Circ_0025033 deficiency suppresses paclitaxel resistance and malignant development of paclitaxel-resistant ovarian cancer cells by modulating the miR-532-3p/FOXM1 network.

BACKGROUND: Ovarian cancer (OC) is the main cause of cancer-related death in women, and drug resistance is a leading cause of treatment failure. Recently, the involvement of circular RNAs (circRNAs) in cancer progression has become an area of increased investigation. The objective of this study is to uncover the function and regulatory mechanism of circ_0025033 in paclitaxel (PTX)-resistant OC cells. METHODS: The expression of circ_0025033, FOXM1 and miR-532-3p was investigated using quantitative real-time polymerase chain reaction (qRT-PCR), and the protein expression of FOXM1 was quantified by western blot. Cell biological functions, including cell viability, migration/invasion and apoptosis, were explored using 3-(4, 5-Dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assays, transwell assays and flow cytometry assays. The interaction between miR-532-3p and circ_0025033 or FOXM1 predicted by bioinformatics analysis was validated by pull-down assay and dual-luciferase reporter assay. Exosomes were isolated to determine the further function of circ_0025033. RESULT: Circ_0025033 and FOXM1 were highly expressed, while miR-532-3p was poorly expressed in OC tissues and cells, and the expression pattern was greater in PTX-resistant OC cells. Circ_0025033 knockdown lessened PTX resistance, suppressed migration/invasion and promoted apoptosis of PTX-resistant cells. With respect to mechanism, circ_0025033 upregulated the expression of FOXM1 by targeting miR-532-3p, and circ_0025033 knockdown blocked the malignant activities of PTX-resistant OC cells by enriching miR-532-3p and suppressing FOXM1. Exosomes derived from PTX-resistant cells with circ_0025033 knockdown also could repress the malignant actions of PTX-resistant OC cells. CONCLUSION: Circ_0025033 downregulation impaired PTX resistance and malignant activities of PTX-resistant OC cells by regulating the miR-532-3p/FOXM1 network.

Corrosion rate prediction and influencing factors evaluation of low-alloy steels in marine atmosphere using machine learning approach.

The empirical modeling methods are widely used in corrosion behavior analysis. But due to the limited regression ability of conventional algorithms, modeling objects are often limited to individual factors and specific environments. This study proposed a modeling method based on machine learning to simulate the marine atmospheric corrosion behavior of low-alloy steels. The correlations between material, environmental factors and corrosion rate were evaluated, and their influences on the corrosion behavior of steels were analyzed intuitively. By using the selected dominating factors as input variables, an optimized random forest model was established with a high prediction accuracy of corrosion rate (R2 values, 0.94 and 0.73 to the training set and testing set) to different low-alloy steel samples in several typical marine atmospheric environments. The results demonstrated that machine learning was efficient in corrosion behavior analysis, which usually involves a regression analysis of multiple factors.

Visual Analysis of Odor Interaction Based on Support Vector Regression Method.

The complex odor interaction between odorants makes it difficult to predict the odor intensity of their mixtures. The analysis method is currently one of the factors limiting our understanding of the odor interaction laws. We used a support vector regression algorithm to establish odor intensity prediction models for binary esters, aldehydes, and aromatic hydrocarbon mixtures, respectively. The prediction accuracy to both training samples and test samples demonstrated the high prediction capacity of the support vector regression model. Then the optimized model was used to generate extra odor data by predicting the odor intensity of more simulated samples with various mixing ratios and concentration levels. Based on these olfactory measured and model predicted data, the odor interaction was analyzed in the form of contour maps. This intuitive method showed more details about the odor interaction pattern in the binary mixture. We found that that the antagonism effect was commonly observed in these binary mixtures and the interaction degree was more intense when the components' mixing ratio was close. Meanwhile, the odor intensity level of the odor mixture barely influenced the interaction degree. The machine learning algorithms were considered promising tools in odor researches.

One-Step in Situ Synthesis of Reduced Graphene Oxide/Zn-Al Layered Double Hydroxide Film for Enhanced Corrosion Protection of Magnesium Alloys.

As an effective and environmentally friendly material for corrosion prevention, layered double hydroxide (LDH) films have usually been degraded due to their inherent microporous structure. In this study, graphene derivatives were employed to enhance the corrosion resistance of LDH films. After ultrasonic treatment of a reaction solution mixture containing graphene oxide (GO) powder, a reduced graphene oxide/zinc-aluminum LDH (RGO/Zn-Al LDH) film was in situ synthesized on a magnesium alloy substrate by a one-step facile hydrothermal crystallization process. The characterization results demonstrated that the LDH nanosheets grew on both the GO surface and the magnesium substrate, and thus the agglomeration of graphene was effectively prevented. Furthermore, the GO plates were simultaneously reduced into RGO, which has better corrosion resistance. The as-prepared samples were individually assessed by potentiodynamic polarization measurements, and the RGO/Zn-Al LDH film showed good corrosion resistance with a lower corrosion current density (0.546 µA/cm2) than that of the bare substrate (33.2 µA/cm2) and Zn-Al LDH film (4.33 µA/cm2). The penetration resistance of the Zn-Al LDH film to a corrosive environment was significantly improved through the organic combination with graphene oxide, and this method provides a simple and facile approach to effectively enhance the corrosion protection performance of LDH materials.

The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment.

The olfactory evaluation function (e.g., odor intensity rating) of e-nose is always one of the most challenging issues in researches about odor pollution monitoring. But odor is normally produced by a set of stimuli, and odor interactions among constituents significantly influenced their mixture's odor intensity. This study investigated the odor interaction principle in odor mixtures of aldehydes and esters, respectively. Then, a modified vector model (MVM) was proposed and it successfully demonstrated the similarity of the odor interaction pattern among odorants of the same type. Based on the regular interaction pattern, unlike a determined empirical model only fit for a specific odor mixture in conventional approaches, the MVM distinctly simplified the odor intensity prediction of odor mixtures. Furthermore, the MVM also provided a way of directly converting constituents' chemical concentrations to their mixture's odor intensity. By combining the MVM with usual data-processing algorithm of e-nose, a new e-nose system was established for an odor intensity rating. Compared with instrumental analysis and human assessor, it exhibited accuracy well in both quantitative analysis (Pearson correlation coefficient was 0.999 for individual aldehydes (n = 12), 0.996 for their binary mixtures (n = 36) and 0.990 for their ternary mixtures (n = 60)) and odor intensity assessment (Pearson correlation coefficient was 0.980 for individual aldehydes (n = 15), 0.973 for their binary mixtures (n = 24), and 0.888 for their ternary mixtures (n = 25)). Thus, the observed regular interaction pattern is considered an important foundation for accelerating extensive application of olfactory evaluation in odor pollution monitoring.

Use of a modified vector model for odor intensity prediction of odorant mixtures.

Odor intensity (OI) indicates the perceived intensity of an odor by the human nose, and it is usually rated by specialized assessors. In order to avoid restrictions on assessor participation in OI evaluations, the Vector Model which calculates the OI of a mixture as the vector sum of its unmixed components' odor intensities was modified. Based on a detected linear relation between the OI and the logarithm of odor activity value (OAV-a ratio between chemical concentration and odor threshold) of individual odorants, OI of the unmixed component was replaced with its corresponding logarithm of OAV. The interaction coefficient (cosα) which represented the degree of interaction between two constituents was also measured in a simplified way. Through a series of odor intensity matching tests for binary, ternary and quaternary odor mixtures, the modified Vector Model provided an effective way of relating the OI of an odor mixture with the lnOAV values of its constituents. Thus, OI of an odor mixture could be directly predicted by employing the modified Vector Model after usual quantitative analysis. Besides, it was considered that the modified Vector Model was applicable for odor mixtures which consisted of odorants with the same chemical functional groups and similar molecular structures.

Research on odor interaction between aldehyde compounds via a partial differential equation (PDE) model.

In order to explore the odor interaction of binary odor mixtures, a series of odor intensity evaluation tests were performed using both individual components and binary mixtures of aldehydes. Based on the linear relation between the logarithm of odor activity value and odor intensity of individual substances, the relationship between concentrations of individual constituents and their joint odor intensity was investigated by employing a partial differential equation (PDE) model. The obtained results showed that the binary odor interaction was mainly influenced by the mixing ratio of two constituents, but not the concentration level of an odor sample. Besides, an extended PDE model was also proposed on the basis of the above experiments. Through a series of odor intensity matching tests for several different binary odor mixtures, the extended PDE model was proved effective at odor intensity prediction. Furthermore, odorants of the same chemical group and similar odor type exhibited similar characteristics in the binary odor interaction. The overall results suggested that the PDE model is a more interpretable way of demonstrating the odor interactions of binary odor mixtures.

An odor interaction model of binary odorant mixtures by a partial differential equation method.

A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.

Characteristic analysis for odor gas emitted from food waste anaerobic fermentation in the pretreatment workshop.

Gas chromatography-mass spectrometry, olfactometry, and other related methods were applied for the qualitative and quantitative analysis of the characteristics of odorous gases in the pretreatment workshop. The composition of odorous gases emitted from municipal food waste was also investigated in this study. The results showed that the tested gases are mainly composed of aromatic gases, which account for 49% of the total volatile organic compounds (VOC) concentrations. The nitrogenous compounds comprise 15% of the total concentration and the other gases comprise the remaining 36%. The level of odor concentration ranged from 2523 odor units (OU) m(-3) to 3577 OU m(-3). The variation of the total chemical composition ranged from 19,725 microg m(-3) to 24,184 microg m(-3). Among the selected four sampling points, the discharge outlet was detected to have the highest concentration in terms of odor, total chemical, sulfur compounds, and aromatics. The correlation analysis showed that the odor concentrations were evidently related to the total chemical composition, sulfur compounds, and aromatics (P < 0.05, n = 5). The odor activity value analysis identified the top three compounds, hydrogen sulfide (91.8), ethyl sulfide (35.8), and trimethylamine (70.6), which contribute to air pollution complaint of waste materials.

Hydrophobicity and Improved Corrosion Resistance of Weathering Steel via a Facile Sol-Gel Process with a Natural Rust Film.

Weathering steel, which has a protective corrosion product film, is widely used in various construction and landscaping applications. However, it causes metal contamination in the receiving ecosystem via corrosion-induced metal dissolution and rust runoff. Traditional corrosion prevention methods, such as surface coating, also suffer from environmental pollution and high maintenance costs. In this study, we propose a novel method to make the rust film hydrophobic to prevent corrosion while retaining its original appearance. The crystalline rust is used as a natural skeleton, and nano-SiO2 particles are synthesized in situ on it by a facile sol-gel method. The microscopic analysis shows that the flower-like rust flakes provide a primary structure (micrometric scales) and the nano-SiO2 particles form a secondary structure (nanoscale bumps), which is the essential micronanostructure for forming a hydrophobic surface. The as-synthesized film shows strong corrosion resistance, with the corrosion current density being 4 orders of magnitude lower than that of the samples without hydrophobicity. The hydrophobic surface not only prevents corrosive substances from penetrating into the rust layer but also reduces the risk of contamination through its self-cleaning properties. Therefore, the weathering steel with a hydrophobic rust film can be more stable and environmentally friendly for multiscenario applications.

Carbon nanotube/Chitosan hydrogel for adsorption of acid red 73 in aqueous and soil environments.

Acid red 73 is an azo dye, and its residue can pollute the environment and seriously threaten human health and life. In this study, glutaraldehyde was used as the crosslinking agent, chitosan and polyvinyl alcohol were crosslinked under appropriate conditions to obtain a chitosan hydrogel film, and carbon nanotubes were dispersed in the chitosan hydrogel film. The FTIR, XRD, BET, SEM were applied to chatacterize the structure and the morphology of the absorbent and results showed that when the mass fraction of the carbon nanotubes was 1%, the structure was a three-dimensional network with microporous, and the water absorption reached to the maximum value of 266.07% and the elongation at break reached to a maximum of 98.87%. The ability to remove acid red 73 from aqueous and soil environments was evaluated by UV. In the aqueous samples, 70 mg of the adsorbent reached a saturated adsorption capacity of 101.07 mg/g and a removal rate of 92.23% at pH = 5. The thermodynamics conformed with the Langmuir adsorption isotherm and pseudo second-order adsorption kinetic models. In the soil samples, 100 mg of the adsorbent reached an adsorption capacity of 24.73 mg/g and removal rate of 49.45%. When the pH of the soil is between 4 and 7, the removal rate and adsorption capacity do not change much; hence, the pH should be maintained between 5.2 and 6.8, which is extremely suitable for the growth of general plants. Moreover, the experimental results demonstrated that the adsorbent maintained a good removal rate of acid red 73 over six adsorption cycles.

Effects of Different Natural Factors on Rheological Properties of SBS Modified Asphalt.

Typical climatic environments such as UV radiation, high temperature and strong wind in cold and arid regions have a significant effect on asphalt aging. The intent of this work is to reveal the evolution law of natural aging of SBS-modified asphalt under the complex adverse climate environment in cold and arid regions. Furthermore, the contribution rate of various environmental factors of natural aging of asphalt in cold and arid regions was analyzed. Based on rheological parameters, this paper characterized the influence of natural aging on the viscoelastic properties, rutting resistance at a high temperature, fatigue resistance and cracking resistance at a low temperature of SBS-modified asphalt. The evolution law of natural aging performance of SBS-modified asphalt was revealed. A quantitative evaluation index (CIi) of natural aging contribution rate of asphalt was put forward and the contribution rate of various environmental factors to asphalt natural aging was analyzed. The results showed that the effects of simulated aging and natural aging on asphalt properties were similar. After aging, the viscoelastic properties of asphalt were deteriorated, and the risk of fatigue cracking and low temperature cracking was increased. It also enhanced the deformation resistance of asphalt and increased the rutting resistance at high temperature. The aging contribution index CIi obtained based on rheological parameters such as complex modulus and rutting factor could directly reflect the influence of different natural factors on the performance of asphalt during aging. Among them, the effect of thermal oxygen was more obvious on the natural aging of SBS-modified asphalt.

Analysis of Environmental Factors Affecting the Atmospheric Corrosion Rate of Low-Alloy Steel Using Random Forest-Based Models.

As one of the factors (e.g., material properties, surface quality, etc.) influencing the corrosion processes, researchers have always been exploring the role of environmental factors to understand the mechanism of atmospheric corrosion. This study proposes a random forest algorithm-based modeling method that successfully maps both the steel's chemical composition and environmental factors to the corrosion rate of low-alloy steel under the corresponding environmental conditions. Using the random forest models based on the corrosion data of three different atmospheric environments, the environmental factors were proved to have different importance sequence in determining the environmental corrosivity of open and sheltered exposure test conditions. For each exposure test site, the importance of environmental features to the corrosion rate is also ranked and analyzed. Additionally, the feasibility of the random forest model to predict the corrosion rate of steel samples in the new environment is also demonstrated. The volume and representativeness of the corrosion data in the training data are considered to be the critical factors in determining its prediction performance. The above results prove that machine learning provides a useful tool for the analysis of atmospheric corrosion mechanisms and the evaluation of corrosion resistance.

Involvement of p53-dependent apoptosis signal in antitumor effect of Colchicine on human papilloma virus (HPV)-positive human cervical cancer cells.

Colchicine, a plant-derived alkaloid with relatively low toxicity on normal human epidermal keratinocytes (HEKn), has selective inhibitory effect on the growth of CaSki (HPV16-positive) and HeLa (HPV18-positive) human cervical cancer cell lines via the induction of apoptosis. Colchicine (2.5, 5.0 and 10.0 ng/ml) significantly reduced the expression of human papilloma virus (HPV) 16 E6/E7 mRNA and protein in CaSki and HeLa cells. Moreover, reduced expression of E6 and E7 induced by Colchicine resulted in the up-regulation of tumor suppressor proteins, p53 and Rb, as well as down-regulation of phospho Rb (pRb) protein. In addition, Bax, cytosolic cytochrome c and cleaved caspase-3 protein were increased while Bcl-2 protein was decreased significantly by 48 h of Colchicine treatment. These results implied that Colchicine could be explored as a potent candidate agent for the treatment and prevention of HPV-associated cervical cancer without deleterious effects.

Assessment of the health risks and odor concentration of volatile compounds from a municipal solid waste landfill in China.

Municipal solid waste (MSW) landfills are a source of odorous and toxic compounds. In this work, we present an integrated assessment of the odor concentration and human health risks of volatile compounds to evaluate the environmental quality at a MSW landfill. Air samples were collected seasonally from six areas of the landfill with different functions. The total concentrations of the compounds ranged from 204.0 to 7426.7 µg m-3, and the concentrations in temporarily and permanently capped areas were 50.3 and 83.4% lower than those in the tipping area, respectively. The odor concentration was greatest at the leachate collection tank (1732-6254 ouE m-3) and tipping area (1573-4113 ouE m-3) and was mainly caused by hydrogen sulfide (57.9 and 49.1%, respectively). Moreover, the odor concentration was positively correlated with the temperature (r = 0.500, p < 0.05, n = 24). Although the non-carcinogenic (HI) and carcinogenic (R) risks of most compounds were largely below the acceptable levels (HI = 1, R = 1.0E-6), HI values of hydrogen sulfide (2.3), trichloropropane (2.0), and naphthalene (1.2) as well as R values of naphthalene (1.3E-4) and trimethylbenzene (1.2E-4) in the waste areas exceeded acceptable levels. Moreover, the cumulative HI (2.5-5.7) and R (1.0E-04 to 3.4E-04) in the waste areas should receive special attention since they were above acceptable levels during all of the seasons. Aromatic and halogenated compounds dominated the cumulative R, accounting for 79 and 21% of the total, on average, while for the cumulative HI, sulfur compounds contributed the most (67%).

[Study on the relationship between odor intensity and components concentrations of odor mixture].

Odor pollution has become a serious environmental problem arising from volatile organic compounds (VOCs) and other pollutants. But the studies on odor intensity and other olfactory evaluations are seriously influenced by the diversity, distinct concentration fluctuation and complex interaction of pollutants. In order to explore the relationship between odor intensity and components concentrations of odor mixture, several typical VOCs in indoor environment were used to simulate odor mixtures. A panel of six sensory assessors was employed to rate the odor intensities of the mixture and its unmixed components. The outcome showed that the presence of an odorant barely influenced the odor intensity of the mixture when its nature logarithm of odor activity value (OAV) was lower than 20% of the mixture's total amount. The application of this method as a pretreatment method for the odor mixture could apparently simplify the studies on odor interaction and olfactory evaluation.