The Antarctic Muon and Neutrino Detector Array (AMANDA) began collecting data with ten strings in 1997. Results from the first year of operation are presented. Neutrinos coming through the Earth from the Northern Hemisphere are identified by secondary muons moving upward through the array. Cosmic rays in the atmosphere generate a background of downward moving muons, which are about 10^6 times more abundant than the upward moving muons. Over 130 days of exposure, we observed a total of about 300 neutrino events. In the same period, a background of 1.05*10^9 cosmic ray muon events was recorded. The observed neutrino flux is consistent with atmospheric neutrino predictions. Monte Carlo simulations indicate that 90% of these events lie in the energy range 66 GeV to 3.4 TeV. The observation of atmospheric neutrinos consistent with expectations establishes AMANDA-B10 as a working neutrino telescope.

The mucus layer coating the gastrointestinal tract is the front line of innate host defense, largely because of the secretory products of intestinal goblet cells. Goblet cells synthesize secretory mucin glycoproteins (MUC2) and bioactive molecules such as epithelial membrane-bound mucins (MUC1, MUC3, MUC17), trefoil factor peptides (TFF), resistin-like molecule β (RELMβ), and Fc-γ binding protein (Fcgbp). The MUC2 mucin protein forms trimers by disulfide bonding in cysteine-rich amino terminal von Willebrand factor (vWF) domains, coupled with crosslinking provided by TFF and Fcgbp proteins with MUC2 vWF domains, resulting in a highly viscous extracellular layer. Colonization by commensal intestinal microbiota is limited to an outer “loose” mucus layer, and interacts with the diverse oligosaccharides of mucin glycoproteins, whereas an “inner” adherent mucus layer is largely devoid of bacteria. Defective mucus layers resulting from lack of MUC2 mucin, mutated Muc2 mucin vWF domains, or from deletion of core mucin glycosyltransferase enzymes in mice result in increased bacterial adhesion to the surface epithelium, increased intestinal permeability, and enhanced susceptibility to colitis caused by dextran sodium sulfate. Changes in mucin gene expression and mucin glycan structures occur in cancers of the intestine, contributing to diverse biologic properties involved in the development and progression of cancer. Further research is needed on identification and functional significance of various components of mucus layers and the complex interactions among mucus layers, microbiota, epithelial cells, and the underlying innate and adaptive immunity. Further elucidation of the regulatory mechanisms involved in mucin changes in cancer and inflammation may lead to the development of novel therapeutic approaches.

The mucus layer coating the gastrointestinal tract is the front line of innate host defense, largely because of the secretory products of intestinal goblet cells. Goblet cells synthesize secretory mucin glycoproteins (MUC2) and bioactive molecules such as epithelial membrane-bound mucins (MUC1, MUC3, MUC17), trefoil factor peptides (TFF), resistin-like molecule beta (RELMbeta), and Fc-gamma binding protein (Fcgbp). The MUC2 mucin protein forms trimers by disulfide bonding in cysteine-rich amino terminal von Willebrand factor (vWF) domains, coupled with crosslinking provided by TFF and Fcgbp proteins with MUC2 vWF domains, resulting in a highly viscous extracellular layer. Colonization by commensal intestinal microbiota is limited to an outer "loose" mucus layer, and interacts with the diverse oligosaccharides of mucin glycoproteins, whereas an "inner" adherent mucus layer is largely devoid of bacteria. Defective mucus layers resulting from lack of MUC2 mucin, mutated Muc2 mucin vWF domains, or from deletion of core mucin glycosyltransferase enzymes in mice result in increased bacterial adhesion to the surface epithelium, increased intestinal permeability, and enhanced susceptibility to colitis caused by dextran sodium sulfate. Changes in mucin gene expression and mucin glycan structures occur in cancers of the intestine, contributing to diverse biologic properties involved in the development and progression of cancer. Further research is needed on identification and functional significance of various components of mucus layers and the complex interactions among mucus layers, microbiota, epithelial cells, and the underlying innate and adaptive immunity. Further elucidation of the regulatory mechanisms involved in mucin changes in cancer and inflammation may lead to the development of novel therapeutic approaches.

HIV status disclosure is a key support strategy to start and maintain HIV care and treatment and to reduce HIV transmission. We explored the patterns and correlates of disclosure and described the effectiveness of nurse-facilitated disclosure among HIV-infected mothers of infants in coastal Tanzania. We enrolled 400 HIV positive women in an observational longitudinal study in 2011, interviewed them about maternal sociodemographic and economic characteristics, maternal and child health and history of HIV disclosure experiences and offered nurse-facilitated HIV disclosure at enrolment or at follow-up 1 month later. Mothers frequently disclosed their status to husbands and/or female relatives and experienced predominantly positive reactions. Economically vulnerable women disclosed more often to elderly female relatives, indicating that Infant and Young Child Feeding counseling given to HIV positive women should garner the support of elderly female relatives for implementing appropriate feeding practices. Nurse-facilitated disclosure was feasible in this low resource setting and was used by patients to help them with both first-time disclosure and disclosure to new persons.

We examined the characteristics associated with hepatitis C virus (HCV) antibody (anti-HCV) prevalence and HCV clearance between injection drug using (IDU) and non-IDU men who have sex with men (MSM). Stored serum and plasma samples were tested for anti-HCV and HCV RNA to determine the HCV status of 6925 MSM at enrolment into the Multicentre AIDS Cohort Study (MACS). Prevalence and clearance ratios were calculated to determine the characteristics associated with HCV prevalence and clearance. Multivariable analyses were performed using Poisson regression methods with robust variance estimation. Anti-HCV prevalence was significantly higher among IDU than among non-IDU MSM (42.9% vs 4.0%), while clearance was significantly lower among IDU MSM (11.5% vs 34.5% among non-IDU MSM). HIV infection, Black race, and older age were independently associated with higher prevalence in both groups, while smoking, transfusion history, and syphilis were significantly associated with prevalence only among non-IDU MSM. The rs12979860-C/C genotype was the only characteristic independently associated with HCV clearance in both groups, but the effects of both rs12979860-C/C genotype [clearance ratio (CR) = 4.16 IDUs vs 1.71 non-IDUs; P = 0.03] and HBsAg positivity (CR = 5.06 IDUs vs 1.62 non-IDUs; P = 0.03) were significantly larger among IDU MSM. HIV infection was independently associated with lower HCV clearance only among non-IDU MSM (CR = 0.59, 95% CI = 0.40-0.87). IDU MSM have higher anti-HCV prevalence and lower HCV clearance than non-IDU MSM. Differences in the factors associated with HCV clearance suggest that the mechanisms driving the response to HCV may differ according to the mode of acquisition.

PURPOSE: Quantitative Imaging and CAD tasks performed with CT (e.g. lung nodule detection, assessment of tumor size, etc.) may be sensitive to image acquisition and reconstruction parameters such as dose level, image thickness and reconstruction method (FBP, iterative, etc.). The purpose of this work was to develop a research pipeline for generating CT image series that represent a wide variety of acquisition and reconstruction conditions under which CAD and Quantitative Imaging performance would be evaluated. METHODS: With IRB approval, we have collected the raw CT data from hundreds of patients. These raw sinogram files serve as the input to the research pipeline. To simulate a wide range of dose levels, we developed software which adds noise to the sinogram. Multiple reduced-dose sinograms can be generated for a single patient, and those reduced-dose sinograms are then fed either to the scanner's reconstruction engine or to our in-house reconstruction engine; each has conventional filtered back projection (FBP) and iterative reconstruction methods. After generating image series across a range of dose levels and reconstruction methods, we can evaluate the performance of various quantitative imaging or CAD tools in tasks such as automated and semi-automated lesion segmentation, assessment of lesion size, and measurement of density or texture. RESULTS: We have successfully applied this pipeline across a range of clinical CT applications, including: (1) chest oncology, where the pipeline was used to quantify the effects of dose and reconstruction method on nodule volumetry, and (2) lung cancer screening, where the pipeline is being used to measure the robustness of an automated CAD algorithm with respect to dose. CONCLUSION: The acquisition/reconstruction pipeline shows promise for investigating and quantifying the effects of dose and reconstruction method on various clinical CT applications. NCI grant U01 CA181156 (Quantitative Imaging Network); Tobacco Related Disease Research Project grant 22RT-0131.

PURPOSE: Texture features have been investigated as a biomarker of response and malignancy. Because these features reflect local differences in density, they may be influenced by acquisition and reconstruction parameters. The purpose of this study was to investigate the effects of radiation dose level and reconstruction method on features derived from lung lesions. METHODS: With IRB approval, 33 lung tumor cases were identified from clinically indicated thoracic CT scans in which the raw projection (sinogram) data were available. Based on a previously-published technique, noise was added to the raw data to simulate reduced-dose versions of each case at 25%, 10% and 3% of the original dose. Original and simulated reduced dose projection data were reconstructed with conventional and two iterative-reconstruction settings, yielding 12 combinations of dose/recon conditions. One lesion from each case was contoured. At the reference condition (full dose, conventional recon), 17 lesions were randomly selected for repeat contouring (repeatability). For each lesion at each dose/recon condition, 151 texture measures were calculated. A paired differences approach was employed to compare feature variation from repeat contours at the reference condition to the variation observed in other dose/recon conditions (reproducibility). The ratio of standard deviation of the reproducibility to repeatability was used as the variation measure for each feature. RESULTS: The mean variation (standard deviation) across dose levels and kernel was significantly different with a ratio of 2.24 (±5.85) across texture features (p=0.01). The mean variation (standard deviation) across dose levels with conventional recon was also significantly different with 2.30 (7.11) (p=0.025). The mean variation across reconstruction settings of original dose has a trend in showing difference with 1.35 (2.60) among all features (p=0.09). CONCLUSION: Texture features varied considerably with variations in dose and reconstruction condition. Care should be taken to standardize these conditions when using texture as a quantitative feature. This effort supported in part by a grant from the National Cancer Institute's Quantitative Imaging Network (QIN): U01 CA181156; The UCLA Department of Radiology has a Master Research Agreement with Siemens Healthcare; Dr. McNitt-Gray has previously received research support from Siemens Healthcare.

Purpose

To investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules.

Methods

This study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions. In the second component, raw projection (sinogram) data were obtained for 33 lung nodules from patients scanned as a part of their clinical practice, where low dose acquisitions were simulated by adding noise to sinograms acquired at clinical dose levels (a total of four dose levels) and reconstructed using one FBP kernel and two IR kernels for a total of 12 conditions. For the water phantom, spherical regions of interest (ROIs) were created at multiple locations within the water phantom on one reference image obtained at a reference condition. For the lung nodule cases, the ROI of each nodule was contoured semiautomatically (with manual editing) from images obtained at a reference condition. All ROIs were applied to their corresponding images reconstructed at different conditions. For 17 of the nodule cases, repeat contours were performed to assess repeatability. Histogram (eight features) and gray level co-occurrence matrix (GLCM) based texture features (34 features) were computed for all ROIs. For the lung nodule cases, the reference condition was selected to be 100% of clinical dose with FBP reconstruction using the B45f kernel; feature values calculated from other conditions were compared to this reference condition. A measure was introduced, which the authors refer to as Q, to assess the stability of features across different conditions, which is defined as the ratio of reproducibility (across conditions) to repeatability (across repeat contours) of each feature.

Results

The water phantom results demonstrated substantial variability among feature values calculated across conditions, with the exception of histogram mean. Features calculated from lung nodules demonstrated similar results with histogram mean as the most robust feature (Q ≤ 1), having a mean and standard deviation Q of 0.37 and 0.22, respectively. Surprisingly, histogram standard deviation and variance features were also quite robust. Some GLCM features were also quite robust across conditions, namely, diff. variance, sum variance, sum average, variance, and mean. Except for histogram mean, all features have a Q of larger than one in at least one of the 3% dose level conditions.

Conclusions

As expected, the histogram mean is the most robust feature in their study. The effects of acquisition and reconstruction conditions on GLCM features vary widely, though trending toward features involving summation of product between intensities and probabilities being more robust, barring a few exceptions. Overall, care should be taken into account for variation in density and texture features if a variety of dose and reconstruction conditions are used for the quantification of lung nodules in CT, otherwise changes in quantification results may be more reflective of changes due to acquisition and reconstruction conditions than in the nodule itself.