GPX4 regulates cellular necrosis and host resistance in Mycobacterium tuberculosis infection

Cellular necrosis during Mycobacterium tuberculosis (Mtb) infection promotes both immunopathology and bacterial dissemination. Glutathione peroxidase-4 (Gpx4) is an enzyme that plays a critical role in preventing iron-dependent lipid peroxidation–mediated cell death (ferroptosis), a process previously implicated in the necrotic pathology seen in Mtb-infected mice. Here, we document altered GPX4 expression, glutathione levels, and lipid peroxidation in patients with active tuberculosis and assess the role of this pathway in mice genetically deficient in or overexpressing Gpx4. We found that Gpx4-deficient mice infected with Mtb display substantially increased lung necrosis and bacterial burdens, while transgenic mice overexpressing the enzyme show decreased bacterial loads and necrosis. Moreover, Gpx4-deficient macrophages exhibited enhanced necrosis upon Mtb infection in vitro, an outcome suppressed by the lipid peroxidation inhibitor, ferrostatin-1. These findings provide support for the role of ferroptosis in Mtb-induced necrosis and implicate the Gpx4/GSH axis as a target for host-directed therapy of tuberculosis

Activation of Ventral Tegmental Area 5-HT2C Receptors Reduces Incentive Motivation

FUNDING AND DISCLOSURE The research was funded by Wellcome Trust (WT098012) to LKH; and National Institute of Health (DK056731) and the Marilyn H. Vincent Foundation to MGM. The University of Michigan Transgenic Core facility is partially supported by the NIH-funded University of Michigan Center for Gastrointestinal Research (DK034933). The remaining authors declare no conflict of interest. ACKNOWLEDGMENTS We thank Dr Celine Cansell, Ms Raffaella Chianese and the staff of the Medical Research Facility for technical assistance. We thank Dr Vladimir Orduña for the scientific advice and technical assistance.Peer reviewedPublisher PD

Rewriting a Deep Generative Model

A deep generative model such as a GAN learns to model a rich set of semantic and physical rules about the target distribution, but up to now, it has been obscure how such rules are encoded in the network, or how a rule could be changed. In this paper, we introduce a new problem setting: manipulation of specific rules encoded by a deep generative model. To address the problem, we propose a formulation in which the desired rule is changed by manipulating a layer of a deep network as a linear associative memory. We derive an algorithm for modifying one entry of the associative memory, and we demonstrate that several interesting structural rules can be located and modified within the layers of state-of-the-art generative models. We present a user interface to enable users to interactively change the rules of a generative model to achieve desired effects, and we show several proof-of-concept applications. Finally, results on multiple datasets demonstrate the advantage of our method against standard fine-tuning methods and edit transfer algorithms.Comment: ECCV 2020 (oral). Code at https://github.com/davidbau/rewriting. For videos and demos see https://rewriting.csail.mit.edu

Speed/Accuracy Trade-Off between the Habitual and the Goal-Directed Processes

Instrumental responses are hypothesized to be of two kinds: habitual and goal-directed, mediated by the sensorimotor and the associative cortico-basal ganglia circuits, respectively. The existence of the two heterogeneous associative learning mechanisms can be hypothesized to arise from the comparative advantages that they have at different stages of learning. In this paper, we assume that the goal-directed system is behaviourally flexible, but slow in choice selection. The habitual system, in contrast, is fast in responding, but inflexible in adapting its behavioural strategy to new conditions. Based on these assumptions and using the computational theory of reinforcement learning, we propose a normative model for arbitration between the two processes that makes an approximately optimal balance between search-time and accuracy in decision making. Behaviourally, the model can explain experimental evidence on behavioural sensitivity to outcome at the early stages of learning, but insensitivity at the later stages. It also explains that when two choices with equal incentive values are available concurrently, the behaviour remains outcome-sensitive, even after extensive training. Moreover, the model can explain choice reaction time variations during the course of learning, as well as the experimental observation that as the number of choices increases, the reaction time also increases. Neurobiologically, by assuming that phasic and tonic activities of midbrain dopamine neurons carry the reward prediction error and the average reward signals used by the model, respectively, the model predicts that whereas phasic dopamine indirectly affects behaviour through reinforcing stimulus-response associations, tonic dopamine can directly affect behaviour through manipulating the competition between the habitual and the goal-directed systems and thus, affect reaction time

Effort-related functions of nucleus accumbens dopamine and associated forebrain circuits

Background Over the last several years, it has become apparent that there are critical problems with the hypothesis that brain dopamine (DA) systems, particularly in the nucleus accumbens, directly mediate the rewarding or primary motivational characteristics of natural stimuli such as food. Hypotheses related to DA function are undergoing a substantial restructuring, such that the classic emphasis on hedonia and primary reward is giving way to diverse lines of research that focus on aspects of instrumental learning, reward prediction, incentive motivation, and behavioral activation. Objective The present review discusses dopaminergic involvement in behavioral activation and, in particular, emphasizes the effort-related functions of nucleus accumbens DA and associated forebrain circuitry. Results The effects of accumbens DA depletions on food-seeking behavior are critically dependent upon the work requirements of the task. Lever pressing schedules that have minimal work requirements are largely unaffected by accumbens DA depletions, whereas reinforcement schedules that have high work (e.g., ratio) requirements are substantially impaired by accumbens DA depletions. Moreover, interference with accumbens DA transmission exerts a powerful influence over effort-related decision making. Rats with accumbens DA depletions reallocate their instrumental behavior away from food-reinforced tasks that have high response requirements, and instead, these rats select a less-effortful type of food-seeking behavior. Conclusions Along with prefrontal cortex and the amygdala, nucleus accumbens is a component of the brain circuitry regulating effort-related functions. Studies of the brain systems regulating effort-based processes may have implications for understanding drug abuse, as well as energy-related disorders such as psychomotor slowing, fatigue, or anergia in depression

Bilateral Acetabular Fractures Associated with Seizures: A Report of 2 Cases.

CASES:Two elderly women with significant medical comorbidities presented to a community hospital setting after new-onset generalized seizure activity while in bed without a history of trauma. Both were diagnosed by computed tomography scan with bilateral acetabular fractures. Owing to altered mental status from a postictal period, both were unable to be reliably assessed for pain, which resulted in a diagnostic delay. CONCLUSIONS:These cases highlight the importance of a proper secondary survey on mentally altered patients even without a history of significant trauma, a high index of suspicion for associated injuries in seizure patients, and the use of appropriate advanced imaging