MICROSTRUCTURE AND MECHANICAL PROPERTIES OF Al-3 VOL% CNT NANOCOMPOSITES PROCESSED BY HIGH-PRESSURE TORSION

Al-3 vol% CNT nanocomposites were processed by high-pressure torsion (HPT) at room temperature under the pressure in the range of 2.5-10 GPa for up to 10 turns. Optical microscopy, scanning electron microscopy, and transmission electron microscopy (TEM) were used to investigate the microstructural evolutions upon HPT. Mechanical properties of the HPT-processed disks were studied using tensile tests and microhardness measurements. The results show gradual evolutions in the density, microstructure, and hardness with increasing the number of turns and applied presure. Nanostructured and elongated Al grains with an average grain thickness of similar to 40 nm perpendicular to the compression axis of HPT and an aspect ratio of similar to 3 are formed after 10 turns under 6 GPa. Evaluating the mechanical properties of the 10-turn processed Al/CNT nanocomposites indicates a tensile strength of 321 MPa and a hardness of 122 Hv. The tensile fracture surface of the Al/CNT nanocomposite mostly demonstrates a smooth fracture manner with fine dimples resulting in a low tensile ductility of similar to 1.5%.11Ysciescopu

Fast and fully-scalable synthesis of reduced graphene oxide

Exfoliation of graphite is a promising approach for large-scale production of graphene. Oxidation of graphite effectively facilitates the exfoliation process, yet necessitates several lengthy washing and reduction processes to convert the exfoliated graphite oxide (graphene oxide, GO) to reduced graphene oxide (RGO). Although filtration, centrifugation and dialysis have been frequently used in the washing stage, none of them is favorable for large-scale production. Here, we report the synthesis of RGO by sonication-assisted oxidation of graphite in a solution of potassium permanganate and concentrated sulfuric acid followed by reduction with ascorbic acid prior to any washing processes. GO loses its hydrophilicity during the reduction stage which facilitates the washing step and reduces the time required for production of RGO. Furthermore, simultaneous oxidation and exfoliation significantly enhance the yield of few-layer GO. We hope this one-pot and fully-scalable protocol paves the road toward out of lab applications of graphene.1111688Ysciescopu

Estimation and prediction for proportional hazard family based on a simple step-stress model with Type-II censored data

The accelerated life testing is the key methodology of assessing product reliability rapidly. This type of life testing is more efficient with low cost than the classical reliability testing. For this, estimating of the underlying model and predicting the future life failure times are issues deserve the attention and follow-up. In this paper, a simple step-stress testing experiment is considered when the lifetime data comes from a proportional hazard family under Type-II censoring. We discuss frequentist and Bayes estimates of the underlying model parameters. Prediction of unobserved or censored lifetimes is also tackled here, and frequentist and Bayesian predictors are developed. An algorithm is presented to generate ordered lifetime data from the proportional hazard family under the simple step-stress accelerated lifetime testing. Two numerical examples are also provided to illustrate the estimation and prediction methods presented in this paper. Finally, a Monte Carlo simulation experiment is performed to evaluate the performance of the various estimation and prediction methods developed in this paper

Natural Killer T Cells Infiltrate Neuroblastomas Expressing the Chemokine CCL2

CD1d-restricted Vα24-Jα18–invariant natural killer T cells (iNKTs) are potentially important in tumor immunity. However, little is known about their localization to tumors. We analyzed 98 untreated primary neuroblastomas from patients with metastatic disease (stage 4) for tumor-infiltrating iNKTs using TaqMan® reverse transcription polymerase chain reaction and immunofluorescent microscopy. 52 tumors (53%) contained iNKTs, and oligonucleotide microarray analysis of the iNKT+ and iNKT− tumors revealed that the former expressed higher levels of CCL2/MCP-1, CXCL12/SDF-1, CCL5/RANTES, and CCL21/SLC. Eight tested neuroblastoma cell lines secreted a range of CCL2 (0–21.6 ng/ml), little CXCL12 (≤0.1 ng/ml), and no detectable CCL5 or CCL21. CCR2, the receptor for CCL2, was more frequently expressed by iNKT compared with natural killer and T cells from blood (P < 0.001). Supernatants of neuroblastoma cell lines that produced CCL2 induced in vitro migration of iNKTs from blood of patients and normal adults; this was abrogated by an anti-CCL2 monoclonal antibody. CCL2 expression by tumors was found to inversely correlate with MYCN proto-oncogene amplification and expression (r = 0.5, P < 0.001), and MYCN-high/CCL2-low expression accurately predicted the absence of iNKTs (P < 0.001). In summary, iNKTs migrate toward neuroblastoma cells in a CCL2-dependent manner, preferentially infiltrating MYCN nonamplified tumors that express CCL2

Optimal confidence regions for the two-parameter exponential distribution based on records

In this article, we propose two families of optimal confidence regions for the location and scale parameters of the two-parameter exponential distribution based on upper records. Constrained optimization problems are used to find the smallest-area confidence regions for the exponential parameters with a specified confidence level. Optimal prediction interval for the future records is also proposed. Two numerical examples as well as a simulation study, are presented for illustrative purposes. It is shown that the reduction in area of the optimal joint confidence region with respect to the existing confidence regions is substantial

Angiotensin-converting enzyme inhibitor, Enalapril, inhibits tumor growth and potentiates the antitumor efficacy of 5-FU in colorectal cancer

OBJECTIVE: Colorectal cancer (CRC) is among the leading causes of cancer-related death, indicating the need for the identification of novel therapeutic approaches to increase the activity of current therapy or have better efficacy. Angiotensin-converting enzyme (ACE) is being reported to be associated with aggressive behaviors of CRC cells and poor prognosis. Here we explored the therapeutic potency of targeting ACE by Enalapril in CRC in vivo model. MATERIALS AND METHODS: A xenograft model of CRC was used to investigate the effects of Enalapril alone, or in combination with 5-FU, on tumor growth following histological staining (Hematoxylin and Eosin and Masson trichrome staining) and biochemical studies of Malondialdehyde (MDA), total thiols, superoxide dismutase (SOD) and catalase (CAT) activities. RESULTS: Enalapril reduced tumor growth and increased tumor necrosis; this effect was more pronounced in Enalapril plus 5-FU combination. Enalapril/5-FU was able to decrease tumor fibrosis and collagen content. ACE inhibitors also increased MDA level, as an oxidative stress marker, while reducing total thiol group levels, SOD and CAT enzyme activity. CONCLUSIONS: Our findings provide a novel insight on the therapeutic potential targeting of the renin–angiotensin system as a new therapeutic option in combination with current therapeutic agents 5-FU in the treatment of CRC

The genetic landscape of high-risk neuroblastoma

Neuroblastoma is a malignancy of the developing sympathetic nervous system that often presents with widespread metastatic disease, resulting in survival rates of less than 50%1. To determine the spectrum of somatic mutation in high-risk neuroblastoma, we studied 240 cases using a combination of whole exome, genome and transcriptome sequencing as part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative. Here we report a low median exonic mutation frequency of 0.60 per megabase (0.48 non-silent), and remarkably few recurrently mutated genes in these tumors. Genes with significant somatic mutation frequencies included ALK (9.2% of cases), PTPN11 (2.9%), ATRX (2.5%, an additional 7.1% had focal deletions), MYCN (1.7%, a recurrent p.Pro44Leu alteration), and NRAS (0.83%). Rare, potentially pathogenic germline variants were significantly enriched in ALK, CHEK2, PINK1, and BARD1. The relative paucity of recurrent somatic mutations in neuroblastoma challenges current therapeutic strategies reliant upon frequently altered oncogenic drivers

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around to per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is (95% CI: ,)and under the linear model, the mean mutation rate per locus per repeat unit is (95% CI: ,). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future