Immune-mediated competition in rodent malaria is most likely caused by induced changes in innate immune clearance of merozoites

Malarial infections are often genetically diverse, leading to competitive interactions between parasites. A quantitative understanding of the competition between strains is essential to understand a wide range of issues, including the evolution of virulence and drug resistance. In this study, we use dynamical-model based Bayesian inference to investigate the cause of competitive suppression of an avirulent clone of Plasmodium chabaudi (AS) by a virulent clone (AJ) in immuno-deficient and competent mice. We test whether competitive suppression is caused by clone-specific differences in one or more of the following processes: adaptive immune clearance of merozoites and parasitised red blood cells (RBCs), background loss of merozoites and parasitised RBCs, RBC age preference, RBC infection rate, burst size, and within-RBC interference. These processes were parameterised in dynamical mathematical models and fitted to experimental data. We found that just one parameter μ, the ratio of background loss rate of merozoites to invasion rate of mature RBCs, needed to be clone-specific to predict the data. Interestingly, μ was found to be the same for both clones in single-clone infections, but different between the clones in mixed infections. The size of this difference was largest in immuno-competent mice and smallest in immuno-deficient mice. This explains why competitive suppression was alleviated in immuno-deficient mice. We found that competitive suppression acts early in infection, even before the day of peak parasitaemia. These results lead us to argue that the innate immune response clearing merozoites is the most likely, but not necessarily the only, mediator of competitive interactions between virulent and avirulent clones. Moreover, in mixed infections we predict there to be an interaction between the clones and the innate immune response which induces changes in the strength of its clearance of merozoites. What this interaction is unknown, but future refinement of the model, challenged with other datasets, may lead to its discovery

Comparison of embedded and added motor imagery training in patients after stroke: Study protocol of a randomised controlled pilot trial using a mixed methods approach

Copyright @ 2009 Schuster et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Two different approaches have been adopted when applying motor imagery (MI) to stroke patients. MI can be conducted either added to conventional physiotherapy or integrated within therapy sessions. The proposed study aims to compare the efficacy of embedded MI to an added MI intervention. Evidence from pilot studies reported in the literature suggests that both approaches can improve performance of a complex motor skill involving whole body movements, however, it remains to be demonstrated, which is the more effective one.Methods/Design: A single blinded, randomised controlled trial (RCT) with a pre-post intervention design will be carried out. The study design includes two experimental groups and a control group (CG). Both experimental groups (EG1, EG2) will receive physical practice of a clinical relevant motor task ('Going down, laying on the floor, and getting up again') over a two week intervention period: EG1 with embedded MI training, EG2 with MI training added after physiotherapy. The CG will receive standard physiotherapy intervention and an additional control intervention not related to MI.The primary study outcome is the time difference to perform the task from pre to post-intervention. Secondary outcomes include level of help needed, stages of motor task completion, degree of motor impairment, balance ability, fear of falling measure, motivation score, and motor imagery ability score. Four data collection points are proposed: twice during baseline phase, once following the intervention period, and once after a two week follow up. A nested qualitative part should add an important insight into patients' experience and attitudes towards MI. Semi-structured interviews of six to ten patients, who participate in the RCT, will be conducted to investigate patients' previous experience with MI and their expectations towards the MI intervention in the study. Patients will be interviewed prior and after the intervention period.Discussion: Results will determine whether embedded MI is superior to added MI. Findings of the semi-structured interviews will help to integrate patient's expectations of MI interventions in the design of research studies to improve practical applicability using MI as an adjunct therapy technique

Borrelia valaisiana resist complement-mediated killing independently of the recruitment of immune regulators and inactivation of complement components

Spirochetes belonging to the Borrelia (B.) burgdorferi sensu lato complex differ in their resistance to complement-mediated killing, particularly in regard to human serum. In the present study, we elucidate the serum and complement susceptibility of B. valaisiana, a genospecies with the potential to cause Lyme disease in Europe as well as in Asia. Among the investigated isolates, growth of ZWU3 Ny3 was not affected while growth of VS116 and Bv9 was strongly inhibited in the presence of 50% human serum. Analyzing complement activation, complement components C3, C4 and C6 were deposited on the surface of isolates VS116 and Bv9, and similarly the membrane attack complex was formed on their surface. In contrast, no surface-deposited components and no aberrations in cell morphology were detected for serum-resistant ZWU3 Ny3. While further investigating the protective role of bound complement regulators in mediating complement resistance, we discovered that none of the B. valaisiana isolates analyzed bound complement regulators Factor H, Factor H-like protein 1, C4b binding protein or C1 esterase inhibitor. In addition, B. valaisiana also lacked intrinsic proteolytic activity to degrade complement components C3, C3b, C4, C4b, and C5. Taken together, these findings suggest that certain B. valaisiana isolates differ in their capability to resist complement-mediating killing by human serum. The molecular mechanism utilized by B. valaisiana to inhibit bacteriolysis appears not to involve binding of the key host complement regulators of the alternative, classical, and lectin pathways as already known for serum-resistant Lyme disease or relapsing fever borreliae

Acyl Homoserine Lactones from Culture Supernatants of Pseudomonas aeruginosa Accelerate Host Immunomodulation

The virulence of Pseudomonas aeruginosa is multifactorial and under the control of quorum sensing signals, such as acyl homoserine lactones (AHLs). The importance of these molecules in the establishment of infection has been previously reported. These molecules either improve the virulence potential of P. aeruginosa or modulate the host immune response. To establish the immune modulating potential of quorum sensing signal molecules, previous studies have only used synthetic AHLs. However, there can be differences in the biological properties of synthetic and natural AHLs. The use of naturally extracted AHLs from the culture supernatant of P. aeruginosa is likely to simulate natural conditions more than the use of synthetic AHLs. Therefore, in the present study, the immune modulating potential of synthetic and naturally extracted AHLs was compared using a thymidine uptake assay, immunophenotyping and sandwich ELISA in order to assess mouse T-cell proliferation and production of Th1 and Th2 cytokines. Natural AHLs were able to suppress T-cell proliferation, even at low concentrations, compared to synthetic AHLs. The majority of cells undergoing proliferation were CD4+, as revealed by immunophenotyping. The inhibition of T-cells was stronger with natural AHLs compared to synthetic AHLs. Moreover, the natural AHLs were also able to shift immune responses away from host protective Th1 responses to pathogen protective Th2 responses

Generalized linear models for flexible parametric modeling of the hazard function

Background: Parametric modelling of survival data is important and reimbursement decisions may depend on the selected distribution. Accurate predictions require sufficiently flexible models to describe adequately the temporal evolution of the hazard function. A rich class of models is available among the framework of generalised linear models (GLMs) and its extensions, but these models are rarely applied to survival data. This manuscript describes the theoretical properties of these more flexible models, and compares their performance to standard survival models in a reproducible case- study. Methods: We describe how survival data may be analysed with GLMs and its extensions: fractional polynomials, spline models, generalised additive models, generalised linear mixed (frailty) models and dynamic survival models. For each, we provide a comparison of the strengths and limitations of these approaches. For the case-study we compare within-sample fit, the plausibility of extrapolations and extrapolation performance based on data-splitting. Results: Viewing standard survival models as GLMs shows that many impose a restrictive assumption of linearity. For the case-study, GLMs provided better within-sample fit and more plausible extrapolations. However, they did not improve extrapolation performance. We also provide guidance to aid in choosing between the different approaches based on GLMs and its extensions. Conclusions: The use of GLMs for parametric survival analysis can out-perform standard parametric survival models, although the improvements were modest in our case-study. This approach is currently seldom used. We provide guidance on both implementing these models and choosing between them. The reproducible case-study will help to increase uptake of these models

Bayesian Integration and Non-Linear Feedback Control in a Full-Body Motor Task

A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task

Novel Primate Model of Serotonin Transporter Genetic Polymorphisms Associated with Gene Expression, Anxiety and Sensitivity to Antidepressants

This is the final version of the article. It first appeared from Nature Publishing Group via https://dx.doi.org/10.1038/npp.2016.41Genetic polymorphisms in the repeat upstream region of the serotonin transporter gene (SLC6A4) are associated with individual differences in stress reactivity, vulnerability to affective disorders and response to pharmacotherapy. However, the molecular, neurodevelopmental and psychopharmacological mechanisms underlying the link between SLC6A4 polymorphisms and the emotionally vulnerable phenotype are not fully understood. Thus, using the marmoset monkey Callithrix jacchus we characterize here a new neurobiological model to help to address these questions. We first sequenced the marmoset SLC6A4 promoter and identified a double nucleotide polymorphism (−2053AC/CT) and two single nucleotide polymorphisms (−2022C/T and −1592G/C) within the repeat upstream region. We showed their association with gene expression using in vivo quantitative PCR and with affective behavior using a primate test of anxiety (human intruder test). The low-expressing haplotype (AC/C/G) was linked with high anxiety whilst the high-expressing one (CT/T/C) was associated with an active coping strategy in response to threat. Pharmacological challenge with an acute dose of the selective serotonin reuptake inhibitor (SSRI), citalopram, revealed a genotype-dependent behavioral response. Whilst individuals homozygous for the high anxiety-related haplotype AC/C/G exhibited a dose-dependent, anxiogenic response, individuals homozygous for the low anxiety-related haplotype CT/T/C showed an opposing, dose-dependent anxiolytic effect. These findings provide a novel genetic and behavioral primate model to study the molecular, neurodevelopmental and psychopharmacological mechanisms that underlie genetic variation-associated complex behaviors, with specific implications for the understanding of normal and abnormal serotonin actions and the development of personalized pharmacological treatments for psychiatric disorders.Work was supported by an MRC Programme (ACR; G0901884) and performed within the Behavioural and Clinical Neuroscience Institute, University of Cambridge, funded jointly by the Wellcome Trust and MRC. AMS was supported by a McDonnell Foundation grant (PI’s: E. Phelps, T.W. Robbins; Co-Investigators: ACR and J. LeDoux; 22002015501) and currently supported by MRC; YS supported by the Long Term Student Support Program provided by Osaka University and the Ministry of Education, Culture, Sports, Science and Technology of Japan; HC supported by MRC Career Development Award and ACFS/MI supported by grants from the MRC and Wellcome Trust. GC supported by the Behavioural and Clinical Neuroscience Institute, Cambridge, United Kingdom. EHSS was self-funded

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability distributions. An alternative view is that the brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property takes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that the inference strategies employed by humans may deviate from Bayes-optimal integration when the computational demands are high