respectively. In ROC analysis, the sensitivity and specificity of the positive predictive values was 62.1% and 89.1%, respectively, while that of negative predicting values were 75% and 81.7%, respectively(AUC = 0.76, P = 0.00).Conclusions The combination of WBC < 4.0×109/L, LDH > 320 U/L and lymphadenectasis may be useful in discriminating infectious diseases from non-infectious diseases in patients hospitalized as FUO.展开更多
ObjectiveeThisstudy used data-independent acquisition(DIA)proteomics to analyze plasma protein expression in sepsis-induced coagulopathy(SIC),identify key biomarkers,and develop a diagnostic model.Methods This prospec...ObjectiveeThisstudy used data-independent acquisition(DIA)proteomics to analyze plasma protein expression in sepsis-induced coagulopathy(SIC),identify key biomarkers,and develop a diagnostic model.Methods This prospective study included 46 adult sepsis patients from the intensive care unit.Patients were categorized into a general sepsis group(n=26)and an SIC group(n=20)based on established SIC criteria.Plasma samples underwent proteomic and bioinformatics analyses toidentifyydifferentiallyexpressed protein(DEP)using LASSO regression and Random Forest.A diagnostic model was constructed and assessedvia receiver operating characteristic(ROC)curve analysis.Results The baseline data revealed that SIC patients exhibited longer prothrombin times,lower platelet counts,and higher D-dimer,fibrin degradation products,blood lactate,SOFA scores,and APACHE II scores compared with general sepsis patients(P<0.05).DIA proteomics identified 2637 proteins,with 240 DEP meeting the criteria(fold change>1.5,P<0.05),including 81 upregulated and 159 downregulated DEP.Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear.Gene ontology(GO)annotation showed that DEP were mainly involved in cellular physiology,biological regulation,and stress response processes in biological processes.Domain annotation revealed a predominance of immunoglobulin V regions in DEP,which are crucial for antigen recognition and binding.KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity,glycosylphosphatidylinositol anchor biosynthesis,tumor necrosis factor signaling,and NF-kB signaling.LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP.The SIC diagnostic nomogram showed an area under the curve of 0.896,with 0.731 specificity and 0.900 sensitivity.Conclusion The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis。展开更多
Hepatocellular carcinoma(HCC)is a critical cancerworldwide due to its low survival rate[1].In the United States,the overall 5-year survival rate of patients with HCC is 22%,which decreases sharply with cancer progress...Hepatocellular carcinoma(HCC)is a critical cancerworldwide due to its low survival rate[1].In the United States,the overall 5-year survival rate of patients with HCC is 22%,which decreases sharply with cancer progression[2].Early detection of HCC improves patient survival.Serum alpha-fetoprotein(AFP)is a widely used biomarker for the diagnosis of HCC,but it is often elevated in patients with cirrhosis,resulting in false-positive results[3].Diagnostic markers for early detection of HCC have been investigated previously[4],but none are widely applied in clinical settings.展开更多
To enhance the safety operation management of the subway and ascertain the level of the subway department's emergency response capability,a cloud diagnostic model is proposed.This model,grounded in the 4R crisis m...To enhance the safety operation management of the subway and ascertain the level of the subway department's emergency response capability,a cloud diagnostic model is proposed.This model,grounded in the 4R crisis management theory and the subway's unique characteristics,constructs a comprehensive diagnostic system.The DEMATEL-ANP model is employed to identify the interactive coupling relationship between various indicators in the diagnostic system,and the diagnostic level is judiciously divided.The cloud model is then utilized to holisticaly diagnose the subway's emergency handling capacity,thereby pinpointing the specific areas for improvement in subway emergency capacity and bolstering the safety and reliability of subway operation.To circumvent the emergence of imaginary numbers in the digital features of the cloud model,the MBCT-SR algorithm is implemented to enhance the cloud model,and the pSCM algorithm is applied to optimize the precision of cloud similarity discrimination.Using the Nanjing Metro Line 2 as a case study,the analysis reveals that the first-level indicators A and B of the object under diagnosis are underperforming.This necessitates a targeted enhancement of both organizational management of subway emergency personnel and capabilities for monitoring and early warning.Vltimately,the comprehensive diagnostic outcome was classified as a'good'level,which is consistent with the actual situation,verifying the effectiveness and practical application value of the diagnostic model.展开更多
Background:Immunoglobulin A nephropathy(IgAN)is the most common pathological type of glomerular disease.Kidney biopsy,the gold standard for IgAN diagnosis,has not been routinely applied in hospitals worldwide due to i...Background:Immunoglobulin A nephropathy(IgAN)is the most common pathological type of glomerular disease.Kidney biopsy,the gold standard for IgAN diagnosis,has not been routinely applied in hospitals worldwide due to its invasion nature.Thus,we aim to establish a non-invasive diagnostic model and determine markers to evaluate disease severity by analyzing the serological parameters and pathological stages of patients with IgAN.Methods:A total of 272 biopsy-diagnosed IgAN inpatients and 518 non-IgA nephropathy inpatients from the Department of Nephrology of Chinese People's Liberation Army General Hospital were recruited for this study.Routine blood examination,blood coagulation testing,immunoglobulin-complement testing,and clinical biochemistry testing were conducted and pathological stages were analyzed according to Lee grading system.The serological parameters and pathological stages were analyzed.The receiver operating characteristic(ROC)analysis was performed to estimate the diagnostic value of the clinical factors.Logistic regression was used to establish the diagnostic model.Results:There were 15 significantly different serological parameters between the IgAN and non-IgAN groups(all P<0.05).The ROC analysis was performed to measure the diagnostic value for IgAN of these parameters and the results showed that the area under the ROC curve(AUC)of total protein(TP),total cholesterol(TC),fibrinogen(FIB),D-dimer(D2),immunoglobulin A(IgA),and immunoglobulin G(IgG)were more than 0.70.The AUC of the"TC+FIB+D2+IgA+age"combination was 0.86,with a sensitivity of 85.98%and a specificity of 73.85%.Pathological grades ofⅠ,Ⅱ,Ⅲ,Ⅳ,andⅤaccounted for 2.21%,17.65%,62.50%,11.76%,and 5.88%,respectively,with gradeⅢbeing the most prevalent.The levels of urea nitrogen(UN)(13.57土5.95 vs.6.06土3.63,5.92+2.97,5.41±1.73,and 8.41±3.72μmol/L,respectively)and creatinine(Cr)(292.19±162.21 vs.80.42±24.75,103.79±72.72,96.41±33.79,and 163.04±47.51μmol/L,respectively)were significantly higher in grade V than in the other grades,and the levels of TP(64.45±7.56,67.16±6.94,63.22±8.56,and 61.41±10.86 vs.37.47±5.6 mg/d,respectively),direct bilirubin(DB)(2.34±1.23,2.58±1.40,1.91±0.97,and 1.81±1.44 vs.0.74±0.57μmol/L,respectively),and IgA(310.35±103.78,318.48±107.54,292.58±81.85,and 323.29±181.67 vs.227.17±68.12g/L,respectively)were significantly increased in grades II-V compared with grade I(all P<0.05).Conclusions:The established diagnostic model that combined multiple factors(TC,FIB,D2,IgA,and age)might be used for IgAN non-invasive diagnosis.TP,DB,IgA,Cr,and UN have the potential to be used to evaluate IgAN disease severity.展开更多
Background:Clinical opportunistic screening is a cost-effective cancer screening modality.This study aimed to establish an easyto-use diagnostic model serving as a risk stratification tool for identification of indivi...Background:Clinical opportunistic screening is a cost-effective cancer screening modality.This study aimed to establish an easyto-use diagnostic model serving as a risk stratification tool for identification of individuals with malignant gastric lesions for opportunistic screening.Methods:We developed a questionnaire-based diagnostic model using a joint dataset including two clinical cohorts from northern and southern China.The cohorts consisted of 17,360 outpatients who had undergone upper gastrointestinal endoscopic examination in endoscopic clinics.The final model was derived based on unconditional logistic regression,and predictors were selected according to the Akaike information criterion.External validation was carried out with 32,614 participants from a community-based randomized controlled trial.Results:This questionnaire-based diagnostic model for malignant gastric lesions had eight predictors,including advanced age,male gender,family history of gastric cancer,low body mass index,unexplained weight loss,consumption of leftover food,consumption of preserved food,and epigastric pain.This model showed high discriminative power in the development set with an area under the receiver operating characteristic curve(AUC)of 0.791(95%confidence interval[CI]:0.750-0.831).External validation of the model in the general population generated an AUC of 0.696(95%CI:0.570-0.822).This model showed an ideal ability for enriching prevalent malignant gastric lesions when applied to various scenarios.Conclusion:This easy-to-use questionnaire-based model for diagnosis of prevalent malignant gastric lesions may serve as an effective prescreening tool in clinical opportunistic screening for gastric cancer.展开更多
Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of D...Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN.Kidney biopsy is the gold standard for diagnosing DN;however,its invasive character is its primary limitation.The machine learning approach provides a non-invasive and specific criterion for diagnosing DN,although traditional machine learning algorithms need to be improved to enhance diagnostic performance.Methods:We applied high-throughput RNA sequencing to obtain the genes related to DN tubular tissues and normal tubular tissues of mice.Then machine learning algorithms,random forest,LASSO logistic regression,and principal component analysis were used to identify key genes(CES1G,CYP4A14,NDUFA4,ABCC4,ACE).Then,the genetic algorithm-optimized backpropagation neural network(GA-BPNN)was used to improve the DN diagnostic model.Results:The AUC value of the GA-BPNN model in the training dataset was 0.83,and the AUC value of the model in the validation dataset was 0.81,while the AUC values of the SVM model in the training dataset and external validation dataset were 0.756 and 0.650,respectively.Thus,this GA-BPNN gave better values than the traditional SVM model.This diagnosis model may aim for personalized diagnosis and treatment of patients with DN.Immunohistochemical staining further confirmed that the tissue and cell expression of NADH dehydrogenase(ubiquinone)1 alpha subcomplex,4-like 2(NDUFA4L2)in tubular tissue in DN mice were decreased.Conclusion:The GA-BPNN model has better accuracy than the traditional SVM model and may provide an effective tool for diagnosing DN.展开更多
In this paper,a tbree-dimensional (3-D) baroclinic diagnostic model for short-range numerical forecast is proposed to calculate the monthly averaged flow field in the Bohai Sea. By using the model and monthly averaged...In this paper,a tbree-dimensional (3-D) baroclinic diagnostic model for short-range numerical forecast is proposed to calculate the monthly averaged flow field in the Bohai Sea. By using the model and monthly averaged tempeature and salinity date, monthly barotropic and baroclinic flow field are calculated,and 2-D and 3-D characteristics of flow are described and demonstrated. On the basis of the analysis of the modelling results and the observed temperature,salinity and wind data,the monthly and seasonal characteristics and generation mechanism of circulation in the Bohai Sea are also discussed. It is pointed out in this paper that in spring and autumn,the monthly averaged flow fields are not representative, for the wind direction varies in a wide range and the averaged wind field is much weaker than the instantaneous one. These results show the reliability of the model for describing the monthly characteristics in numerical forecast of ocean current.展开更多
Introduction:This study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy(DN)and construct a diagnostic model for DN in Chinese patients with...Introduction:This study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy(DN)and construct a diagnostic model for DN in Chinese patients with type 2 diabetes mellitus(T2DM).Methods:A cross-sectional investigation was conducted in a hospital setting.Based on medical data,a total of 743 patients from a tertiary hospital were selected and categorized into two groups:the diabetic nephropathy group(DN group)and the non-diabetic nephropathy group(non-DN group).Plasma levels of metabolites,including amino acids and acylcarnitines,were determined using a laser counter measurement system(LC-MS).Subsequently,partial least-squares regression was used to assess the significance of these metabolites.Receiver operating characteristic(ROC)curves were generated for factors that ranked highest in terms of relevance.Model performance was assessed using the curve(AUC).Results:Of the 743 patients with T2DM admitted to the hospital,145 had DN.Compared with the non-DN group,the DN group exhibited elevated systolic blood pressure(P=0.001),high-density lipoprotein cholesterol(P=0.01),and low-density lipoprotein cholesterol(P=0.042).Additionally,the DN group had a higher prevalence of stroke patients(P<0.001)and diabetic retinopathy patients(P<0.001).Finally,a risk model that included citrulline,leucine,tyrosine,valine,propionylcarnitine(C3),and palmitoylcarnitine(C16)was developed.This model achieved an AUC of 0.709,with a 95%confidence interval(CI)ranging from 0.626 to 0.793.Conclusions:A diagnostic model consisting of six plasma metabolites to assess the risk of DN in Chinese patients with T2DM may provide clues for future research.展开更多
Objective:A risk-based sequential screening strategy,from questionnaire-based assessment to biomarker measurement and then to endoscopic examination,has the potential to enhance gastric cancer(GC)screening efficiency....Objective:A risk-based sequential screening strategy,from questionnaire-based assessment to biomarker measurement and then to endoscopic examination,has the potential to enhance gastric cancer(GC)screening efficiency.We aimed to evaluate the ability of five common stomach-specific serum biomarkers to further enrich high-risk individuals for GC in the questionnaire-identified high-risk population.Methods:This study was conducted based on a risk-based screening program in Ningxia Hui Autonomous Region,China.We first performed questionnaire assessment involving 23,381 individuals(7,042 outpatients and 16,339 individuals from the community),and those assessed as“high-risk”were then invited to participate in serological assays and endoscopic examinations.The serological biomarker model was derived based on logistic regression,with predictors selected via the Akaike information criterion.Model performance was evaluated by the area under the receiver operating characteristic curve(AUC).Results:A total of 2,011 participants were ultimately included for analysis.The final serological biomarker model had three predictors,comprising pepsinogenⅠ(PGI),pepsinogenⅠ/Ⅱratio(PGR),and anti-Helicobacter pylori immunoglobulin G(anti-H.pylori IgG)antibodies.This model generated an AUC of 0.733(95%confidence interval:0.655-0.812)and demonstrated the best discriminative ability compared with previously developed serological biomarker models.As the risk cut-off value of our model rose,the detection rate increased and the number of endoscopies needed to detect one case decreased.Conclusions:PGI,PGR,and anti-H.pylori Ig G could be jointly used to further enrich high-risk individuals for GC among those selected by questionnaire assessment,providing insight for the development of a multi-stage riskbased sequential strategy for GC screening.展开更多
The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the ...The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.展开更多
Ovarian cancer has one of the highest mortality rates among gynecological malignancies.This disease has a low early detection rate,a high postoperative recurrence rate,and a 5-year survival rate of only 40%.Hence,ther...Ovarian cancer has one of the highest mortality rates among gynecological malignancies.This disease has a low early detection rate,a high postoperative recurrence rate,and a 5-year survival rate of only 40%.Hence,there is an urgent need to improve the early diagnosis and prognosis of ovarian cancer.Prediction models can effectively estimate the risk of disease occurrence,as well as its prognosis.Recently,many studies have established multiple ovarian cancer prediction models based on different regions and populations.These models can improve the detection rate and optimize the prognosis management to a certain extent.Herein,the construction principle of the ovarian cancer risk prediction model and its validation are summarized;furthermore,comprehensive reviews and comparisons of the different types of these models are made.Therefore,our review may be of great significance for the whole course of ovarian cancer management.展开更多
A 2-dimensional global free surface diagnostic model, combined with dynamic calculation, is used to investigate the world ocean circulation; the model has a horizontal resolution of 1/4°×1/4°. The simul...A 2-dimensional global free surface diagnostic model, combined with dynamic calculation, is used to investigate the world ocean circulation; the model has a horizontal resolution of 1/4°×1/4°. The simulated results agree well with the results of other modesl and observations. The distribution of Stream Function suggests that the main circulation systems in the wodd ocean have been represented, including oceanic currents strengthened in the oceanic western. Be close to the observed results, the net mass transport of the Kuroshio axes is estimated about 54Sv; The distribution of the horizontal circulation in each layer shows that the main circulation systems in the world ocean are well simulated, for example, the Kuroshio and the Antarctic Circumpolar Current can go down to the bottom layer, but the Gulf Stream cannot, and its direction reverses at the depths of 1000 to 2 000 m.展开更多
BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition an...BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition and multi-target stool DNA(MT-sDNA)test in the diagnosis of CRC.METHODS We assessed the performance of the MT-sDNA test based on a hospital clinical trial.The intestinal microbiota was tested using 16S rRNA gene sequencing.This case-control study enrolled 54 CRC patients and 51 healthy controls.We identified biomarkers of bacterial structure,analyzed the relationship between different tumor markers and the relative abundance of related flora components,and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size,redundancy analysis,and random forest analysis.RESULTS MT-sDNA was associated with Bacteroides.MT-sDNA and carcinoembryonic antigen(CEA)were positively correlated with the existence of Parabacteroides,and alpha-fetoprotein(AFP)was positively associated with Faecalibacterium and Megamonas.In the random forest model,the existence of Streptococcus,Escherichia,Chitinophaga,Parasutterella,Lachnospira,and Romboutsia can distinguish CRC from health controls.The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%,with a sensitivity and specificity of 98.1%and 92.3%,respectively.CONCLUSION There is a positive correlation of MT-sDNA,CEA,and AFP with intestinal microbiome.Eight biomarkers including six genera of gut microbiota,MT-sDNA,and CEA showed a prominent sensitivity and specificity for CRC prediction,which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.展开更多
基金financial support from the National Key R&D Program of China(Grant No.2020YFB1711100).
文摘To address the challenge of identifying the primary causes of energy consumption fluctuations and accurately assessing the influence of various factors in the converter unit of an iron and steel plant,the focus is placed on the critical components of material and heat balance.Through a thorough analysis of the interactions between various components and energy consumptions,six pivotal factors have been identified—raw material composition,steel type,steel temperature,slag temperature,recycling practices,and operational parameters.Utilizing a framework based on an equivalent energy consumption model,an integrated intelligent diagnostic model has been developed that encapsulates these factors,providing a comprehensive assessment tool for converter energy consumption.Employing the K-means clustering algorithm,historical operational data from the converter have been meticulously analyzed to determine baseline values for essential variables such as energy consumption and recovery rates.Building upon this data-driven foundation,an innovative online system for the intelligent diagnosis of converter energy consumption has been crafted and implemented,enhancing the precision and efficiency of energy management.Upon implementation with energy consumption data at a steel plant in 2023,the diagnostic analysis performed by the system exposed significant variations in energy usage across different converter units.The analysis revealed that the most significant factor influencing the variation in energy consumption for both furnaces was the steel grade,with contributions of−0.550 and 0.379.
基金supported by the Capital Medical Development and Scientific Research Fund(2009-1033)and the Science and Technology Plan of Beijing City(Z101107050210018)
文摘We established a diagnostic model to predict acute Mycoplasma pneumoniae （M. pneumonia） infection in elderly Community-acquired pneumonia （CAP） patients. We divided 456 patients into acute and non-acute M. pneumoniae infection groups. Binary logistic regression and receiver operating characteristic （ROC） curves were used to establish a predictive model. The following independent factors were identified： age 〉 70 years; serum cTNT level 〉 0.0S ng/mL; lobar consolidation; mediastinal lymphadenopathy; and antibody titer in the acute phase 〉 1：40. The area under the ROC curve of the model was 0.923 and a score of 2 7 score predicted acute M. pneumoniae infection in elderly patients with CAP. The predictive model developed in this study has high diagnostic accuracy for the identification of elderly acute M. pneumoniae infection.
基金Chinese Academy of Sciences under contract No.KZCX2-YW-214the National Nat-ural Science Foundation of China under contract Nos 40476014 and 40346029.
文摘A high resolved two-dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate velocity field in the South China Sea(SCS). The study of model results shows that eddy diffusion does not change basic structure of circulation in the SCS and does not change the direction of invasive water, but changes the value of transport considerably especially in straits. The velocity field is not changed whether the wind stress is considered or not. This result shows the circulation is largely determined by a density field which well records most of the important contribution of the wind stress effect. Potential vorticity is calculated to testify the dynamics of the model results. The result shows that a good conservation of the nonlinear PV. This indicates most effects of the important nonlinear processes are well recorded in density and the nonlinear term is negligible so that the simplified model is reliable. The model results show the water exchanges between the SCS and open ocean or surrounding seas. Cold deep water invades through Luzon Strait and Warm shallow water is pushed out mainly through Karimata Straits. The model results also reveal the structure of the circulation in the SCS basin. In two circulations of upper and middle layers, a cyclonic one in the north and an anti-cyclonic one in the south, reflect the climatologic average of the circulation driven by monsoon. In the deep or bottom layer, these two circulations reflect the topography of the basin. Above the middle layer, invasive water enters westward in the north but the way of invasion of Kuroshio is not clear. Below the deep layer, a current goes down south near the east basin ,and invasive water enters in the basin from the west Pacific.
基金Supported by the Projects of Public Science and Technology Research Funds of Ocean Sector of China(No.201205009)the National Natural Science Foundation of China(No.41201569)
文摘Presently, research is lacking regarding the diagnosis and evaluation of habitat degradation in enclosed bay systems. We established a diagnostic model for enclosed bay habitat degradation(EBHD model) using a multi-approach integrated diagnostic method in consideration of driving force-pressurestate-infl uence-response. The model optimizes the indicator standardization with annual average change rate of habitat degradation as the basic element, to refl ect accurately the impact of the change and speed of degradation on the diagnostic results, to quantify reasonably the contribution of individual diagnostic indicator to habitat degradation, and to solve the issue regarding the infl uence of subjective factors on the evaluation results during indicator scoring. We then applied the EBHD model for the Sansha Bay in Fujian Province, China, evaluated comprehensively the situation of habitat degradation in the bay, and screened out the major controlling factors in the study area. Results show that the diagnostic results are consistent in overall with the real situation of the study area. Therefore, the EBHD model is advantageous in terms of objectivity and accuracy, making a breakthrough in diagnosis and evaluation for habitat degradation in enclosed bay systems.
文摘AIM： To build a clinical diagnostic model of primary open angle glaucoma （POAG） using the normal probability chart of frequency-domain optical coherence tomography （FD-OCT）. METHODS： This is a cross-sectional study. Total 133 eyes from 133 healthy subjects and 99 eyes from 99 early POAG patients were included in the study. The retinal nerve fibre layer （RNFL） thickness parameters of optic nerve head （ONH） and RNFL3.45 scan were measured in one randomly selected eye of each subject using RTVue-100 FD-OCT. Then, we used these parameters to establish the diagnostic models. Four different diagnostic models based on two different area partition strategies on ONH and RNFL3.45 parameters, including ONH traditional area partition model （ONH-T）, ONH new area partition model （ONH-N）, RNFL3.45 traditional area partition model （RNFL3.45-T） and RNFL3.45 new area partition model （RNFL3.45-N）, were built and tested by cross-validation. RESULTS： The new area partition models had higher area under the receiver operating characteristic （AROC; ONH-N： 0.990; RNFL3.45-N： 0.939） than corresponding traditional area partition models （ONH-T： 0.979; RNFL3.45-T： 0.881）. There was no statistical difference among AROC of ONH-T, ONH-N, and RNFL3.45-N. Nevertheless, ONH-N was the simplest model. CONCLUSION： The new area partition models had higher diagnostic accuracy than corresponding traditional area partition models, which can improve the diagnostic ability of early POAG. In particular, the simplest ONH-N diagnostic model may be convenient for clinical application.
文摘Mining rich semantic information hidden in heterogeneous information network is one of the important tasks of data mining. Generally, a nuclear medicine text consists of the description of disease (<i>i.e.</i>, lesions) and diagnostic results. However, how to construct a computer-aided diagnostic model with a large number of medical texts is a challenging task. To automatically diagnose diseases with SPECT imaging, in this work, we create a knowledge-based diagnostic model by exploring the association between a disease and its properties. Firstly, an overview of nuclear medicine and data mining is presented. Second, the method of preprocessing textual nuclear medicine diagnostic reports is proposed. Last, the created diagnostic modes based on random forest and SVM are proposed. Experimental evaluation conducted real-world data of diagnostic reports of SPECT imaging demonstrates that our diagnostic models are workable and effective to automatically identify diseases with textual diagnostic reports.
文摘Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin(FUO) hospitalized in Xiangya Hospital Central South University, from January, 2006 to April, 2011 were retrospectively analyzed. Patients enrolled were divided into two groups. The first group was used to develop a diagnostic model: independent variables were recorded and considered in a logistic regression analysis to identify infectious and non-infectious diseases(αin = 0.05, αout = 0.10). The second group was used to evaluate the diagnostic model and make ROC analysis.Results The diagnostic rate of 143 patients in the first group was 87.4%, the diagnosis included infectious disease(52.4%), connective tissue diseases(16.8%), neoplastic disease(16.1%) and miscellaneous(2.1%). The diagnostic rate of 168 patients in the second group was 88.4%, and the diagnosis was similar to the first group. Logistic regression analysis showed that decreased white blood cell count(WBC < 4.0×109/L), higher lactate dehydrogenase level(LDH > 320 U/L) and lymphadenectasis were independent risk factors associated with non-infectious diseases. The odds ratios were 14.74, 5.84 and 5.11(P ≤ 0.01), respectively. In ROC analysis, the sensitivity and specificity of the positive predictive values was 62.1% and 89.1%, respectively, while that of negative predicting values were 75% and 81.7%, respectively(AUC = 0.76, P = 0.00).Conclusions The combination of WBC < 4.0×109/L, LDH > 320 U/L and lymphadenectasis may be useful in discriminating infectious diseases from non-infectious diseases in patients hospitalized as FUO.
文摘ObjectiveeThisstudy used data-independent acquisition(DIA)proteomics to analyze plasma protein expression in sepsis-induced coagulopathy(SIC),identify key biomarkers,and develop a diagnostic model.Methods This prospective study included 46 adult sepsis patients from the intensive care unit.Patients were categorized into a general sepsis group(n=26)and an SIC group(n=20)based on established SIC criteria.Plasma samples underwent proteomic and bioinformatics analyses toidentifyydifferentiallyexpressed protein(DEP)using LASSO regression and Random Forest.A diagnostic model was constructed and assessedvia receiver operating characteristic(ROC)curve analysis.Results The baseline data revealed that SIC patients exhibited longer prothrombin times,lower platelet counts,and higher D-dimer,fibrin degradation products,blood lactate,SOFA scores,and APACHE II scores compared with general sepsis patients(P<0.05).DIA proteomics identified 2637 proteins,with 240 DEP meeting the criteria(fold change>1.5,P<0.05),including 81 upregulated and 159 downregulated DEP.Subcellular localization analysis revealed that DEPs were predominantly extracellular and nuclear.Gene ontology(GO)annotation showed that DEP were mainly involved in cellular physiology,biological regulation,and stress response processes in biological processes.Domain annotation revealed a predominance of immunoglobulin V regions in DEP,which are crucial for antigen recognition and binding.KEGG enrichment analysis showed significant enrichment of DEP in pathways related to natural killer cell-mediated cytotoxicity,glycosylphosphatidylinositol anchor biosynthesis,tumor necrosis factor signaling,and NF-kB signaling.LASSO regression identified angiogenin and C-type lectin domain family 10 member A as key DEP.The SIC diagnostic nomogram showed an area under the curve of 0.896,with 0.731 specificity and 0.900 sensitivity.Conclusion The nomogram incorporating angiogenin and C-type lectin domain family 10 member A provides an accurate tool for SIC diagnosis。
基金the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT,and Future Planning(NRF-2020R1C1C1007431,NRF-2022R1A2C1003118,RS-2024-00341766,RS-2025-00514590,NRF-2021R1A5A2021614)the Korean Fund for Regenerative Medicine(KFRM)grant funded by the Korean government(the Ministry of Science and ICT,the Ministry of Health&Welfare,21A0404L1)the KRIBB Research Initiative Program.
文摘Hepatocellular carcinoma(HCC)is a critical cancerworldwide due to its low survival rate[1].In the United States,the overall 5-year survival rate of patients with HCC is 22%,which decreases sharply with cancer progression[2].Early detection of HCC improves patient survival.Serum alpha-fetoprotein(AFP)is a widely used biomarker for the diagnosis of HCC,but it is often elevated in patients with cirrhosis,resulting in false-positive results[3].Diagnostic markers for early detection of HCC have been investigated previously[4],but none are widely applied in clinical settings.
基金mainly supported by the following projects:the National Natural Science Foundation of China(Grant No.51178157)the Six Talent Peaks project in Jiangsu Province(Grant No.JXQC-021)the Key Science and Technology Program of Henan Province(Grant No.182102310004).
文摘To enhance the safety operation management of the subway and ascertain the level of the subway department's emergency response capability,a cloud diagnostic model is proposed.This model,grounded in the 4R crisis management theory and the subway's unique characteristics,constructs a comprehensive diagnostic system.The DEMATEL-ANP model is employed to identify the interactive coupling relationship between various indicators in the diagnostic system,and the diagnostic level is judiciously divided.The cloud model is then utilized to holisticaly diagnose the subway's emergency handling capacity,thereby pinpointing the specific areas for improvement in subway emergency capacity and bolstering the safety and reliability of subway operation.To circumvent the emergence of imaginary numbers in the digital features of the cloud model,the MBCT-SR algorithm is implemented to enhance the cloud model,and the pSCM algorithm is applied to optimize the precision of cloud similarity discrimination.Using the Nanjing Metro Line 2 as a case study,the analysis reveals that the first-level indicators A and B of the object under diagnosis are underperforming.This necessitates a targeted enhancement of both organizational management of subway emergency personnel and capabilities for monitoring and early warning.Vltimately,the comprehensive diagnostic outcome was classified as a'good'level,which is consistent with the actual situation,verifying the effectiveness and practical application value of the diagnostic model.
基金grants from the National Key R&D Program of China(No.2016YFC1305500)the National Natural Science Foundation of China(Nos.61471399,61671479,and 81670663)+1 种基金the National Key Research and Development Program(No.2016YFC1305404)and the Joint Funds of National Natural Science Foundation of China and Henan Province(No.U1604284).
文摘Background:Immunoglobulin A nephropathy(IgAN)is the most common pathological type of glomerular disease.Kidney biopsy,the gold standard for IgAN diagnosis,has not been routinely applied in hospitals worldwide due to its invasion nature.Thus,we aim to establish a non-invasive diagnostic model and determine markers to evaluate disease severity by analyzing the serological parameters and pathological stages of patients with IgAN.Methods:A total of 272 biopsy-diagnosed IgAN inpatients and 518 non-IgA nephropathy inpatients from the Department of Nephrology of Chinese People's Liberation Army General Hospital were recruited for this study.Routine blood examination,blood coagulation testing,immunoglobulin-complement testing,and clinical biochemistry testing were conducted and pathological stages were analyzed according to Lee grading system.The serological parameters and pathological stages were analyzed.The receiver operating characteristic(ROC)analysis was performed to estimate the diagnostic value of the clinical factors.Logistic regression was used to establish the diagnostic model.Results:There were 15 significantly different serological parameters between the IgAN and non-IgAN groups(all P<0.05).The ROC analysis was performed to measure the diagnostic value for IgAN of these parameters and the results showed that the area under the ROC curve(AUC)of total protein(TP),total cholesterol(TC),fibrinogen(FIB),D-dimer(D2),immunoglobulin A(IgA),and immunoglobulin G(IgG)were more than 0.70.The AUC of the"TC+FIB+D2+IgA+age"combination was 0.86,with a sensitivity of 85.98%and a specificity of 73.85%.Pathological grades ofⅠ,Ⅱ,Ⅲ,Ⅳ,andⅤaccounted for 2.21%,17.65%,62.50%,11.76%,and 5.88%,respectively,with gradeⅢbeing the most prevalent.The levels of urea nitrogen(UN)(13.57土5.95 vs.6.06土3.63,5.92+2.97,5.41±1.73,and 8.41±3.72μmol/L,respectively)and creatinine(Cr)(292.19±162.21 vs.80.42±24.75,103.79±72.72,96.41±33.79,and 163.04±47.51μmol/L,respectively)were significantly higher in grade V than in the other grades,and the levels of TP(64.45±7.56,67.16±6.94,63.22±8.56,and 61.41±10.86 vs.37.47±5.6 mg/d,respectively),direct bilirubin(DB)(2.34±1.23,2.58±1.40,1.91±0.97,and 1.81±1.44 vs.0.74±0.57μmol/L,respectively),and IgA(310.35±103.78,318.48±107.54,292.58±81.85,and 323.29±181.67 vs.227.17±68.12g/L,respectively)were significantly increased in grades II-V compared with grade I(all P<0.05).Conclusions:The established diagnostic model that combined multiple factors(TC,FIB,D2,IgA,and age)might be used for IgAN non-invasive diagnosis.TP,DB,IgA,Cr,and UN have the potential to be used to evaluate IgAN disease severity.
基金supported by grants from the National Science and Technology Fundamental Resources Investigation Program of China(No.2019FY101102)the National Natural Science Foundation of China(No.82073626)+1 种基金the National Key Research and Development Program of China(No.2021YFC2500405)the Sanming Project of Shenzhen(No.SZSM201612061).
文摘Background:Clinical opportunistic screening is a cost-effective cancer screening modality.This study aimed to establish an easyto-use diagnostic model serving as a risk stratification tool for identification of individuals with malignant gastric lesions for opportunistic screening.Methods:We developed a questionnaire-based diagnostic model using a joint dataset including two clinical cohorts from northern and southern China.The cohorts consisted of 17,360 outpatients who had undergone upper gastrointestinal endoscopic examination in endoscopic clinics.The final model was derived based on unconditional logistic regression,and predictors were selected according to the Akaike information criterion.External validation was carried out with 32,614 participants from a community-based randomized controlled trial.Results:This questionnaire-based diagnostic model for malignant gastric lesions had eight predictors,including advanced age,male gender,family history of gastric cancer,low body mass index,unexplained weight loss,consumption of leftover food,consumption of preserved food,and epigastric pain.This model showed high discriminative power in the development set with an area under the receiver operating characteristic curve(AUC)of 0.791(95%confidence interval[CI]:0.750-0.831).External validation of the model in the general population generated an AUC of 0.696(95%CI:0.570-0.822).This model showed an ideal ability for enriching prevalent malignant gastric lesions when applied to various scenarios.Conclusion:This easy-to-use questionnaire-based model for diagnosis of prevalent malignant gastric lesions may serve as an effective prescreening tool in clinical opportunistic screening for gastric cancer.
基金the National Natural Science Foundation of China(Grant Number:81970631 to W.L.).
文摘Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN.Kidney biopsy is the gold standard for diagnosing DN;however,its invasive character is its primary limitation.The machine learning approach provides a non-invasive and specific criterion for diagnosing DN,although traditional machine learning algorithms need to be improved to enhance diagnostic performance.Methods:We applied high-throughput RNA sequencing to obtain the genes related to DN tubular tissues and normal tubular tissues of mice.Then machine learning algorithms,random forest,LASSO logistic regression,and principal component analysis were used to identify key genes(CES1G,CYP4A14,NDUFA4,ABCC4,ACE).Then,the genetic algorithm-optimized backpropagation neural network(GA-BPNN)was used to improve the DN diagnostic model.Results:The AUC value of the GA-BPNN model in the training dataset was 0.83,and the AUC value of the model in the validation dataset was 0.81,while the AUC values of the SVM model in the training dataset and external validation dataset were 0.756 and 0.650,respectively.Thus,this GA-BPNN gave better values than the traditional SVM model.This diagnosis model may aim for personalized diagnosis and treatment of patients with DN.Immunohistochemical staining further confirmed that the tissue and cell expression of NADH dehydrogenase(ubiquinone)1 alpha subcomplex,4-like 2(NDUFA4L2)in tubular tissue in DN mice were decreased.Conclusion:The GA-BPNN model has better accuracy than the traditional SVM model and may provide an effective tool for diagnosing DN.
文摘In this paper,a tbree-dimensional (3-D) baroclinic diagnostic model for short-range numerical forecast is proposed to calculate the monthly averaged flow field in the Bohai Sea. By using the model and monthly averaged tempeature and salinity date, monthly barotropic and baroclinic flow field are calculated,and 2-D and 3-D characteristics of flow are described and demonstrated. On the basis of the analysis of the modelling results and the observed temperature,salinity and wind data,the monthly and seasonal characteristics and generation mechanism of circulation in the Bohai Sea are also discussed. It is pointed out in this paper that in spring and autumn,the monthly averaged flow fields are not representative, for the wind direction varies in a wide range and the averaged wind field is much weaker than the instantaneous one. These results show the reliability of the model for describing the monthly characteristics in numerical forecast of ocean current.
基金Funding for this project was provided by the Project for the National Key Research and Development Program of China(2021YFA1301202)the National Natural Science Foundation of China(82273676)the Liaoning Province Scientific and Technological Project(2021JH2/10300039).
文摘Introduction:This study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy(DN)and construct a diagnostic model for DN in Chinese patients with type 2 diabetes mellitus(T2DM).Methods:A cross-sectional investigation was conducted in a hospital setting.Based on medical data,a total of 743 patients from a tertiary hospital were selected and categorized into two groups:the diabetic nephropathy group(DN group)and the non-diabetic nephropathy group(non-DN group).Plasma levels of metabolites,including amino acids and acylcarnitines,were determined using a laser counter measurement system(LC-MS).Subsequently,partial least-squares regression was used to assess the significance of these metabolites.Receiver operating characteristic(ROC)curves were generated for factors that ranked highest in terms of relevance.Model performance was assessed using the curve(AUC).Results:Of the 743 patients with T2DM admitted to the hospital,145 had DN.Compared with the non-DN group,the DN group exhibited elevated systolic blood pressure(P=0.001),high-density lipoprotein cholesterol(P=0.01),and low-density lipoprotein cholesterol(P=0.042).Additionally,the DN group had a higher prevalence of stroke patients(P<0.001)and diabetic retinopathy patients(P<0.001).Finally,a risk model that included citrulline,leucine,tyrosine,valine,propionylcarnitine(C3),and palmitoylcarnitine(C16)was developed.This model achieved an AUC of 0.709,with a 95%confidence interval(CI)ranging from 0.626 to 0.793.Conclusions:A diagnostic model consisting of six plasma metabolites to assess the risk of DN in Chinese patients with T2DM may provide clues for future research.
基金supported by the Tencent Charity Foundationthe Ningxia Hui Autonomous Region Key Research and Development Program(No.2021BEG 02025)+1 种基金the Flexible Introduction of Technological Innovation Teams of Ningxia Hui Autonomous Region(No.2021RXTDLX15)the Natural Science Foundation of China(No.82160644)。
文摘Objective:A risk-based sequential screening strategy,from questionnaire-based assessment to biomarker measurement and then to endoscopic examination,has the potential to enhance gastric cancer(GC)screening efficiency.We aimed to evaluate the ability of five common stomach-specific serum biomarkers to further enrich high-risk individuals for GC in the questionnaire-identified high-risk population.Methods:This study was conducted based on a risk-based screening program in Ningxia Hui Autonomous Region,China.We first performed questionnaire assessment involving 23,381 individuals(7,042 outpatients and 16,339 individuals from the community),and those assessed as“high-risk”were then invited to participate in serological assays and endoscopic examinations.The serological biomarker model was derived based on logistic regression,with predictors selected via the Akaike information criterion.Model performance was evaluated by the area under the receiver operating characteristic curve(AUC).Results:A total of 2,011 participants were ultimately included for analysis.The final serological biomarker model had three predictors,comprising pepsinogenⅠ(PGI),pepsinogenⅠ/Ⅱratio(PGR),and anti-Helicobacter pylori immunoglobulin G(anti-H.pylori IgG)antibodies.This model generated an AUC of 0.733(95%confidence interval:0.655-0.812)and demonstrated the best discriminative ability compared with previously developed serological biomarker models.As the risk cut-off value of our model rose,the detection rate increased and the number of endoscopies needed to detect one case decreased.Conclusions:PGI,PGR,and anti-H.pylori Ig G could be jointly used to further enrich high-risk individuals for GC among those selected by questionnaire assessment,providing insight for the development of a multi-stage riskbased sequential strategy for GC screening.
基金supported by National Natural Science Foundation of China(Grant No.61378037)the Fundamental Research Funds for the Central Universities(Nos.2013B33614,2017B15214)+1 种基金the Research Funds of Innovation and Entrepreneurship Education Reform for Chinese Universities(No.16CCJG01Z004)the Changzhou Science and Technology Program(No.CJ20160027)
文摘The capacitively coupled radio frequency（CCRF）plasma has been widely used in various fields.In some cases,it requires us to estimate the range of key plasma parameters simpler and quicker in order to understand the behavior in plasma.In this paper,a glass vacuum chamber and a pair of plate electrodes were designed and fabricated,using 13.56 MHz radio frequency（RF）discharge technology to ionize the working gas of Ar.This discharge was mathematically described with equivalent circuit model.The discharge voltage and current of the plasma were measured atdifferent pressures and different powers.Based on the capacitively coupled homogeneous discharge model,the equivalent circuit and the analytical formula were established.The plasma density and temperature were calculated by using the equivalent impedance principle and energy balance equation.The experimental results show that when RF discharge power is 50–300 W and pressure is 25–250 Pa,the average electron temperature is about 1.7–2.1 e V and the average electron density is about 0.5？×10^17–3.6？×10^17m^-3.Agreement was found when the results were compared to those given by optical emission spectroscopy and COMSOL simulation.
基金the Shanghai Municipal Key Clinical Specialty Program(No.shslczdzk06302)。
文摘Ovarian cancer has one of the highest mortality rates among gynecological malignancies.This disease has a low early detection rate,a high postoperative recurrence rate,and a 5-year survival rate of only 40%.Hence,there is an urgent need to improve the early diagnosis and prognosis of ovarian cancer.Prediction models can effectively estimate the risk of disease occurrence,as well as its prognosis.Recently,many studies have established multiple ovarian cancer prediction models based on different regions and populations.These models can improve the detection rate and optimize the prognosis management to a certain extent.Herein,the construction principle of the ovarian cancer risk prediction model and its validation are summarized;furthermore,comprehensive reviews and comparisons of the different types of these models are made.Therefore,our review may be of great significance for the whole course of ovarian cancer management.
基金supported by the Project Funding of the Fund Committee of Science Department (No.40346029)National Natural Science Foundation (40346029)the offing comprehensive evaluation of our country (908-02-01-03)
文摘A 2-dimensional global free surface diagnostic model, combined with dynamic calculation, is used to investigate the world ocean circulation; the model has a horizontal resolution of 1/4°×1/4°. The simulated results agree well with the results of other modesl and observations. The distribution of Stream Function suggests that the main circulation systems in the wodd ocean have been represented, including oceanic currents strengthened in the oceanic western. Be close to the observed results, the net mass transport of the Kuroshio axes is estimated about 54Sv; The distribution of the horizontal circulation in each layer shows that the main circulation systems in the world ocean are well simulated, for example, the Kuroshio and the Antarctic Circumpolar Current can go down to the bottom layer, but the Gulf Stream cannot, and its direction reverses at the depths of 1000 to 2 000 m.
基金Supported by the Medical and Health Research Project of Zhejiang Province,No.2021KY1048 and 2022KY1142Ningbo Health Young Technical Backbone Talents Training Program,No.2020SWSQNGG-02the Key Science and Technology Project of Ningbo City,No.2021Z133.
文摘BACKGROUND Colorectal cancer(CRC)is a major global health burden.The current diagnostic tests have shortcomings of being invasive and low accuracy.AIM To explore the combination of intestinal microbiome composition and multi-target stool DNA(MT-sDNA)test in the diagnosis of CRC.METHODS We assessed the performance of the MT-sDNA test based on a hospital clinical trial.The intestinal microbiota was tested using 16S rRNA gene sequencing.This case-control study enrolled 54 CRC patients and 51 healthy controls.We identified biomarkers of bacterial structure,analyzed the relationship between different tumor markers and the relative abundance of related flora components,and distinguished CRC patients from healthy subjects by the linear discriminant analysis effect size,redundancy analysis,and random forest analysis.RESULTS MT-sDNA was associated with Bacteroides.MT-sDNA and carcinoembryonic antigen(CEA)were positively correlated with the existence of Parabacteroides,and alpha-fetoprotein(AFP)was positively associated with Faecalibacterium and Megamonas.In the random forest model,the existence of Streptococcus,Escherichia,Chitinophaga,Parasutterella,Lachnospira,and Romboutsia can distinguish CRC from health controls.The diagnostic accuracy of MT-sDNA combined with the six genera and CEA in the diagnosis of CRC was 97.1%,with a sensitivity and specificity of 98.1%and 92.3%,respectively.CONCLUSION There is a positive correlation of MT-sDNA,CEA,and AFP with intestinal microbiome.Eight biomarkers including six genera of gut microbiota,MT-sDNA,and CEA showed a prominent sensitivity and specificity for CRC prediction,which could be used as a non-invasive method for improving the diagnostic accuracy for this malignancy.
