Search

Rationale Neutrophils constitute massive cellular constituents in inflammatory human gastric cancer (GC) tissues, but their roles in pathogenesis of inflammatory T helper (Th) subsets are still unknown. Methods Flow cytometry analysis and immunohistochemistry were used to analyze the responses and phenotypes of neutrophils in different samples from 51 patients with GC. Kaplan‐Meier plots and Multivariate analysis for the survival of patients were used by log‐rank tests and Cox proportional hazards models. Neutrophils and CD4+ T cells were purified and cultured for ex vivo, in vitro and in vivo regulation and function assays. Results GC patients exhibited increased tumoral neutrophil infiltration with GC progression and poor patient prognosis. Intratumoral neutrophils accumulated in GC tumors via CXCL6/CXCL8‐CXCR1‐mediated chemotaxis, and expressed activated molecule CD54 and co‐signaling molecule B7‐H2. Neutrophils induced by tumors strongly expressed CD54 and B7‐H2 in both dose‐ and time‐dependent manners, and a close correlation was obtained between the expressions of CD54 and B7‐H2 on intratumoral neutrophils. Tumor‐derived tumor necrosis factor‐α (TNF‐α) promoted neutrophil activation and neutrophil B7‐H2 expression through ERK‐NF‐κB pathway, and a significant correlation was found between the levels of TNF‐α and CD54+ or B7‐H2+ neutrophils in tumor tissues. Tumor‐infiltrating and tumor‐conditioned neutrophils effectively induced IL‐17A‐producing Th subset polarization through a B7‐H2‐dependent manner ex vivo and these polarized IL‐17A‐producing Th cells exerted protumorigenic roles by promoting GC tumor cell proliferation via inflammatory molecule IL‐17A in vitro, which promoted the progression of human GC in vivo; these effects could be reversed when IL‐17A is blocked. Moreover, increased B7‐H2+ neutrophils and IL‐17A in tumors were closely related to advanced GC progression and predicted poor patient survival. Conclusion We illuminate novel underlying mechanisms that TNF‐α‐activated neutrophils link B7‐H2 to protumorigenic IL‐17A‐producing Th subset polarization in human GC. Blocking this pathological TNF‐α‐B7‐H2‐IL‐17A pathway may be useful therapeutic strategies for treating GC., Our results illuminate a novel mechanism that TNF‐α‐activated neutrophils link B7‐H2 to protumorigenic IL‐17A‐producing Th subset polarization in human GC. Blocking this pathological TNF‐α‐B7‐H2‐IL‐17A pathway may be useful therapeutic strategies for treating GC.

Neutrophils are conspicuous components of gastric cancer (GC) tumors, increasing with tumor progression and poor patient survival. However, the phenotype, regulation and clinical relevance of neutrophils in human GC are presently unknown. Most intratumoral neutrophils showed an activated CD54+ phenotype and expressed high level B7-H3. Tumor tissue culture supernatants from GC patients induced the expression of CD54 and B7-H3 on neutrophils in time-dependent and dose-dependent manners. Locally enriched CD54+ neutrophils and B7-H3+ neutrophils positively correlated with increased granulocyte-macrophage colony stimulating factor (GM-CSF) detection ex vivo; and in vitro GM-CSF induced the expression of CD54 and B7-H3 on neutrophils in both time-dependent and dose-dependent manners. Furthermore, GC tumor-derived GM-CSF activated neutrophils and induced neutrophil B7-H3 expression via JAK-STAT3 signaling pathway activation. Finally, intratumoral B7-H3+ neutrophils increased with tumor progression and independently predicted reduced overall survival. Collectively, these results suggest B7-H3+ neutrophils to be potential biomarkers in GC.

Midazolam is an anesthetic agent commonly used during clinical and surgical procedures, which has been shown to exert ROS‑suppressing and apoptosis‑modulating pharmacological activities in various cellular systems. However, the effects of midazolam on oxidative stress in neuronal cells require elucidation. The present study investigated the effects of midazolam on buthionine sulfoximine (BSO)‑ and hydrogen peroxide (H2O2)‑induced oxidative stress in primary cortical neuronal cells. In addition, the effects of midazolam on middle cerebral artery occlusion (MCAO) in mice and on ethanol‑induced neuroapoptosis in the brains of neonatal mice were determined. Subsequently, cell viability was detected using the MTT assay; intracellular reactive oxygen species (ROS) generation was determined using the 2',7'‑dichlorodihydrofluorescein diacetate method with confocal microscopy; terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining was conducted to detect apoptotic cells; immunohistochemistry was performed to detect activated caspase‑3; neuronal deficit and infarct volume analyses were conducted; and quantitative polymerase chain reaction and western blotting were performed to detect the expression levels of genes and proteins associated with apoptosis and cell survival pathways. The results demonstrated that BSO (10 mM) and H2O2 (1 mM) suppressed proliferation of cortical neuronal cells by inducing apoptosis. These effects were suppressed following treatment with midazolam in a dose‑dependent manner. In addition, BSO and H2O2 induced ROS generation in neuronal cells; however, this was effectively suppressed by midazolam (100 µM). Beneficial synergistic effects were detected when midazolam was used in combination with the known antioxidant trolox. BSO and H2O2 also suppressed the protein expression levels of c‑Jun N‑terminal kinases (JNK), phosphorylated (p)JNK, extracellular signal‑regulated kinases (ERK)1/2, pERK1/2, AKT and nuclear factor‑κB; however, expression was recovered following treatment with midazolam. Midazolam also activated protein kinase C‑e, which was suppressed by BSO, in cortical neuronal cells. In MCAO mice, midazolam post‑conditioning significantly suppressed infarct size and reduced the number of TUNEL‑positive cells. In addition, the expression levels of caspase‑3 and poly (ADP‑ribose) polymerase were suppressed in a dose‑dependent manner. In neonatal mice, midazolam reduced ethanol‑induced activated caspase‑3 staining and apoptotic TUNEL staining. The results of the present study demonstrated that midazolam may protect against neuronal degeneration and neuroapoptosis induced by physiological and oxidative stress.

One of the major challenges is small sample size as compared to large features number for microarray data. Variable selection is an important step for improving diagnostics of cancer or the classification according to the phenotypes via gene expression data. In this study, we propose a modified sequential backward selection (SBS) algorithm to deal with the case where the covariance matrix is singular. Then we propose a variable selection algorithm based on the weighted Mahalanobis distance and modified SBS methods. Furthermore, based on the proposed variable selection algorithm, a Fisher linear discriminant method is proposed to improve the accuracy of tumor classification through simultaneously taking into account genes’ joint discriminatory power. To validate the efficiency, we apply the proposed discriminant method to two different DNA microarray data sets for experiment investigation. The empirical results show that our method for tumor classification can obtain better classification effectiveness than Markov random field method and independent variable group analysis I methods, which demonstrates that the proposed variable selection method can obtain more correct and informative gene subset if taking into account the joint discriminatory power of genes for tumor classification.

In this article we consider the problem of detecting changes in level and trend in time series model in which the number of change-points is unknown. The approach of Bayesian stochastic search model selection is introduced to detect the configuration of changes in a time series. The number and positions of change-points are determined by a sequence of change-dependent parameters. The sequence is estimated by its posterior distribution via the maximum a posteriori (MAP) estimation. Markov chain Monte Carlo (MCMC) method is used to estimate posterior distributions of parameters. Some actual data examples including a time series of traffic accidents and two hydrological time series are analyzed.

The ferrite transformation kinetics of severely hot-deformed austenite has been studiedby considering ferrite nucleation from dislocation cell blocks inside austenite grains. The size ofdislocation cell blocks and ferrite grain size just after phase transformation are acknowledged to beinversely proportional to the square root of dislocation density. It is found that the ferrite nucleationrate in this area can reach the saturated state at a high temperature just under Ae3, and the ferritetransformation finishes within a very short time. The kinetics of ferrite volume fraction and theferrite grain growth after phase transformation for plain carbon (0.1%C, 0.2%Si, 1.0%Mn) steelhave been studied using a THERMECMASTER hot-compression testing machine. These modelscan be applied to the hot and warm forming processes of plain carbon steel to predict the ferritetransformation from severely deformed austenite.

We have derived the predictive distributions of future responses and the regression matrix in the multivariate linear regression model, under the singular or nonsingular matrix variate elliptically contoured distribution with noninformative prior, with respect to the Hausdorff measure. The predictive distributions are also derived under the singular or nonsingular matrix variate normal distribution with normal–inverse Wishart conjugate prior as a particular case of the matrix elliptically contoured distribution. The predictive distributions are singular or nonsingular matrix-T distributions introduced by Diaz-Garcia and Gutierrez-Jaimez [J.A. Diaz-Garcia, R. Gutierrez-Jaimez, Distribution of the generalized inverse of a random matrix and its applications, J. Statist. Plann. Inference 136 (2006) 183–192], both in the noninformative and conjugate prior cases. The first result gives inference robustness with respect to departures from the underlying distribution assumption in the direction of elliptically contoured distributions, even in the singularly distributed case.

Undisturbed soil monolith lysimeter was used to investigate the effectiveness of DCD (dicyandiamide) in reducing N2O emissions in vegetable (Chinese cabbage and pepper) field. Results showed that DCD significantly reduced total N2O emission in vegetable field. Total N2O emissions from the urea treatment without DCD reached 0.215 kg x hm(-2) for Chinese cabbage, and it reduced to 0.109 kg x hm(-2), equivalent to a 49.3% reduction. The total N2O emissions for pepper were much higher compared with those for Chinese cabbage. The total N2O emitted from the urea treatment was 2.32 kg x hm(-2) (without DCD) and it was reduced to 1.14 kg x hm(-2) with DCD application, representing a 50.9% reduction. In the control treatments where no urea was applied, the daily N2O flux was very low and it never exceeded 9 microg x (m2 x h) (-1) for Chinese cabbage and 22 microg x (m2 x h) (-1) for pepper, respectively, but DCD also reduced N2O emissions (33.5% for Chinese cabbage and 33.4% for pepper). In addition, the urea-N emission factor (EF) was 0.15%, 0.99% for Chinese cabbage and pepper without DCD, respectively, and it was reduced to 0.07%, 0.52% when DCD was applied. These results demonstrated the potential of using nitrification inhibitors (DCD) to mitigate N2O emissions in vegetable system.

Assuming that the random matrix X has a singular or non-singular matrix variate elliptically contoured distribution, the density function of the Moore–Penrose inverse Z = ( X ′ X ) + is given with respect to the Hausdorff measure. The result is applied to Bayesian inference for a general multivariate linear regression model with matrix variate elliptically distributed errors. Some results concerning the posterior joint and marginal distributions of the parameters are obtained.