Publications

Mucus hypersecretion is a prominent manifestation in patients with chronic inflammatory airway diseases. MUC5AC mucin is a major component of airway mucus, and its expression is modulated by a TNF-alpha-converting enzyme (TACE)-EGF receptor pathway that can be activated by reactive oxygen species (ROS). Dual oxidase 1 (Duox1), a homologue of glycoprotein p91(phox), is expressed in airway epithelium and generates ROS. We hypothesize that Duox1 activates TACE, cleaving pro-TGF-alpha into soluble TGF-alpha, resulting in mucin expression. To examine this hypothesis, we stimulated both normal human bronchial epithelial cells and NCI-H292 airway epithelial cells with phorbol 12-myristate 13-acetate and with human neutrophil elastase. These stimuli induced TACE activation, TGF-alpha release, and mucin expression, effects that were inhibited by ROS scavengers, implicating ROS in TACE activation. Inhibition of epithelial NADPH oxidase or knockdown of Duox1 expression with small interfering RNA prevented ROS generation, TGF-alpha release, and mucin expression by these stimuli, implicating Duox1 in TACE activation and mucin expression. Furthermore, the PKCdelta/PKC inhibitor rottlerin prevented the effects induced by phorbol 12-myristate 13-acetate and human neutrophil elastase, suggesting that PKCdelta and PKC are involved in Duox1 activation. From these results, we conclude that Duox1 plays a critical role in mucin expression by airway epithelial cells through PKCdelta/PKC-Duox1-ROS-TACE-pro-ligand-EGF receptor cascade.

BACKGROUND

Recent trials have demonstrated better outcomes with intensive than with moderate statin treatment. Intensive treatment produced greater reductions in both low-density lipoprotein (LDL) cholesterol and C-reactive protein (CRP), suggesting a relationship between these two biomarkers and disease progression.

METHODS

We performed intravascular ultrasonography in 502 patients with angiographically documented coronary disease. Patients were randomly assigned to receive moderate treatment (40 mg of pravastatin orally per day) or intensive treatment (80 mg of atorvastatin orally per day). Ultrasonography was repeated after 18 months to measure the progression of atherosclerosis. Lipoprotein and CRP levels were measured at baseline and follow-up.

RESULTS

In the group as a whole, the mean LDL cholesterol level was reduced from 150.2 mg per deciliter (3.88 mmol per liter) at baseline to 94.5 mg per deciliter (2.44 mmol per liter) at 18 months (P<0.001), and the geometric mean CRP level decreased from 2.9 to 2.3 mg per liter (P<0.001). The correlation between the reduction in LDL cholesterol levels and that in CRP levels was weak but significant in the group as a whole (r=0.13, P=0.005), but not in either treatment group alone. In univariate analyses, the percent change in the levels of LDL cholesterol, CRP, apolipoprotein B-100, and non-high-density lipoprotein cholesterol were related to the rate of progression of atherosclerosis. After adjustment for the reduction in these lipid levels, the decrease in CRP levels was independently and significantly correlated with the rate of progression. Patients with reductions in both LDL cholesterol and CRP that were greater than the median had significantly slower rates of progression than patients with reductions in both biomarkers that were less than the median (P=0.001).

CONCLUSIONS

For patients with coronary artery disease, the reduced rate of progression of atherosclerosis associated with intensive statin treatment, as compared with moderate statin treatment, is significantly related to greater reductions in the levels of both atherogenic lipoproteins and CRP.

High-density lipoprotein (HDL) is part of innate immunity, protecting against infection and inflammation. Using a proteomic approach, we identified an amino acid sequence in a hamster HDL protein that showed homology to rat and mouse parotid secretory protein (PSP), a salivary protein secreted from the parotid glands. We cloned the cDNA encoding a putative hamster homolog of rat and mouse PSP. Searches for conserved domains of the protein showed that the COOH terminus of hamster PSP contains a region homologous to the NH2 termini of a family of HDL-associated proteins, including LPS-binding protein, cholesteryl ester transfer protein, and phospholipid transfer protein. In mice, PSP was also associated with HDL but was not detected in very-low-density lipoprotein, low-density lipoprotein, or lipoprotein-deficient sera. In addition to salivary glands, we found that PSP mRNA was expressed in lung, testis, and ovary. The level of PSP in HDL was increased after endotoxin injection in hamsters, but not in mice. Recombinant PSP inhibits growth of Candida albicans in culture. In summary, our results showed that PSP is a novel anticandidal protein associated with HDL.

The implementation of tissue inhomogeneity correction in image-based treatment planning will improve the accuracy of radiation dose calculations for patients undergoing external-beam radiotherapy. Before the tissue inhomogeneity correction can be applied, the relationship between the computed tomography (CT) value and density must be established. This tissue characterization relationship allows the conversion of CT value in each voxel of the CT images into density for use in the dose calculations. This paper describes the proper procedure of establishing the CT value to density conversion relationship. A tissue characterization phantom with 17 inserts made of different materials was scanned using a GE Lightspeed Plus CT scanner (120 kVp). These images were then downloaded into the Eclipse and Pinnacle treatment planning systems. At the treatment planning workstation, the axial images were retrieved to determine the CT value of the inserts. A region of interest was drawn on the central portion of the insert and the mean CT value and its standard deviation were determined. The mean CT value was plotted against the density of the tissue inserts and fitted with bilinear equations. A new set of CT values vs. densities was generated from the bilinear equations and then entered into the treatment planning systems. The need to obtain CT values through the treatment planning system is very clear. The 2 treatment planning systems use different CT value ranges, one from -1024 to 3071 and the other from 0 to 4096. If the range is correct, it would result in inappropriate use of the conversion curve. In addition to the difference in the range of CT values, one treatment planning system uses physical density, while the other uses relative electron density.