Prediction of Abdominal Visceral Obesity From Body Mass Index,Waist Circumference and Waist-hip Ratio in Chinese Adults:Receiver Operating Characteristic Curves Analysis

Objective To evaluate the sensitivity and specificity of body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) measurements in diagnosing abdominal visceral obesity. Methods BMI, WC, and WHR were assessed in 690 Chinese adults (305 men and 385 women) and compared with magnetic resonance imaging (MRI) measurements of abdominal visceral adipose tissue (VA). Receiver operating characteristic (ROC) curves were generated and used to determine the threshold point for each anthropometric parameter. Results 1) MRI showed that 61.7% of overweight/obese individuals (BMI≥25 kg/m2) and 14.2% of normal weight (BMI<25 kg/m2) individuals had abdominal visceral obesity (VA≥100 cm2). 2) VA was positively correlated with each anthropometric variable, of which WC showed the highest correlation (r=0.73-0.77, P<0.001). 3) The best cut-off points for assessing abdominal visceral obesity were as followed: BMI of 26 kg/m2, WC of 90 cm, and WHR of 0.93, with WC being the most sensitive and specific factor. 4) Among subjects with BMI≥28 kg/m2 or WC≥95 cm, 95% of men and 90% of women appeared to have abdominal visceral obesity. Conclusion Measurements of BMI, WC, and WHR can be used in the prediction of abdominal visceral obesity, of which WC was the one with better accuracy.

Effectiveness of magnetic resonance imaging and spiral computed tomography in the staging and treatment prognosis of colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a prevalent cancer type in clinical settings;its early signs can be difficult to detect,which often results in late-stage diagnoses in many patients.The early detection and diagnosis of CRC are crucial for improving treatment success and patient survival rates.Recently,imaging techniques have been hypothesized to be essential in managing CRC,with magnetic resonance imaging(MRI)and spiral computed tomography(SCT)playing a significant role in enhancing diagnostic and treatment approaches.AIM To explore the effectiveness of MRI and SCT in the preoperative staging of CRC and the prognosis of laparoscopic treatment.METHODS Ninety-five individuals admitted to Zhongshan Hospital Xiamen University underwent MRI and SCT and were diagnosed with CRC.The precision of MRI and SCT for the presurgical classification of CRC was assessed,and pathological staging was used as a reference.Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of blood volume,blood flow,time to peak,permeability surface,blood reflux constant,volume transfer constant,and extracellular extravascular space volume fraction on the prognosis of patients with CRC.RESULTS Pathological biopsies confirmed the following CRC stages:23,23,32,and 17 at T1,T2,T3,and T4,respectively.There were 39 cases at the N0 stage,22 at N1,34 at N2,44 at M0 stage,and 51 at M1.Using pathological findings as the benchmark,the combined use of MRI and SCT for preoperative TNM staging in patients with CRC demonstrated superior sensitivity,specificity,and accuracy compared with either modality alone,with a statistically significant difference in accuracy(P<0.05).Receiver operating characteristic curve analysis revealed the predictive values for laparoscopic treatment prognosis,as indicated by the areas under the curve for blood volume,blood flow,time to peak,and permeability surface,blood reflux constant,volume transfer constant,and extracellular extravascular space volume fraction were 0.750,0.683,0.772,0.761,0.709,0.719,and 0.910,respectively.The corresponding sensitivity and specificity values were also obtained(P<0.05).CONCLUSION MRI with SCT is effective in the clinical diagnosis of patients with CRC and is worthy of clinical promotion.

Comparative study of CEA and CA19-9 in esophageal,gastric and colon cancers individually and in combination(ROC curve analysis)

Objective： To determine the clinical serum levels of carcinoembryonic antigen （CEA） and carbohydrate antigen 19-9 （CA19-9）, individually and in combination, for the diagnosis of 50 healthy subjects and 150 cases of esophageal, gastric, and colon cancers. Methods： The sensitivities of the two markers were compared individually and in combination, with specificity set at 100%. Receiver operating characteristic （ROC） curves were plotted. Results： Serum CEA levels were significantly higher in cancer patients than in the control group. The sensitivity of CEA was determined： in esophageal cancer, sensitivity=28%, negative predictive value （NPV）=61.72%, and AUC=0.742 （SE=0.05）, with a significance level of P〈0.0001; in gastric cancer, sensitivity=30%, NPV=58.82%, and AUC=0.734 （SE=0.0S）, with a significance level of P〈0.0001; in colon cancer, sensitivity=74%, NPV=79.36%, and AUC=0.856 （SE=0.04）, with a significance level of P〈0.0001. The sensitivity of CA19-9 was also evaluated： in esophageal cancer, sensitivity=18%, NPV=54.94%, and AUC=0.573 （SE=0.05）, with a significance level of P=0.2054. In gastric cancer, sensitivity=42%, NPV=63.29%, and AUC=0.679 （SE=0.05）, with a significance level of P〈0.0011. In colon cancer, sensitivity=26%, NPV=57.47%, and AUC=0.S80 （SE=0.05）, with a significance level ofP=0.1670. The following were the sensitivities of CEA/CA19-9 combined： in esophageal cancer, sensitivity=42%, NPV=63.29%, SE=0.078 （95% CI： 0.0159-0.322）; gastric cancer, sensitivity=S8%, NPV=70.42%, SE=0.072 （9$% CI： -0.0866-0.198）; and colon cancer, sensitivity=72%, NPV=78.12%, SE=0.070 （9S% CI： 0.137-0.415）. Conclusion： CEA exhibited the highest sensitivity for colon cancer, and CA19-9 exhibited the highest sensitivity for gastric cancer. Combined analysis indicated an increase in diagnostic sensitivity in esophageal and gastric cancer compared with that in colon cancer.

Prediction of Flash Flood Susceptibility of Hilly Terrain Using Deep Neural Network:A Case Study of Vietnam

Flash floods are one of the most dangerous natural disasters,especially in hilly terrain,causing loss of life,property,and infrastructures and sudden disruption of traffic.These types of floods are mostly associated with landslides and erosion of roads within a short time.Most of Vietnamis hilly and mountainous;thus,the problem due to flash flood is severe and requires systematic studies to correctly identify flood susceptible areas for proper landuse planning and traffic management.In this study,three Machine Learning(ML)methods namely Deep Learning Neural Network(DL),Correlation-based FeatureWeighted Naive Bayes(CFWNB),and Adaboost(AB-CFWNB)were used for the development of flash flood susceptibility maps for hilly road section(115 km length)of National Highway(NH)-6 inHoa Binh province,Vietnam.In the proposedmodels,88 past flash flood events were used together with 14 flash floods affecting topographical and geo-environmental factors.The performance of themodels was evaluated using standard statisticalmeasures including Receiver Operating Characteristic(ROC)Curve,Area Under Curve(AUC)and Root Mean Square Error(RMSE).The results revealed that all the models performed well(AUC>0.80)in predicting flash flood susceptibility zones,but the performance of the DL model is the best(AUC:0.972,RMSE:0.352).Therefore,the DL model can be applied to develop an accurate flash flood susceptibility map of hilly terrain which can be used for proper planning and designing of the highways and other infrastructure facilities besides landuse management of the area.

Support vector machine for prediction of siRNA silencing efficacy

In order to assist the design of short interfering ribonucleic acids （siRNA）, 573 non-redundant siRNAs were collected from published literatures and the relationship between siRNAs sequences and RNA interference （RNAi） effect is analyzed by a support vector machine （SVM） based algorithm relied on a basebase correlation （BBC） feature. The results show that the proposed algorithm has the highest area under curve （AUC） value （0. 73） of the receive operating characteristic （ROC） curve and the greatest r value （0. 43） of the Pearson＇s correlation coefficient. This indicates that the proposed algorithm is better than the published algorithms on the collected datasets and that more attention should be paid to the base-base correlation information in future siRNA design.

Clinical value of serum CA19-9 levels in evaluating resectability of pancreatic carcinoma

AIM:To evaluate the clinical value of serum CA19-9 levels in predicting the respectability of pancreatic carcinoma according to receiver operating characteristic(ROC) curve analysis. METHODS:Serum CA19-9 levels were measured in 104 patients with pancreatic cancer which were possible to be resected according to the imaging. ROC curve was plotted for the CA19-9 levels. The point closest to the upper left-hand corner of the graph were chosen as the cut-off point. The sensitivity,specificity,positive and negative predictive values of CA19-9 at this cut-off point were calculated. RESULTS:Resectable pancreatic cancer was detected in 58(55.77%) patients and unresectable pancreatic cancer was detected in 46(44.23%) patients. The area under the ROC curve was 0.918 and 95% CI was 0.843-0.992. The CA19-9 level was 353.15 U/mL,and the sensitivity and specificity of CA19-9 at this cut-off point were 93.1% and 78.3%,respectively. The positive and negative predictive value was 84.38% and 90%,respectively. CONCLUSION:Preoperative serum CA19-9 level is a useful marker for further evaluating the resectability of pancreatic cancer. Obviously increased serum levels of CA19-9(> 353.15 U/mL) can be regarded as an ancillary parameter for unresectable pancreatic cancer.

Serum N-glycan markers for diagnosing liver fibrosis induced by hepatitis B virus

BACKGROUND Hepatitis B virus (HBV) infection is the primary cause of hepatitis with chronic HBV infection,which may develop into liver fibrosis,cirrhosis and hepatocellular carcinoma.Detection of early-stage fibrosis related to HBV infection is of great clinical significance to block the progression of liver lesion.Direct liver biopsy is regarded as the gold standard to detect and assess fibrosis;however,this method is invasive and prone to clinical sampling error.In order to address these issues,we attempted to find more convenient and effective serum markers for detecting HBV-induced early-stage liver fibrosis.AIM To investigate serum N-glycan profiling related to HBV-induced liver fibrosis and verify multiparameter diagnostic models related to serum N-glycan changes.METHODS N-glycan profiles from the sera of 432 HBV-infected patients with liver fibrosis were analyzed.Significant changed N-glycan levels (peaks)(P <0.05) in differentfibrosis stages were selected in the modeling group,and multiparameter diagnostic models were established based on changed N-glycan levels by logistic regression analysis.The receiver operating characteristic (ROC) curve analysis was performed to evaluate diagnostic efficacy of N-glycans models.These models were then compared with the aspartate aminotransferase to platelet ratio index (APRI),fibrosis index based on the four factors (FIB-4),glutamyltranspeptidase platelet albumin index (S index),GlycoCirrho-test,and GlycoFibro-test.Furthermore,we combined multiparameter diagnostic models with alanine aminotransferase (ALT) and platelet (PLT) tests and compared their diagnostic power.In addition,the diagnostic accuracy of N-glycan models was also verified in the validation group of patients.RESULTS Multiparameter diagnostic models constructed based on N-glycan peak 1,3,4and 8 could distinguish between different stages of liver fibrosis.The area under ROC curves (AUROCs) of Model A and Model B were 0.890 and 0.752,respectively differentiating fibrosis F0-F1 from F2-F4,and F0-F2 from F3-F4,and surpassing other serum panels.However,AUROC (0.747) in Model C used for the diagnosis of F4 from F0-F3 was lower than AUROC (0.795) in FIB-4.In combination with ALT and PLT,the multiparameter models showed better diagnostic power (AUROC=0.912,0.829,0.885,respectively) when compared with other models.In the validation group,the AUROCs of the three combined models (0.929,0.858,and 0.867,respectively) were still satisfactory.We also applied the combined models to distinguish adjacent fibrosis stages of 432patients (F0-F1/F2/F3/F4),and the AUROCs were 0.917,0.720 and 0.785.CONCLUSION Multiparameter models based on serum N-glycans are effective supplementary markers to distinguish between adjacent fibrosis stages of patients caused by HBV,especially in combination with ALT and PLT.

Predictive role of interleukin-6 and CAT score in mechanical ventilation in patients with chronic obstructive pulmonary disease at the acute exacerbation stage in the emergency department

BACKGROUND:The study aimed to evaluate the predictive role of interleukin-6(IL-6)and chronic obstructive pulmonary disease(COPD)assessment test(CAT)score in mechanical ventilation(MV)in COPD patients at the acute exacerbation stage in the emergency department(ED).METHODS:For a one-year period,among adult patients in the ED who met the criteria of acute exacerbation of COPD,158 who received MV within 48 hours after admission were compared to 294 who didn't require MV within the same period after admission.IL-6 level and CAT score were compared between the two groups.The predicted value of IL-6 and CAT score was assessed by logistic regression analysis and a receiver operating characteristic(ROC)curve.RESULTS:The IL-6 and CAT scores in the 158 MV patients were much higher than those without.IL-6 and CAT scores were independent predictors of MV within 48 hours using logistic regression analysis(IL-6:odds ratio[OR]1.053,95%confidence interval[CI]1.039–1.067,P<0.001;CAT score:OR 1.122,95%CI 1.086–1.159,P<0.001).The combination of IL-6 and CAT scores(area under ROC curve[AUC]0.826,95%CI 0.786–0.866,P<0.001)improved the accuracy of predicting MV within 48 hours when compared with IL-6(AUC 0.752,95%CI 0.703–0.800,P<0.001)and CAT scores alone(AUC 0.739,95%CI 0.692–0.786,P<0.001).The sensitivity and specificity were 69.6%,74.1%,75.32%and 63.6%,respectively.CONCLUSION:The combined of IL-6 and CAT scores is useful for evaluating the risk of COPD patients at acute exacerbation in ED,and can provide a predictive value for MV or not within 48 hours.

Prognostic relevance of β-catenin expression in T2-3N0M0 esophageal squamous cell carcinoma

AIM: To study the expression of β-catenin in esophageal squamous cell carcinoma (ESCC) at stage T2-3N0M0 and its relation with the prognosis of ESCC patients. METHODS: Expression of β-catenin in 227 ESCC speci-mens was detected by immunohistochemistry (IHC). A reproducible semi-quantitative method which takes both staining percentage and intensity into account was applied in IHC scoring, and receiver operating char-acteristic curve analysis was used to select the cut-off score for high or low IHC reactivity. Then, correlation of β-catenin expression with clinicopathological features and prognosis of ESCC patients was determined. RESULTS: No significant correlation was observed between β-catenin expression and clinicopathological parameters in terms of gender, age, tumor size, tumor grade, tumor location, depth of invasion and pathologi-cal stage. The Kaplan-Meier survival curve showed that the up-regulated expression of β-catenin indicated a poorer post-operative survival rate of ESCC patients at stage T2-3N0M0 (P = 0.004), especially of those with T3 lesions (P = 0.014) or with stage ⅡB diseases (P = 0.007). Multivariate analysis also confirmed that β-catenin was an independent prognostic factor for the overall survival rate of ESCC patients at stage T2-3N0M0 (relative risk = 1.642, 95% CI: 1.159-2.327, P = 0.005). CONCLUSION: Elevated β-catenin expression level may be an adverse indicator for the prognosis of ESCC patients at stage T2-3N0M0, especially for those with T3 lesions or stage ⅡB diseases.

Serum gastrin-17 concentration for prediction of upper gastrointestinal tract bleeding risk among peptic ulcer patients

BACKGROUND Serum gastrin-17(G-17),pepsinogen I(PGI),and pepsinogen II(PGII)concentrations regulate gastric acid secretion,and hypersecretion of gastric acid increases the risks of peptic ulcer and upper gastrointestinal bleeding.These associations suggest that serum G-17,PGI,and(or)PGII may predict gastrointestinal bleeding risk among peptic ulcer patients.AIM To evaluate the efficacies of serum G-17,PGI,PGII,and PGI/PGII ratio(PGR)for predicting upper gastrointestinal bleeding among peptic ulcer patients.METHODS A total of 199 patients diagnosed with peptic ulcer confirmed by gastroscopy and positivity for Helicobacter pylori by the 14C-urea breath test were recruited,including 107 patients with simple peptic ulcer and 92 cases complicated by upper gastrointestinal bleeding.Serum PGI,PGII,G-17,and PGR were measured by immune methods and compared between bleeding and non-bleeding groups by univariate analysis.The specificity and sensitivity of PGs and G-17 for evaluating upper gastrointestinal bleeding risk were then assessed by constructing receiver operating characteristic(ROC)curves.RESULTS Serum G-17 was significantly higher among peptic ulcer patients with upper gastrointestinal bleeding compared to simple peptic ulcer patients(25.34±14.29 vs 8.84±8.03 pmol/L,t=9.822,P<0.01),whereas serum PGI,PGII,and PGR did not differ significantly between bleeding and non-bleeding groups(all P>0.05).The risk of bleeding was significantly higher among peptic ulcer patients with elevated serum G-17(>15 pmol/L)compared to patients with normal or low serum G-17(73.2%vs 27.4%,χ2=40.72,P<0.01).The area under the ROC curve for serum G-17 was 0.866±0.024,and a cut-off of 9.86 pmol/L yielded 90.2%sensitivity and 68.2%specificity for distinguishing peptic ulcer with and without upper gastrointestinal bleeding.CONCLUSION Serum G-17 is significantly upregulated in peptic ulcer patients and higher levels are predictive of upper gastrointestinal bleeding.Conversely,serum PGI,PGII,and PGR have no predictive value.Further prospective studies are warranted to examine if high G-17 can be used to assess risk of bleeding prior to onset.

Comparison of diagnostic validity of two autism rating scales for suspected autism in a large Chinese sample

BACKGROUND Autism is the most common clinical developmental disorder in children.The childhood autism rating scale(CARS)and autistic autism behavior checklist(ABC)are the most commonly used assessment scales for diagnosing autism.However,the diagnostic validations and the corresponding cutoffs for CARS and ABC in individuals with suspected autism spectrum disorder(ASD)remain unclear.Furthermore,for suspected ASD in China,it remains unclear whether CARS is a better diagnostic tool than ABC.Also unclear is whether the current cutoff points for ABC and CARS are suitable for the accurate diagnosis of ASD.AIM To investigate the diagnostic validity of CARS and ABC based on a large Chinese sample.METHODS A total of 591 outpatient children from the ASD Unit at Beijing Children’s Hospital between June and November 2019 were identified.First,the Clancy autism behavior scale(CABS)was used to screen out suspected autism from these children.Then,each suspected ASD was evaluated by CARS and ABC.Receiver operating characteristic(ROC)curve analysis was used to compare diagnostic validations.We also calculated the area under the curve(AUC)for both CARS and ABC.RESULTS We found that the Cronbach alpha coefficients of CARS and ABC were 0.772 and 0.426,respectively.Therefore,the reliability of the CARS was higher than that of the ABC.In addition,we found that the correlation between CARS and CABS was 0.732.Next,we performed ROC curve analysis for CARS and ABC,which yielded AUC values of 0.846 and 0.768,respectively.The cutoff value,which is associated with the maximum Youden index,is usually applied as a decision threshold.We found that the cutoff values of CARS and ABC were 34 and 67,respectively.CONCLUSION This result indicated that CARS is superior to ABC in the Chinese population with suspected ASD.

Serum neuron-specific enolase:A promising biomarker of silicosis

BACKGROUND Silicosis is a type of chronic pulmonary fibrosis caused by long-term inhalation of silica dust particles.There has been no ideal biomarker for the diagnosis and differential diagnosis of silicosis until now.Studies have found that elevated neuron-specific enolase(NSE)concentration in the serum of silicosis patients is helpful for diagnosis and severity assessment of the disease.However,the number of cases in these studies was not enough to arouse attention.AIM To investigate the clinical significance of serum NSE in the diagnosis and staging of silicosis.METHODS From January 2017 to June 2019,326 cases of silicosis confirmed in Quanzhou First Hospital Affiliated to Fujian Medical University were included in the silicosis group.A total of 328 healthy individuals or medical patients without silicosis were included in the control group.Serum NSE concentrations of all subjects were determined by electrochemical luminescence.RESULTS There were no significant differences in sex,age,smoking index and complications between the silicosis and control groups.The mean serum NSE concentration was 26.57±20.95 ng/mL in the silicosis group and 12.42±2.68 ng/mL in the control group.The difference between the two groups was significant(U=15187,P=0.000).Among the 326 patients with silicosis,103 had stage I silicosis,and the mean serum NSE concentration was 15.55±6.23 ng/mL.The mean serum NSE concentration was 21.85±12.05 ng/mL in 70 patients with stage II silicosis.The mean serum NSE concentration was 36.14±25.72 ng/mL in 153 patients with stage III silicosis.Kruskal-Wallis H test suggested that the difference in serum NSE concentration in silicosis patients in the three groups was significant(H=130.196,P=0.000).Receiver operating characteristic curve analysis indicated that the area under the curve was 0.858(95%confidence interval:0.828-0.888;P=0.000).When the NSE concentration was 15.82 ng/mL,the Jorden index was the largest,the sensitivity was 72%,and the specificity was 90%.CONCLUSION Serum NSE concentration may be a promising biomarker for the diagnosis and assessment of severity of silicosis.

Tumor size as a prognostic factor in patients with advanced gastric cancer in the lower third of the stomach

AIM: To explore the impact of tumor size on outcomes in patients with advanced gastric cancer in the lower third of the stomach. METHODS: We retrospectively analyzed the clinical records of 430 patients with advanced gastric cancer in the lower third of the stomach who underwent distal subtotal gastrectomy and D2 lymphadenectomy in our hospital from January 1998 to June 2004. Receiver-operating characteristic (ROC) curve analysis was used to determine the appropriate cutoff value for tumor size, which was measured as maximum tumor diameter. Based on this cutoff value, patients were divided into two groups: those with large-sized tumors (LSTs) and those with small-sized tumors (SSTs). The correlations between other clinicopathologic factors and tumor size were investigated, and the 5-year overall survival (OS) rate was compared between the two groups. Potential prognostic factors were evaluated by univariate KaplanMeier survival analysis and multivariate Cox's propor-tional hazard model analysis. The 5-year OS rates in the two groups were compared according to pT stage and pN stage. RESULTS: The 5-year OS rate in the 430 patients with advanced gastric cancer in the lower third of the stomach was 53.7%. The mean ± SD tumor size was 4.9 ± 1.9 cm, and the median tumor size was 5.0 cm. ROC analysis indicated that the sensitivity and specificity results for the appropriate tumor size cutoff value of 4.8 cm were 80.0% and 68.2%, respectively (AUC=0.795, 95%CI: 0.751-0.839, P=0.000). Using this cutoff value, 222 patients (51.6%) had LSTs (tumor size ≥ 4.8 cm) and 208 (48.4%) had SSTs (tumor size<4.8 cm). Tumor size was significantly correlated with histological type (P=0.039), Borrmann type (P=0.000), depth of tumor invasion (P=0.000), lymph node metastasis (P=0.000), tumor-nodes metastasis stage (P=0.000), mean number of metastatic lymph nodes (P=0.000) and metastatic lymph node ratio (P=0.000). Patients with LSTs had a significantly lower 5-year OS rate than those with SSTs (37.1% vs 63.3%, P=0.000). Univariate analysis showed that depth of tumor invasion (c 2=69.581, P=0.000), lymph node metastasis (c 2=138.815, P=0.000), tumor size (c 2=78.184, P=0.000) and metastatic lymph node ratio (c 2=139.034, P=0.000) were significantly associated with 5-year OS rate. Multivariate analysis revealed that depth of tumor invasion (P=0.000), lymph node metastasis (P=0.019) and tumor size (P=0.000) were independent prognostic factors. Gastric cancers were divided into 12 subgroups: pT2N0; pT2N1; pT2N2; pT2N3; pT3N0; pT3N1; pT3N2; pT3N3; pT4aN0; pT4aN1; pT4aN2; and pT4aN3. In patients with pT2-3N3 stage tumors and patients with pT4a stage tumors, 5-year OS rates were significantly lower for LSTs than for SSTs (P<0.05 each), but there were no significant differences in the 5-year OS rates in LST and SST patients with pT23N0-2 stage tumors (P > 0.05). CONCLUSION: Using a tumor size cutoff value of 4.8cm, tumor size is a prognostic factor in patients with pN3 stage or pT4a stage advanced gastric cancer located in the lower third of the stomach.

TWIN SUPPORT TENSOR MACHINES FOR MCS DETECTION

Tensor representation is useful to reduce the overfitting problem in vector-based learning algorithm in pattern recognition.This is mainly because the structure information of objects in pattern analysis is a reasonable constraint to reduce the number of unknown parameters used to model a classifier.In this paper, we generalize the vector-based learning algorithm TWin Support Vector Machine(TWSVM) to the tensor-based method TWin Support Tensor Machines(TWSTM), which accepts general tensors as input.To examine the effectiveness of TWSTM, we implement the TWSTM method for Microcalcification Clusters(MCs) detection.In the tensor subspace domain, the MCs detection procedure is formulated as a supervised learning and classification problem, and TWSTM is used as a classifier to make decision for the presence of MCs or not.A large number of experiments were carried out to evaluate and compare the performance of the proposed MCs detection algorithm.By comparison with TWSVM, the tensor version reduces the overfitting problem.

Angiopoietin-2/angiopoietin-1 as non-invasive biomarker of cirrhosis in chronic hepatitis C

AIM To evaluate the efficacy of peripheral blood concentrations of angiopoietins(Ang) as cirrhosis biomarkers of chronic hepatitis C(CHC).METHODS Ang1 and Ang2 serum levels were measured by enzyme-linked immunosorbent assays(ELISA) in samples from 179 cirrhotic and non-cirrhotic CHC patients, classified according to the METAVIR system.Groups were compared by non-parametric MannWhitney U test. Subsequently, the association of peripheral concentrations of angiopoietins with the stage of fibrosis was analyzed using Spearman correlation test. Finally, the accuracy, sensitivity and specificity of circulating angiopoietins for cirrhosis diagnosis were determined by the study of the respective area under the curve of receiver operator characteristics(AUC-ROC).RESULTS Peripheral blood concentrations of Ang1 and Ang2 in CHC patients were significantly related to fibrosis. While Ang1 was decreased in cirrhotic subjects compared to non-cirrhotic(P < 0.0001), Ang2 was significantly increased as CHC progressed to the end stage of liver disease(P < 0.0001). Consequently, Ang2/Ang1 ratio was notably amplified and significantly correlated with fibrosis(P < 0.0001). Interestingly, the individual performance of each angiopoietin for the diagnosis of cirrhosis reached notable AUC-ROC values(above 0.7, both), but the Ang2/Ang1 ratio was much better(AUC-ROC = 0.810) and displayed outstanding values of sensitivity(71%), specificity(84%) and accuracy(82.1%) at the optimal cut-off(10.33). Furthermore, Ang2/Ang1 ratio improved the performance of many other previously described biomarkers or scores of liver cirrhosis in CHC.CONCLUSION Ang2/Ang1 ratio might constitute a useful tool for monitoring the progression of chronic liver disease towards cirrhosis and play an important role as therapeutic target.

Evaluation of high-risk factors and the diagnostic value of alpha-fetoprotein in the stratification of primary liver cancer

BACKGROUND Alpha-fetoprotein(AFP)is one of the diagnostic standards for primary liver cancer(PLC);however,AFP exhibits insufficient sensitivity and specificity for diagnosing PLC.AIM To evaluate the effects of high-risk factors and the diagnostic value of AFP in stratified PLC.METHODS In total,289 PLC cases from 2013 to 2019 were selected for analysis.First,the contributions of high-risk factors in stratifying PLC were compared according to the following criteria:Child–Pugh score,clinical stage of liver cirrhosis,tumor size,and Barcelona Clinic Liver Cancer(BCLC)stage.Then,the diagnostic value of AFP was evaluated in different stratifications of PLC by receiver operating characteristic curves.For PLC cases in which AFP played little role,the diagnostic values of carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA 19-9),gamma-glutamyl transferase(GGT),and AFP were analyzed.RESULTS The roles of high-risk factors differed in stratified PLC.The incidence of smoking and drinking history was higher in PLC with Child–Pugh scores of C(P<0.0167).The hepatitis B virus(HBV)infection rate in PLC with cirrhosis was more than in PLC without cirrhosis(P<0.0167).Small tumors were more prone to cirrhosis than large tumors(P<0.005).BCLC stage D PLC was more likely to be associated with HBV infection and cirrhosis(P<0.0083).AFP levels were higher in PLC with cirrhosis,diffuse tumors,and BCLC stage D disease.In diagnosing PLC defined as Child–Pugh A,B,and C,massive hepatoma,diffuse hepatoma,BCLC stage B,C,and D,and AFP showed significant diagnostic value[all area under the curve(AUC)>0.700].However,these measures were meaningless(AUC<0.600)in small hepatomas and BCLC A stage PLC,but could be replaced by the combined detection of CEA,CA 19-9,GGT,and AFP(AUC=0.810 and 0.846,respectively).CONCLUSION Stratification of PLC was essential for precise diagnoses and benefited from evaluating AFP levels.

Fraud Identification of Chinese Listed Companies——an Improvement Based on M-Score

To evaluate the applicability of the M-score model in the Chinese capital market,this research observed 190 financial fraud samples punished by the China Securities Regulatory Commission(CSRC)in the years from 2014 to 2018.The test results indicate that two types of errors are high,which means that the applicability of the M-score is unacceptable.Therefore,in this paper,a 9-index model is constructed by Wald's backward stepwise regression method,and the optimal threshold is set by the Beneish expected cost method(ECM).The accuracy of the modified M-score is significantly improved,especially the Type I error rate of is reduced from 70.37%to 19.75%.The receiver operating characteristic(ROC)curve test also proves the superior identification effect of the modified M-score applied in the Chinese market.Finally,variables such as current ratio,fixed asset index,and equity concentration in the modified model could represent the fraud characteristics of Chinese listed companies.

Atherogenic index of plasma combined with waist circumference and body mass index to predict metabolic-associated fatty liver disease

BACKGROUND Early identification of metabolic-associated fatty liver disease(MAFLD)is urgent.Atherogenic index of plasma(AIP)is a reference predictor of obesity-related diseases,but its predictive value for MAFLD remains unclear.No studies have reported whether its combination with waist circumference(WC)and body mass index(BMI)can improve the predictive performance for MAFLD.AIM To systematically explore the relationship between AIP and MAFLD and evaluate its predictive value for MAFLD and to pioneer a novel noninvasive predictive model combining AIP,WC,and BMI while validating its predictive performance for MAFLD.METHODS This cross-sectional study consecutively enrolled 864 participants.Multivariate logistic regression analysis and receiver operating characteristic curve were used to evaluate the relationship between AIP and MAFLD and its predictive power for MAFLD.The novel prediction model A-W-B combining AIP,WC,and BMI to predict MAFLD was established,and internal verification was completed by magnetic resonance imaging diagnosis.RESULTS Subjects with higher AIP exhibited a significantly increased risk of MAFLD,with an odds ratio of 12.420(6.008-25.675)for AIP after adjusting for various confounding factors.The area under receiver operating characteristic curve of the A-W-B model was 0.833(0.807-0.858),which was significantly higher than that of AIP,WC,and BMI(all P<0.05).Subgroup analysis illustrated that the A-W-B model had significantly higher area under receiver operating characteristic curves in female,young and nonobese subgroups(all P<0.05).The best cutoff values for the A-W-B model to predict MAFLD in males and females were 0.5932 and 0.4105,respectively.Additionally,in the validation set,the area under receiver operating characteristic curve of the A-W-B model to predict MAFLD was 0.862(0.791-0.916).The A-W-B level was strongly and positively associated with the liver proton density fat fraction(r=0.630,P<0.001)and significantly increased with the severity of MAFLD(P<0.05).CONCLUSION AIP was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD.The novel prediction model A-W-B combining AIP,WC,and BMI can significantly improve the predictive ability of MAFLD and provide better services for clinical prediction and screening of MAFLD.

ROC analysis of CT hemodynamic in the diagnosis of breast cancer

Objective:The aim of this study was evaluate the diagnostic value of computed tomography(CT) perfusion in breast cancer by the method of receiver operator characteristic curve(ROC) analysis.Methods:Eighty-one cases with breast masses found by health examination or mammography were scanned by multi-slice spiral CT(MSCT) perfusion and hemodynamic parameters of blood flow(BF), mean transit time(MTT) and blood volume(BV) were calculated by deconvolution arithmetic.According to the pathologic results, two groups, benign and malignant were classified and statistical analysis were performed between them.The ROC characteristics of BF, MTT, BV were compared for each and the diagnostic value of the hemodynamic parameters were confirmed.Results:In the malignant group, BF was(0.735 ± 0.440) mL/min/mL, MTT was(22.771 ± 7.647) s and BV was 0.234 ± 0.082.In the benign group, BF was(0.466 ± 0.527) mL/min/mL, MTT was(26.712 ± 12.934) s and BV was 0.179 ± 0.117.There was a significant difference for BF and BV between the benign and malignant groups.When the hemodynamic parameters were used to discriminate the breast lesions, the area under the ROC curve(AUCROC) of BF was 0.832 ± 0.086, the maximum, while AUCROC of BV was 0.695 ± 0.092.There was no significant statistical difference between BF and BV.AUCROC of MTT was 0.473 ± 0.102, which was minimal.Since the threshold of BF was 0.381 mL/min/mL, the sensitivity was 82.3%, the specificity was 73.2%, the positive likelihood ratio(LR) was 3.071 and the negative LR was 0.242.The threshold of BV was 0.190 with sensitivity 73.3%, specificity 56.5%, positive likelihood ratio 1.685 and negative LR 0.473.Conclusion:BF and BV among CT hemodynamic parameters have certain diagnostic value in breast cancer, but BF or BV can not yet be single index to confirm or deny the diagnosis.

A method of line spectrum extraction based on target radiated spectrum feature and its post-processing

To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.