In the present study, we evaluated the role of phosphatidylinositol-3 OH kinase/protein kinase B (PI3K/Akt) signaling on changes to epithelial-to-mesenchymal reverting transition (EMrT) in nasopharyngeal carcinoma (NPC). Protein expression levels of p-Akt (Ser473), and the epithelial‑to-mesenchymal transition (EMT) markers E-cadherin, vimentin, α smooth muscle actin (α-SMA), were examined in clinical samples from 130 cases of undifferentiated non-keratinizing NPC, and 20 cases of benign nasopharyngitis. The relationship between protein expression levels and the statue of NPC lymph node metastasis was analyzed. The poorly‑differentiated NPC cell line CNE2Z was treated with various concentrations of the PI3K inhibitor, LY294002, and western blotting and quantitative polymerase chain reaction assays were used to analyze the activation of PI3K/Akt signaling and expression of E-cadherin, vimentin and α-SMA. The ability of cellular migration and invasion was assessed using Transwell assays. The in vivo effects of LY294002 on metastasis and expression of EMT markers in CNE2Z cells was evaluated using tumor xenograft experiments. The expression levels of p-Akt (Ser473) in NPC samples were higher than those in nasopharyngitis. There were reduced levels of membrane E-cadherin protein expression, and increased cytosol vimentin and α-SMA expression levels in NPC samples compared with those in nasopharyngitis samples. High expression levels of p-Akt (Ser473), vimentin, and α-SMA, and low expression levels of E-cadherin were positively associated with lymph node metastasis of NPC cells. Treating CNE2Z cells with LY294002 inhibited p-Akt (Ser473), vimentin and α-SMA expression but upregulated E-cadherin expression, leading to significantly attenuated cell invasion and migration. Administration of mice with LY294002 resulted in upregulation of membrane E-cadherin, and downregulation of vimentin and α-SMA in CNE2Z xenografts, with reduced pulmonary metastasis. Our findings suggest that inhibiting the PI3K/Akt pathway using LY294002 attenuated NPC metastasis via induction of EMrT.

Total organic carbon (TOC) estimation is significantly crucial for shale reservoir characterization. Traditional TOC estimation methods (such as Passey and Schmoker method) do not provide accurate TOC predictions in shale gas reservoirs especially for the self-generated and self-stored reservoirs. This study proposes, for the first time, a new TOC prediction method based on Gaussian Process Regression (GPR) bridging geostatistics and machine learning technique. The method utilizes a non-parametric regression approach in shale TOC predictions, and not only provides the expert solutions in high-dimension processing, small samples and non-linear problems, but also has a better adaptation and generalization ability compared with other machine learning methods. The approach accounts for all the well logging attributes and chooses the relevant logs to build TOC estimation model, and 7 different kernel functions and 5 attributes groups are analyzed to get the optimized hyperparameters in practice. Application of the developed model to two shale gas reservoirs showed that the model predicted TOC matched well with that from the laboratory measurements. The proposed model based on GPR method provides an accurate way for the TOC prediction in the tight shale gas reservoirs.

IntroductionTransplantation of bone marrow mesenchymal stem cells (BMSCs) can repair injured hearts. However, whether BMSC populations contain cells with cardiac stem cell characteristics is ill-defined. We report here that Notch signalling can promote differentiation of c-KitPOS/NKX2.5POS BMSCs into cardiomyocyte-like cells.MethodsTotal BMSCs were isolated from Sprague–Dawley rat femurs and c-KitPOS cells were purified. c-KitPOS/NKX2.5POS cells were isolated by single-cell cloning, and the presence of cardiomyocyte, smooth muscle cell (SMC), and endothelial cell differentiation markers assessed by immunofluorescence staining and semi-quantitative reverse-transcription polymerase chain reaction (RT-PCR) analysis. Levels of c-Kit and Notch1–4 in total BMSCs and c-KitPOS/NKX2.5POS BMSCs were quantitated by flow cytometry. Following infection with an adenovirus over-expressing Notch1 intracellular domain (NICD), total BMSCs and c-KitPOS/NKX2.5POS cells were assessed for differentiation to cardiomyocyte, SMC, and endothelial cell lineages by immunofluorescence staining and real-time quantitative RT-PCR. Total BMSCs and c-KitPOS/NKX2.5POS cells were treated with the Notch1 ligand Jagged1 and markers of cardiomyocyte, SMC, and endothelial cell differentiation were examined by immunofluorescence staining and real-time quantitative RT-PCR analysis.Resultsc-KitPOS/NKX2.5POS cells were present among total BMSC populations, and these cells did not express markers of adult cardiomyocyte, SMC, or endothelial cell lineages. c-KitPOS/NKX2.5POS BMSCs exhibited a multi-lineage differentiation potential similar to total BMSCs. Following sorting, the c-Kit level in c-KitPOS/NKX2.5POS BMSCs was 84.4%. Flow cytometry revealed that Notch1 was the predominant Notch receptor present in total BMSCs and c-KitPOS/NKX2.5POS BMSCs. Total BMSCs and c-KitPOS/NKX2.5POS BMSCs overexpressing NICD had active Notch1 signalling accompanied by differentiation into cardiomyocyte, SMC, and endothelial cell lineages. Treatment of total BMSCs and c-KitPOS/NKX2.5POS BMSCs with exogenous Jagged1 activated Notch1 signalling and drove multi-lineage differentiation, with a tendency towards cardiac lineage differentiation in c-KitPOS/NKX2.5POS BMSCs.Conclusionsc-KitPOS/NKX2.5POS cells exist in total BMSC pools. Activation of Notch1 signalling contributed to multi-lineage differentiation of c-KitPOS/NKX2.5POS BMSCs, favouring differentiation into cardiomyocytes. These findings suggest that modulation of Notch1 signalling may have potential utility in stem cell translational medicine.Electronic supplementary materialThe online version of this article (doi:10.1186/s13287-015-0085-2) contains supplementary material, which is available to authorized users.

No abstract

Lowly permeable sandstone reservoirs play an important role in the exploration and exploitation of natural gas and petroleum in China. The reservoirs are major lowly permeable sandstone reservoirs in Chang 2 division, Yanchang Formation, Upper Triassic in Zhang-Han oilfield, which located in the northern Shaanxi slope of Ordos Basin. According to the distribution and composition of sand beds, integrated measured physical properties, micro-pore structure analysis, cast thin section observation, scanning electron microscopy, the impacts of deposition and diagenesis on porosity evolution are analyzed. The essential diagenesis causing the porosity loss is evaluated quantitatively, and finally the origin mechanisms of low permeability reservoir in Zhang-Han oilfield are discussed. The results show: (1) Fine particle and low compositional maturity arkose are the material foundation of the formation of poor physical property sandstone; (2) The main pore space of reservoir is secondary pores. There are two types of combined pores that including dissolve-residual pores and dissolve-micropores. The porosity values display an approximately normal distribution, and permeability values are asymmetric distribution of the logarithm in lowly permeable sandstones. Their correlation coefficient becomes more and more worse with the decrease of permeability; (3) There are four diagenetic facies, in which three diagenetic facies belong to extra-lowly permeable and ultra-lowly permeable reservoir sandstones and widely distributed, and they are diagenetic lithofacie background of lowly permeability sandstone; (4) In low compositional maturity arkose, its initial porosity is 1/4 lower than conventional reservoir, the secondary and dissolved pores are main pore types of lowly permeable reservoir rocks. It is also a key factor of effective oil-bearing of lowly permeability sandstone.

No abstract

No abstract

Total organic carbon (TOC) estimation is very important for shale gas reservoir characterization. There are many introduced methods for TOC prediction in organic-rich shales. However, there are still some weaknesses with the most of the methods. This paper proposes a new method using machine learning, Gaussian Process Regression, which is expert in processing high-dimension, small samples, and non-linear problems. Compare to the Neural Network, and Support Vector Machine, Gaussian Process Regression has adaptation and generalization ability. This paper takes Zhangjiatan shale of the Yanchang Formation of the Triassic period in the south-eastern Ordos Basin as an example. A total of 7 kernel functions are applied to build the regression model. As a result, the Cauchy kernel is chosen due to lowest error. Then, feature selection is carried on based on the weights which calculated from 4 weights algorithms. Finally, compared the Gaussian Process Regression results to the traditional methods, (e.g., Passey and Schmoker methods), we found that Gaussian Process Regression works well for TOC estimation.