Effect of Nano-Magnesium Oxide on the Expansion Performance and Hydration Process of Cement-Based Materials.

Many scholars are concerned about the effect of nano-MgO as an expansion agent on the performance of cement-based materials at an early age, but over a long period less attention is paid to expansion stability and mechanical properties. This article examines the influence of nano-MgO on the long-term consistency, fluidity, expansion stability, hydration, and mechanical properties of 30% fly ash cement-based materials and improves research into nano-MgO as an expansion agent. Expansion performance, flexural and compressive strength, and stability after boiling and autoclave treatment were tested for specimens mixed with a 2, 4, 6, 8 and 10% cementitious material mass of nano-MgO. X-ray diffraction (XRD) and scanning electronic microscopy (SEM) were employed to study their hydration process and microstructure. The results showed that nano-MgO had an obvious effect on the consistency, fluidity and expansion performance of cement paste. After curing in water for 365 days and autoclaving thereafter, the hydration of nano-MgO was relatively complete. The volumetric expansion pressure of the magnesium hydroxide (Mg(OH)2) crystals and the crystallization pressure generated after their continuous precipitation were the main reasons for the expansion of the slurry. Nano-MgO improved the microstructure of cement paste and significantly enhanced its long-term flexural strength and compressive strength. When the content of nano-MgO was less than 10%, the cement with 30% fly ash had good long-term stability with the potential to compensate for the shrinkage of large-volume concrete.

The Value of a Seven-Autoantibody Panel Combined with the Mayo Model in the Differential Diagnosis of Pulmonary Nodules.

BACKGROUND: Identifying malignant pulmonary nodules and detecting early-stage lung cancer (LC) could reduce mortality. This study investigated the clinical value of a seven-autoantibody (7-AAB) panel in combination with the Mayo model for the early detection of LC and distinguishing benign from malignant pulmonary nodules (MPNs). METHODS: The concentrations of the elements of a 7-AAB panel were quantitated by enzyme-linked immunosorbent assay (ELISA) in 806 participants. The probability of MPNs was calculated using the Mayo predictive model. The performances of the 7-AAB panel and the Mayo model were analyzed by receiver operating characteristic (ROC) analyses, and the difference between groups was evaluated by chi-square tests (χ 2). RESULTS: The combined area under the ROC curve (AUC) for all 7 AABs was higher than that of a single one. The sensitivities of the 7-AAB panel were 67.5% in the stage I-II LC patients and 60.3% in the stage III-IV patients, with a specificity of 89.6% for the healthy controls and 83.1% for benign lung disease patients. The detection rate of the 7-AAB panel in the early-stage LC patients was higher than that of traditional tumor markers. The AUC of the 7-AAB panel in combination with the Mayo model was higher than that of the 7-AAB panel alone or the Mayo model alone in distinguishing MPN from benign nodules. For early-stage MPN, the sensitivity and specificity of the combination were 93.5% and 58.0%, respectively. For advanced-stage MPN, the sensitivity and specificity of the combination were 91.4% and 72.8%, respectively. The combination of the 7-AAB panel with the Mayo model significantly improved the detection rate of MPN, but the positive predictive value (PPV) and the specificity were not improved when compared with either the 7-AAB panel alone or the Mayo model alone. CONCLUSION: Our study confirmed the clinical value of the 7-AAB panel for the early detection of lung cancer and in combination with the Mayo model could be used to distinguish benign from malignant pulmonary nodules.

Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant.

BACKGROUND: While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model. RESULTS: CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO2) and ozone (O38h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: "logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO2 + 0.0008 *O38h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92." The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor. CONCLUSION: Low temperatures, wind speed, and SO2 and high daily temperature changes, O38h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning.

LncRNA TGFB2-AS1 regulates lung adenocarcinoma progression via act as a sponge for miR-340-5p to target EDNRB expression.

Long non-coding RNA TGFB2-antisense RNA1 (TGFB2-AS1) has been reported could regulate tumorigenesis. However, the roles of TGFB2-AS1 in lung adenocarcinoma (LUAD) remain largely unknown. In this work, we aimed to explore the expression levels of TGFB2-AS1 and mechanisms in regulating LUAD progression. Expression level of TGFB2-AS1 in LUAD tissues and normal tissues was analyzed at StarBase. Moreover, its expression in LUAD cells and normal cell was analyzed with quantitative real-time polymerase chain reaction method. Gain- and loss-of-function studies were conducted to analyze the biological roles of TGFB2-AS1 in LUAD. Results indicated TGFB2-AS1 was evidently downregulated in LUAD tissues and cells. Moreover, as analyzed by cell counting kit-8 assay, wound-healing and transwell invasion assays, results revealed TGFB2-AS1 overexpression could suppress proliferation, migration and invasion abilities of LUAD cells in vitro and tumor growth in vivo. In addition, LncBase V2.0 and TargetScan prediction tools showed TGFB2-AS1 and endothelin receptor type B (EDNRB) shares binding site in microRNA-340-5p (miR-340-5p). Furthermore, luciferase activity reporter assay and RT-qPCR assay validated these prediction results. Furthermore, we showed TGFB2-AS1 functions as sponge for miR-340-5p to regulate EDNRB expression. Collectively, our results indicated TGFB2-AS1/miR-340-5p/EDNRB axis plays crucial roles in regulating LUAD progression, indicating TGFB2-AS1 may be a novel therapeutic target for LUAD.

Lack of Efficacy of Combined Carbohydrate Antigen Markers for Lung Cancer Diagnosis.

BACKGROUND: Lung cancer (LC) is top-ranked in cancer incidence and is the leading cause of cancer death globally. Combining serum biomarkers can improve the accuracy of LC diagnosis. The identification of the best potential combination of traditional tumor markers is essential for LC diagnosis. Patients and Methods. Blood samples were collected from 132 LC cases and 118 benign lung disease (BLD) controls. The expression levels of ten serum tumor markers (CYFR21, CEA, NSE, SCC, CA15-3, CA 19-9, CA 125, CA50, CA242, and CA724) were assayed, and that the expression in the levels of tumor markers were evaluated, isolated, and combined in different patients. The performance of the biomarkers was analyzed by receiver operating characteristic (ROC) analyses, and the difference between combinations of biomarkers was compared by Chi-square (χ 2) tests. RESULTS: As single markers, CYFR21 and CEA showed good diagnostic efficacy for nonsmall cell lung cancer (NSCLC) patients, while NSE and CEA were the most sensitive in the diagnosis of small cell lung cancer (SCLC). The area under the curve (AUC) value was 0.854 for the panel of four biomarkers (CYFR21, CEA, NSE, and SCC), 0.875 for the panel of six biomarkers (CYFR21, CEA, NSE, SCC, CA125, and CA15-3), and 0.884 for the panel of ten markers (CYFR21, CEA, NSE, SCC, CA125, CA15-3, CA19-9, CA50, CA242, and CA724). With a higher sensitivity and negative predictive value (NPV), the diagnostic accuracy of the three panels was better than that of any single biomarker, but there were no statistically significant differences among them (all P values > 0.05). However, the panel of six carbohydrate antigen (CA) biomarkers (CA125, CA15-3, CA19-9, CA50, CA242, and CA724) showed a lower diagnostic value (AUC: 0.776, sensitivity: 59.8%, specificity: 73.0%, and NPV: 60.4%) than the three panels (P value < 0.05). The performance was similar even when analyzed individually by LC subtypes. CONCLUSION: The biomarkers isolated are elevated for different types of lung cancer, and the panel of CYFR21, CEA, NSE, and SCC seems to be a promising serum biomarker for the diagnosis of lung cancer, while the combination with carbohydrate antigen markers does not improve the diagnostic efficacy.

[Value of detecting p16 gene methylation in the diagnosis of malignant pleural effusion].

OBJECTIVE: To investigate aberrant methylation in the promoter of p16 gene in the sediment cells of pleural effusion and evaluate its clinical significance in the differentiating benign and malignant pleural effusion. METHODS: Using methylation-specific PCR (MSP), aberrant promoter methylation of p16 gene was detected in the sedimental cells of pleural effusion samples from 66 patients with pleural effusion. RESULTS: Of the 66 patients with pleural effusion, 36 had a definite diagnosis of malignant pleural effusion, and the rest were confirmed to have benign pleural effusion. The positivity rate of p16 gene promoter methylation was 69.4% (25/36) in malignant pleural effusion and 13.3% (4/30) in benign pleural effusion specimens, showing a significant difference between them (χ² = 20.915, P < 0.01). The diagnostic sensitivity, specificity and accuracy of aberrant promoter methylation of p16 gene in the 36 malignant cases were 69.4%, 86.7% and 77.3%, respectively. The positive expression of p16 gene promoter methylation in malignant pleural effusion was not correlated to the histological type or the pathological grade of the tumor (P > 0.05). CONCLUSION: Detection of aberrant methylation in p16 gene promoter in the sediment cells of pleural effusion specimens by MSP method allows differentiation between benign and malignant pleural effusion.

[Clinical value of monitoring serum cardiac biomarkers in pulmonary thromboembolism-induced myocardial injury].

OBJECTIVE: To investigate the clinical value of monitoring the serum cardiac biomarkers in patients with pulmonary thromboembolism (PTE) and secondary myocardial injury. METHODS: The serum cardiac biomarkers including aspartate aminotransferase (AST), lactate dehydrogenase (LDH), alpha-hydroxybutyrate dehydrogenase (HBDH), creatine kinase (CK), creatine kinase isoenzyme (CK-MB), cardiac tropnin I (cTnI) and myoglobin (Myo) were measured using immunochemiluminescent assays in 36 patients with PTE, who were diagnosed according to imaging findings in the recent 5 years. The measurements in concomitant non-PTE patients free of heart, liver, or kidney diseases were used as the baseline values of the biomarkers. Correlation analysis of the measurements was conducted in relation to the pulmonary embolism area, pulmonary hypertension and mortality rate. RESULTS: The PTE patients exhibited significantly elevated levels of the serum cardiac biomarkers including AST (56.14-/+15.73 U/L), LDH (303.06-/+94.99 U/L), HBDH (234.67-/+87.86 U/L), CK-MB (26.19-/+12.39 U/L), CK (129.25-/+76.14 U/L), Myo (70.63-/+45.75 ng/ml), and cTnI (0.45-/+0.41 ng/ml) in comparison with the baseline values (P < 0.01). Of these biomarkers, AST and CK-MB showed a significant correlation to the mortality, cTnI was correlated to pulmonary hypertension, and Myo was correlated to pulmonary hypertension and massive pulmonary embolism. CONCLUSION: Measurements of these serum cardiac biomarkers may serve as indicators for diagnosis of myocardial injury secondary to PTE. AST, CK-MB, cTnI, and Myo can help assess the prognosis of the patients.