Synergistic Effects of Multiple Environmental Factors on Degradation of Silicone Rubber Seals under Marine Atmosphere.

In this research, the degradation behavior and failure mechanism of silicone rubber seal rings under the synergistic effects of multiple factors in the marine atmosphere are fully investigated. Firstly, four aging factors of air, temperature, compressive stress, and chemical medium were determined by analyzing the service environment profile of silicone rubber seal under a marine atmosphere environment. Secondly, to better simulate the actual service environment of silicone rubber and shorten the test period, an artificially accelerated aging test was designed and carried out in the laboratory. In this paper, temperature is utilized as the accelerating stress. According to the results of the pre-test, the accelerating stress level is finally determined to be 110-150 ∘C. In addition, the compression set applied is consistent with the constant compression permanent deformation value of 28% of the silicone rubber in the actual service process. Finally, through the macroscopic physical properties and microstructure analysis of the samples before and after aging, the corresponding test results are given, and the failure mechanism is analyzed and discussed in detail. Through the above test results and discussion, it can be concluded that the aging process of multi-factor coupling on the lower silicone rubber seal ring is uneven, and its aging process is not a simple superposition of multiple environmental factors. More importantly, the above test data and results are of great significance for evaluating the service life of silicone rubber seals, which can be utilized in the future to improve the reliability and durability of related equipment in the marine environment.

A comprehensive investigation of statistical and machine learning approaches for predicting complex human diseases on genomic variants.

Quantifying an individual's risk for common diseases is an important goal of precision health. The polygenic risk score (PRS), which aggregates multiple risk alleles of candidate diseases, has emerged as a standard approach for identifying high-risk individuals. Although several studies have been performed to benchmark the PRS calculation tools and assess their potential to guide future clinical applications, some issues remain to be further investigated, such as lacking (i) various simulated data with different genetic effects; (ii) evaluation of machine learning models and (iii) evaluation on multiple ancestries studies. In this study, we systematically validated and compared 13 statistical methods, 5 machine learning models and 2 ensemble models using simulated data with additive and genetic interaction models, 22 common diseases with internal training sets, 4 common diseases with external summary statistics and 3 common diseases for trans-ancestry studies in UK Biobank. The statistical methods were better in simulated data from additive models and machine learning models have edges for data that include genetic interactions. Ensemble models are generally the best choice by integrating various statistical methods. LDpred2 outperformed the other standalone tools, whereas PRS-CS, lassosum and DBSLMM showed comparable performance. We also identified that disease heritability strongly affected the predictive performance of all methods. Both the number and effect sizes of risk SNPs are important; and sample size strongly influences the performance of all methods. For the trans-ancestry studies, we found that the performance of most methods became worse when training and testing sets were from different populations.

Reaction mechanism of chloramphenicol with hydroxyl radicals for advanced oxidation processes using DFT calculations.

The structure properties of chloramphenicol (CAP), including bond information and the Fukui function for the atoms in the main chain, were investigated computationally by density functional theory (DFT). The result shows that the chiral carbons in CAP offer the most active positions for chemical reactions, which is in good agreement with the experiment. The detailed degradation mechanism for CAP with hydroxyl radicals in advanced oxidation processes is further studied at the SMD/M06-2X/6-311 + G(d,p) level of theory. The main reaction methods, including the addition-elimination reaction, hydrogen abstract reaction, hydroxyl radical addition, and bond-breaking processes, are calculated. The results show that the nitro-elimination reaction is the most likely reaction in the first step of the degradation of CAP, and the latter two processes are more likely to be hydrogen abstract reactions. The details for the transition states, intermediate radicals, and free energy surfaces for all proposed reactions are given, which makes up for a lack of experimental knowledge.

Sulfate Resistance of Recycled Aggregate Concrete with GGBS and Fly Ash-Based Geopolymer.

There is a constant drive for the development of ultra-high-performance concrete using modern green engineering technologies. These concretes have to exhibit enhanced durability and incorporate energy-saving and environment-friendly functions. The object of this work was to develop a green concrete with an improved sulfate resistance. In this new type of concrete, recycled aggregates from construction and demolition (C&D) waste were used as coarse aggregates, and granulated blast furnace slag (GGBS) and fly ash-based geopolymer were used to totally replace the cement in concrete. This study focused on the sulfate resistance of this geopolymer recycled aggregate concrete (GRAC). A series of measurements including compression, X-ray diffraction (XRD), and scanning electron microscopy (SEM) tests were conducted to investigate the physical properties and hydration mechanisms of the GRAC after different exposure cycles in a sulfate environment. The results indicate that the GRAC with a higher content of GGBS had a lower mass loss and a higher residual compressive strength after the sulfate exposure. The proposed GRACs, showing an excellent sulfate resistance, can be used in construction projects in sulfate environments and hence can reduce the need for cement as well as the disposal of C&D wastes.

Protective role of sitagliptin against oxidative stress in a kainic acid-induced status epilepticus in rats models via Nrf2/HO-1 pathway.

AIM: Sitagliptin (Sita) is a dipeptidyl peptidase-4 inhibitor which has been approved as a curing medicine for Type 2 diabetes (T2D) and has also reported its neuroprotective and antioxidant activity. This article describes the therapeutic effects of Sita on induced rat model of SE by kainic acid (KA) and investigated the antioxidative pathway of sita. METHODS: Sprague-Dawley male rats were used randomly divided in four groups: vehicle control, KA and Sita + KA in a 5 and 10 mg/kg doses respectively in further groups. SE in rats was induced by the administration of KA in Phosphate buffered saline (PBS) intraperitoneally (IP) in a dose of 15 mg/kg. Seizure intensity, oxidative stress parameters, TUNEL assay, histopathology, and Nrf2/HO-1 expressions were evaluated. RESULTS: Increment in the latency in SE results in delaying the initiation of disease in the pretreated rats by Sita compared to induce group (KA) as well the percentage of occurrence of SE was decreased. The content of MDA elevates whereas the SOD production decreases on administering the KA at various time intervals. Sita shows protective action against the KA-induced SE by reducing the oxidative stress thus inhibiting the change in SOD and MDA was observed after KA administration prior SE onset. Based on the above results, the study explains possible molecular mechanism of Sita. Sita Pretreatment showed significant elevation in expression of Nrf2 and HO-1 proteins in hippocampus region of the brain. CONCLUSION: Above parameters defines the potential effect of Sita on brain injury occurred due to SE by anti-oxidative pathway.

Radiotherapy with temozolomide provides better survival in the newly diagnosed glioblastoma multiforme: A meta-analysis.

BACKGROUND: The optimal treatment for patients with newly diagnosed glioblastoma multiforme (GBM) remains controversial. The purpose of this meta-analysis was to systematically evaluate radiotherapy/temozolomide (TMZ) versus radiotherapy for treating newly diagnosed GBM. MATERIALS AND METHODS: Six electronic databases (PubMed, EMBASE, MEDLINE, Web of Science, Cochrane Library, and CNKI) were searched for relevant publications up to November 05, 2014. RevMan version 5.2 software was used for statistical analysis. RESULTS: A total of 9 studies were identified in this analyses, which included 986 patients. The summary risk ratio (RR) for overall survival and the progression-free survival (PFS) was the measure of interest. Results revealed that the addition of TMZ to radiotherapy resulted in a statistically significant survival benefit in poor prognosis patients with newly diagnosed glioblastoma (RR = 2.93 [95% confidence interval (CI) 2.29, 3.75], P < 0.00001). Moreover, radiotherapy plus TMZ was more beneficial than radiotherapy alone in improving PFS (RR = 3.52, [95% CI 2.53, 4.89], P < 0.00001). However, certain grade 3-4 hematological toxicities were significantly more common with TMZ. CONCLUSIONS: This meta-analysis suggests that radiotherapy/TMZ provides better survival than radiotherapy alone in treating GBM.