Aβ43 aggregates exhibit enhanced prion-like seeding activity in mice.

When injected into genetically modified mice, aggregates of the amyloid-β (Aβ) peptide from the brains of Alzheimer's disease (AD) patients or transgenic AD mouse models seed cerebral Aβ deposition in a prion-like fashion. Within the brain, Aβ exists as a pool of distinct C-terminal variants with lengths ranging from 37 to 43 amino acids, yet the relative contribution of individual C-terminal Aβ variants to the seeding behavior of Aβ aggregates remains unknown. Here, we have investigated the relative seeding activities of Aβ aggregates composed exclusively of recombinant Aβ38, Aβ40, Aβ42, or Aβ43. Cerebral Aβ42 levels were not increased in AppNL-F knock-in mice injected with Aβ38 or Aβ40 aggregates and were only increased in a subset of mice injected with Aβ42 aggregates. In contrast, significant accumulation of Aβ42 was observed in the brains of all mice inoculated with Aβ43 aggregates, and the extent of Aβ42 induction was comparable to that in mice injected with brain-derived Aβ seeds. Mice inoculated with Aβ43 aggregates exhibited a distinct pattern of cerebral Aβ pathology compared to mice injected with brain-derived Aβ aggregates, suggesting that recombinant Aβ43 may polymerize into a unique strain. Our results indicate that aggregates containing longer Aβ C-terminal variants are more potent inducers of cerebral Aβ deposition and highlight the potential role of Aβ43 seeds as a crucial factor in the initial stages of Aβ pathology in AD

Environmental novelty exacerbates stress hormones and Aβ pathology in an Alzheimer’s model

Cognitive stimulation has been proposed as a non-pharmacological intervention to be used in primary, secondary and tertiary prevention approaches for Alzheimer’s disease. A common familial Alzheimer’s disease transgenic model showed heightened levels of the stress hormone, corticosterone. When exposed to periodic enhanced cognitive stimulation, these animals demonstrated further heightened levels of corticosterone as well as increased Aβ pathology. Hence, Alzheimer’s disease may be associated with hypothalamic-pituitary-adrenal (HPA) axis dysfunction, causing stimulatory environments to become stress-inducing, leading to a glucocorticoid-pathology cycle contributing to further Aβ release and plaque formation. This finding suggests that stimulation-based interventions and local environments for people with Alzheimer’s disease need to be designed to minimise a stress response that may exacerbate brain pathology

"It's making contacts" : notions of social capital and implications for widening access to medical education

Acknowledgements Our thanks to the Medical Schools Council (MSC) of the UK for funding Study A; REACH Scotland for funding Study B; and Queen Mary University of London, and to the medical school applicants and students who gave their time to be interviewed. Our thanks also to Dr Sean Zhou and Dr Sally Curtis, and Manjul Medhi, for their help with data collection for studies A and B respectively. Our thanks also to Dr Lara Varpio, Uniformed Services University of the USA, for her advice and guidance on collating data sets and her comments on the draft manuscript.Peer reviewedPublisher PD

Selecting patients for randomized trials: a systematic approach based on risk group

BACKGROUND: A key aspect of randomized trial design is the choice of risk group. Some trials include patients from the entire at-risk population, others accrue only patients deemed to be at increased risk. We present a simple statistical approach for choosing between these approaches. The method is easily adapted to determine which of several competing definitions of high risk is optimal. METHOD: We treat eligibility criteria for a trial, such as a smoking history, as a prediction rule associated with a certain sensitivity (the number of patients who have the event and who are classified as high risk divided by the total number patients who have an event) and specificity (the number of patients who do not have an event and who do not meet criteria for high risk divided by the total number of patients who do not have an event). We then derive simple formulae to determine the proportion of patients receiving intervention, and the proportion who experience an event, where either all patients or only those at high risk are treated. We assume that the relative risk associated with intervention is the same over all choices of risk group. The proportion of events and interventions are combined using a net benefit approach and net benefit compared between strategies. RESULTS: We applied our method to design a trial of adjuvant therapy after prostatectomy. We were able to demonstrate that treating a high risk group was superior to treating all patients; choose the optimal definition of high risk; test the robustness of our results by sensitivity analysis. Our results had a ready clinical interpretation that could immediately aid trial design. CONCLUSION: The choice of risk group in randomized trials is usually based on rather informal methods. Our simple method demonstrates that this decision can be informed by simple statistical analyses

What is the correct cost functional for variational data assimilation?

Variational approaches to data assimilation, and weakly constrained four dimensional variation (WC-4DVar) in particular, are important in the geosciences but also in other communities (often under different names). The cost functions and the resulting optimal trajectories may have a probabilistic interpretation, for instance by linking data assimilation with maximum aposteriori (MAP) estimation. This is possible in particular if the unknown trajectory is modelled as the solution of a stochastic differential equation (SDE), as is increasingly the case in weather forecasting and climate modelling. In this situation, the MAP estimator (or “most probable path” of the SDE) is obtained by minimising the Onsager–Machlup functional. Although this fact is well known, there seems to be some confusion in the literature, with the energy (or “least squares”) functional sometimes been claimed to yield the most probable path. The first aim of this paper is to address this confusion and show that the energy functional does not, in general, provide the most probable path. The second aim is to discuss the implications in practice. Although the mentioned results pertain to stochastic models in continuous time, they do have consequences in practice where SDE’s are approximated by discrete time schemes. It turns out that using an approximation to the SDE and calculating its most probable path does not necessarily yield a good approximation to the most probable path of the SDE proper. This suggest that even in discrete time, a version of the Onsager–Machlup functional should be used, rather than the energy functional, at least if the solution is to be interpreted as a MAP estimator

Combination of G-CSF and a TLR4 inhibitor reduce inflammation and promote regeneration in a mouse model of ACLF

BACKGROUND & AIMS: Acute-on-chronic liver failure (ACLF) is characterised by high short-term mortality, systemic inflammation, and failure of hepatic regeneration. Its treatment is an unmet medical need. This study was conducted to explore whether combining TAK-242, a Toll-like receptor-4 (TLR4) antagonist, with Granulocyte-Colony Stimulating Factor (G-CSF) targets inflammation whilst enhancing liver regeneration. METHODS: Two mouse models of ACLF were investigated. Chronic liver injury was induced by carbon tetrachloride followed by either lipopolysaccharide (LPS) or galactosamine (GalN) as extrahepatic or hepatic insults, respectively. G-CSF and/or TLR4-antagonist, TAK-242, were administered daily. The treatment duration was 24h and 5d in the LPS model and 48h in the GalN model, respectively. RESULTS: In a LPS-induced ACLF mouse model treatment with G-CSF was associated with a significant mortality of 66% after 48 hours compared with 0% without G-CSF. Addition of TAK-242 to G-CSF abrogated mortality (0%) and significantly reduced liver cell death, macrophage infiltration and inflammation. In the GalN model, both G-CSF and TAK-242, when used individually, reduced liver injury but their combination was significantly more effective. G-CSF treatment, with or without TAK-242, was associated with activation of the pro-regenerative and anti-apoptotic STAT3 pathway. LPS-driven ACLF was characterized by p21 over-expression suggesting hepatic senescence and inhibition of hepatocyte regeneration. While TAK-242 treatment mitigated the effect on senescence, G-CSF, when co-administered with TAK-242, resulted in a significant increase of markers of hepatocyte regeneration. CONCLUSION: TLR4 inhibition with TAK-242 rescued G-CSF-driven cell death, inflammation, enhanced tissue repair, and significantly induced regeneration thus suggesting that the combination of G-CSF and TAK-242 is a novel approach for the treatment of ACLF. LAY SUMMARY: The combinatorial therapy of Granulocyte-Colony Stimulating Factor and TAK-242, a Toll-like Receptor-4 inhibitor, achieves the dual aim of reducing hepatic inflammation and inducing liver regeneration for the treatment of acute-on-chronic liver failure

The role of ongoing dendritic oscillations in single-neuron dynamics

The dendritic tree contributes significantly to the elementary computations a neuron performs while converting its synaptic inputs into action potential output. Traditionally, these computations have been characterized as temporally local, near-instantaneous mappings from the current input of the cell to its current output, brought about by somatic summation of dendritic contributions that are generated in spatially localized functional compartments. However, recent evidence about the presence of oscillations in dendrites suggests a qualitatively different mode of operation: the instantaneous phase of such oscillations can depend on a long history of inputs, and under appropriate conditions, even dendritic oscillators that are remote may interact through synchronization. Here, we develop a mathematical framework to analyze the interactions of local dendritic oscillations, and the way these interactions influence single cell computations. Combining weakly coupled oscillator methods with cable theoretic arguments, we derive phase-locking states for multiple oscillating dendritic compartments. We characterize how the phase-locking properties depend on key parameters of the oscillating dendrite: the electrotonic properties of the (active) dendritic segment, and the intrinsic properties of the dendritic oscillators. As a direct consequence, we show how input to the dendrites can modulate phase-locking behavior and hence global dendritic coherence. In turn, dendritic coherence is able to gate the integration and propagation of synaptic signals to the soma, ultimately leading to an effective control of somatic spike generation. Our results suggest that dendritic oscillations enable the dendritic tree to operate on more global temporal and spatial scales than previously thought

Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time

Background Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique. Methods We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool. Results Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small. Conclusion Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for. The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses