Wave-Absorbing Properties of Multi-Walled Carbon Nanotubes Reinforced Cement-Based Composites

Multi-walled carbon nanotube (MWCNT)/Portland cement (PC) composites have been prepared to evaluate their electromagnetic wave absorbing properties. The effects of MWCNTs content and sample thickness were discussed in the frequency ranges of 2–18 GHz. Results show that the absorbing properties of cement-based composites are affected by the content of MWCNT and the thickness of the samples. When MWCNTs contents are 0, 0.25, 0.50, 0.75, and 1.00%, absorbing property of sample of 5 mm is unstable due to the resonance absorption. Samples of 10 mm and 15 mm thickness show stable microwave absorbing properties, and a sample of 15 mm thickness has better absorbing property than that of 10 mm. Optimum contents of carbon nanotube (CNT) of 0.75, 0.50, and 0.5% by mass are found in 5, 10, and 15 mm thick samples, respectively. A sample with thickness of 5 mm and 0.50% mass content of CNT has the best absorbing property and the peak is –15.3 dB

The Effect of Nano-SiO2 Dispersed Methods on Mechanical Properties of Cement Mortar

Nano-SiO2 is added to the cement by using different dispersion methods, through the macroscopic mechanical properties to characterize its dispersion in the cement, it can be used to explore the best experimental process. The results show that the compressive strength of cement samples with different dispersion methods is different. When the physical dispersion method is used, the intensity is not improved, but the ultrasonic dispersion method is the smallest, and the dispersion of nano-SiO2 is -9.11%. When the surfactant is used as dispersant, the dispersion of nano-SiO2 by Naphthalene water reducer is the best, and the compressive strength is increased by 6.68%. By using polymeric dispersing agent, polyethylene glycol has a certain effect on the dispersion of nano-SiO2, but it has some damage to the cement (set-retarder, etc.). Based on the above experiments, we have obtained the best dispersion method, which uses ultrasonic dispersion, and also needs to add naphthalene water reducer

Dysregulations of metabolites and gut microbes and their associations in rats with noise induced hearing loss

BackgroundNoise exposure could lead to hearing loss and disorders of various organs. Recent studies have reported the close relations of environmental noise exposure to the metabolomics dysregulations and gut microbiota disturbance in the exposers. However, the associations between gut microbial homeostasis and the body metabolism during noise-induced hearing loss (NIHL) were unclear. To get a full understanding of their synergy in noise-associated diseases, it is essential to uncover their impacts and associations under exposure conditions.MethodsWith ten male rats with background noise exposure (≤ 40 dB) as controls (Ctr group), 20 age- and weight-matched male rats were exposed to 95 dB Sound pressure level (SPL) (LN group, n = 10) or 105 dB SPL noise (HN group, n = 10) for 30 days with 4 h/d. The auditory brainstem response (ABR) of the rats and their serum biochemical parameters were detected to investigate their hearing status and the potential effects of noise exposure on other organs. Metabolomics (UPLC/Q-TOF-MS) and microbiome (16S rDNA gene sequencing) analyses were performed on samples from the rats. Multivariate analyses and functional enrichments were applied to identify the dysregulated metabolites and gut microbes as well as their associated pathways. Pearson correlation analysis was performed to investigate the associations of the dysregulations of microbiota and the metabolites.ResultsNIHL rat models were constructed. Many biochemical parameters were altered by noise exposure. The gut microbiota constitution and serum metabolic profiles of the noise-exposed rats were also dysregulated. Through metabolomics analysis, 34 and 36 differential metabolites as well as their associated pathways were identified in LN and HN groups, respectively. Comparing with the control rats, six and 14 florae were shown to be significantly dysregulated in the LN group and HN group, respectively. Further association analysis showed significant correlations between differential metabolites and differential microbiota.ConclusionThere were cochlea injuries and abnormalities of biochemical parameters in the rats with NIHL. Noise exposure could also disrupt the metabolic profiles and the homeostatic balance of gut microbes of the host as well as their correlations. The dysregulated metabolites and microbiota might provide new clues for prevention of noise-related disorders

Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis

Background Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. Methods The mRNA data of 369 HCC patients and the clinical information were downloaded from the Cancer Genome Atlas project (TCGA). The 310 patients with certain HCC-related risk factors were included for analysis and divided into seven groups according to the risk factors. Survival analyses were applied for the HCC patients of different groups. The patients with hepatitis B virus or hepatitis C virus infection only were combined into the HCC-V group for further analysis. The differentially expressed genes (DEGs) between the HCCs with alcohol consumption only (HCC-A) and HCC-V tumors were identified through limma package in R with cutoff criteria│log2 fold change (logFC)|>1.0 and p 2.0 and adj.p < 0.05. The intersection of the two sets of DEGs was considered SKGs which were then investigated for their specificity through comparisons between HCC-A and other four HCC groups. The SKGs were analyzed for their correlations with HCC-A stage and grade and their prognostic power for HCC-A patients. The expressional differences of the SKGs in the HCCs in whole were also investigated through Gene Expression Profiling Interactive Analysis (GEPIA). The SKGs in HCC were validated through Oncomine database analysis. Results Pathological stage is an independent prognostic factor for HCC patients. HCC-A patients were diagnosed later than HCC patients with other risk factors. Ten SKGs were identified and nine of them were confirmed for their differences in paired samples of HCC-A patients. Three (SLC22A10, CD5L, and UROC1) and four (SLC22A10, UROC1, CSAG3, and CSMD1) confirmed genes were correlated with HCC-A stage and grade, respectively. SPP2 had a lower trend in HCC-A tumors and was negatively correlated with HCC-A stage and grade. The SKGs each was differentially expressed between HCC-A and at least one of other HCC groups. CD5L was identified to be favorable prognostic factor for overall survival while CSMD1 unfavorable prognostic factor for disease-free survival for HCC-A patients and HCC patients in whole. Through Oncomine database, the dysregulations of the SKGs in HCC and their clinical significance were confirmed. Conclusion The poor prognosis of HCC-A patients might be due to their later diagnosis. The SKGs, especially the four stage-correlated genes (CD5L, SLC22A10, UROC1, and SPP2) might play important roles in HCC development, especially alcohol-related HCC development and progression. CD5L might be useful for overall survival and CSMD1 for disease-free survival predication in HCC, especially alcohol-related HCC

Association of Short Tandem Repeat Polymorphism in the Promoter of Prostate Cancer Antigen 3 Gene with the Risk of Prostate Cancer

BACKGROUND: PCA3 (prostate cancer antigen 3) gene is one of the most prostate cancer-specific genes at present. Consequently, the prostate-specific expression and the sharp up-regulation of PCA3 mRNA in prostate cancer suggest a unique transcriptional regulation, which possibly can be attributed to promoter polymorphism. In our study, we evaluated whether there is polymorphism in PCA3 promoter region and also assess the association of the polymorphism with prostate cancer. METHODOLOGY/PRINCIPAL FINDINGS: We designed a specific primer set to screen the promoter of PCA3 gene by polymerase chain reaction (PCR)-based cloning and sequencing with the DNA extracted from peripheral blood samples of prostate cancer (PCa) cases (n = 186) and healthy control cases (n = 135). Genotype-specific risks were estimated as odds ratios (ORs) with associated 95% confidence intervals (CIs) by chi-square test. Possible deviation of the genotype frequencies from controls and PCa cases expected under Hardy-Weinberg equilibrium was assessed by the chi-square test. Short tandem repeat polymorphism of TAAA was found in the promoter region of PCA3 gene, five polymorphisms and eight genotypes were identified. The eight genotypes were divided into three groups: ≤10TAAA, 11TAAA, ≥12TAAA. The group 11TAAA and ≥12TAAA were associated with higher relative risk for prostate cancer than group ≤10TAAA (OR = 1.76, 95%CI = 1.07-2.89[for group 11TAAA]; OR = 5.28, 95%CI = 1.76-15.89[for group ≥12TAAA]). CONCLUSIONS/SIGNIFICANCE: The presence of the (TAAA)n short tandem repeat polymorphisms in the PCA3 promoter region may be a risk factor for prostate cancer in the Chinese population

Phosphorus adsorption and desorption characteristics and its response to soil properties of black soil under long-term different fertilization

editorial reviewedObjective: Fertilizer is generally added to agricultural soil to meet the needs of crop production, but long-term over fertilization changes soil phosphorus (P) pool and soil properties. This study evaluated the characteristics change of P adsorption and desorption and its response to soil properties under long-term fertilization, to do a favor to provide theoretical basis of rational fertilizer application and improve the P availability of black soil. Method: Four treatments, including no fertilizer (CK), urea and potash sulphate (NK), urea, super-calcium phosphate and potash sulphate (NPK), and NPK plus pig manure (NPKM), were investigated in a 21-year (1989-2010) long-term fertilization experiment at Gongzhuling (Jilin Province) of China. The crop of cropping system was maize. Soil samples were collected in 1990, 2000 and 2010 at 0-20 cm depth to analyze soil properties and to measure soil P adsorption and desorption characteristics. Langmuir equation was used to fit the P adsorption curve, and then the maximum adsorption capacity (Qmax), adsorption constant (K), buffering capacity of soil P (MBC), and P sorption saturation (DPS) were calculated according to Langmuir equation. Result: There was a good fitness between the P adsorption curve and Langmuir equation (R2=0.93-0.99, P<0.01). There existed difference for P adsorption and desorption characteristic under the four treatments. Over time, compared with initial year, for CK and NK treatments, the Qmax value increased by 1.83 and 1.61 times, MBC value increased by 0.80% and 49.40%, DPS value decreased by 92.04% and 87.50%, Readily Desorbable Phosphorus (RDP) value decreased by 20.00% and 82.83%, respectively; for NPK treatment, Qmax and DPS value increased by 81.87% and 79.56%, MBC and RDP value decreased by 79.37% and 48.57%, respectively, while under NPKM treatment, the Qmax and MBC value decreased by 33.35% and 78.52%, DPS and RDP values increased by 11.36 and 1.48 times, respectively. After 21 years experiments, compared with CK and NPK treatments, the Qmax and MBC value of NPKM treatment decreased by 64.66% and 49.52%, 81.87% and 79.56%, respectively; the DPS and RDP value of NPKM treatment increased by 110 and 3.81 times, 4.36 times and 78.57%, respectively. Compared with other treatments, the Total-P, Olsen-P, soil organic matter (SOM) and CaCO3 contents increased and SSA decreased significantly, but the pH, free Fe2O3 and Al2O3 value kept unchanged under NPKM treatment. RDA test showed that SOM and Total-P were the main factors that explained 49.5% and 18.7% of the total variation (P<0.05) which caused the difference of P adsorption desorption characteristic parameters among four treatments. Conclusion: Long-term combination of NPK fertilizers with manures could significantly increase SOM and P accumulation contents, decrease the soil adsorption capacity and increase desorption capacity, and improve P availability in soil, but it significantly increased the DPS value, easily thereby caused the risk of phosphorus loss. Therefore, various management practices and inorganic and organic P fertilizer input amounts should be considered to reduce P losses from this area

Sigma metrics for assessing the analytical quality of clinical chemistry assays: a comparison of two approaches

Introduction: Two approaches were compared for the calculation of coefficient of variation (CV) and bias, and their effect on sigma calculation, when different allowable total error (TEa) values were used to determine the optimal method for Six Sigma quality management in the clinical laboratory. Materials and methods: Sigma metrics for routine clinical chemistry tests using three systems (Beckman AU5800, Roche C8000, Siemens Dimension) were determined in June 2017 in the laboratory of Peking Union Medical College Hospital. Imprecision (CV%) and bias (bias%) were calculated for ten routine clinical chemistry tests using a proficiency testing (PT)- or an internal quality control (IQC)-based approach. Allowable total error from the Clinical Laboratory Improvement Amendments of 1988 and the Chinese Ministry of Health Clinical Laboratory Center Industry Standard (WS/ T403-2012) were used with the formula: Sigma = (TEa − bias) / CV to calculate the Sigma metrics (σCLIA, σWS/T) for each assay for comparative analysis. Results: For the PT-based approach, eight assays on the Beckman AU5800 system, seven assays on the Roche C8000 system and six assays on the Siemens Dimension system showed σCLIA > 3. For the IQC-based approach, ten, nine and seven assays, respectively, showed σCLIA > 3. Some differences in σ were therefore observed between the two calculation methods and the different TEa values. Conclusions: Both methods of calculating σ can be used for Six Sigma quality management. In practice, laboratories should evaluate Sigma multiple times when optimizing a quality control schedule

Authenticating the geographic origins of Atractylodes lancea rhizome chemotypes in China through metabolite marker identification

IntroductionAtractylodes lancea is widely distributed in East Asia, ranging from Amur to south-central China. The rhizome of A. lancea is commonly used in traditional Chinese medicine, however, the quality of products varies across different regions with different geochemical characteristics.MethodThis study aimed to identify the chemotypes of A. lancea from different areas and screen for chemical markers by quantifying volatile organic compounds (VOCs) using a targeted metabolomics approach based on GC–MS/MS.ResultsThe A. lancea distributed in Hubei, Anhui, Shaanxi, and a region west of Henan province was classified as the Hubei Chemotype (HBA). HBA is characterized by high content of β-eudesmol and hinesol with lower levels of atractylodin and atractylon. In contrast, the Maoshan Chemotype (MA) from Jiangsu, Shandong, Shanxi, Hebei, Inner Mongolia, and other northern regions, exhibited high levels of atractylodin and atractylon. A total of 15 categories of VOCs metabolites were detected and identified, revealing significant differences in the profiles of terpenoid, heterocyclic compound, ester, and ketone among different areas. Multivariate statistics indicated that 6 compounds and 455 metabolites could serve as candidate markers for differentiating A. lancea obtained from the southern, northern, and Maoshan areas.DiscussionThis comprehensive analysis provides a chemical fingerprint of selected A. lancea. Our results highlight the potential of metabolite profiling combined with chemometrics for authenticating the geographical origin of A. lancea