Facilitation of coke gasification by coking wastewater and its degradation properties in thermochemical reactions.

The thermochemical reaction between coking wastewater and gasification-coke is a new way to achieve efficient and clean use of coal and solve the problem of coking wastewater treatment in the Gansu Longdong region. To further investigate the thermochemical reaction characteristics of coking wastewater and gasification-coke, this paper explores the effect of coking wastewater on syngas production from coke gasification at 1000 °C, the degradation effect of organic pollutants in coking wastewater, the thermochemical reactivity of gasification-coke, and the reasons why wastewater promotes coke gasification and wastewater degradation. The results showed that the thermochemical reaction of coking wastewater with gasification-coke not only facilitates the improvement of syngas yield and low-level calorific value but also improves the thermochemical reactivity of gasification-coke. Notably, phenol in coking wastewater plays a major role in promoting the gasification of gasification-coke. During the thermochemical reaction, the organic pollutants in the wastewater were effectively degraded, the degradation rate of CODCr reached more than 85%, and the degradation of organic pollutants reached more than 75%. Phenol water and coking wastewater can not only improve the dispersion of the ash phase on the surface of gasification-coke, effectively inhibiting the sintering and agglomeration of the ash phase in gasification-coke, but also change the type and number of organic functional groups in gasification-coke. Therefore, coking wastewater can promote the gasification of coke. The thermochemical reaction between coke wastewater and gasification-coke can simultaneously promote coke gasification and the degradation of coke wastewater and achieve the resourceful use of coke wastewater.

Development of a predictive nomogram for postembolization syndrome after transcatheter arterial chemoembolization of hepatocellular carcinoma.

Post-embolization syndrome (PES) is a frequent complication after receiving transcatheter arterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC), but only a few studies have focused on the factors influencing PES in those patients. In this study, the impact factors of PES were explored and a nomogram was constructed to predict the occurrence of PES in HCC patients with TACE. This was a retrospective cohort study of HCC patients who underwent TACE obtained from the third affiliated Hospital of Kunming Medical University between January 1, 2020, and September 1, 2022. T­test and Chi­square test were used to search for factors influencing PES occurrence, and then the nomogram was further established based on multivariable logistic regression analysis. Validation of the predictive nomogram was also evaluated by calibration curve, concordance index (C-index), and receiver operating characteristic (ROC) curves. The enrolled patients (n = 258) were randomly assigned to the primary cohort (n = 180) and validation cohort (n = 78) in a 7:3 ratio. Among 180 patients in the primary cohort, 106 (58.89%) experienced PES. TACE types (P = 0.015), embolization degree (P = 0.008), and tumor number (P = 0.026) were identified as predictors by the logistic regression analysis and were used to develop the predictive nomogram. The internally validated and externally validated C-indexes were 0.713 and 0.703, respectively. The calibration curves presented good consistency between actual and predictive survival. Types of embolic agents, embolization degree, and tumor number were found to be the predictors of PES after TACE. The nomogram could reliably predict PES in HCC patients with TACE. This predictive model might be considered for clinical practice.

Treatment of coking wastewater using a needle coke electro-Fenton cathode: optimizing of COD, NH4+-N, and TOC removal and characterization of pollutants.

Coking wastewater is a typical organic refractory wastewater characterized by high chemical oxygen demand (COD), NH4+-N, and total organic carbon (TOC). Herein, coking wastewater was treated using a heterogeneous electro-Fenton (EF) system comprising a novel iron-loaded needle coke composite cathode (Fe-NCCC) and a dimensionally stable anode. The response surface methodology was used to optimize the reaction conditions. The predicted and actual COD removal rates were 92.13 and 89.96% under optimum conditions of an applied voltage of 4.92 V, an electrode spacing of 2.29 cm, and an initial pH of 3.01. The optimized removal rate of NH4+-N and TOC was 84.12 and 73.44%, respectively. The color of coking wastewater decreased from 250-fold to colorless, and the BOD5/COD increased from 0.126 to 0.34. Gas chromatography-mass spectrometry and Fourier transform infrared spectroscopy show that macromolecular heterocyclic organic compounds decomposed into straight-chain small molecules and even completely mineralized. The energy consumption of the EF process was 23.5 RMB Yuan per cubic meter of coking wastewater. The EF system comprising the Fe-NCCC can effectively remove pollutants from coking wastewater, has low electricity consumption, and can simultaneously reduce various pollution indicators with potential applications in the treatment of high-concentration and difficult-to-degrade organic wastewater.

The Current Status and Future Prospects for Conversion Therapy in the Treatment of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths worldwide. In China, most HCC patients are diagnosed with advanced disease and in these cases surgery is challenging. Conversion therapy can be used to change unresectable HCC into resectable disease and is a potential breakthrough treatment strategy. The resection rate for unresectable advanced HCC has recently improved as a growing number of patients have benefited from conversion therapy. While conversion therapy is at an early stage of development, progress in patient selection, optimum treatment methods, and the timing of surgery have the potential to deliver significant benefits. In this article, we review the current evidence and clinical experience of conversion therapy in HCC. General conversion modalities such as systemic treatments (systemic chemotherapy, targeted therapy, or immunotherapy), locoregional therapy (transarterial chemoembolization, hepatic arterial infusion chemotherapy, or selective internal radiation therapy), and combination therapy were summarized. We also discuss the current challenges of conversion therapy and provide identify areas for future research to improve the development of conversion therapy in advanced HCC.

Development of a predictive model to identify patients most likely to benefit from surgery in metastatic breast cancer.

Primary tumor resection for metastatic breast cancer (MBC) has demonstrated a survival advantage, however, not all patients with MBC benefit from surgery. The purpose of this study was to develop a predictive model to select patients with MBC who are most likely to benefit from surgery at the primary site. Data from patients with MBC were obtained from the Surveillance, Epidemiology and End Results (SEER) cohort and patients treated at the Yunnan Cancer Hospital. The patients from the SEER database were divided into surgery and non-surgery groups and a 1:1 propensity score matching (PSM) was used to balance baseline characteristics. We hypothesized that patients who underwent local resection of primary tumors had improved overall survival (OS) compared to those who did not undergo surgery. Based on the median OS time of the non-surgery group, patients from the surgery group were further categorized into beneficial and non-beneficial groups. Logistic regression analysis was performed to identify independent factors associated with improved survival in the surgery group and a nomogram was established using the most significant predictive factors. Finally, internal and external validation of the prognostic nomogram was also evaluated by concordance index (C-index) and using a calibration curve. A total of 7759 eligible patients with MBC were identified in the SEER cohort and 92 with MBC patients who underwent surgery at the Yunnan Cancer Hospital. Amongst the SEER cohort, 3199 (41.23%) patients received surgery of the primary tumor. After PSM, the OS between the surgery and non-surgery group was significantly different based on Kaplan-Meier survival analysis (46 vs. 31 months, P < 0.001), In the surgery group, 562 (55.20%) patients survived for longer than 31 months and were classified in the beneficial group. Significant differences were observed in patient characteristics between the beneficial and non-beneficial groups including age, grade, tumor size, liver metastasis, breast cancer subtype and marital status. These factors were used as independent predictors to create a nomogram. The internally and externally validated C-indices of the nomogram were 0.703 and 0.733, respectively, indicating strong consistency between the actual and predicted survival. A nomogram was developed and used to identify MBC patients who are most likely to benefit from primary tumor resection. This predictive model has the potential to improve clinical decision-making and should be considered routine clinical practice.

Robust Multi-View Clustering With Incomplete Information.

The success of existing multi-view clustering methods heavily relies on the assumption of view consistency and instance completeness, referred to as the complete information. However, these two assumptions would be inevitably violated in data collection and transmission, thus leading to the so-called Partially View-unaligned Problem (PVP) and Partially Sample-missing Problem (PSP). To overcome such incomplete information challenges, we propose a novel method, termed robuSt mUlti-view clusteRing with incomplEte information (SURE), which solves PVP and PSP under a unified framework. In brief, SURE is a novel contrastive learning paradigm which uses the available pairs as positives and randomly chooses some cross-view samples as negatives. To reduce the influence of the false negatives caused by random sampling, SURE is with a noise-robust contrastive loss that theoretically and empirically mitigates or even eliminates the influence of the false negatives. To the best of our knowledge, this could be the first successful attempt that simultaneously handles PVP and PSP using a unified solution. In addition, this could be one of the first studies on the noisy correspondence problem (i.e., the false negatives) which is a novel paradigm of noisy labels. Extensive experiments demonstrate the effectiveness and efficiency of SURE comparing with 10 state-of-the-art approaches on the multi-view clustering task.

Dual Contrastive Prediction for Incomplete Multi-View Representation Learning.

In this article, we propose a unified framework to solve the following two challenging problems in incomplete multi-view representation learning: i) how to learn a consistent representation unifying different views, and ii) how to recover the missing views. To address the challenges, we provide an information theoretical framework under which the consistency learning and data recovery are treated as a whole. With the theoretical framework, we propose a novel objective function which jointly solves the aforementioned two problems and achieves a provable sufficient and minimal representation. In detail, the consistency learning is performed by maximizing the mutual information of different views through contrastive learning, and the missing views are recovered by minimizing the conditional entropy through dual prediction. To the best of our knowledge, this is one of the first works to theoretically unify the cross-view consistency learning and data recovery for representation learning. Extensive experimental results show that the proposed method remarkably outperforms 20 competitive multi-view learning methods on six datasets in terms of clustering, classification, and human action recognition. The code could be accessed from https://pengxi.me.

Construction and validation of a prognostic nomogram in metastatic breast cancer patients of childbearing age: A study based on the SEER database and a Chinese cohort.

Introduction: Cancer in patients of childbearing age continues to become increasingly common. The purpose of this study was to explore the impact of metastatic breast cancer (MBC) on overall survival (OS) and cancer-specifific survival (CSS) in patients of childbearing age and to construct prognostic nomograms to predict OS and CSS. Methods: Data from MBC patients of childbearing age were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and the patients were randomly assigned into the training and validation cohorts. Univariate and multivariate Cox analyses were used to search for independent prognostic factors impacting OS and CSS, and these data were used to construct nomograms. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to determine the predictive accuracy and discriminative ability of the nomograms. Additional data were obtained from patients at the Yunnan Cancer Hospital to further verify the accuracy of the nomograms. Results: A total of 1,700 MBC patients of childbearing age were identifified from the SEER database, and an additional 92 eligible patients were enrolled at the Yunnan Cancer Hospital. Multivariate Cox analyses identifified 10 prognostic factors for OS and CSS that were used to construct the nomograms. The calibration curve for the probabilities of OS and CSS showed good agreement between nomogram prediction and clinical observations. The C-index of the nomogram for OS was 0.735 (95% CI = 0.725-0.744); the AUC at 3 years was 0.806 and 0.794 at 5 years.The nomogram predicted that the C-index of the CSS was 0.740 (95% CI = 0.730- 0.750); the AUC at 3 years was 0.811 and 0.789 at 5 years. The same results were observed in the validation cohort. Kaplan- Meier curves comparing the low-,medium-, and high-risk groups showed strong prediction results for the prognostic nomogram. Conclusion: We identifified several independent prognostic factors and constructed nomograms to predict the OS and CSS for MBC patients of childbearing age.These prognostic models should be considered in clinical practice to individualize treatments for this group of patients.

Gut microbiota may be involved in Alzheimer's disease pathology by dysregulating pyrimidine metabolism in APP/PS1 mice.

Introduction: Alzheimer's disease (AD) is the most common form of dementia worldwide. The biological mechanisms underlying the pathogenesis of AD aren't completely clear. Studies have shown that the gut microbiota could be associated with AD pathogenesis; however, the pathways involved still need to be investigated. Aims: To explore the possible pathways of the involvement of gut microbiota in AD pathogenesis through metabolites and to identify new AD biomarkers. Methods: Seven-month-old APP/PS1 mice were used as AD models. The Morris water maze test was used to examine learning and memory ability. 16S rRNA gene sequencing and widely targeted metabolomics were used to identify the gut microbiota composition and fecal metabolic profile, respectively, followed by a combined analysis of microbiomics and metabolomics. Results: Impaired learning abilities were observed in APP/PS1 mice. Statistically significant changes in the gut microbiota were detected, including a reduction in ß-diversity, a higher ratio of Firmicutes/Bacteroidota, and multiple differential bacteria. Statistically significant changes in fecal metabolism were also detected, with 40 differential fecal metabolites and perturbations in the pyrimidine metabolism. Approximately 40% of the differential fecal metabolites were markedly associated with the gut microbiota, and the top two bacteria associated with the most differential metabolites were Bacillus firmus and Rikenella. Deoxycytidine, which causes changes in the pyrimidine metabolic pathway, was significantly correlated with Clostridium sp. Culture-27. Conclusions: Gut microbiota may be involved in the pathological processes associated with cognitive impairment in AD by dysregulating pyrimidine metabolism. B. firmus, Rikenella, Clostridium sp. Culture-27, and deoxyuridine may be important biological markers for AD. Our findings provide new insights into the host-microbe crosstalk in AD pathology and contribute to the discovery of diagnostic markers and therapeutic targets for AD.

Unsupervised Neural Rendering for Image Hazing.

Image hazing aims to render a hazy image from a given clean one, which could be applied to a variety of practical applications such as gaming, filming, photographic filtering, and image dehazing. To generate plausible haze, we study two less-touched but challenging problems in hazy image rendering, namely, i) how to estimate the transmission map from a single image without auxiliary information, and ii) how to adaptively learn the airlight from exemplars, i.e., unpaired real hazy images. To this end, we propose a neural rendering method for image hazing, dubbed as HazeGEN. To be specific, HazeGEN is a knowledge-driven neural network which estimates the transmission map by leveraging a new prior, i.e., there exists the structure similarity (e.g., contour and luminance) between the transmission map and the input clean image. To adaptively learn the airlight, we build a neural module based on another new prior, i.e., the rendered hazy image and the exemplar are similar in the airlight distribution. To the best of our knowledge, this could be the first attempt to deeply render hazy images in an unsupervised fashion. Compared with existing haze generation methods, HazeGEN renders the hazy images in an unsupervised, learnable, and controllable manner, thus avoiding the labor-intensive efforts in paired data collection and the domain-shift issue in haze generation. Extensive experiments show the promising performance of our method comparing with some baselines in both qualitative and quantitative comparisons. The code is available at https://github.com/XLearning-SCU.

Development of a prognostic nomogram for metastatic pancreatic ductal adenocarcinoma integrating marital status.

Previous studies have shown that marital status can affect the overall survival (OS) of cancer patients yet its role in metastatic pancreatic ductal adenocarcinoma (mPDAC) remains unclear. This study aimed to explore the impact of marital status on the OS of mPDAC patients and to construct a prognostic nomogram to predict OS outcomes. Data from patients diagnosed with mPDAC were obtained from the Surveillance, Epidemiology, and End Results database between 1973 and 2015. The patients were randomized into primary and validation cohorts. Kaplan-Meier survival analysis was performed to compare differences in survival depending on marital status. Univariate and multivariate analyses were conducted to identify independent prognostic factors and a nomogram was established based using Cox regression analyses. Validation of the prognostic nomogram was evaluated with a calibration curve and concordance index (C-index). Our data showed significant differences in the OS of mPDAC patients with different marital status by Kaplan-Meier analysis (P < 0.05). Univariate and multivariate analyses confirmed that marital status was an independent OS-related factor in mPDAC patients. Based on the multivariate models of the primary cohort, a nomogram was developed that combined marital status, age, grade, tumor size, surgery of primary site, surgery of lymph node and metastatic. The nomogram showed that marital status had a moderate influence on predicting the OS of mPDAC patients. Moreover, the internally and externally validated C-indexes were 0.633 and 0.619, respectively. A calibration curve confirmed favorable consistency between the observed and predicted outcomes. Marital status was identified as an independent prognostic factor for OS of mPDAC patients and is a reliable and valid parameter to predict the survival of patients with mPDAC. This prognostic model has value and may be integrated as a tool to inform decision-making in the clinic.

[Characteristics and Source Analysis of VOCs Pollution During the Period of Ozone Exceeding the Standard in Zibo City].

In recent years, ozone pollution has been growing increasingly serious in the urban areas of China. Volatile organic compounds (VOCs) are important precursors of O3 formation, which is of great significance to studying the main characteristics and sources of VOCs for controlling O3 pollution. In this study, we conducted online VOCs observation in Zibo City from May to September in 2019, monitoring 56 species in total. During the observation, the over-standard rate of ozone was up to 67.8%, the average of ρ(VOCs) was 140.71 µg·m-3, and the concentration of VOCs in the ozone over standard days was 1.04 times that on the non-standard days. The rank of VOC classes was aromatic hydrocarbons>alkanes>alkenes>alkynes. Among them, 1,3,5-tritoluene, o-ethyltoluene, 1-butene, and n-hexane achieved high emission in the exceeding O3 and non-exceeding days. Aromatic hydrocarbon and alkenes contributed more to the potential of ozone formation. According to the PMF source analysis results, VOCs sources in the urban area mainly included motor vehicle sources, fixed combustion sources, solvent sources, process sources, and natural plant sources, among which motor vehicle sources were the most important source of VOCs in the urban area. In addition, motor vehicle sources accounted for 32.3%, and fixed combustion sources accounted for 24.2% on days when ozone exceeded the standard, which increased by 3.3% and 6.9%, respectively, compared with those on days when ozone did not exceed the standard. However, the proportion of solvent sources and process sources decreased by 5.1% when ozone exceeded the standard compared with that on a non-standard day.

[Characteristics of Ozone Pollution and Influencing Factors in Urban and Suburban Areas in Zibo].

In this study, we obtained monitoring data of O3 and its precursors (NOx, VOCs, and CO), as well as meteorological data (temperature, relative humidity, wind speed, and visibility), in 2019 to analyze the characteristics of O3 pollution and the influencing factors in urban and suburban areas. The results showed that the O3 episodes accounted for 25.8% of the whole observation period, mostly occurring from May to September. The concentration of NOx in urban areas was higher than that in suburban areas, whereas the concentrations of O3 and VOCs were lower. The hourly rate of variation in each pollutant had obvious seasonal characteristics; for example, the time of O3 rise and precursor decline in autumn and winter was approximately 1 h later than that in summer, and the peak period of O3 generation and accumulation was shortened. The increase rate in O3 in urban areas was higher than that in suburban areas. Correlation analysis and partial correlation analysis were used to study the relationship between O3 and its influencing factors. The results showed that O3 was negatively correlated with precursors and relative humidity and positively correlated with visibility, temperature, and wind speed, and these factors interacted with each other. According to the multivariate linear regression analysis, the main controlling factors in urban areas were relative humidity, NOx, visibility, and VOCs, whereas in suburban areas they were relative humidity, temperature, NOx, and VOCs.

Treatment of landfill leachate evaporation concentrate by a modified electro-Fenton method.

Landfill leachate evaporation concentrate (LLEC) is difficult to treat due to its complex pollutant composition, which involves large amount of organic matter and inorganic salts such as scaling ions. Because of its high conductivity and high chloride-ion content, this study employed the modified electro-Fenton method with a self-developed iron-loaded cathode to treat LLEC wastewater. The operating variables were optimized according to the response surface methodology where the chemical oxygen demand (COD) removal efficiency was considered as the response based on single-factor experiments. A second-order polynomial regression model was obtained, and an application experiment revealed that it could be applied to determine LLEC treatment conditions. The removal rates of COD and colour were 100% and 99.8%, respectively, under the optimal operating conditions of an initial pH of 6, electrode spacing of 1 cm and applied voltage of 9 V. Three-dimensional fluorescence spectroscopy demonstrated that the humic acid and fulvic acid pollutants were almost completely removed. Scanning electron microscopy and energy dispersive spectroscopy analysis showed that the iron catalyst was loaded in activated carbon pores and exhibited almost no consumption during the reaction, which effectively solved the problem of iron sludge precipitation caused by electro-Fenton oxidation technology. The atomic distribution in the crystal was also analyzed by X-ray diffraction. The specific energy consumption of electrochemical oxidation was 0.498 Wh·mg-1 COD. The results indicate that the modified electro-Fenton technique with the proposed novel cathode is an effective method for treating LLEC.

Enhancing parameter design for full-aperture rapid planar polishing based on fuzzy optimization.

Full-aperture rapid planar polishing (RPP) has been widely used in optics manufacturing for high-power laser systems. A new, to the best of our knowledge, fuzzy optimization method was presented to assess the precision and productivity of RPP. Unlike the traditional method that can only set one objective, the proposed method can combine different objectives for RPP into one overall indicator. The material removal rate, material removal uniformity, and synthetical fuzzy indicator of RPP (SFIRPP) were selected as the objectives to prove the validity of fuzzy optimization. The rotational speed of optics, polishing pressure, and swing speed were set as the optimized parameters. The orthogonal design was introduced to simplify the operations of experiments. A semi-gamma distribution was used to fit the curve of SFIRPP. The experimental results indicated that the optimized parameters under SFIRPP obtained better manufacturing precision and productivity for flat optics simultaneously. The proposed fuzzy optimization provides the potential for enhancing the optimal parameters of RPP.

[Emission Characteristics of Volatile Organic Compounds from Typical Industries in Zibo].

To study the emission characteristics of volatile organic compounds (VOCs) in Zibo, nine key industries and their representative enterprises were selected to conduct a field investigation and measurement. The emitted VOC characteristics in different industries were analyzed. Based on measurement data, the emissions of VOCs from all monitored enterprises were calculated to obtain the localization emission factors. The results showed that different industries exhibited some differences in VOCs components, and the major VOCs components were alkane and halo hydrocarbon. Ethane, acetylene, chloromethane (conclude 1,1-dichloroethane, 1,1,1-trichloroethane), and Freon (Freon 12 or Freon 114) were the characteristic species in most industries. The results indicated that the major VOCs emission links in different types of petrochemical industries were equipment leakage, loading volatilization, storage volatilization losses, and organized discharge, which accounted for more than 40% of emissions. Local emission factors of VOCs calculated in the synthetic rubber and steel manufacturing industries were close to the recommended values in the guide, whereas there were large gaps in other industries.

The effect of n-π* electronic transitions on the N2 photofixation ability of carbon self-doped honeycomb-like g-C3N4 prepared via microwave treatment.

Light harvesting is an important part of the photocatalysis process. In this work, carbon self-doped honeycomb-like g-C3N4 with outstanding N2 photofixation ability was prepared via microwave treatment. XRD, N2 adsorption, UV-Vis, SEM, XPS, ESR and PL were used to characterize the as-prepared catalysts. Combining the carbon self-doping with microwave treatment, the n-π* transition was successfully stimulated. The remarkable red shift of absorption edge from 465 nm to near 600 nm was observed, leading to the obviously promoted visible light absorption. The synergy effect of carbon doping and microwave treatment also enhances the surface area and separation efficiency of electron-hole pairs. The as-prepared catalyst displays the highest NH4 + concentration of 5.3 mg L-1 gcat -1, over 11 times higher than that of neat g-C3N4, as well as excellent photocatalytic stability. DFT calculation was also used to further prove our point of view. This paper provides a new way for the construction of high efficiency photocatalysts.

[Determination of Trace Germanium in Plant Samples by Dry Ashing-Atomic Fluorescence Spectrometry].

To reduce the limit of detection (LOD) and allow the accurate determination of Ge, a dry ashing method was performed to enrich the Ge in plant samples. A method for the determination.of trace Ge in plant samples by HG-AFS was established. Study of the effect of temperature on the ashing of plant samples showed that no volatile loss of Ge occurred even at 900 °C. Additional experiments indicated that a 4 h burning process at 600 °C would be sufficient to fully ash the plant samples. Various digestion methods (involving nitric acid, hydrofluoric acid, and sulfuric acid digestion methods) for ashed samples were investigated. High-temperature ashing with large sample weights was used, which could reduce the reagent doses and the method's LOD effectively and simultaneously, the precision of the method was improved. The method's LOD was 0.27 ng · g(-1), and the relative standard deviation was 3.99%-6.81%. Verified with national biological reference materials (grade I), the proposed method was accurate and reliable.

c-Myc suppressed E-cadherin through miR-9 at the post-transcriptional level.

c-Myc oncoprotein is overexpressed in most human cancers and regulates different genes and pathways in different cell types. E-cadherin expression is repressed by MYC through a post-transcriptional mechanism, but the exact mechanism remains elusive. Since E-cadherin is a direct target of miR-9 and miR-9 can be activated by MYC and MYCN, this suggests that c-Myc negatively modulates E-cadherin through a microRNA pathway. We have established a c-Myc-inducible expression system in which the protein level and transcriptional activity of c-Myc is significantly upregulated upon doxycycline induction. Overexpressed c-Myc led to an EMT-like conversion in the T-REx-293 cells and resulted in a significant decrease in E-cadherin and an increase in Vimentin. Stem-loop RT-PCR showed elevated expression of miR-9 when c-Myc was induced to be overexpressed. Regarding the relationship of c-Myc, miR-9 and E-cadherin, the expression of miR-9 was curtailed by using antagomir-9 in induced overexpressing c-Myc. Restoration of E-cadherin expression became much stronger in the presence of c-Myc. Thus c-Myc represses E-cadherin at the post-transcriptional level through miR-9.

miR-106a is frequently upregulated in gastric cancer and inhibits the extrinsic apoptotic pathway by targeting FAS.

Emerging evidence has shown the association of aberrantly expressed miR-106a with cancer development, however, little is known about its potential role in gastric carcinogenesis. In our present study, obviously overexpressed miR-106a was found in gastric cancer tissues compared with their nontumor counterparts. Suppression of miR-106a significantly inhibited gastric cancer cell proliferation and triggered apoptosis. Bioinformatic analysis combining with validation experiments identified FAS as a direct target of miR-106a. Rescue experiments and examination of caspase-8, PARP and caspase-3 further approved that miR-106a could inhibit gastric cancer cell apoptosis through interfering with FAS-mediated apoptotic pathway. Moreover, a significant inverse correlation was found between miR-106a and FAS expression not only in gastric cancer cell lines but also in gastric cancer specimens. Taken together, these findings suggest that ectopicly overexpressed miR-106a may play an oncogenic role in gastric carcinogenesis and impair extrinsic apoptotic pathway through targeting FAS.