Increased male reproductive success in Ts65Dn “Down syndrome” mice

The Ts65Dn mouse is trisomic for orthologs of about half the genes on Hsa21. A number of phenotypes in these trisomic mice parallel those in humans with trisomy 21 (Down syndrome), including cognitive deficits due to hippocampal malfunction that are sufficiently similar to human that “therapies” developed in Ts65Dn mice are making their way to human clinical trials. However, the impact of the model is limited by availability. Ts65Dn cannot be completely inbred and males are generally considered to be sterile. Females have few, small litters and they exhibit poor care of offspring, frequently abandoning entire litters. Here we report identification and selective breeding of rare fertile males from two working colonies of Ts65Dn mice. Trisomic offspring can be propagated by natural matings or by in vitro fertilization (IVF) to produce large cohorts of closely related siblings. The use of a robust euploid strain as recipients of fertilized embryos in IVF or as the female in natural matings greatly improves husbandry. Extra zygotes cultured to the blastocyst stage were used to create trisomic and euploid embryonic stem (ES) cells from littermates. We developed parameters for cryopreserving sperm from Ts65Dn males and used it to produce trisomic offspring by IVF. Use of cryopreserved sperm provides additional flexibility in the choice of oocyte donors from different genetic backgrounds, facilitating rapid production of complex crosses. This approach greatly increases the power of this important trisomic model to interrogate modifying effects of trisomic or disomic genes that contribute to trisomic phenotypes

Adhesion of perfume-filled microcapsules to model fabric surfaces

The retention and adhesion of melamine formaldehyde (MF) microcapsules on a model fabric surface in aqueous solution were investigated using a customised flow chamber technique and atomic force microscopy (AFM). A cellulose film was employed as a model fabric surface. Modification of the cellulose with chitosan was found to increase the retention and adhesion of microcapsules on the model fabric surface. The AFM force–displacement data reveal that bridging forces resulting from the extension of cellulose chains dominate the adhesion between the microcapsule and the unmodified cellulose film, whereas electrostatic attraction helps the microcapsules adhere to the chitosan-modified cellulose film. The correlation between results obtained using these two complementary techniques suggests that the flow chamber device can be potentially used for rapid screening of the effect of chemical modification on the adhesion of microparticles to surfaces, reducing the time required to achieve an optimal formulation

Adjustment for time-invariant and time-varying confounders in ‘unexplained residuals’ models for longitudinal data within a causal framework and associated challenges

‘Unexplained residuals’ models have been used within lifecourse epidemiology to model an exposure measured longitudinally at several time points in relation to a distal outcome. It has been claimed that these models have several advantages, including: the ability to estimate multiple total causal effects in a single model, and additional insight into the effect on the outcome of greater-than-expected increases in the exposure compared to traditional regression methods. We evaluate these properties and prove mathematically how adjustment for confounding variables must be made within this modelling framework. Importantly, we explicitly place unexplained residual models in a causal framework using directed acyclic graphs. This allows for theoretical justification of appropriate confounder adjustment and provides a framework for extending our results to more complex scenarios than those examined in this paper. We also discuss several interpretational issues relating to unexplained residual models within a causal framework. We argue that unexplained residual models offer no additional insights compared to traditional regression methods, and, in fact, are more challenging to implement; moreover, they artificially reduce estimated standard errors. Consequently, we conclude that unexplained residual models, if used, must be implemented with great care

Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here

Chronic Helminth Infections Protect Against Allergic Diseases by Active Regulatory Processes

Developed countries are suffering from an epidemic rise in immunologic disorders, such as allergy-related diseases and certain autoimmunities. Several studies have demonstrated a negative association between helminth infections and inflammatory diseases (eg, allergy), providing a strong case for the involvement of helminth infections in this respect. However, some studies point in the opposite direction. The discrepancy may be explained by differences in frequency, dose, time, and type of helminth. In this review, new studies are discussed that may support the concept that chronic helminth infections in particular—but not acute infections—are associated with the expression of regulatory networks necessary for downmodulating allergic immune responses to harmless antigens. Furthermore, different components of regulatory networks are highlighted, such as the role of regulatory T and B cells, modulation of dendritic cells, early innate signals from structural cells (eg, epithelial cells), and their individual contributions to protection against allergic diseases. It is of great interest to define and characterize specific helminth molecules that have profound immunomodulatory capacities as targets for therapeutic application in the treatment or prophylaxis of allergic manifestations

Acupuncture and chiropractic care for chronic pain in an integrated health plan: a mixed methods study

<p>Abstract</p> <p>Background</p> <p>Substantial recent research examines the efficacy of many types of complementary and alternative (CAM) therapies. However, outcomes associated with the "real-world" use of CAM has been largely overlooked, despite calls for CAM therapies to be studied in the manner in which they are practiced. Americans seek CAM treatments far more often for chronic musculoskeletal pain (CMP) than for any other condition. Among CAM treatments for CMP, acupuncture and chiropractic (A/C) care are among those with the highest acceptance by physician groups and the best evidence to support their use. Further, recent alarming increases in delivery of opioid treatment and surgical interventions for chronic pain--despite their high costs, potential adverse effects, and modest efficacy--suggests the need to evaluate real world outcomes associated with promising non-pharmacological/non-surgical CAM treatments for CMP, which are often well accepted by patients and increasingly used in the community.</p> <p>Methods/Design</p> <p>This multi-phase, mixed methods study will: (1) conduct a retrospective study using information from electronic medical records (EMRs) of a large HMO to identify unique clusters of patients with CMP (e.g., those with differing demographics, histories of pain condition, use of allopathic and CAM health services, and comorbidity profiles) that may be associated with different propensities for A/C utilization and/or differential outcomes associated with such care; (2) use qualitative interviews to explore allopathic providers' recommendations for A/C and patients' decisions to pursue and retain CAM care; and (3) prospectively evaluate health services/costs and broader clinical and functional outcomes associated with the receipt of A/C relative to carefully matched comparison participants receiving traditional CMP services. Sensitivity analyses will compare methods relying solely on EMR-derived data versus analyses supplementing EMR data with conventionally collected patient and clinician data.</p> <p>Discussion</p> <p>Successful completion of these aggregate aims will provide an evaluation of outcomes associated with the real-world use of A/C services. The trio of retrospective, qualitative, and prospective study will also provide a clearer understanding of the decision-making processes behind the use of A/C for CMP and a transportable methodology that can be applied to other health care settings, CAM treatments, and clinical populations.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01345409">NCT01345409</a></p

The macrophage in HIV-1 infection: From activation to deactivation?

Macrophages play a crucial role in innate and adaptative immunity in response to microorganisms and are an important cellular target during HIV-1 infection. Recently, the heterogeneity of the macrophage population has been highlighted. Classically activated or type 1 macrophages (M1) induced in particular by IFN-γ display a pro-inflammatory profile. The alternatively activated or type 2 macrophages (M2) induced by Th-2 cytokines, such as IL-4 and IL-13 express anti-inflammatory and tissue repair properties. Finally IL-10 has been described as the prototypic cytokine involved in the deactivation of macrophages (dM). Since the capacity of macrophages to support productive HIV-1 infection is known to be modulated by cytokines, this review shows how modulation of macrophage activation by cytokines impacts the capacity to support productive HIV-1 infection. Based on the activation status of macrophages we propose a model starting with M1 classically activated macrophages with accelerated formation of viral reservoirs in a context of Th1 and proinflammatory cytokines. Then IL-4/IL-13 alternatively activated M2 macrophages will enter into the game that will stop the expansion of the HIV-1 reservoir. Finally IL-10 deactivation of macrophages will lead to immune failure observed at the very late stages of the HIV-1 disease