Contrasting Effects of the Cytotoxic Anticancer Drug Gemcitabine and the EGFR Tyrosine Kinase Inhibitor Gefitinib on NK Cell-Mediated Cytotoxicity via Regulation of NKG2D Ligand in Non-Small-Cell Lung Cancer Cells

IntroductionSeveral cytotoxic anticancer drugs inhibit DNA replication and/or mitosis, while EGFR tyrosine kinase inhibitors inactivate EGFR signalling in cancer cell. Both types of anticancer drugs improve the overall survival of the patients with non-small-cell lung cancer (NSCLC), although tumors often become refractory to this treatment. Despite several mechanisms by which the tumors become resistant having been described the effect of these compounds on anti-tumor immunity remains largely unknown.MethodsThis study examines the effect of the cytotoxic drug Gemcitabine and the EGFR tyrosine kinase inhibitor Gefitinib on the expression of NK group 2 member D (NKG2D) ligands as well as the sensitivity of NSCLC cells to the NK-mediated lysis.ResultsWe demonstrate that Gemcitabine treatment leads to an enhanced expression, while Gefitinib downregulated the expression of molecules that act as key ligands for the activating receptor NKG2D and promote NK cell-mediated recognition and cytolysis. Gemcitabine activated ATM and ATM- and Rad-3-related protein kinase (ATR) pathways. The Gemcitabine-induced phosphorylation of ATM as well as the upregulation of the NKG2D ligand expression could be blocked by an ATM-ATR inhibitor. In contrast, Gefitinib attenuated NKG2D ligand expression. Silencing EGFR using siRNA or addition of the PI3K inhibitor resulted in downregulation of NKG2D ligands. The observations suggest that the EGFR/PI3K pathway also regulates the expression of NKG2D ligands. Additionally, we showed that both ATM-ATR and EGFR regulate MICA/B via miR20a.ConclusionIn keeping with the effect on NKG2D expression, Gemcitabine enhanced NK cell-mediated cytotoxicity while Gefitinib attenuated NK cell killing in NSCLC cells.     

The Volume Ratio of Ground Glass Opacity in Early Lung CT Predicts Mortality in Acute Paraquat Poisoning

Background

Pulmonary injury is the main cause of death in acute paraquat (PQ) poisoning. However, whether quantitative lung computed tomography (CT) can be useful in predicting the outcome of PQ poisoning remains unknown. We aimed to identify early findings of quantitative lung CT as predictors of outcome in acute PQ poisoning.

Methods

Lung CT scanning (64-slide) and quantitative CT lesions were prospectively measured for patients after PQ intoxication within 5 days. The study outcome was mortality during 90 days follow-up. Survival curves were derived by the Kaplan-Meier method, and mortality risk factors were analyzed by the forward stepwise Cox regression analysis.

Results

Of 97 patients, 41 (42.3%) died. Among the eight different types of lung CT findings which appeared in the first 5-day of PQ intoxication, four ones discriminated between survivors and non-survivors including ground glass opacity (GGO), consolidation, pneumomediastinum and “no obvious lesion”. With a cutoff value of 10.8%, sensitivity of 85.4% and specificity of 89.3%, GGO volume ratio is better than adopted outcome indicators in predicting mortality, such as estimated amount of PQ ingestion, plasma or urine PQ concentration, acute physiology and chronic health evaluation (APACHE) II and sequential organ failure assessment (SOFA) scores. GGO volume ratios above 10.8% were associated with increased mortality (hazard ratio, 5.82; 95% confidence interval, 4.77-7.09; P < 0.001).

Conclusions

The volume ratio of GGO exceeding 10.8% is a novel, reliable and independent predictors of outcome in acute PQ poisoning.     

Adaptive Tensor-Based Principal Component Analysis for Low-Dose CT Image Denoising

Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods.     

A new rhodamine‐based fluorescent chemodosimeter for mercuric ions in water media

A new rhodamine–ethylenediamine–nitrothiourea conjugate (RT) was synthesized and its sensing property as a fluorescent chemodosimeter toward metal ions was explored in water media. Analytical results from absorption and fluorescence spectra revealed that the addition of Hg²⁺ ions to the aqueous solution of the chemodosimeter RT caused a distinct fluorescence OFF–ON response with a remarkable visual color change from colorless to pink; however, no clear spectral and color changes were observed from other metal ions including: Zn²⁺, Cu²⁺, Cd²⁺, Pb²⁺, Ag⁺, Fe²⁺, Cr³⁺, Co³⁺, Ni²⁺, Ca²⁺, Mg²⁺, K⁺ and Na⁺. The sensing results and the molecular structure suggested that a Hg²⁺‐induced a desulfurization reaction and cyclic guanylation of the thiourea moiety followed by ring‐opening of the rhodamine spirolactam in RT are responsible for a distinct fluorescence turn‐on signal, indicating that RT is a remarkably sensitive and selective chemodosimeter for Hg²⁺ ions in aqueous solution. Hg²⁺ within a concentration range from 0.1 to 25 μM can be determined using RT as a chemodosimeter and a detection limit of 0.04 μM is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Genome-Wide Assessment of Outer Membrane Vesicle Production in Escherichia coli

The production of outer membrane vesicles by Gram-negative bacteria has been well documented; however, the mechanism behind the biogenesis of these vesicles remains unclear. Here a high-throughput experimental method and systems-scale analysis was conducted to determine vesiculation values for the whole genome knockout library of Escherichia coli mutant strains (Keio collection). The resultant dataset quantitatively recapitulates previously observed phenotypes and implicates nearly 150 new genes in the process of vesiculation. Gene functional and biochemical pathway analyses suggest that mutations that truncate outer membrane structures such as lipopolysaccharide and enterobacterial common antigen lead to hypervesiculation, whereas mutants in oxidative stress response pathways result in lower levels. This study expands and refines the current knowledge regarding the cellular pathways required for outer membrane vesiculation in E. coli.     

Use of random forest in FTIR analysis of LDL cholesterol and tri‐glycerides for hyperlipidemia

A quantitative determination method for the diagnosis of hyperlipidemia was developed using Fourier transform infrared (FTIR) spectroscopy. Random forest (RF) was demonstrated as a potential multivariate algorithm for the FTIR analysis of low‐density lipoprotein cholesterol (LDL‐C) and tri‐glycerides (TG) in human serum samples. The informative wavebands for LDL‐C and TG were selected based on the Gini importance. The selected wavebands were mainly within the fingerprint region. The RF modeling results were better than those derived using PLS in validation process, because the chance for over‐fitting was possibly eliminated in RF algorithm. ARF also demonstrated favorable results in the test process. The prospective model exhibited a higher than 90% true prediction in negative/positive properties for male and female samples. These clinical statistical results indicated the optimization of RF algorithm performed accurately in the FTIR determination of LDL‐C and TG. RF is evaluated as a promising tool for diagnosing and controlling hyperlipidemia in populations. The parameter optimization methodology is useful in the improving model accuracy using FTIR spectroscopic technology. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1693–1702, 2015