The Intestinal Microbiota Contributes to the Ability of Helminths to Modulate Allergic Inflammation.

Intestinal helminths are potent regulators of their host's immune system and can ameliorate inflammatory diseases such as allergic asthma. In the present study we have assessed whether this anti-inflammatory activity was purely intrinsic to helminths, or whether it also involved crosstalk with the local microbiota. We report that chronic infection with the murine helminth Heligmosomoides polygyrus bakeri (Hpb) altered the intestinal habitat, allowing increased short chain fatty acid (SCFA) production. Transfer of the Hpb-modified microbiota alone was sufficient to mediate protection against allergic asthma. The helminth-induced anti-inflammatory cytokine secretion and regulatory T cell suppressor activity that mediated the protection required the G protein-coupled receptor (GPR)-41. A similar alteration in the metabolic potential of intestinal bacterial communities was observed with diverse parasitic and host species, suggesting that this represents an evolutionary conserved mechanism of host-microbe-helminth interactions.

MASCG: Multi-Atlas Segmentation Constrained Graph method for accurate segmentation of hip CT images

This paper addresses the issue of fully automatic segmentation of a hip CT image with the goal to preserve the joint structure for clinical applications in hip disease diagnosis and treatment. For this purpose, we propose a Multi-Atlas Segmentation Constrained Graph (MASCG) method. The MASCG method uses multi-atlas based mesh fusion results to initialize a bone sheetness based multi-label graph cut for an accurate hip CT segmentation which has the inherent advantage of automatic separation of the pelvic region from the bilateral proximal femoral regions. We then introduce a graph cut constrained graph search algorithm to further improve the segmentation accuracy around the bilateral hip joint regions. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 15-fold cross validation. When the present approach was compared to manual segmentation, an average surface distance error of 0.30 mm, 0.29 mm, and 0.30 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. A further look at the bilateral hip joint regions demonstrated an average surface distance error of 0.16 mm, 0.21 mm and 0.20 mm for the acetabulum, the left femoral head, and the right femoral head, respectively.

Predicting 5- and 10-year survival in older women with early-stage breast cancer: self-rated health and walking ability.

OBJECTIVES To determine life expectancy for older women with breast cancer. DESIGN Prospective longitudinal study with 10 years of follow-up data. SETTING Hospitals or collaborating tumor registries in four geographic regions (Los Angeles, California; Minnesota; North Carolina; Rhode Island). PARTICIPANTS Women aged 65 and older at time of breast cancer diagnosis with Stage I to IIIA disease with measures of self-rated health (SRH) and walking ability at baseline (N = 615; 17% aged ≥80, 52% Stage I, 58% with ≥2 comorbidities). MEASUREMENTS Baseline SRH, baseline self-reported walking ability, all-cause and breast cancer-specific estimated probability of 5- and 10-year survival. RESULTS At the time of breast cancer diagnosis, 39% of women reported poor SRH, and 28% reported limited ability to walk several blocks. The all-cause survival curves appear to separate after approximately 3 years, and the difference in survival probability between those with low SRH and limited walking ability and those with high SRH and no walking ability limitation was significant (0.708 vs 0.855 at 5 years, P ≤ .001; 0.300 vs 0.648 at 10 years, P < .001). There were no differences between the groups in breast cancer-specific survival at 5 and 10 years (P = .66 at 5 years, P = .16 at 10 years). CONCLUSION The combination of low SRH and limited ability to walk several blocks at diagnosis is an important predictor of worse all-cause survival at 5 and 10 years. These self-report measures easily assessed in clinical practice may be an effective strategy to improve treatment decision-making in older adults with cancer.

Dish Detection and Segmentation for Dietary Assessment on Smartphones

Diet-related chronic diseases severely affect personal and global health. However, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images. We propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods were evaluated on a database of over 1600 manually annotated images. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions.

Ability to Work and Employment Rates in Human Immunodeficiency Virus (HIV)-1-Infected Individuals Receiving Combination Antiretroviral Therapy: The Swiss HIV Cohort Study

Background.  Limited data exist on human immunodeficiency virus (HIV)-infected individuals' ability to work after receiving combination antiretroviral therapy (cART). We aimed to investigate predictors of regaining full ability to work at 1 year after starting cART. Methods.  Antiretroviral-naive HIV-infected individuals <60 years who started cART from January 1998 through December 2012 within the framework of the Swiss HIV Cohort Study were analyzed. Inability to work was defined as a medical judgment of the patient's ability to work as 0%. Results.  Of 5800 subjects, 4382 (75.6%) were fully able to work, 471 (8.1%) able to work part time, and 947 (16.3%) were unable to work at baseline. Of the 947 patients unable to work, 439 (46.3%) were able to work either full time or part time at 1 year of treatment. Predictors of recovering full ability to work were non-white ethnicity (odds ratio [OR], 2.06; 95% confidence interval [CI], 1.20-3.54), higher education (OR, 4.03; 95% CI, 2.47-7.48), and achieving HIV-ribonucleic acid <50 copies/mL (OR, 1.83; 95% CI, 1.20-2.80). Older age (OR, 0.55; 95% CI, .42-.72, per 10 years older) and psychiatric disorders (OR, 0.24; 95% CI, .13-.47) were associated with lower odds of ability to work. Recovering full ability to work at 1 year increased from 24.0% in 1998-2001 to 41.2% in 2009-2012, but the employment rates did not increase. Conclusions.  Regaining full ability to work depends primarily on achieving viral suppression, absence of psychiatric comorbidity, and favorable psychosocial factors. The discrepancy between patients' ability to work and employment rates indicates barriers to reintegration of persons infected with HIV.

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Design, synthesis and cellular and molecular pharmacology of 2$\sp\prime$-bromo-4$\sp\prime$-epidaunorubicin (WP401): A novel non-cross-resistant anthracycline antibiotic with the intrinsic ability to circumvent P -glycoprotein-mediated drug resistance

We designed and synthesized a novel daunorubicin (DNR) analogue that effectively circumvents P-glycoprotein (P-gp)-mediated drug resistance. The fully protected carbohydrate intermediate 1,2-dibromoacosamine was prepared from acosamine and effectively coupled to daunomycinone in high yield. Deprotection under alkaline conditions yielded 2$\sp\prime$-bromo-4$\sp\prime$-epidaunorubicin (WP401). The in vitro cytotoxicity and cellular and molecular pharmacology of WP401 were compared with those of DNR in a panel of wild-type cell lines (KB-3-1, P388S, and HL60S) and their multidrug-resistant (MDR) counterparts (KB-V1, P388/DOX, and HL60/DOX). Fluorescent spectrophotometry, flow cytometry, and confocal laser scanning microscopy were used to measure intracellular accumulation, retention, and subcellular distribution of these agents. All MDR cell lines exhibited reduced DNR uptake that was restored, upon incubation with either verapamil (VER) or cyclosporin A (CSA), to the level found in sensitive cell lines. In contrast, the uptake of WP401 was essentially the same in the absence or presence of VER or CSA in all tested cell lines. The in vitro cytotoxicity of WP401 was similar to that of DNR in the sensitive cell lines but significantly higher in resistant cell lines (resistance index (RI) of 2-6 for WP401 vs 75-85 for DNR). To ascertain whether drug-mediated cytotoxicity and retention were accompanied by DNA strand breaks, DNA single- and double-strand breaks were assessed by alkaline elution. High levels of such breaks were obtained using 0.1-2 $\mu$g/mL of WP401 in both sensitive and resistant cells. In contrast, DNR caused strand breaks only in sensitive cells and not much in resistant cells. We also compared drug-induced DNA fragmentation similar to that induced by DNR. However, in P-gp-positive cells, WP401 induced 2- to 5-fold more DNA fragmentation than DNR. This increased DNA strand breakage by WP401 was correlated with its increased uptake and cytotoxicity in these cell lines. Overall these results indicate that WP401 is more cytotoxic than DNR in MDR cells and that this phenomenon might be related to the reduced basicity of the amino group and increased lipophilicity of WP401. ^

Road environment modeling using robust perspective analysis and recursive Bayesian segmentation

Recently, vision-based advanced driver-assistance systems (ADAS) have received a new increased interest to enhance driving safety. In particular, due to its high performance–cost ratio, mono-camera systems are arising as the main focus of this field of work. In this paper we present a novel on-board road modeling and vehicle detection system, which is a part of the result of the European I-WAY project. The system relies on a robust estimation of the perspective of the scene, which adapts to the dynamics of the vehicle and generates a stabilized rectified image of the road plane. This rectified plane is used by a recursive Bayesian classi- fier, which classifies pixels as belonging to different classes corresponding to the elements of interest of the scenario. This stage works as an intermediate layer that isolates subsequent modules since it absorbs the inherent variability of the scene. The system has been tested on-road, in different scenarios, including varied illumination and adverse weather conditions, and the results have been proved to be remarkable even for such complex scenarios.

Assessment of the effects of ozone exposure and plant competition on the reproductive ability of three therophytic clover species from Iberian pastures

Ozone (O3) phytototoxicity has been reported on a wide range of crops and wild Central European plantspecies, however no information has been provided regarding the sensitivity of plantspecies from dehesa Mediterranean therophytic grasslands in spite of their great plantspecies richness and the high O3 levels that are recorded in this area. A study was carried out in open-top chambers (OTCs) to assess the effects of O3 and competition on the reproductiveability of threecloverspecies: Trifolium cherleri, Trifolium subterraneum and Trifolium striatum. A phytometer approach was followed, therefore plants of these species were grown in mesoscosms composed of monocultures of four plants of each species, of threeplants of each species competing against a Briza maxima individual or of a single plant of each cloverspecies competing with threeB. maximaplants. Three O3 treatments were adopted: charcoal filtered air (CFA), non-filtered air (NFA) and non-filtered air supplemented with 40 nl l−1 of O3 (NFA+). The different mesocosms were exposed to the different O3 treatments for 45 days and then they remained in the open. Ozoneexposure caused reductions in the flower biomass of the threecloverspecies assessed. In the case of T. cherleri and T. subterraneum this effect was found following their exposure to the different O3 treatments during their vegetative period. An attenuation of these effects was found when the plants remained in the open. Ozone-induced detrimental effects on the seed output of T. striatum were also observed. The flower biomass of the cloverplants grown in monocultures was greater than when competing with one or threeB. maxima individuals. An increased flower biomass was found in the CFA monoculture mesocosms of T. cherleri when compared with the remaining mesocosms, once the plants were exposed in the open for 60 days. The implications of these effects on the performance of dehesa acid grasslands and for the definition of O3 critical levels is discussed

Optimal Multiresolution 3D Level-Set Method for Liver Segmentation incorporating Local Curvature Constraints

Advanced liver surgery requires a precise pre-operative planning, where liver segmentation and remnant liver volume are key elements to avoid post-operative liver failure. In that context, level-set algorithms have achieved better results than others, especially with altered liver parenchyma or in cases with previous surgery. In order to improve functional liver parenchyma volume measurements, in this work we propose two strategies to enhance previous level-set algorithms: an optimal multi-resolution strategy with fine details correction and adaptive curvature, as well as an additional semiautomatic step imposing local curvature constraints. Results show more accurate segmentations, especially in elongated structures, detecting internal lesions and avoiding leakages to close structures

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation.