PIVKA-II combined with alpha-fetoprotein for the diagnostic value of hepatic tumors in children: a multicenter, prospective observational study.

BACKGROUND: To investigate whether protein induced by vitamin K antagonist-II (PIVKA-II) combined with alpha-fetoprotein (AFP) can improve the diagnostic and differential diagnostic accuracy of childhood hepatic tumors. METHODS: A multi-center prospective observational study was performed at nine regional institutions around China. Children with hepatic mass (Group T) were divided into hepatoblastoma group (Group THB) and hemangioendothelioma group (Group THE), children with extrahepatic abdominal mass (Group C). Peripheral blood was collected from each patient prior to surgery or chemotherapy. The area under the curve (AUROC) was used to evaluate the diagnostic efficiency of PIVKA-II and the combined tumor markers with AFP. RESULTS: The mean levels of PIVKA-II and AFP were both significantly higher in Group T than Group C (p = 0.001, p < 0.001), in Group THB than Group THE (p = 0.018, p = 0.013) and in advanced HB than non-advanced HB (p = 0.001, p = 0.021). For the diagnosis of childhood hepatic tumors, AUROC of PIVKA-II (cut-off value 32.6 mAU/mL) and AFP (cut-off value 120 ng/mL) was 0.867 and 0.857. The differential diagnostic value of PIVKA-II and AFP in hepatoblastoma from hemangioendothelioma was further assessed, AUROC of PIVKA-II (cut-off value 47.1mAU/mL) and AFP (cut-off value 560 ng/mL) was 0.876 and 0.743. The combined markers showed higher AUROC (0.891, 0.895 respectively) than PIVKA-II or AFP alone. CONCLUSIONS: The serum level of PIVKA-II was significantly higher in children with hepatic tumors, especially those with malignant tumors. The combination of PIVKA-II with AFP further increased the diagnostic performance. TRIAL REGISTRATION: Clinical Trials, NCT03645655. Registered 20 August 2018, https://www. CLINICALTRIALS: gov/ct2/show/NCT03645655 .

High-performance shim coil design and engineering optimization for use in an extremely high field superconducting magnet.

The extremely high field has significant advantages in imaging quality and analyzing the fine structure of substances. However, its excellent performance requires the support of a higher-performance shim technique. In this paper, a novel structural design pattern of the shim coil for a 27 T extremely high field superconducting magnet is proposed. According to the contours of the stream function, we designed and optimized the shim coil pattern and engineering processing. The novel design was realized by using the contours as the centerline, and the wire spacing was controlled at 1 mm. The performance of the novel pattern was compared with those of alternative winding schemes. The results indicate that the novel design can improve coil performance, achieving higher fidelity and lower power dissipation.

Thallium removal from wastewater using sulfidized zero-valent manganese: Effects of sulfidation method and liquid nitrogen pretreatment.

Zero-valent manganese (ZVMn) possesses high reducibility in theory, while sulfide exhibits strong affinity towards a variety of heavy metals owing to the low solubility of metal sulfides. Yet the performance and mechanisms on using sulfidized zero-valent manganese (SZVMn) to remove thallium (Tl) from wastewater still remain unclear. In this study, the performance of Tl(I) removal using SZVMn synthesized by borohydrides reduction followed by sulfides modification, with and without liquid nitrogen treatment, was compared and the mechanism behind was investigated. The results show that at a S/Mn molar ratio of 1.0, liquid nitrogen modified SZVMn (LSZVMn) possessed more interior channels and pores than SZVMn, with 65.3% higher specific surface area and 73.7% higher porosity, leading to 6.4-8.1% improvement in adsorption of Tl(I) at pH 4-10. LSZVMn showed effectiveness and robustness in Tl(I) removal in the presence of co-existing ions up to 0.1 M. The adsorption of Tl(I) conformed to the pseudo-1st-order kinetic model, and followed the Langmuir isothermal model, with the maximum Tl adsorption capacity of 264.9 mg·g-1 at 288 K. The mechanism of Tl(I) removal with SZVMn was found to include sulfidation-induced precipitation, manganese reduction, surface complexation, and electrostatic attraction. The liquid nitrogen pretreatment embrittled and cracked the outer shell of S/Mn compounds, resulted in a highly hierarchical structure, enhancing the manganese reduction and improving the Tl(I) removal. Based on the above results, the SZVMn and its liquid nitrogen-modified derivatives are novel and effective environmental materials for Tl(I) removal from wastewater, and the application of SZVMn to the removal of other pollutants merits investigation in future study.

G2O-Pose: Real-Time Monocular 3D Human Pose Estimation Based on General Graph Optimization.

Monocular 3D human pose estimation is used to calculate a 3D human pose from monocular images or videos. It still faces some challenges due to the lack of depth information. Traditional methods have tried to disambiguate it by building a pose dictionary or using temporal information, but these methods are too slow for real-time application. In this paper, we propose a real-time method named G2O-pose, which has a high running speed without affecting the accuracy so much. In our work, we regard the 3D human pose as a graph, and solve the problem by general graph optimization (G2O) under multiple constraints. The constraints are implemented by algorithms including 3D bone proportion recovery, human orientation classification and reverse joint correction and suppression. When the depth of the human body does not change much, our method outperforms the previous non-deep learning methods in terms of running speed, with only a slight decrease in accuracy.

Oil/water separation using elastic bio-aerogels derived from bagasse: Role of fabrication steps.

Bio-aerogels hold great promise for selective oil separation from water due to their light weight and high sustainability. However, how the fabrication methods impact the elasticity and oil sorption performance of bio-aerogels still needs systematic comparison and in-depth investigation. In this study, the fabrication of hydrophobic bio-aerogels with good elasticity and reusability was optimized using a factorial design based on the dosages of bagasse-derived cellulose nanofiber, sodium alginate, and calcium carbonate. The role of each key fabrication step, including ice-templating, calcium crosslinking, solvent dehydration, freeze-drying, and silanization, played in the material properties was also elucidated. The optimized bio-aerogels had a low density (7.55 mg/cm3), high porosity (99.47%), large specific surface area (39 m2/g), and strong hydrophobicity (water contact angle of 135°). In addition, the bio-aerogels exhibited outstanding selective oil separation ability towards the oil-water mixture, with oil sorption capacity of 89-126 times its weight. The in-situ calcium crosslinking and solvent dehydration were vital to create porosity and preserve the microstructure of the bio-aerogels. The chemical vapor deposition rendered the bio-aerogels hydrophobic and oleophilic, greatly enhancing the separability of oil from the water-oil mixture.

Unsupervised 3D Reconstruction with Multi-Measure and High-Resolution Loss.

Multi-view 3D reconstruction technology based on deep learning is developing rapidly. Unsupervised learning has become a research hotspot because it does not need ground truth labels. The current unsupervised method mainly uses 3DCNN to regularize the cost volume to regression image depth. This approach results in high memory requirements and long computing time. In this paper, we propose an end-to-end unsupervised multi-view 3D reconstruction network framework based on PatchMatch, Unsup_patchmatchnet. It dramatically reduces memory requirements and computing time. We propose a feature point consistency loss function. We incorporate various self-supervised signals such as photometric consistency loss and semantic consistency loss into the loss function. At the same time, we propose a high-resolution loss method. This improves the reconstruction of high-resolution images. The experiment proves that the memory usage of the network is reduced by 80% and the running time is reduced by more than 50% compared with the network using 3DCNN method. The overall error of reconstructed 3D point cloud is only 0.501 mm. It is superior to most current unsupervised multi-view 3D reconstruction networks. Then, we test on different data sets and verify that the network has good generalization.

Diagnostic Value and Effectiveness of an Artificial Neural Network in Biliary Atresia.

Objectives: Biliary atresia (BA) is a devastating pediatric liver disease. Early diagnosis is important for timely intervention and better prognosis. Using clinical parameters for non-invasive and efficient BA diagnosis, we aimed to establish an artificial neural network (ANN). Methods: A total of 2,384 obstructive jaundice patients from 2012 to 2017 and their 137 clinical parameters were screened for eligibility. A standard binary classification feed-forward ANN was employed. The network was trained and validated for accuracy. Gamma-glutamyl transpeptidase (GGT) level was used as an independent predictor and a comparison to assess the network effectiveness. Results: We included 46 parameters and 1,452 patients for ANN modeling. Total bilirubin, direct bilirubin, and GGT were the most significant indicators. The network consisted of an input layer, 3 hidden layers with 12 neurons each, and an output layer. The network showed good predictive property with a high area under curve (AUC) (0.967, sensitivity 97.2% and specificity 91.0%). Five-fold cross validation showed the mean accuracy for training data of 93.2% and for validation data of 88.6%. Conclusions: The high accuracy and efficiency demonstrated by the ANN model is promising in the noninvasive diagnosis of BA and could be considered as in a low-cost and independent expert diagnosis system.

Development and validation of a novel diagnostic model for assessing lung cancer metastasis in a Chinese population based on multicenter real-world data.

BACKGROUND: Accurate disease staging plays an important role in lung cancer's clinical management. However, due to the limitation of the CT scan, it is still an unmet medical need in practice. In the present study, we attempted to develop diagnostic models based on biomarkers and clinical parameters for assessing lung cancer metastasis. METHODS: This study consisted of 799 patients with pulmonary lesions from three regional centers in China. It included 274 benign lesions patients, 326 primary lung cancer patients without metastasis, and 199 advanced lung cancer patients with lymph node or organ metastasis. The patients were divided into nodules group and masses group according to tumor size. RESULTS: Four nomogram models based on patient characteristics and tumor biomarkers were developed and evaluated for patients with nodules and masses, respectively. In patients with pulmonary nodules, the AUC to identify metastatic lung cancer from unidentified nodules (including benign nodules and lung cancer, model 1) reached 0.859 (0.827-0.887, 95% CI). Model 2 was used to predict metastasis in patients with lung cancer with AUC of 0.838 (0.795-0.876, 95% CI). In patients with pulmonary masses, the AUC to identify metastatic lung cancer from unidentified masses (model 3) reached 0.773 (0.717-0.823, 95% CI). Model 4 was used to predict metastasis in patients with lung cancer and AUC reached 0.731 (0.771-0.793, 95% CI). Decision curve analysis corroborated good clinical applicability of the nomograms in predicting metastasis. CONCLUSION: All new models demonstrated promising discrimination, allowing for estimating the risk of lymph node or organ metastasis of lung cancer. Such integration of blood biomarker testing with CT imaging results will be an efficient and effective approach to benefit the accurate staging and treatment of lung cancer.

Red blood cell distribution width and platelet counts are independent prognostic factors and improve the predictive ability of IPI score in diffuse large B-cell lymphoma patients.

BACKGROUND: Elevated red blood cell distribution width (RDW) and decreased platelet count (PLT) can be clinically relevant to the prognosis in cancer patients. However, their prognostic values in patients with diffuse large B-cell lymphoma (DLBCL) need to be further explored. METHODS: Healthy donors (n = 130) and patients with DLBCL (n = 349) were included and evaluated retrospectively in this study. The prognostic influence of clinical and pathological factors including RDW and PLT on overall survival (OS) and progression-free survival (PFS) were studied by Kaplan-Meier curves. To evaluate the independent prognostic relevance of RDW and PLT, univariate and multivariate Cox proportional hazards regression models were applied. The adjusted IPI model was established based on the results of multivariate analysis, and verified by Harrell's C statistical analysis. RESULTS: Kaplan-Meier curves indicated that an elevated RDW value and thrombocytopenia are poor factors for OS (P < 0.001, P = 0.006) and PFS (P = 0.003, P < 0.001) in DLBCL patients. Multivariate analysis confirmed that elevated RDW value (HR = 2.026, 95%CI = 1.263-3.250, P = 0.003) and decreased PLT count (HR =1.749, 95%CI = 1.010-3.028, P = 0.046) were both independent prognostic factors. The c-index of IPI and NCCN-IPI were increased when RDW level and PLT were supplemented in our cohort. CONCLUSIONS: Our study shows that elevated RDW level and decreased PLT are independent poor prognostic factors in newly diagnosed DLBCL patients. Adding RDW and PLT to the IPI score may improve its predictive ability, and the adjusted IPI may be more powerful in predicting the survival of DLBCL patients in the rituximab era.

A Novel Online Calculator Based on Serum Biomarkers to Detect Hepatocellular Carcinoma among Patients with Hepatitis B.

BACKGROUND: Early detection of hepatocellular carcinoma (HCC) among hepatitis B virus (HBV)-infected patients remains a challenge, especially in China. We sought to create an online calculator of serum biomarkers to detect HCC among patients with chronic hepatitis B (CHB). METHODS: Participants with HBV-HCC, CHB, HBV-related liver cirrhosis (HBV-LC), benign hepatic tumors, and healthy controls (HCs) were recruited at 11 Chinese hospitals. Potential serum HCC biomarkers, protein induced by vitamin K absence or antagonist-II (PIVKA-II), α-fetoprotein (AFP), lens culinaris agglutinin A-reactive fraction of AFP (AFP-L3) and α-l-fucosidase (AFU) were evaluated in the pilot cohort. The calculator was built in the training cohort via logistic regression model and validated in the validation cohort. RESULTS: In the pilot study, PIVKA-II and AFP showed better diagnostic sensitivity and specificity compared with AFP-L3 and AFU and were chosen for further study. A combination of PIVKA-II and AFP demonstrated better diagnostic accuracy in differentiating patients with HBV-HCC from patients with CHB or HBV-LC than AFP or PIVKA-II alone [area under the curve (AUC), 0.922 (95% CI, 0.908-0.935), sensitivity 88.3% and specificity 85.1% for the training cohort; 0.902 (95% CI, 0.875-0.929), 87.8%, and 81.0%, respectively, for the validation cohort]. The nomogram including AFP, PIVKA-II, age, and sex performed well in predicting HBV-HCC with good calibration and discrimination [AUC, 0.941 (95% CI, 0.929-0.952)] and was validated in the validation cohort [AUC, 0.931 (95% CI, 0.909-0.953)]. CONCLUSIONS: Our results demonstrated that a web-based calculator including age, sex, AFP, and PIVKA-II accurately predicted the presence of HCC in patients with CHB. CLINICALTRIALSGOV IDENTIFIER: NCT03047603.

A novel nomogram for the differential diagnosis between advanced and early appendicitis in pediatric patients.

Aim: To develop a nomogram for differential diagnosis between advanced and early pediatric appendicitis (PA). Patients & methods: We retrospectively studied 669 PA patients. Patient characteristics and 24 serum markers were subjected to univariate and multivariate analysis, based on which the nomogram was constructed. Results: Fibrin degradation product, CRP and Na+ differed significantly between the advanced and early PA. The value of area under the receiver operating characteristic curve (AUC) was 0.8602, which was greater than that of a single serum marker. Furthermore, the nomogram showed better discriminative ability than the biomarker alone. Notably, validation indicated high stability and reproducibility. Conclusion: The nomogram is superior to the serum marker alone, and may hold promise in clinical application.

Clinical performance of α-L-fucosidase for early detection of hepatocellular carcinoma.

Aim: To evaluate the diagnostic performance of serum AFU for early stage hepatocellular carcinoma (HCC). Methods: Concentration of AFU and AFP were measured in 512 patients. The performance was compared for AFU and AFP alone or in combination. Results: The area under the curve (AUC) for AFU was 0.68, with a sensitivity of 56.1% and specificity of 69.2% at the cut-off value of 24 U/l; whereas the AUC for AFP was 0.83, with a sensitivity of 58.2% and specificity of 85.2% at cut-off value of 20 ng/ml. The AUC of AFU alone or the combination with AFP were lower than that of AFP alone. Conclusion: AFU is a suboptimal biomarker for early detection of HCC.

Diagnostic value of alpha-fetoprotein combined with neutrophil-to-lymphocyte ratio for hepatocellular carcinoma.

BACKGROUND: To investigate the diagnostic performance of alpha-fetoprotein (AFP) and neutrophil-to-lymphocyte ratio (NLR) as well as their combinations with other markers. METHODS: Serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), AFP and levels as well as the numbers of neutrophils and lymphocytes of all enrolled patients were collected. The NLR was calculated by dividing the number of neutrophils by the number of lymphocytes. Receiver operating characteristic (ROC) curve analysis was conducted to determine the ability of each marker and combination of markers to distinguish HCC and liver disease patients. RESULTS: In total, 545 patients were included in this study. The area under the ROC curve (AUC) values for AFP, ALT, AST, and NLR were 0.775 (0.738-0.810), 0.504 (0.461-0.547), 0.660 (0.618-0.699), and 0.738 (0.699-0.774) with optimal cut-off values of 24.6 ng/mL, 111 IU/mL, 27 IU/mL, and 2.979, respectively. Of the four biomarkers, AFP and NLR showed comparable specificity (0.881 and 0.858) and sensitivity (0.561 and 0.539). The combination of AFP and NLR showed the highest AUC (0.769) with a significantly higher sensitivity (0.767) and a lower specificity (0.773) compared to AFP or NLR alone, and it had the highest sum of sensitivity and specificity (1.54) among all combinations. In patients with AFP < 20 ng/mL, the NLR showed the highest AUC and combination with other markers did not improve the diagnostic accuracy. CONCLUSIONS: Our data indicate that the combination of AFP and NLR offers better diagnostic performance than either marker alone for differentiating HCC from liver disease, which may benefit clinical screening.

Protein induced by vitamin K absence or antagonist-II versus alpha-fetoprotein in the diagnosis of hepatocellular carcinoma: A systematic review with meta-analysis.

BACKGROUND: As a promising biomarker of hepatocellular carcinoma (HCC), protein induced by vitamin K absence or antagonist-II (PIVKA-II) has been studied extensively. However, its diagnostic capability varies across HCC studies. This study aimed to compare the performance of PIVKA-II with alpha-fetoprotein (AFP) in the diagnosis of HCC. DATA SOURCES: A systematic literature search was conducted to identify the studies from MEDLINE, Embase and Cochrane Library Databases, which were published up to December 20, 2017 to compare the diagnostic capability of PIVKA-II and AFP for HCC. The data were pooled using random effects model. Pooled sensitivity and specificity were calculated. Summary receiver operating characteristic curve (ROC) was employed to evaluate the diagnostic accuracy of each marker. RESULTS: Thirty-one studies were included. The pooled sensitivity (95% CI) of PIVKA-II and AFP was 0.66 (0.65-0.68) and 0.66 (0.65-0.67), respectively in diagnosis of HCC; and the corresponding pooled specificity (95% CI) was 0.89 (0.88-0.90) and 0.84 (0.83-0.85), respectively. The area under the ROC curve (AUC) of PIVKA-II and AFP was 0.856 (0.817-0.895) and 0.770 (0.728-0.811), respectively. Subgroup analysis showed that PIVKA-II was superior to AFP in terms of the AUC for both small HCC (< 3 cm) [0.863 (0.825-0.901) vs 0.717 (0.658-0.776)] and large HCC (≥ 3 cm) [0.854 (0.811-0.897) vs 0.729 (0.682-0.776)]; for American [0.926 (0.897-0.955) vs 0.698 (0.594-0.662)], European [0.772 (0.743-0.801) vs 0.628 (0.594-0.662)], Asian [0.838 (0.812-0.864) vs 0.785 (0.764-0.806)] and African [0.812 (0.794-0.840) vs 0.721 (0.675-0.767)] HCC patients; and for HBV-related [0.909 (0.866-0.951) vs 0.714 (0.673-0.755)] and mixed-etiology [0.847 (0.821-0.873) vs 0.794 (0.772-0.816)] HCC. CONCLUSION: This meta-analysis indicates that PIVKA-II is better than AFP in terms of the accuracy for diagnosing HCC, regardless of tumor size, patient ethnic group, or HCC etiology.

Development and Validation of Novel Diagnostic Models for Biliary Atresia in a Large Cohort of Chinese Patients.

BACKGROUND & AIMS: The overlapping features of biliary atresia (BA) and the other forms of neonatal cholestasis (NC) with different causes (non-BA) has posed challenges for the diagnosis of BA. This study aimed at developing new and better diagnostic models for BA. METHODS: We retrospectively analyzed data from 1728 newborn infants with neonatal obstructive jaundice (NOJ). New prediction models, including decision tree (DT), random forest (RF), and multivariate logistic regression-based nomogram for BA were created and externally validated in an independent set of 508 infant patients. RESULTS: Fiver predictors, including gender, weight, direct bilirubin (DB), alkaline phosphatase (ALP), and gamma-glutamyl transpeptidase (GGT) were significantly different between the BA and non-BA groups (P < .05), from which DT, RF, and nomogram models were developed. The area under the receiver operating characteristic (ROC) curve (AUC) value for the nomogram was 0.898, which was greater than that of a single biomarker in the prediction of BA. Performance comparison of the three diagnostic models showed that the nomogram displayed better discriminative ability (sensitivity, 85.7%; specificity, 80.3%; PPV, 0.969) at the optimal cut-off value compared with DT and RF, which had relatively similar high sensitivity and PPV (0.941 and 0.947, respectively), but low specificity in the modeling group. In sub-analysis of the discriminative capacity between the nomogram and GGT (<300 or ≥ 300), we found that the nomogram was superior to the GGT alone in the preoperative diagnosis of BA. CONCLUSIONS: The nomogram has demonstrated better performance for the prediction of BA, holding promise for future clinical application.

Circulating tumor cells detection in neuroblastoma patients by EpCAM-independent enrichment and immunostaining-fluorescence in situ hybridization.

Detecting circulating tumor cells (CTCs) has proven valuable for evaluating the prognosis of cancer patients and for studying the mechanisms of treatment resistance. Owing to the lack of universal and specific tumor markers for neuroblastoma (NB), in this prospective study, we adopted an EpCAM-independent method to detect CTCs in the peripheral blood of NB patients. We used an EpCAM-independent assay to delete leukocytes and to enrich the CTCs. CTCs were identified by immunostaining of CD45, DAPI and DNA fluorescence in situ hybridization (FISH) of the centromere of chromosome 8 probe (CEP8). Cells that were DAPI+/CD45-/CEP8 ≥ 3 were considered CTCs. We collected peripheral blood from 28 NB patients as well as clinical and follow-up data. The number of CTCs among the different risk groups were significantly different (p = .0208, Kruskal-Wallis test). Patients with metastasis had more CTCs than those without metastasis (p < .0001, Mann-Whitney test). Patients with ≥3 CTCs per 4 ml of peripheral blood had an increased likelihood of having metastasis (sensitivity, 88.89%; specificity, 78.59%), and patients with ≥10 CTCs per 4 ml of peripheral blood had poorer overall survival. The EpCAM-independent assay along with immunostaining-FISH (i-FISH) described here can detect CTCs in patients with NB at a high sensitivity and may have clinical value for prognosis evaluation and diagnosing metastasis when imaging data are ambiguous.

Review on Vitamin K Deficiency and its Biomarkers: Focus on the Novel Application of PIVKA-II in Clinical Practice.

BACKGROUND: Vitamin K (VK) is a co-factor of the γ-glutamyl carboxylase that catalyzes the conversion of glutamate residues to γ-carboxyglutamate in VK-dependent proteins. The carboxylation reaction imparts the essential calcium-binding residues for the biological function of several proteins involved in the process of coagulation and bone metabolism. VK deficiency is frequently encountered in newborns and can lead to fatal hemorrhagic complications. This review describes and discusses the clinical application of VK deficiency testing. METHODS: References and data were researched in PubMed and reviewed. RESULTS: In adults, VK deficiency is associated with uncontrolled bleeding, liver dysfunction, osteoporosis, and coronary diseases. An improved understanding of the role of VK deficiency in health and illness can be achieved by setting a gold-standard in the inter-laboratory estimations of VK. However, conventional methods used to measure the VK deficiency based upon the coagulation time lack sensitivity and specificity. Recently, the alterations in proteins induced by VK absence or antagonism (PIVKA) have proven to be suitable biomarkers for detecting VK deficiency. The measurement of PIVKA-II exhibits an enhanced sensitivity and specificity in comparison to other methods conventionally used for the assessment of VK deficiency in newborns and adults. CONCLUSIONS: PIVKA-II could potentially be employed as an effective biomarker in the diagnosis of VK deficiency.

MicroRNA-29b/142-5p contribute to the pathogenesis of biliary atresia by regulating the IFN-γ gene.

Biliary atresia is one of the most common liver disease in infancy. The cause and pathogenesis remain largely unknown. This study aimed to investigate the potential regulatory effect of miR-29b/142-5p on IFN-γ gene methylation. miRNAs microarray was performed on four pairs of liver and blood specimens from biliary atresia and choledochal cysts. We found the overexpression of miR-142-5p and mRNA level of DNA methyltransferase (DNMT) 1, and miR-29b and DNMT3a/DNMT3b were significantly negatively correlated in biliary atresia livers. Meanwhile, the methylation of the LINE-1, ALU and SAT2 repetitive sequences and the IFN-γ promoter was lower, but the expression of IFN-γ was upregulated. After transfected with DNMTs siRNAs, downregulation of DNMTs exerted a significant hypomethylating effect on the repetitive sequences, which led to upregulation of IFN-γ in Jurkat cells. The direct interactions between miR-29b and DNMT3a/3b, and miR-142-5p and DNMT1 were identified using luciferase reporter assays. By transfecting mimics of miR-29b/142-5p into Jurkat cells, we found overexpression of miR-29b/142-5p markedly suppressed expression of DNMTs. Furthermore, the methylation of repetitive sequences and the IFN-γ promoter region were remarkably downregulated, and with elevated IFN-γ expression. After transfecting the miRNA inhibitors, the levels of DNMTs and the methylation of the IFN-γ gene promoter region was upregulated, while levels of IFN-γ were markedly suppressed. Our study suggested that miRNA-29b/142-5p overexpression and targeted inhibition of DNMTs expression resulted in decreased overall gene methylation and overexpression of the methylation-sensitive IFN-γ gene.

Reference Intervals of Cytokeratin-19 Fragment (CYFRA 21-1) in Healthy Adults in China.

BACKGROUND: The reference intervals for serum cytokeratin-19 fragment (CYFRA 21-1) have not been established in Chinese population. This study aimed to measure serum CYFRA 21-1 levels in healthy Chinese subjects. METHODS: This cross-sectional, four-center study in two Chinese provinces enrolled participants (aged 18 - 85 years) with normal liver/kidney function and normal results for routine blood tests/urinalysis. Serum CYFRA 211 level was measured by ARCHITECT immunoassay (Abbott Diagnostics). RESULTS: The study included 3,366 participants. The median (interquartile range) value for serum CYFRA 21-1 level was 1.38 (1.00 - 1.89) ng/mL and tended to increase with age. The upper limit of the 97.5th percentile was 3.55 ng/mL and tended to increase with age. Serum CYFRA 21-1 median level varied between the four centers from 1.22 (0.89, 1.71) to 1.55 (1.12, 2.18) ng/mL, while the 97.5th percentile varied from 3.24 to 4.09 ng/mL. CYFRA 21-1 level correlated weakly with age and creatinine level. CONCLUSIONS: These new data can help to establish the 'normal range' of serum CYFRA 21-1 in people in China.

Development and validation of a novel diagnostic nomogram model based on tumor markers for assessing cancer risk of pulmonary lesions: A multicenter study in Chinese population.

PURPOSE: This study aimed to build a valid diagnostic nomogram for assessing the cancer risk of the pulmonary lesions identified by chest CT. PATIENTS AND METHODS: A total of 691 patients with pulmonary lesions were recruited from three centers in China. The cut-off value for each tumor marker was confirmed by minimum P value method with 1000 bootstrap replications. The nomogram was based on the predictive factors identified by univariate and multivariate analysis. The predictive performance of the nomogram was measured by concordance index and calibrated with 1000 bootstrap samples to decrease the overfit bias. We also evaluated the net benefit of the nomogram via decision curve analysis. Finally, the nomogram was validated externally using a separate cohort of 305 patients enrolled from two additional institutions. RESULTS: The cut-off for CEA, SCC, CYFRA21-1, pro-GRP, and HE4 was 4.8 ng/mL, 1.66 ng/mL, 1.83 ng/mL, 56.55 pg/mL, and 63.24Lpmol/L, respectively. Multivariate logistic regression model (LRM) identified tumor size, CEA, SCC, CYFRA21-1, pro-GRP, and HE4 as independent risk factors for lung cancer. The nomogram based on LRM coefficients showed concordance index of 0.901 (95% CI: 0.842-0.960; P < 0.001) for lung cancer in the training set and 0.713 (95% CI: 0.599-0.827; P < 0.001) in the validation set. Decision curve analysis reported a net benefit of 87.6% at 80% threshold probability superior to the baseline model. CONCLUSION: Our diagnostic nomogram provides a useful tool for assessing the cancer risk of pulmonary lesions identified in CT screening test.