Sulfate reduction behavior in response to landfill dynamic pressure changes.

During the long-term stabilization process of landfills, the pressure field undergoes constant changes. This study constructed dynamic pressure changes scenarios of high-pressure differentials (0.6 MPa) and low-pressure differentials (0.2 MPa) in the landfill pressure field at 25 °C and 50 °C, and investigated the sulfate reduction behavior in response to landfill dynamic pressure changes. The results showed that the pressurization or depressurization of high-pressure differentials caused more significant differences in sulfate reduction behavior than that of low-pressure differentials. The lowest hydrogen sulfide (H2S) release peak concentration under pressurization was only 29.67% of that under initial pressure condition; under depressurization, the highest peak concentration of H2S was up to 21,828 mg m-3, posing a serious risk of H2S pollution. Microbial community and correlation analysis showed that pressure had a negative impact on the sulfate-reducing bacteria (SRB) community, and the SRB community adjusted its structure to adapt to pressure changes. Specific SRBs were further enriched with pressure changes. Differential H2S release behavior under pressure changes in the 25 °C pressure environments were mediated by Desulfofarcimen (ASV343) and Desulfosporosinus (ASV1336), while Candidatus Desulforudis (ASV24) and Desulfohalotomaculum (ASV94) played a key role at 50 °C. This study is helpful in the formulation of control strategies for the source of odor pollution in landfills.

Sulfate reduction behavior in response to changing of pressure coupling with temperature inside landfill.

The behavior of sulfate reduction, which was the source of hydrogen sulfide (H2S) odor, was investigated under changing pressure and temperature conditions inside landfills. The results showed that the release of H2S and methyl mercaptan (MM) was significantly inhibited at 25 °C and 50 °C under pressure, and the highest H2S and MM concentrations released were only 0.82 %-1.30 % and 1.87 %-4.32 % of atmospheric pressure, respectively. Analysis of the microbial community structure and identification of sulfate-reducing bacteria (SRB) revealed that temperature significantly altered the microbial community in the landfill environment, while pressure inhibited some bacteria and induced the growth and reproduction of specific bacteria. Key SRB (Desulfosporosinus-ASV212, Desulfitibacter-ASV1744) mediated differentiated sulfate reduction behavior in the pressure-bearing environment at 25 °C, while key SRB (Dethiobacter-ASV177, Desulfitibacter-ASV2355 and ASV316) were involved at 50 °C. This study provides a theoretical basis for the formulation of landfill gas management and control strategies.

Sulfate reduction behavior in pressure-bearing leachate saturated zone.

Attention should be paid to the sulfate reduction behavior in a pressure-bearing leachate saturated zone. In this study, within the relative pressure range of 0-0.6 MPa, the ambient temperature with the highest sulfate reduction rate of 50°C was selected to explore the difference in sulfate reduction behavior in a pressure-bearing leachate saturated zone. The results showed that the sulfate reduction rate might further increase with an increase in pressure; however, owing to the effect of pressure increase, the generated hydrogen sulfide (H2S) could not be released on time, thereby decreasing its highest concentration by approximately 85%, and the duration extended to about two times that of the atmospheric pressure. Microbial community structure and functional gene abundance analyses showed that the community distribution of sulfate-reducing bacteria was significantly affected by pressure conditions, and there was a negative correlation between disulfide reductase B (dsrB) gene abundance and H2S release rate. Other sulfate reduction processes that do not require disulfide reductase A (dsrA) and dsrB genes may be the key pathways affecting the sulfate reduction rate in the pressure-bearing leachate saturated zone. This study improves the understanding of sulfate reduction in landfills as well as provides a theoretical basis for the operation and management of landfills.

Wnt signaling pathway-derived score for predicting therapeutic resistance and tumor microenvironment in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Due to tumor heterogeneity, understanding the pathological mechanism of tumor progression helps to improve the diagnosis process and clinical treatment strategies of LUAD patients. Methods: The transcriptome pattern, mutant expression and complete clinical information were obtained from the cancer genome atlas (TCGA) database and microarray data from gene expression omnibus (GEO) database. Firstly, we used single sample Gene Set Enrichment Analysis (ssGSEA) to estimate the activation of Wnt signaling pathway in each sample. Consensus clustering algorithm was used to classify LUAD samples into different subgroups according to the transcription patterns of 152 Wnt signaling pathway related genes. Then, ESTIMATE, ssGSEA and Gene Set Variation Analysis (GSVA) algorithms were used to assess the biological pathways and immunocytes infiltration between different subtypes. LASSO-COX algorithm was conducted to construct prognostic model. Kaplan-Meier and multivariate Cox analysis were performed to evaluate the predictive performance of risk model. Gene features were further confirmed using external datasets. Finally, we conducted vitro assay for validating hub gene (LEF1). Results: Based on the transcription patterns of 152 Wnt signaling pathway related genes, four different subtypes of LUAD patients were screened out by consensus clustering algorithm. Subsequently, it was found that patients with cluster A and B had massive immunocytes infiltration, and the survival rate of patients with cluster B was better than that of other subgroups. According to the coefficients in the LASSO- Cox model and the transcriptome patterns of these 18 genes, the risk score was constructed for each sample. The degree of malignancy of LUAD patients with high-risk subgroup was remarkable higher than that of patients with low-risk subgroup (p < 0.001). Subsequently, five top prognostic genes (AXIN1, CTNNB1, LEF1, FZD2, FZD4.) were screened, and their expression values were different between cancer and normal tissues. FZD2 and LEF1 were negatively related to ImmunoScore, and AXIN1 was negatively related to ImmunoScore. The significant correlation between LUAD patient risk score and overall survival (OS) was verified in external datasets. In the A549 cell line, knockdown of LEF1 can reduce the invasive and proliferation ability of LUAD cells. Conclusion: A innovative 18 genes predictive feature based on transcriptome pattern was found in patients with lung adenocarcinoma. These investigations further promote the insight of the prognosis of lung adenocarcinoma and may contribute to disease management at risk stratification.

Bounded Cost Path Planning for Underwater Vehicles Assisted by a Time-Invariant Partitioned Flow Field Model.

A bounded cost path planning method is developed for underwater vehicles assisted by a data-driven flow modeling method. The modeled flow field is partitioned as a set of cells of piece-wise constant flow speed. A flow partition algorithm and a parameter estimation algorithm are proposed to learn the flow field structure and parameters with justified convergence. A bounded cost path planning algorithm is developed taking advantage of the partitioned flow model. An extended potential search method is proposed to determine the sequence of partitions that the optimal path crosses. The optimal path within each partition is then determined by solving a constrained optimization problem. Theoretical justification is provided for the proposed extended potential search method generating the optimal solution. The path planned has the highest probability to satisfy the bounded cost constraint. The performance of the algorithms is demonstrated with experimental and simulation results, which show that the proposed method is more computationally efficient than some of the existing methods.

The mineral dust-induced gene, mdig, regulates angiogenesis and lymphangiogenesis in lung adenocarcinoma by modulating the expression of VEGF-A/C/D via EGFR and HIF-1α signaling.

Mineral dust­induced gene (mdig) is a novel lung cancer­related oncogene. The aim of this study was to explore the effects of mdig on angiogenesis and lymphangiogenesis by vascular endothelial growth factor (VEGF) in lung adenocarcinoma. mdig­overexpressing A549, H1299 and 293T cells, mdig­silenced A549, human umbilical vein endothelial cells (HUVECs) and human lymphatic endothelial cells (HLECs) were cultured under normoxic and hypoxic conditions. Protein expression levels of mdig, epidermal growth factor receptor (EGFR), phospho(p)­EGFR Tyr1068, hypoxia­inducible factor­1α (HIF­1α), VEGF­A/C/D and VEGF­R1/R2/R3 were assessed using western blotting. mRNA expression levels of mdig, EGFR and HIF­1α were measured using RT­qPCR. Tube formation and xenograft tumor experiments were performed to examine the mechanism of mdig in angiogenesis and lymphangiogenesis. Protein expression levels of EGFR, HIF­1α and VEGF­A/C/D were significantly upregulated in cells cultured under hypoxic conditions compared with those cultured under normoxic conditions, whereas the levels of mdig were decreased. Protein expression levels of EGFR, p­EGFR and VEGF­A/R1/R2 were significantly increased in the mdig­overexpressing cells, whereas the levels of HIF­1α and VEGF­C/D/R3 were decreased compared with those in control cells, all of which were reversed in mdig­silenced cells. Tumor volumes and density of angiogenesis in the mdig­overexpressing group were significantly increased compared with those in the control group, whereas the density of lymphangiogenesis was decreased. No tumors formed in the mdig­silenced group after 3 weeks of assessment in vivo. Protein expression levels of EGFR, p­EGFR, VEGF­A and angiogenesis density were significantly reduced in the mdig­overexpressing cells treated with an EGFR inhibitor, whereas the levels of HIF­1α, VEGF­C/D and the lymphangiogenesis density were significantly increased in mdig­overexpressing cells treated with a HIF­1α agonist. All changes in protein expression were reversed in EGFR agonist and HIF­1α inhibitor treated mdig­silenced cells. In conclusion, mdig is an oxygen­sensitive protein that promotes tumor growth and angiogenesis by activating the EGFR/p­EGFR/VEGF­A/VEGF­R1/R2 pathway and inhibits lymphangiogenesis by blocking the HIF­1α/VEGF­C/D/VEGF­R3 pathway.

MDIG promotes cisplatin resistance of lung adenocarcinoma by regulating ABC transporter expression via activation of the WNT/ß-catenin signaling pathway.

Mineral dust-induced gene (MDIG) is a proto- oncogene associated with lung cancer that serves a key role in the biological processes of tumorigenesis. The aim of the present study was to determine whether MDIG is involved in cisplatin (DDP) resistance in lung adenocarcinoma, and to investigate the associated molecular mechanism. In the present study, MDIG-knockdown and MDIG-overexpressing A549 cells and DDP-resistant A549/DDP cells were initially constructed, and then the mRNA and protein expression levels of MDIG and ATP-binding cassette (ABC) transporters (ABCB1, ABCC1, ABCG2), and the expression levels of the major associated proteins in the WNT/ß-catenin pathway were determined by reverse transcription-quantitative PCR and Western blotting experiments. The results revealed that the mRNA and protein expression levels of MDIG in A549/DDP cells were significantly higher compared with those in A549 cells, and that the protein expression levels of MDIG increased in a dose-dependent manner with increasing DDP concentrations. Overexpression of MDIG in A549 and A549/DDP cells led to an increase in the IC50 value, whereas silencing of MDIG led to a clear reduction in the IC50 value. The overexpression of MDIG in the A549 and A549/DDP cells markedly upregulated the mRNA and protein expression levels of ABCB1, ABCC1, ABCG2, WNT family member 5A, WNT family member 3A and active ß-catenin, and these were markedly decreased following MDIG silencing. Taken together, these results demonstrated that the DDP resistance of lung adenocarcinoma may be associated with an upregulation of MDIG expression, and that the expression levels of MDIG are positively associated with the degree of DDP resistance. Furthermore, MDIG promoted the expression of ABC transporters in tumor cells by activating the WNT/ß-catenin signaling pathway, which may, in turn, lead to DDP resistance in lung adenocarcinoma.

A strategy combining intrinsic time-scale decomposition and a feedforward neural network for automatic seizure detection.

Epilepsy is a common neurological disorder which can occur in people of all ages globally. For the clinical treatment of epileptic patients, the detection of epileptic seizures is of great significance. OBJECTIVE: Electroencephalography (EEG) is an essential component in the diagnosis of epileptic seizures, from which brain surgeons can detect important pathological information about patient epileptiform discharges. This paper focuses on adaptive seizure detection from EEG recordings. We propose a new feature extraction model based on an adaptive decomposition method, named intrinsic time-scale decomposition (ITD), which is suitable for analyzing non-linear and non-stationary data. APPROACH: Firstly, using the ITD technique, every EEG recording is decomposed into several proper rotation components (PRCs). Secondly, the instantaneous amplitudes and frequencies of these PRCs can be calculated and then we extract their statistical indices. Furthermore, we combine all these statistical indices of the corresponding five PRCs as the feature vector of each EEG signal. Finally, these feature vectors are fed into a feedforward neural network (FNN) classifier for EEG classification. The whole process of feature extraction proposed in this paper only involves one parameter and the role of the ITD method is based on a piecewise linear function, which makes the computation of the model simple and fast. More useful information for classification can be obtained since we take advantage of both instantaneous amplitude and instantaneous frequency for feature extraction. MAIN RESULTS: We consider the 17 classification problems which contain normal versus epileptic, non-seizure versus seizure and normal versus interictal versus ictal using a FNN classifier which only contains one hidden layer. Experimental results show that the proposed method can catch the discriminative features of EEG signals and obtain comparable results when compared with state-of-the-art detection methods. SIGNIFICANCE: Therefore, the proposed system has a great potential in real-time seizure detection and provides physicians with a real-time diagnostic aid in their practice.

Development of spatial representation of power in children.

Systematic evidence demonstrates that power is mentally represented as vertical space by adults. However, little is known about the developmental progress of such representation. Using the explicit power evaluation task, this study investigated the development of the spatial representation of power. Participants were Chinese children (5-7 years old) and adults. The results revealed that vertical motor responses interfered with responding for all age groups; that is, they responded to words representing powerless groups faster with the down cursor key than with the up cursor key (and vice versa for powerful groups). More important, the size of the effect did not show much developmental change. The findings suggest that even children aged 5 years have developed a spatial representation of power once they understand the power concept.

Mdig suppresses epithelial-mesenchymal transition and inhibits the invasion and metastasis of non­small cell lung cancer via regulating GSK-3ß/ß-catenin signaling.

Mineral dust-induced gene (mdig) can inhibit the invasion and metastasis of A549 cells. The main purpose of this study was to explore the molecular mechanism underlying the inhibitory effect of mdig on cell invasion and metastasis. Mdig-knockdown and mdig-overexpressing A549 cells and an mdig-overexpressing human umbilical vein endothelial cell (HUVEC) line were constructed using lentiviral vectors, and western blot analysis was performed to verify the silencing and overexpression of the mdig protein. A Transwell invasion assay was used to detect the invasive abilities of each experimental group, and Transwell migration and scratch assays were used to detect cell migration ability. Western blotting was subsequently conducted to detect the major biochemical indices of the GSK-3ß/ß-catenin pathway and the protein expression levels and modifications of epithelial­mesenchymal transition (EMT) transcription factors, as well as changes in the expression levels of EMT molecular markers and intercellular adhesion proteins. The results indicated that overexpression of mdig in A549 cells inhibited cell invasion and metastasis, while silencing of mdig increased the invasive and metastatic properties of cells. The molecular mechanism underlying the effects of mdig downregulation on A549 cell invasion and metastasis was found to involve the inhibition of GSK-3ß phosphorylation, which in turn promoted the phosphorylation and destabilization of ß-catenin. This was associated with downregulation of the downstream transcription factors slug, snail and ZEB1, thus leading to increased expression levels of epithelial cell markers and upregulation of the intercellular adhesion molecules E-cadherin, claudin­1, ZO­1, integrin ß1 and integrin ß4, which was accompanied by downregulation of the mesenchymal cell markers vimentin and N-cadherin. The HUVECs were used to validate the aforementioned molecular mechanisms and the same conclusions were obtained. The present results indicate that mdig can inhibit the phosphorylation of GSK-3ß and promote the phosphorylation and destabilization of ß-catenin, in order to suppress the expression of slug, snail, and ZEB1 and the occurrence of EMT, and thereby inhibit the invasion and metastasis of non-small cell lung cancer (NSCLC).

Total variation regularization for 3D reconstruction in fluorescence tomography: experimental phantom studies.

Fluorescence tomography (FT) is depth-resolved three-dimensional (3D) localization and quantification of fluorescence distribution in biological tissue and entails a highly ill-conditioned problem as depth information must be extracted from boundary measurements. Conventionally, L2 regularization schemes that penalize the euclidean norm of the solution and possess smoothing effects are used for FT reconstruction. Oversmooth, continuous reconstructions lack high-frequency edge-type features of the original distribution and yield poor resolution. We propose an alternative regularization method for FT that penalizes the total variation (TV) norm of the solution to preserve sharp transitions in the reconstructed fluorescence map while overcoming ill-posedness. We have developed two iterative methods for fast 3D reconstruction in FT based on TV regularization inspired by Rudin-Osher-Fatemi and split Bregman algorithms. The performance of the proposed method is studied in a phantom-based experiment using a noncontact constant-wave trans-illumination FT system. It is observed that the proposed method performs better in resolving fluorescence inclusions at different depths.

Model for efficient simulation of spatially incoherent light using the Wiener chaos expansion method.

We demonstrate a new and efficient technique for modeling and simulation of spatially incoherent sources using the Wiener chaos expansion method. By implementing this new model, we show that a practical-size photonic structure with a spatially incoherent input source can be analyzed more than 2 orders of magnitude faster compared with the conventional models without sacrificing the accuracy.

Total variation wavelet-based medical image denoising.

We propose a denoising algorithm for medical images based on a combination of the total variation minimization scheme and the wavelet scheme. We show that our scheme offers effective noise removal in real noisy medical images while maintaining sharpness of objects. More importantly, this scheme allows us to implement an effective automatic stopping time criterion.