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

Heavy-to-light baryonic form factors at large recoil

We analyze heavy-to-light baryonic form factors at large recoil and derive the scaling behavior of these form factors in the heavy quark limit. It is shown that only one universal form factor is needed to parameterize Lambda_b to p and Lambda_b to Lambda matrix elements in the large recoil limit of light baryons, while hadronic matrix elements of Lambda_b to Sigma transition vanish in the large energy limit of Sigma baryon due to the space-time parity symmetry. The scaling law of the soft form factor eta(P^{\prime} \cdot v), P^{\prime} and v being the momentum of nucleon and the velocity of Lambda_b baryon, responsible for Lambda_b to p transitions is also derived using the nucleon distribution amplitudes in leading conformal spin. In particular, we verify that this scaling behavior is in full agreement with that from light-cone sum rule approach in the heavy-quark limit. With these form factors, we further investigate the Lambda baryon polarization asymmetry alpha in Lambda_b to Lambda gamma and the forward-backward asymmetry A_{FB} in Lambda_b to Lambda l^{+} l^{-}. Both two observables (alpha and A_{FB}) are independent of hadronic form factors in leading power of 1/m_b and in leading order of alpha_s. We also extend the analysis of hadronic matrix elements for Omega_b to Omega transitions to rare Omega_b to Omega gamma and Omega_b to Omega l^{+} l^{-} decays and find that radiative Omega_b to Omega gamma decay is probably the most promising FCNC b to s radiative baryonic decay channel. In addition, it is interesting to notice that the zero-point of forward-backward asymmetry of Omega_b to Omega l^{+} l^{-} is the same as the one for Lambda_b to Lambda l^{+} l^{-} to leading order accuracy provided that the form factors \bar{\zeta}_i (i=3, 4, 5) are numerically as small as indicated from the quark model.Comment: 19 page

Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting

We present an analytical method to quantify clustering in super-resolution localization images of static surfaces in two dimensions. The method also describes how over-counting of labeled molecules contributes to apparent self-clustering and how the effective lateral resolution of an image can be determined. This treatment applies to clustering of proteins and lipids in membranes, where there is significant interest in using super-resolution localization techniques to probe membrane heterogeneity. When images are quantified using pair correlation functions, the magnitude of apparent clustering due to over-counting will vary inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. Over-counting does not yield apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (Fc{\epsilon}RI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM) and scanning electron microscopy (SEM). We find that apparent clustering of labeled IgE bound to Fc{\epsilon}RI detected with both methods arises from over-counting of individual complexes. Thus our results indicate that these receptors are randomly distributed within the resolution and sensitivity limits of these experiments.Comment: 22 pages, 5 figure

The Precursors and Products of Justice Climates: Group Leader Antecedents and Employee Attitudinal Consequences

Drawing on the organizational justice, organizational climate, leadership and personality, and social comparison theory literatures, we develop hypotheses about the effects of leader personality on the development of three types of justice climates (e.g., procedural, interpersonal, and informational), and the moderating effects of these climates on individual level justice- attitude relationships. Largely consistent with the theoretically-derived hypotheses, the results showed that leader (a) agreeableness was positively related to procedural, interpersonal and informational justice climates, (b) conscientiousness was positively related to a procedural justice climate, and (c) neuroticism was negatively related to all three types of justice climates. Further, consistent with social comparison theory, multilevel data analyses revealed that the relationship between individual justice perceptions and job attitudes (e.g., job satisfaction, commitment) was moderated by justice climate such that the relationships were stronger when justice climate was high

What do hospital decision-makers in Ontario, Canada, have to say about the fairness of priority setting in their institutions?

BACKGROUND: Priority setting, also known as rationing or resource allocation, occurs at all levels of every health care system. Daniels and Sabin have proposed a framework for priority setting in health care institutions called 'accountability for reasonableness', which links priority setting to theories of democratic deliberation. Fairness is a key goal of priority setting. According to 'accountability for reasonableness', health care institutions engaged in priority setting have a claim to fairness if they satisfy four conditions of relevance, publicity, appeals/revision, and enforcement. This is the first study which has surveyed the views of hospital decision makers throughout an entire health system about the fairness of priority setting in their institutions. The purpose of this study is to elicit hospital decision-makers' self-report of the fairness of priority setting in their hospitals using an explicit conceptual framework, 'accountability for reasonableness'. METHODS: 160 Ontario hospital Chief Executive Officers, or their designates, were asked to complete a survey questionnaire concerning priority setting in their publicly funded institutions. Eight-six Ontario hospitals completed this survey, for a response rate of 54%. Six close-ended rating scale questions (e.g. Overall, how fair is priority setting at your hospital?), and 3 open-ended questions (e.g. What do you see as the goal(s) of priority setting in your hospital?) were used. RESULTS: Overall, 60.7% of respondents indicated their hospitals' priority setting was fair. With respect to the 'accountability for reasonableness' conditions, respondents indicated their hospitals performed best for the relevance (75.0%) condition, followed by appeals/revision (56.6%), publicity (56.0%), and enforcement (39.5%). CONCLUSIONS: For the first time hospital Chief Executive Officers within an entire health system were surveyed about the fairness of priority setting practices in their institutions using the conceptual framework 'accountability for reasonableness'. Although many hospital CEOs felt that their priority setting was fair, ample room for improvement was noted, especially for the enforcement condition

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis

Defining Potential Therapeutic Targets in Coronavirus Disease 2019: A Cross-Sectional Analysis of a Single-Center Cohort

OBJECTIVES: Multiple mechanisms have been proposed to explain disease severity in coronavirus disease 2019. Therapeutic approaches need to be underpinned by sound biological rationale. We evaluated whether serum levels of a range of proposed coronavirus disease 2019 therapeutic targets discriminated between patients with mild or severe disease. DESIGN: A search of ClinicalTrials.gov identified coronavirus disease 2019 immunological drug targets. We subsequently conducted a retrospective observational cohort study investigating the association of serum biomarkers within the first 5 days of hospital admission relating to putative therapeutic biomarkers with illness severity and outcome. SETTING: University College London, a tertiary academic medical center in the United Kingdom. PATIENTS: Patients admitted to hospital with a diagnosis of coronavirus disease 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Eighty-six patients were recruited, 44 (51%) with mild disease and 42 (49%) with severe disease. We measured levels of 10 cytokines/signaling proteins related to the most common therapeutic targets (granulocyte-macrophage colony-stimulating factor, interferon-α2a, interferon-β, interferon-γ, interleukin-1β, interleukin-1 receptor antagonist, interleukin-6, interleukin-7, interleukin-8, tumor necrosis factor-α), immunoglobulin G antibodies directed against either coronavirus disease 2019 spike protein or nucleocapsid protein, and neutralization titers of antibodies. Four-hundred seventy-seven randomized trials, including 168 different therapies against 83 different pathways, were identified. Six of the 10 markers (interleukin-6, interleukin-7, interleukin-8, interferon-α2a, interferon-β, interleukin-1 receptor antagonist) discriminated between patients with mild and severe disease, although most were similar or only modestly raised above that seen in healthy volunteers. A similar proportion of patients with mild or severe disease had detectable spike protein or nucleocapsid protein immunoglobulin G antibodies with equivalent levels between groups. Neutralization titers were higher among patients with severe disease. CONCLUSIONS: Some therapeutic and prognostic biomarkers may be useful in identifying coronavirus disease 2019 patients who may benefit from specific immunomodulatory therapies, particularly interleukin-6. However, biomarker absolute values often did not discriminate between patients with mild and severe disease or death, implying that these immunomodulatory treatments may be of limited benefit