Protective Effects of Non-Anticoagulant Activated Protein C Variant (D36A/L38D/A39V) in a Murine Model of Ischaemic Stroke

Ischaemic stroke is caused by occlusive thrombi in the cerebral vasculature. Although tissue-plasminogen activator (tPA) can be administered as thrombolytic therapy, it has major limitations, which include disruption of the blood-brain barrier and an increased risk of bleeding. Treatments that prevent or limit such deleterious effects could be of major clinical importance. Activated protein C (APC) is a natural anticoagulant that regulates thrombin generation, but also confers endothelial cytoprotective effects and improved endothelial barrier function mediated through its cell signalling properties. In murine models of stroke, although APC can limit the deleterious effects of tPA due to its cell signalling function, its anticoagulant actions can further elevate the risk of bleeding. Thus, APC variants such as APC(5A), APC(Ca-ins) and APC(36-39) with reduced anticoagulant, but normal signalling function may have therapeutic benefit. Human and murine protein C (5A), (Ca-ins) and (36-39) variants were expressed and characterised. All protein C variants were secreted normally, but 5-20% of the protein C (Ca-ins) variants were secreted as disulphide-linked dimers. Thrombin generation assays suggested reductions in anticoagulant function of 50- to 57-fold for APC(36-39), 22- to 27-fold for APC(Ca-ins) and 14- to 17-fold for APC(5A). Interestingly, whereas human wt APC, APC(36-39) and APC(Ca-ins) were inhibited similarly by protein C inhibitor (t½ - 33 to 39 mins), APC(5A) was inactivated ~9-fold faster (t½ - 4 mins). Using the murine middle cerebral artery occlusion ischaemia/repurfusion injury model, in combination with tPA, APC(36-39), which cannot be enhanced by its cofactor protein S, significantly improved neurological scores, reduced cerebral infarct area by ~50% and reduced oedema ratio. APC(36-39) also significantly reduced bleeding in the brain induced by administration of tPA, whereas wt APC did not. If our data can be extrapolated to clinical settings, then APC(36-39) could represent a feasible adjunctive therapy for ischaemic stroke

Role of CD56-expressing immature biliary epithelial cells in biliary atresia

published_or_final_versio

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating

IFNAR1-Signalling Obstructs ICOS-mediated Humoral Immunity during Non-lethal Blood-Stage Plasmodium Infection

Funding: This work was funded by a Career Development Fellowship (1028634) and a project grant (GRNT1028641) awarded to AHa by the Australian National Health & Medical Research Council (NHMRC). IS was supported by The University of Queensland Centennial and IPRS Scholarships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Evidence for Pervasive Adaptive Protein Evolution in Wild Mice

The relative contributions of neutral and adaptive substitutions to molecular evolution has been one of the most controversial issues in evolutionary biology for more than 40 years. The analysis of within-species nucleotide polymorphism and between-species divergence data supports a widespread role for adaptive protein evolution in certain taxa. For example, estimates of the proportion of adaptive amino acid substitutions (alpha) are 50% or more in enteric bacteria and Drosophila. In contrast, recent estimates of alpha for hominids have been at most 13%. Here, we estimate alpha for protein sequences of murid rodents based on nucleotide polymorphism data from multiple genes in a population of the house mouse subspecies Mus musculus castaneus, which inhabits the ancestral range of the Mus species complex and nucleotide divergence between M. m. castaneus and M. famulus or the rat. We estimate that 57% of amino acid substitutions in murids have been driven by positive selection. Hominids, therefore, are exceptional in having low apparent levels of adaptive protein evolution. The high frequency of adaptive amino acid substitutions in wild mice is consistent with their large effective population size, leading to effective natural selection at the molecular level. Effective natural selection also manifests itself as a paucity of effectively neutral nonsynonymous mutations in M. m. castaneus compared to humans

Disease-specific survival for limited-stage small-cell lung cancer affected by statistical method of assessment

BACKGROUND: In general, prognosis and impact of prognostic/predictive factors are assessed with Kaplan-Meier plots and/or the Cox proportional hazard model. There might be substantive differences from the results using these models for the same patients, if different statistical methods were used, for example, Boag log-normal (cure-rate model), or log-normal survival analysis. METHODS: Cohort of 244 limited-stage small-cell lung cancer patients, were accrued between 1981 and 1998, and followed to the end of 2005. The endpoint was death with or from lung cancer, for disease-specific survival (DSS). DSS at 1-, 3- and 5-years, with 95% confidence limits, are reported for all patients using the Boag, Kaplan-Meier, Cox, and log-normal survival analysis methods. Factors with significant effects on DSS were identified with step-wise forward multivariate Cox and log-normal survival analyses. Then, DSS was ascertained for patients with specific characteristics defined by these factors. RESULTS: The median follow-up of those alive was 9.5 years. The lack of events after 1966 days precluded comparison after 5 years. DSS assessed by the four methods in the full cohort differed by 0–2% at 1 year, 0–12% at 3 years, and 0–1% at 5 years. Log-normal survival analysis indicated DSS of 38% at 3 years, 10–12% higher than with other methods; univariate 95% confidence limits were non-overlapping. Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction significantly impacted DSS. DSS assessed by the Cox and log-normal survival analysis methods for four clinical risk groups differed by 1–6% at 1 year, 15–26% at 3 years, and 0–12% at 5 years; multivariate 95% confidence limits were overlapping in all instances. CONCLUSION: Surgical resection, hemoglobin level, lymph node involvement, and superior vena cava (SVC) obstruction all significantly impacted DSS. Apparent DSS for patients was influenced by the statistical methods of assessment. This would be clinically relevant in the development or improvement of clinical management strategies