Prevention and treatment of murine experimental allergic encephalomyelitis with T cell receptor Vβ-specific antibodies

Experimental allergic encephalomyelitis (EAE) is a model system for T cell-mediated autoimmune disease. Symptoms of EAE are similar to those of multiple sclerosis (MS) in humans. EAE is induced in susceptible animal strains by immunization with myelin basic protein (MBP) and potent adjuvant. The major T cell response to MBP in B10.PL mice is directed towards an NH2-terminal epitope and involves T cells expressing either V beta 8.2 or V beta 13 gene segments. Animals treated with a TCR V beta 8-specific mAb have a reduced incidence of EAE. We report here that the in vivo administration of a combination of anti-V beta 8.2 and anti-V beta 13 mAbs results in a long-term elimination of T cells involved in the response to MBP. When given before MBP immunization, anti-TCR antibody treatment leads to nearly complete protection against EAE. Antibody treatment also results in a dramatic reversal of paralysis in diseased animals. Thus, treatment with a combination of V beta-specific antibodies is a very effective therapy for the prevention and treatment of EAE. It is hoped that the future characterization of TCR V gene usage in human autoimmune diseases may lead to similar strategies of immune intervention

Amortised learning by wake-sleep

Models that employ latent variables to capture structure in observed data lie at the heart of many current unsupervised learning algorithms, but exact maximum-likelihood learning for powerful and flexible latent-variable models is almost always intractable. Thus, state-of-the-art approaches either abandon the maximum-likelihood framework entirely, or else rely on a variety of variational approximations to the posterior distribution over the latents. Here, we propose an alternative approach that we call amortised learning. Rather than computing an approximation to the posterior over latents, we use a wake-sleep Monte-Carlo strategy to learn a function that directly estimates the maximum-likelihood parameter updates. Amortised learning is possible whenever samples of latents and observations can be simulated from the generative model, treating the model as a “black box”. We demonstrate its effectiveness on a wide range of complex models, including those with latents that are discrete or supported on non-Euclidean spaces

Model-based kernel sum rule: kernel Bayesian inference with probabilistic model

Kernel Bayesian inference is a principled approach to nonparametric inference in probabilistic graphical models, where probabilistic relationships between variables are learned from data in a nonparametric manner. Various algorithms of kernel Bayesian inference have been developed by combining kernelized basic probabilistic operations such as the kernel sum rule and kernel Bayes’ rule. However, the current framework is fully nonparametric, and it does not allow a user to flexibly combine nonparametric and model-based inferences. This is inefficient when there are good probabilistic models (or simulation models) available for some parts of a graphical model; this is in particular true in scientific fields where “models” are the central topic of study. Our contribution in this paper is to introduce a novel approach, termed the model-based kernel sum rule (Mb-KSR), to combine a probabilistic model and kernel Bayesian inference. By combining the Mb-KSR with the existing kernelized probabilistic rules, one can develop various algorithms for hybrid (i.e., nonparametric and model-based) inferences. As an illustrative example, we consider Bayesian filtering in a state space model, where typically there exists an accurate probabilistic model for the state transition process. We propose a novel filtering method that combines model-based inference for the state transition process and data-driven, nonparametric inference for the observation generating process. We empirically validate our approach with synthetic and real-data experiments, the latter being the problem of vision-based mobile robot localization in robotics, which illustrates the effectiveness of the proposed hybrid approach

Mantle earthquakes frozen in mylonitized ultramafic pseudotachylytes of spinel-lherzolite facies.

We report a new type of ultramafi c pseudotachylyte that forms a fault- and injection-vein network hosted in the mantle-derived Balmuccia peridotite (Italy). In the fault vein the pseudotachylyte is now deformed and recrystallized into a spinel-lherzolite facies ultramylonite, made of a fi ne (<2 μm) aggregate of olivine, orthopyroxene, clinopyroxene, and spinel, with small amounts of amphibole and dolomite. Electron backscattered diffraction study of the ultramylonite shows a clear crystallographic preferred orientation (CPO) of olivine. The fault vein pseudotachylyte overprints a spinel-lherzolite facies amphibole-bearing mylonite, indicating that shear localization accompanying chemical reaction had taken place in the peridotite before seismic slip produced frictional melting. The occurrence of amphibole in the host mylonite and that of dolomite as well as amphibole in the matrices of ultramylonite and pseudotachylyte may indicate that fl uid was present and had evolved in its composition from H2O-rich to CO2-rich during ductile deformation with metamorphic reactions, which may account for the observed rheological transition from ductile to brittle behavior. The spinel-lherzolite facies assemblage in mylonites, P-T estimations from pyroxene geothermometry and carbonate reactions, and the type of olivine CPO in deformed pseudotachylyte indicate that both the preseismic and the postseismic ductile deformations occurred at ~800 °C and 0.7–1.1 GPa

Assessing the Effectiveness of Phone Call Proactive Naloxone Co-Prescribing Enrollment

Opioid use is increasing at never-before-seen rates. As a result, it is imperative that medical facilities educate and provide resources for those who may be at risk of an opioid overdose. With our study, we aimed to see the demographics of our population here at Rowan Medicine and identify associations of those participating in our naloxone co-prescription program. Majority of enrollees in our program were aged 50 or older and identified as Caucasian. A large proportion also reported being unable to work. Given this information, improvements in our naloxone coprescription program may include spreading more awareness of the benefits of naloxone to minority populations, as well as to the younger population at risk of an opioid overdose

What Motivates Patients to Enroll in a Naloxone Co-Prescribing Program?

Patients were contacted via phone call to establish knowledge of and prescription status regarding naloxone. They were then invited to enroll in a research study consisting of two online surveys. The patients who had been prescribed naloxone by the time the study had started ranked being persuaded by a medical professional as being the most important reason for accepting the naloxone prescription. Insufficient data collected during the six-week time frame to draw statistically significant conclusions about what motivates patients to receive naloxone co-prescriptions. Correlations seen in this study are interesting and warrant further investigation

Observation of thundercloud-related gamma rays and neutrons in Tibet

During the 2010 rainy season in Yangbajing (4300 m above sea level) in Tibet, China, a long-duration count enhancement associated with thunderclouds was detected by a solar-neutron telescope and neutron monitors installed at the Yangbajing Comic Ray Observatory. The event, lasting for ∼40  min, was observed on July 22, 2010. The solar-neutron telescope detected significant γ-ray signals with energies >40  MeV in the event. Such a prolonged high-energy event has never been observed in association with thunderclouds, clearly suggesting that electron acceleration lasts for 40 min in thunderclouds. In addition, Monte Carlo simulations showed that >10  MeV γ rays largely contribute to the neutron monitor signals, while >1  keV neutrons produced via a photonuclear reaction contribute relatively less to the signals. This result suggests that enhancements of neutron monitors during thunderstorms are not necessarily clear evidence for neutron production, as previously thought