Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

In vitro allergy tests compared to intradermal testing in horses with recurrent airway obstruction

Recurrent airway obstruction (RAO) is a common condition in stabled horses characterised by small airway inflammation, airway neutrophilia and obstruction following exposure of susceptible horses to mouldy hay and straw and is thus regarded as a hypersensitivity reaction to mould spores. However, the role of IgE-mediated reactions in RAO remains unclear. The aim of the study was to investigate with a serological IgE ELISA test (Allercept), an in vitro sulfidoleukotriene (sLT) release assay (CAST) and with intradermal testing (IDT) whether serum IgE and IgE-mediated reactions against various mould, mite and pollen extracts are associated with RAO. IDT reactions were evaluated at different times in order to detect IgE-mediated immediate type reactions (type I hypersensitivity reactions, 0.5-1 h), immune complex-mediated late type reactions (type III reactions, 4-10 h) and cell-mediated delayed type reactions (type IV hypersensitivity reactions 24-48 h). In the serological test, overall the control horses displayed more positive reactions than the RAO-affected horses but the difference was not significant. Comparison of the measured IgE levels showed that the RAO-affected horses had slightly higher IgE levels against Aspergillus fumigatus than controls (35 and 16 AU, respectively, p<0.05), but all values were below the cut off (150 AU) of the test. In the sLT release assay, seven positive reactions were observed in the RAO-affected horses and four in the controls but this difference was not significant. A significantly higher proportion of late type IDT reactions was observed in RAO-affected horses compared to controls (25 of 238 possible reactions versus 12 of 238 possible reactions, respectively, p<0.05). Interestingly, four RAO-affected but none of the control horses reacted with the recombinant mould allergen A. fumigatus 8 (rAsp f 8, p<0.05), but only late phase and delayed type reactions were observed. In all three tests the majority of the positive reactions was observed with the mite extracts (64%, 74% and 88% of all positive reactions, respectively) but none of the tests showed a significant difference between RAO-affected and control animals. Our findings do not support that IgE-mediated reactions are important in the pathogenesis of RAO. Further studies are needed to investigate whether sensitisation to mite allergens is of clinical relevance in the horse and to understand the role of immune reactions against rAsp f 8.

A whole-genome scan for recurrent airway obstruction in Warmblood sport horses indicates two positional candidate regions

Recurrent airway obstruction (RAO), or heaves, is a naturally occurring asthma-like disease that is related to sensitisation and exposure to mouldy hay and has a familial basis with a complex mode of inheritance. A genome-wide scanning approach using two half-sibling families was taken in order to locate the chromosome regions that contribute to the inherited component of this condition in these families. Initially, a panel of 250 microsatellite markers, which were chosen as a well-spaced, polymorphic selection covering the 31 equine autosomes, was used to genotype the two half-sibling families, which comprised in total 239 Warmblood horses. Subsequently, supplementary markers were added for a total of 315 genotyped markers. Each half-sibling family is focused around a severely RAO-affected stallion, and the phenotype of each individual was assessed for RAO and related signs, namely, breathing effort at rest, breathing effort at work, coughing, and nasal discharge, using an owner-based questionnaire. Analysis using a regression method for half-sibling family structures was performed using RAO and each of the composite clinical signs separately; two chromosome regions (on ECA13 and ECA15) showed a genome-wide significant association with RAO at P < 0.05. An additional 11 chromosome regions showed a more modest association. This is the first publication that describes the mapping of genetic loci involved in RAO. Several candidate genes are located in these regions, a number of which are interleukins. These are important signalling molecules that are intricately involved in the control of the immune response and are therefore good positional candidates.

Mixed inheritance of equine recurrent airway obstruction

BACKGROUND: Mode of inheritance of equine recurrent airway obstruction (RAO) is unknown. HYPOTHESIS: Major genes are responsible for RAO. ANIMALS: Direct offspring of 2 RAO-affected Warmblood stallions (n = 197; n = 163) and a representative sample of Swiss Warmbloods (n = 401). METHODS: One environmental and 4 genetic models (general, mixed inheritance, major gene, and polygene) were tested for Horse Owner Assessed Respiratory Signs Index (1-4, unaffected to severely affected) by segregation analyses of the 2 half-sib sire families, both combined and separately, using prevalences estimated in a representative sample. RESULTS: In all data sets the mixed inheritance model was most likely to explain the pattern of inheritance. In all 3 datasets the mixed inheritance model did not differ significantly from the general model (P= .62, P= 1.00, and P= .27) but was always better than the major gene model (P < .01) and the polygene model (P < .01). The frequency of the deleterious allele differed considerably between the 2 sire families (P= .23 and P= .06). In both sire families the displacement was large (t= 17.52 and t= 12.24) and the heritability extremely large (h(2)= 1). CONCLUSIONS AND CLINICAL RELEVANCE: Segregation analyses clearly reveal the presence of a major gene playing a role in RAO. In 1 family, the mode of inheritance was autosomal dominant, whereas in the other family it was autosomal recessive. Although the expression of RAO is influenced by exposure to hay, these findings suggest a strong, complex genetic background for RAO.

Nicoletella semolina gen. nov., sp. nov., a new member of Pasteurellaceae isolated from horses with airway disease

Gram-negative, nonmotile bacteria that are catalase, oxidase, and urease positive are regularly isolated from the airways of horses with clinical signs of respiratory disease. On the basis of the findings by a polyphasic approach, we propose that these strains be classified as Nicoletella semolina gen. nov, sp. nov., a new member of the family Pasteurellaceae. N. semolina reduces nitrate to nitrite but is otherwise biochemically inert; this includes the lack of an ability to ferment glucose and other sugars. Growth is fastidious, and the isolates have a distinctive colony morphology, with the colonies being dry and waxy and looking like a semolina particle that can be moved around on an agar plate without losing their shape. DNA-DNA hybridization data and multilocus phylogenetic analysis, including 16S rRNA gene (rDNA), rpoB, and infB sequencing, clearly placed N. semolina as a new genus in the family Pasteurellaceae. In all the phylogenetic trees constructed, N. semolina is on a distinct branch displaying approximately 5% 16S rDNA, approximately 16% rpoB, and approximately 20% infB sequence divergence from its nearest relative within the family Pasteurellaceae. High degrees of conservation of the 16S rDNA (99.8%), rpoB (99.6%), and infB (99.7%) sequences exist within the species, indicating that N. semolina isolates not only are phenotypically homogeneous but also are genetically homogeneous. The type strain of N. semolina is CCUG43639(T) (DSM16380(T)).

Space–oriented EEG segmentation reveals changes in brain electric–field maps under the influence of a nootropic drug

Map landscape-based segmentation of the sequences of momentary potential distribution maps (42-channel recordings) into brain microstates during spontaneous brain activity was used to study brain electric field spatial effects of single doses of piracetam (2.9, 4.8, and 9.6 g Nootropil® UCB and placebo) in a double-blind study of five normal young volunteers. Four 15-second epochs were analyzed from each subject and drug condition. The most prominent class of microstates (covering 49% of the time) consisted of potential maps with a generally anterior-posterior field orientation. The map orientation of this microstate class showed an increasing clockwise deviation from the placebo condition with increasing drug doses (Fisher's probability product, p < 0.014). The results of this study suggest the use of microstate segmentation analysis for the assessment of central effects of medication in spontaneous multichannel electroencephalographic data, as a complementary approach to frequency-domain analysis.

Effect of hay dust extract and cyathostomin antigen stimulation on cytokine expression by PBMC in horses with recurrent airway obstruction

Equine recurrent airway obstruction (RAO) is an inflammatory, obstructive airway disease induced by exposure of susceptible horses to inhaled organic dust particles. The immunological process underlying RAO is still unclear. Previous studies have shown that RAO is linked to the Interleukin-4 receptor (IL-4R) gene in one Warmblood family (F1), but not in another (F2). It has also been shown that in F1, but not in F2, RAO is associated with resistance against parasites, suggesting that this association may have an immuno-genetic basis. Therefore, we hypothesized that the T helper (h)1/Th2/regulatory (Treg) cytokine profiles of RAO-associated antigen- and parasite-antigen-stimulated peripheral blood mononuclear cells (PBMC) differ between RAO-affected and healthy horses depending on their genetic background. In our study, PBMC from 17 RAO-affected and 14 healthy control horses of F1 and F2 were stimulated for 24h with antigens relevant to RAO [hay dust extract (HDE), Aspergillus fumigatus extract (AFE) and lipopolysaccharids (LPS)]; cyathostomin extract (CE) and recombinant cyathostomin antigen (RCA) or with concanavalin A (ConA). Total mRNA levels of IL-4, IL-4R, IL-13, interferon (INF)-γ and IL-10 were examined by qRT-PCR. Stimulation with either HDE or RCA resulted in significant differences in IL-4R mRNA levels between RAO-affected and control horses in F1, but not in F2. For IL-10 mRNA expression, a significant difference between RAO-affected and control horses in F1 but not in F2 was observed only following stimulation with HDE. In contrast to HDE, stimulation with CE resulted in a significant difference of IL-10 mRNA expression level between RAO-affected horses of F2 and healthy horses of F1. No significant differences were detected upon stimulation with any of the other challenge agents. These findings indicate that the immunological response, specifically IL-4R expression, in response to hay dust and cyathostomin antigens, differs between RAO-affected and healthy horses depending on their genetic background. This study shows that analysis of PBMC reveals systemic changes associated with RAO and helps to elucidate immunological pathways involved in this disease.

Hierarchical segmentation-assisted multimodal registration for MR brain images

Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Fully automatic X-ray image segmentation via joint estimation of image displacements.

We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.

Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.

PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.