High expression of erythropoietin-producing hepatoma cell line-B2 (EphB2) predicts the efficiency of the Qingyihuaji formula treatment in pancreatic cancer CFPAC‑1 cells through the EphrinB1‑EphB2 pathway.

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Anti-inflammatory effects of naringin in chronic pulmonary neutrophilic inflammation in cigarette smoke-exposed rats

Naringin, a well-known flavanone glycoside of grapefruit and citrus fruits, was found to be as an effective anti-inflammatory compound in our previous lipopolysaccharide-induced acute lung injury mouse model via blockading activity of nuclear factor κB. The current study sought to explore the anti-inflammatory effects of naringin on chronic pulmonary neutrophilic inflammation in cigarette smoke (CS)-induced rats. Seventy Sprague-Dawley rats were randomly divided into seven groups to study the effects of CS with or without various concentrations of naringin or saline for 8 weeks. The results revealed that naringin supplementation at 20, 40, and 80mg/kg significantly increased body weight of CS-induced rats as compared to that in the CS group. Moreover, naringin of 20, 40, and 80mg/kg prevented CS-induced infiltration of neutrophils and activation of myeloperoxidase and matrix metalloproteinase-9, in parallel with suppression of the release of cytokines, such as tumor necrosis factor-α and interleukin-8 (IL-8). IL-10 in bronchoalveolar lavage fluid was significantly suppressed after CS exposure, but dose dependently elevated by naringin. The results from hematoxylin and eosin staining revealed that naringin dose dependently reduced CS-induced infiltration of inflammatory cells, thickening of the bronchial wall, and expansion of average alveolar airspace. In conclusion, our data suggest that naringin is an effective anti-inflammatory compound for attenuating chronic pulmonary neutrophilic inflammation in CS-induced rats. © Copyright 2012, Mary Ann Liebert, Inc. and Korean Society of Food Science and Nutrition 2012.published_or_final_versio

B-lymphopoiesis is stopped by mobilizing doses of G-CSF and is rescued by overexpression of the anti-apoptotic protein Bcl2

Osteoblasts are necessary to B lymphopoiesis and mobilizing doses of G-CSF or cyclophosphamide inhibit osteoblasts, whereas AMD3100/Plerixafor does not. However, the effect of these mobilizing agents on B lymphopoiesis has not been reported. Mice (wild-type, knocked-out for TNF-α and TRAIL, or over-expressing Bcl-2) were mobilized with G-CSF, cyclophosphamide, or AMD3100. Bone marrow, blood, spleen and lymph node content in B cells was measured. G-CSF stopped medullar B lymphopoiesis with concomitant loss of B-cell colony-forming units, pre-pro-B, pro-B, pre-B and mature B cells and increased B-cell apoptosis by an indirect mechanism. Overexpression of the anti-apoptotic protein Bcl2 in transgenic mice rescued B-cell colony forming units and pre-pro-B cells in the marrow, and prevented loss of all B cells in marrow, blood and spleen. Blockade of endogenous soluble TNF-α with Etanercept, or combined deletion of the TNF-α and TRAIL genes did not prevent B lymphopoiesis arrest in response to G-CSF. Unlike G-CSF, treatments with cyclophosphamide or AMD3100 did not suppress B lymphopoiesis but caused instead robust B-cell mobilization. G-CSF, cyclophosphamide and AMD3100 have distinct effects on B lymphopoiesis and B-cell mobilization with: 1) G-CSF inhibiting medullar B lymphopoiesis without mobilizing B cells in a mechanism distinct from the TNF-α-mediated loss of B lymphopoiesis observed during inflammation or viral infections; 2) CYP mobilizing B cells but blocking their maturation; and 3) AMD3100 mobilizing B cells without affecting B lymphopoiesis. These results suggest that blood mobilized with these three agents may have distinct immune properties. © 2013 Ferrata Storti Foundation

Intracellular Calcium Disturbances Induced by Arsenic and Its Methylated Derivatives in Relation to Genomic Damage and Apoptosis Induction

Arsenic and its methylated derivatives are contaminants of air, water, and food and are known as toxicants and carcinogens. Arsenic compounds are also being used as cancer chemotherapeutic agents. In humans, inorganic arsenic is metabolically methylated to mono-, di-, and trimethylated forms. Recent findings suggest that the methylation reactions represent a toxification rather than a detoxification pathway. In recent years, the correlation between arsenic exposure, cytotoxicity and genotoxicity, mutagenicity, and tumor promotion has been established, as well as the association of arsenic exposure with perturbation of physiologic processes, generation of reactive oxygen species, DNA damage, and apoptosis induction. Trivalent forms of arsenic have been found to induce apoptosis in several cellular systems with involvement of membrane-bound cell death receptors, activation of caspases, release of calcium stores, and changes of the intracellular glutathione level. It is well known that calcium ion deregulation plays a critical role in apoptotic cell death. A calcium increase in the nuclei might lead to toxic effects in the cell. In this review, we highlight the relationship between induced disturbances of calcium homeostasis, genomic damage, and apoptotic cell death caused by arsenic and its organic derivatives

Towards Subject and Diagnostic Identifiability in the Alzheimer’s Disease Spectrum Based on Functional Connectomes

Alzheimer’s disease (AD) is the only major cause of mortality in the world without an effective disease modifying treatment. Evidence supporting the so called “disconnection hypothesis” suggests that functional connectivity biomarkers may have clinical potential for early detection of AD. However, known issues with low test-retest reliability and signal to noise in functional connectivity may prevent accuracy and subsequent predictive capacity. We validate the utility of a novel principal component based diagnostic identifiability framework to increase separation in functional connectivity across the Alzheimer’s spectrum by identifying and reconstructing FC using only AD sensitive components or connectivity modes. We show that this framework (1) increases test-retest correspondence and (2) allows for better separation, in functional connectivity, of diagnostic groups both at the whole brain and individual resting state network level. Finally, we evaluate a posteriori the association between connectivity mode weights with longitudinal neurocognitive outcomes

Cytosine-to-Uracil Deamination by SssI DNA Methyltransferase

The prokaryotic DNA(cytosine-5)methyltransferase M.SssI shares the specificity of eukaryotic DNA methyltransferases (CG) and is an important model and experimental tool in the study of eukaryotic DNA methylation. Previously, M.SssI was shown to be able to catalyze deamination of the target cytosine to uracil if the methyl donor S-adenosyl-methionine (SAM) was missing from the reaction. To test whether this side-activity of the enzyme can be used to distinguish between unmethylated and C5-methylated cytosines in CG dinucleotides, we re-investigated, using a sensitive genetic reversion assay, the cytosine deaminase activity of M.SssI. Confirming previous results we showed that M.SssI can deaminate cytosine to uracil in a slow reaction in the absence of SAM and that the rate of this reaction can be increased by the SAM analogue 5’-amino-5’-deoxyadenosine. We could not detect M.SssI-catalyzed deamination of C5-methylcytosine (m5C). We found conditions where the rate of M.SssI mediated C-to-U deamination was at least 100-fold higher than the rate of m5C-to-T conversion. Although this difference in reactivities suggests that the enzyme could be used to identify C5-methylated cytosines in the epigenetically important CG dinucleotides, the rate of M.SssI mediated cytosine deamination is too low to become an enzymatic alternative to the bisulfite reaction. Amino acid replacements in the presumed SAM binding pocket of M.SssI (F17S and G19D) resulted in greatly reduced methyltransferase activity. The G19D variant showed cytosine deaminase activity in E. coli, at physiological SAM concentrations. Interestingly, the C-to-U deaminase activity was also detectable in an E. coli ung+ host proficient in uracil excision repair

Effects of Stellar Feedback on Stellar and Gas Kinematics of Star-forming Galaxies at 0.6 < z < 1.0

Recent zoom-in cosmological simulations have shown that stellar feedback can flatten the inner density profile of the dark matter halo in low-mass galaxies. A correlation between the stellar/gas velocity dispersion (σ star, σ gas) and the specific star formation rate (sSFR) is predicted as an observational test of the role of stellar feedback in re-shaping the dark matter density profile. In this work we test the validity of this prediction by studying a sample of star-forming galaxies at 0.6 < z < 1.0 from the LEGA-C survey, which provides high signal-to-noise measurements of stellar and gas kinematics. We find that a weak but significant correlation between σ star (and σ gas) and sSFR indeed exists for galaxies in the lowest mass bin (M ∗ ∼ 1010 M o˙). This correlation, albeit with a ∼35% scatter, holds for different tracers of star formation, and becomes stronger with redshift. This result generally agrees with the picture that at higher redshifts star formation rate was generally higher, and galaxies at M ∗ ≲ 1010 M o˙ have not yet settled into a disk. As a consequence, they have shallower gravitational potentials more easily perturbed by stellar feedback. The observed correlation between σ star (and σ gas) and sSFR supports the scenario predicted by cosmological simulations, in which feedback-driven outflows cause fluctuations in the gravitation potential that flatten the density profiles of low-mass galaxies

Access to recreational physical activities by car and bus : an assessment of socio-spatial inequalities in mainland Scotland

Obesity and other chronic conditions linked with low levels of physical activity (PA) are associated with deprivation. One reason for this could be that it is more difficult for low-income groups to access recreational PA facilities such as swimming pools and sports centres than high-income groups. In this paper, we explore the distribution of access to PA facilities by car and bus across mainland Scotland by income deprivation at datazone level. GIS car and bus networks were created to determine the number of PA facilities accessible within travel times of 10, 20 and 30 minutes. Multilevel negative binomial regression models were then used to investigate the distribution of the number of accessible facilities, adjusting for datazone population size and local authority. Access to PA facilities by car was significantly (p<0.01) higher for the most affluent quintile of area-based income deprivation than for most other quintiles in small towns and all other quintiles in rural areas. Accessibility by bus was significantly lower for the most affluent quintile than for other quintiles in urban areas and small towns, but not in rural areas. Overall, we found that the most disadvantaged groups were those without access to a car and living in the most affluent areas or in rural areas

MemBrain: Improving the Accuracy of Predicting Transmembrane Helices

Prediction of transmembrane helices (TMH) in α helical membrane proteins provides valuable information about the protein topology when the high resolution structures are not available. Many predictors have been developed based on either amino acid hydrophobicity scale or pure statistical approaches. While these predictors perform reasonably well in identifying the number of TMHs in a protein, they are generally inaccurate in predicting the ends of TMHs, or TMHs of unusual length. To improve the accuracy of TMH detection, we developed a machine-learning based predictor, MemBrain, which integrates a number of modern bioinformatics approaches including sequence representation by multiple sequence alignment matrix, the optimized evidence-theoretic K-nearest neighbor prediction algorithm, fusion of multiple prediction window sizes, and classification by dynamic threshold. MemBrain demonstrates an overall improvement of about 20% in prediction accuracy, particularly, in predicting the ends of TMHs and TMHs that are shorter than 15 residues. It also has the capability to detect N-terminal signal peptides. The MemBrain predictor is a useful sequence-based analysis tool for functional and structural characterization of helical membrane proteins; it is freely available at http://chou.med.harvard.edu/bioinf/MemBrain/