Host and Environmental Influences on Development of Disease

While many myxozoan parasites produce asymptomatic infections in fish hosts, several species cause diseases whose patterns of prevalence and pathogenicity are highly dependent on host and environmental factors. This chapter reviews how these factors influence pathogenicity and disease prevalence. Influential host factors include age, size and nutritional state. There is also strong evidence for host strains that vary in resistance to infection and that there is a genetic basis for resistance. A lack of co-evolutionary processes appears to generally underly the devastating impacts of diseases caused by myxozoans when introduced fish are exposed to novel parasites (e.g. PKD in rainbow trout in Europe) or when native fish are exposed to an introduced parasite (e.g. whirling disease in North America). Most available information on abiotic factors relates to water temperature, which has been shown to play a crucial role in several host parasite systems (e.g. whirling disease, PKD) and is therefore of concern in view of global warming, fish health and food sustainability. Eutrophication may also influence disease development. Abiotic factors may also drive fish disease via their impact on parasite development in invertebrate hosts.

Fish Immune Responses to Myxozoa

Myxozoans evoke important economic losses in aquaculture production, but there is almost a total lack of disease control methods as no vaccines or commercial treatments are currently available. Knowledge of the immune responses that lead to myxozoan elimination and subsequent disease resistance is vital for shaping the future development of disease control measures. Different fish immune factors triggered by myxozoan parasites are reviewed in this chapter. Detailed information on the phenotypic and underlying molecular aspects of innate and adaptive responses, at both cellular and humoral levels, is provided for some well-studied fishmyxozoan systems. The importance of the local immune response, mainly at mucosal sites, is also highlighted. Myxozoan tactics to disable or avoid immune responses, such as modulation of immune gene transcription and immune evasion, are also reviewed. The existence of innate and acquired resistance to some myxozoan species suggest promising possibilities for controlling myxozooses through immune-based strategies, such as genetic selection for host resistance, vaccination, immune therapies and administration of immunostimulants.

PARP Inhibitor Resistance - What Is Beyond BRCA1 or BRCA2 Restoration?

Nearly 10 years ago the usefulness of poly(ADP-ribose) polymerase (PARP) inhibitors to kill BRCA1 or BRCA2-deficient cells was reported, and this finding has served as a prime example of the concept of synthetic lethality in the context of anticancer therapy. The clinical translation of this finding has undergone several ups and downs, however. Despite spectacular responses seen in some patients with BRCA-deficient breast or ovarian cancers, other patients did not show the expected benefit from PARP inhibitor therapy. Thus, like for all novel tailored anti-cancer drugs, upfront and secondary resistance remain major hurdles in the implementation of the initial preclinical finding. We know at least one clinically relevant mechanism of PARP inhibitor resistance: the reversion of BRCA function by secondary mutations. Nevertheless, it is also clear that this mechanism does not explain all cases of resistance. At the moment, we only have a poor understanding of BRCA reversion-independent resistance mechanisms. Preclinical data have pointed in several directions, e.g. increased drug efflux, reduced drug target levels, or alternative DNA repair. Here, we discuss these mechanisms with a focus on potential DNA repair adaptations.

Modulatory Effects of Eschscholzia californica Alkaloids on Recombinant GABAA Receptors.

The California poppy (Eschscholzia californica Cham.) contains a variety of natural compounds including several alkaloids found exclusively in this plant. Because of the sedative, anxiolytic, and analgesic effects, this herb is currently sold in pharmacies in many countries. However, our understanding of these biological effects at the molecular level is still lacking. Alkaloids detected in E. californica could be hypothesized to act at GABAA receptors, which are widely expressed in the brain mainly at the inhibitory interneurons. Electrophysiological studies on a recombinant α 1 β 2 γ 2 GABAA receptor showed no effect of N-methyllaurotetanine at concentrations lower than 30 μM. However, (S)-reticuline behaved as positive allosteric modulator at the α 3, α 5, and α 6 isoforms of GABAA receptors. The depressant properties of aerial parts of E. californica are assigned to chloride-current modulation by (S)-reticuline at the α 3 β 2 γ 2 and α 5 β 2 γ 2 GABAA receptors. Interestingly, α 1, α 3, and α 5 were not significantly affected by (R)-reticuline, 1,2-tetrahydroreticuline, codeine, and morphine-suspected (S)-reticuline metabolites in the rodent brain.

Non-rigid Free-Form 2D-3D Registration Using Statistical Deformation Model

This paper presents a non-rigid free-from 2D-3D registration approach using statistical deformation model (SDM). In our approach the SDM is first constructed from a set of training data using a non-rigid registration algorithm based on b-spline free-form deformation to encode a priori information about the underlying anatomy. A novel intensity-based non-rigid 2D-3D registration algorithm is then presented to iteratively fit the 3D b-spline-based SDM to the 2D X-ray images of an unseen subject, which requires a computationally expensive inversion of the instantiated deformation in each iteration. In this paper, we propose to solve this challenge with a fast B-spline pseudo-inversion algorithm that is implemented on graphics processing unit (GPU). Experiments conducted on C-arm and X-ray images of cadaveric femurs demonstrate the efficacy of the present approach.

Regulation of Neutrophil Serine Proteases by Intracellular Serpins

Neutrophil granules contain serine proteases that are central components of the antimicrobial weapons of the innate immune system. Neutrophil proteases also contribute to the amplification and resolution of inflammatory responses through defined proteolytic cleavage of mediators, cell surface receptors, and extracellular matrix proteins. In the blood and at mucosal surfaces, neutrophil serine proteases are regulated by serpins found in plasma and by non-serpin secreted inhibitors. Distinct mechanisms leading to neutrophil cell death have been described for the granule serine proteases, neutrophil elastase, cathepsin G, and proteinase-3. Granule leakage in neutrophils triggers death pathways mediated by cathepsin G and proteinase-3, and both proteases are tightly regulated by their inhibitor SERPINB1 in a cell intrinsic manner. Although stored in the same types of granules, neutrophil elastase does not significantly contribute to cell death following intracellular release from granules into the cytoplasm. However, heterozygous mutations in ELANE, the gene encoding elastase, are the cause of severe congenital neutropenia, a life-threatening condition characterized by the death of neutrophils at an early precursor stage in the bone marrow. This chapter focuses on recent work exploring the biology of clade B intracellular serpins that inhibit neutrophil serine proteases and their functions in neutrophil homeostasis and serine protease control at sites of inflammation.

Computer Assisted Diagnosis and Treatment Planning of Femoroacetabular Impingement (FAI)

Femoroacetabular impingement (FAI) is a dynamic conflict of the hip defined by a pathological, early abutment of the proximal femur onto the acetabulum or pelvis. In the past two decades, FAI has received increasing focus in both research and clinical practice as a cause of hip pain and prearthrotic deformity. Anatomical abnormalities such as an aspherical femoral head (cam-type FAI), a focal or general overgrowth of the acetabulum (pincer-type FAI), a high riding greater or lesser trochanter (extra-articular FAI), or abnormal torsion of the femur have been identified as underlying pathomorphologies. Open and arthroscopic treatment options are available to correct the deformity and to allow impingement-free range of motion. In routine practice, diagnosis and treatment planning of FAI is based on clinical examination and conventional imaging modalities such as standard radiography, magnetic resonance arthrography (MRA), and computed tomography (CT). Modern software tools allow three-dimensional analysis of the hip joint by extracting pelvic landmarks from two-dimensional antero-posterior pelvic radiographs. An object-oriented cross-platform program (Hip2Norm) has been developed and validated to standardize pelvic rotation and tilt on conventional AP pelvis radiographs. It has been shown that Hip2Norm is an accurate, consistent, reliable and reproducible tool for the correction of selected hip parameters on conventional radiographs. In contrast to conventional imaging modalities, which provide only static visualization, novel computer assisted tools have been developed to allow the dynamic analysis of FAI pathomechanics. In this context, a validated, CT-based software package (HipMotion) has been introduced. HipMotion is based on polygonal three-dimensional models of the patient’s pelvis and femur. The software includes simulation methods for range of motion, collision detection and accurate mapping of impingement areas. A preoperative treatment plan can be created by performing a virtual resection of any mapped impingement zones both on the femoral head-neck junction, as well as the acetabular rim using the same three-dimensional models. The following book chapter provides a summarized description of current computer-assisted tools for the diagnosis and treatment planning of FAI highlighting the possibility for both static and dynamic evaluation, reliability and reproducibility, and its applicability to routine clinical use.

The Gut Microbiome and Cirrhosis: Basic Aspects

In this chapter the basic aspects helping to understand the microbiome in terms of quantity, diversity, complexity, function, and interaction with the host are discussed. First the nomenclature, definitions of taxa, and measures of diversity as well as methods to unravel this kingdom are outlined. A brief summary on its physiological relevance for general health and the functions exerted specifically by the microbiome is presented. Differences in the composition of the microbiome along the gastrointestinal tract and across the gut wall and its interindividual variations, enterotypes, and stability are highlighted. The reader will be familiarized with all different modulators impacting on the microbiome, namely, intrinsic and extrinsic factors. Intrinsic factors include gastrointestinal secretions (gastric acid, bile, pancreatic juice, mucus), antimicrobial peptides, motility, enteric nervous system, and host genotype. Extrinsic factors are mainly dietary choices, hygiene, stress, alcohol consumption, exercise, and medications. The second part of the chapter focuses on quantitative and qualitative changes in microbiome in liver cirrhosis. The mechanisms contributing to dysbiosis, small intestinal bacterial overgrowth, and bacterial translocation are delineated underscoring their role for the liver-gut axis.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

Nonparametric location estimators in the randomized complete block design

Several tests for the comparison of different groups in the randomized complete block design exist. However, there is a lack of robust estimators for the location difference between one group and all the others on the original scale. The relative marginal effects are commonly used in this situation, but they are more difficult to interpret and use by less experienced people because of the different scale. In this paper two nonparametric estimators for the comparison of one group against the others in the randomized complete block design will be presented. Theoretical results such as asymptotic normality, consistency, translation invariance, scale preservation, unbiasedness, and median unbiasedness are derived. The finite sample behavior of these estimators is derived by simulations of different scenarios. In addition, possible confidence intervals with these estimators are discussed and their behavior derived also by simulations.