The trafficking and targeting of P2X receptors

The functional expression of P2X receptors at the plasma membrane is dependent on their trafficking along secretory and endocytic pathways. There are seven P2X receptor subunits, and these differ in their subcellular distributions because they have very different trafficking properties. Some are retained within the endoplasmic reticulum (ER), while others are predominantly at the cell surface or within endosomes and lysosomes. Changes in recruitment of receptors to and from the plasma membrane provides a way of rapidly up- or down-regulating the cellular response to adenosine triphosphate (ATP). An additional layer of regulation is the targeting of these receptors within the membranes of each compartment, which affects their stability, function and the nature of the effector proteins with which they form signaling complexes. The trafficking and targeting of P2X receptors is regulated by their interactions with other proteins and with lipids and we can expect this to vary in a cell-type specific manner and in response to changes in the environment giving rise to differences in receptor activity and function

P2X receptor trafficking in neurons is subunit specific

P2X receptors within the CNS mediate excitatory synaptic transmission and also act presynaptically to modulate neurotransmitter release. We have studied the targeting and trafficking of P2X4 and P2X2 receptors heterologously expressed in cultured olfactory bulb neurons. Homomeric P2X4 receptors had a punctate distribution, and many of the puncta colocalized with early endosomes. In contrast, P2X2 receptors were primarily localized at the plasma membrane. By antibody-labeling of surface receptors in living neurons, we showed that P2X4 receptors undergo rapid constitutive internalization and subsequent reinsertion into the plasma membrane, whereas P2X2 receptors were not regulated in such a way. The internalization of P2X4 receptors was dynamin-dependent, and the binding of ATP enhanced the basal rate of retrieval in a Ca2+-independent manner. The presence of the P2X4 subunit in a P2X4/6 heteromer governed the trafficking properties of the receptor. P2X receptors acted presynaptically to enhance the release of glutamate, suggesting that the regulated cycling of P2X4-containing receptors might provide a mechanism for modulation of synaptic transmission

A novel tool to measure extracellular glutamate in the Zebrafish nervous system in vivo

Glutamate is the major excitatory neurotransmitter in the brain. Its release and eventual recycling are key to rapid sustained neural activity. We have paired the gfap promoter region with the glutamate reporter molecule, iGluSnFR, to drive expression in glial cells throughout the nervous system. Tg(gfap:iGluSnFR) is expressed on the glial membrane of Müller glia cells in the retina, which rapidly respond to stimulation and the release of extracellular glutamate. As glial cells are associated with most, if not all, synapses, Tg(gfap:iGluSnFR) is a novel and exciting tool to measure neuronal activity and extracellular glutamate dynamics in many regions of the nervous system. Glutamate is the major excitatory neurotransmitter in the brain. Its release and eventual recycling are key to rapid sustained neural activity.1 Glial cells play a key role in the uptake and recycling of glutamate from the synaptic cleft. iGluSnFR has been used to study synaptic activity by measuring glutamate dynamics in the zebrafish nervous system.2,3 Previous work has also used iGluSnFR in glial cells; however, this was done transiently in the mouse using viral vectors.2,4 As such, we designed a transgene to stably express iGluSnFR in the glial cells of the zebrafish nervous system. We report a novel transgenic zebrafish, Tg(gfap:iGluSnFR), that displays the glutamate-sensitive fluorescent reporter iGluSnFR specifically on the membrane of glial cells (Figure 1A–C). This molecule is expressed on the glial membrane in many brain regions and rapidly responds to stimulation and the release of extracellular glutamate (Figure 1D–F, Supplementary Data; Supplementary Data are available online at www.liebertpub.com/zeb). Thus, pairing the sensitivity of iGluSnFR and optical transparency of the zebrafish provides a powerful tool for understanding glutamate dynamics in neural tissues in vivo

Amplification of MHD waves in swirling astrophysical flows

Recently it was found that helical magnetized flows efficiently amplify Alfv\'en waves (Rogava et al. 2003, A&A, v.399, p.421). This robust and manifold nonmodal effect was found to involve regimes of transient algebraic growth (for purely ejectional flows), and exponential instabilities of both usual and parametric nature. However the study was made in the incompressible limit and an important question remained open - whether this amplification is inherent to swirling MHD flows per se and what is the degree of its dependence on the incompressibility condition. In this paper, in order to clear up this important question, we consider full compressible spectrum of MHD modes: Alfv\'en waves (AW), slow magnetosonic waves (SMW) and fast magnetosonic waves (FMW). We find that helical flows inseparably blend these waves with each other and make them unstable, creating the efficient energy transfer from the mean flow to the waves. The possible role of these instabilities for the onset of the MHD turbulence, self-heating of the flow and the overall dynamics of astrophysical flows are discussed.Comment: 8 pages, 9 figures, accepted for publication (18.03.2003) in the "Astronomy and Astrophysics

Swirling astrophysical flows - efficient amplifiers of Alfven waves

We show that a helical shear flow of a magnetized plasma may serve as an efficient amplifier of Alfven waves. We find that even when the flow is purely ejectional (i.e., when no rotation is present) Alfven waves are amplified through the transient, shear-induced, algebraic amplification process. Series of transient amplifications, taking place sequentially along the flow, may result in a cascade amplification of these waves. However, when a flow is swirling or helical (i.e., some rotation is imposed on the plasma motion), Alfven waves become subject to new, much more powerful shear instabilities. In this case, depending on the type of differential rotation, both usual and parametric instabilities may appear. We claim that these phenomena may lead to the generation of large amplitude Alfven waves and the mechanism may account for the appearance of such waves in the solar atmosphere, in accretion-ejecion flows and in accretion columns. These processes may also serve as an important initial (linear and nonmodal) phase in the ultimate subcritical transition to MHD Alfvenic turbulence in various kinds of astrophysical shear flows.Comment: 12 pages, 11 figures, accepted for publication (25-11-02) in Astronomy and Astrophysic

Are Jurors Intuitive Statisticians? Bayesian Causal Reasoning in Legal Contexts

In criminal trials, evidence often involves a degree of uncertainty and decision-making includes moving from the initial presumption of innocence to inference about guilt based on that evidence. The jurors’ ability to combine evidence and make accurate intuitive probabilistic judgments underpins this process. Previous research has shown that errors in probabilistic reasoning can be explained by a misalignment of the evidence presented with the intuitive causal models that people construct. This has been explored in abstract and context-free situations. However, less is known about how people interpret evidence in context-rich situations such as legal cases. The present study examined participants’ intuitive probabilistic reasoning in legal contexts and assessed how people’s causal models underlie the process of belief updating in the light of new evidence. The study assessed whether participants update beliefs in line with Bayesian norms and if errors in belief updating can be explained by the causal structures underpinning the evidence integration process. The study was based on a recent case in England where a couple was accused of intentionally harming their baby but was eventually exonerated because the child’s symptoms were found to be caused by a rare blood disorder. Participants were presented with a range of evidence, one piece at a time, including physical evidence and reports from experts. Participants made probability judgments about the abuse and disorder as causes of the child’s symptoms. Subjective probability judgments were compared against Bayesian norms. The causal models constructed by participants were also elicited. Results showed that overall participants revised their beliefs appropriately in the right direction based on evidence. However, this revision was done without exact Bayesian computation and errors were observed in estimating the weight of evidence. Errors in probabilistic judgments were partly accounted for, by differences in the causal models representing the evidence. Our findings suggest that understanding causal models that guide people’s judgments may help shed light on errors made in evidence integration and potentially identify ways to address accuracy in judgment

Belief updating in the face of misinformation: The role of source reliability

This paper investigates the process of belief updating in the presence of contradictory and potentially misleading information, focusing on the impact of source reliability. Across four experiments, we examined how individuals revise their beliefs when confronted with retracted information and varying source credibility. Experiment 1 revealed that participants discounted retracted information and reverted to their prior beliefs, in contrast to the Continued Influence Effect commonly reported in the literature. Experiment 2 demonstrated that source reliability significantly influences belief updating: reliable sources led participants to discount initial allegations more effectively than unreliable sources. Experiments 3 and 4 examined how people update their beliefs given opposing sources of differing reliability; we found that participants appropriately incorporated source reliability and penalised sources that were corrected, regardless of the corrector's reliability. Additionally, in contrast to previous research, both trustworthiness and expertise contributed to judgments of source reliability. Our results resolve some of the mixed findings in previous research, and highlight that individuals' belief updating are rationally sensitive to differences in source reliability. Our findings have broad implications for correcting misinformation in political, medical, and other applied contexts, and further underscore the need to ground misinformation correction strategies in robust psychological research

Human-AI Interaction Paradigm for Evaluating Explainable Artificial Intelligence

This article seeks to propose a framework and corresponding paradigm for evaluating explanations provided by explainable artificial intelligence (XAI). The article argues for the need for evaluation paradigms – different people performing different tasks in different contexts will react differently to different explanations. It reviews previous research evaluating XAI explanations while also identifying the main contribution of this work – a flexible paradigm researchers can use to evaluate XAI models, rather than a list of factors. The article then outlines a framework which offers causal relationships between five key factors – mental models, probability estimates, trust, knowledge, and performance. It then outlines a paradigm consisting of a training, testing and evaluation phase. The work is discussed in relation to predictive models, guidelines for XAI developers, and adaptive explainable artificial intelligence - a recommender system capable of predicting what the preferred explanations would be for a specific domain-expert on a particular task

Causal judgments about atypical actions are influenced by agents' epistemic states

A prominent finding in causal cognition research is people’s tendency to attribute increased causality to atypical actions. If two agents jointly cause an outcome (conjunctive causation), but differ in how frequently they have performed the causal action before, people judge the atypically acting agent to have caused the outcome to a greater extent. In this paper, we argue that it is the epistemic state of an abnormally acting agent, rather than the abnormality of their action, that is driving people's causal judgments. Given the predictability of the normally acting agent's behaviour, the abnormal agent is in a better position to foresee the consequences of their action. We put this hypothesis to test in four experiments. In Experiment 1, we show that people judge the atypical agent as more causal than the normally acting agent, but also judge the atypical agent to have an epistemic advantage. In Experiment 2, we find that people do not judge a causal difference if no epistemic advantage for the abnormal agent arises. In Experiment 3, we replicate these findings in a scenario in which the abnormal agent's epistemic advantage generalises to a novel context. In Experiment 4, we extend these findings to mental states more broadly construed and develop a Bayesian network model that predicts the degree of outcome-oriented mental states based on action normality and epistemic states. We find that people infer mental states like desire and intention to a greater extent from abnormal behaviour when this behaviour is accompanied by an epistemic advantage. We discuss these results in light of current theories and research on people's preference for abnormal causes