Post-mortem dissection of COVID-19: a pathogenic role for macrophages?

Acute respiratory failure is the leading cause of death in severe COVID-19. By combining rapid tissue sampling at autopsy with high dimensional analyses, including measurement of immune cells, proteins and RNA, unparalleled insights into the mechanisms of dysregulated inflammation in COVID-19 have been obtained1–4. Here we summarise some of the conceptual advances revealed by post-mortem studies of severe COVID-19, and make particular reference to the apparent dominance of macrophages, how this may relate to disease pathophysiology, and the opportunities for targeted therapeutic intervention.ACM is supported by a Medical Research Council Clinician Scientist Fellowship (MR/V006118/1). CDL is supported by a Wellcome Trust Clinical Research Career Development Fellowship (206566/Z/17/Z) and receives funding from the UKRI-NIHR COVID-19 Call (MR/V028790/1). PPV is supported by a Wellcome Trust PhD Training Fellowship for Clinicians (214179/Z/18/Z)

The interferon-induced exonuclease ISG20 exerts antiviral activity through upregulation of type I interferon response proteins

The host immune responses to infection lead to the production of type I interferon (IFN), and the upregulation of interferon-stimulated genes (ISGs) reduces virus replication and virus dissemination within a host. Ectopic expression of the interferon-induced 20-kDa exonuclease ISG20 suppressed replication of chikungunya virus and Venezuelan equine encephalitis virus, two mosquito-vectored RNA alphaviruses. Since the replication of alphavirus genomes occurs exclusively in the cytoplasm, the mechanism of nucleus-localized ISG20 inhibition of replication is unclear. In this study, we determined that ISG20 acts as a master regulator of over 100 genes, many of which are ISGs. Specifically, ISG20 upregulated IFIT1 genes and inhibited translation of the alphavirus genome. Furthermore, IFIT1-sensitive alphavirus replication was increased in Isg20−/− mice compared to the replication of wild-type viruses but not in cells ectopically expressing ISG20. We propose that ISG20 acts as an indirect regulator of RNA virus replication in the cytoplasm through the upregulation of many other ISGs.Type I interferon (IFN)-stimulated genes (ISGs) have critical roles in inhibiting virus replication and dissemination. Despite advances in understanding the molecular basis of ISG restriction, the antiviral mechanisms of many remain unclear. The 20-kDa ISG ISG20 is a nuclear 3′–5′ exonuclease with preference for single-stranded RNA (ssRNA) and has been implicated in the IFN-mediated restriction of several RNA viruses. Although the exonuclease activity of ISG20 has been shown to degrade viral RNA in vitro, evidence has yet to be presented that virus inhibition in cells requires this activity. Here, we utilized a combination of an inducible, ectopic expression system and newly generated Isg20−/− mice to investigate mechanisms and consequences of ISG20-mediated restriction. Ectopically expressed ISG20 localized primarily to Cajal bodies in the nucleus and restricted replication of chikungunya and Venezuelan equine encephalitis viruses. Although restriction by ISG20 was associated with inhibition of translation of infecting genomic RNA, degradation of viral RNAs was not observed. Instead, translation inhibition of viral RNA was associated with ISG20-induced upregulation of over 100 other genes, many of which encode known antiviral effectors. ISG20 modulated the production of IFIT1, an ISG that suppresses translation of alphavirus RNAs. Consistent with this observation, the pathogenicity of IFIT1-sensitive alphaviruses was increased in Isg20−/− mice compared to that of wild-type viruses but not in cells ectopically expressing ISG20. Our findings establish an indirect role for ISG20 in the early restriction of RNA virus replication by regulating expression of other ISGs that inhibit translation and possibly other activities in the replication cycle

A rational model of spatial neglect

Spatial neglect has been a phenomenon of interest for perceptual and neuropsychological researchers for decades. However, the underlying cognitive processes remain unclear. We provide a Bayesian framework for the classic line bisection task in spatial neglect, regarding it as rational inferences in the face of uncertain information. A Bayesian observer perceives the left and right endpoints of a line with uncertainty, and leverages prior expectations about line lengths to compensate for this uncertainty. This Bayesian model provides a basis for characterizing different patterns of behavior. Our model also captures the paradoxical cross-over effect observed in earlier studies as a natural outcome when uncertainty is high and the observer falls back on priors. It provides measures that correlate well with measures from other neglect tests, and can accurately distinguish stroke patients from healthy controls. It has the potential to facilitate spatial neglect studies and inform clinical decisions

Fire effects on temperate forest soil C and N storage

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116995/1/eap20112141189.pd

A case of recurrent epilepsy-associated rosette-forming glioneuronal tumor with anaplastic transformation in the absence of therapy.

Rosette-forming glioneuronal tumor (RGNT) most commonly occurs adjacent to the fourth ventricle and therefore rarely presents with epilepsy. Recent reports describe RGNT occurrence in other anatomical locations with considerable morphologic and genetic overlap with the epilepsy-associated dysembryoplastic neuroepithelial tumor (DNET). Examples of RGNT or DNET with anaplastic change are rare, and typically occur in the setting of radiation treatment. We present the case of a 5-year-old girl with seizures, who underwent near total resection of a cystic temporal lobe lesion. Pathology showed morphologic and immunohistochemical features of RGNT, albeit with focally overlapping DNET-like patterns. Resections of residual or recurrent tumor were performed 1 year and 5 years after the initial resection, but no adjuvant radiation or chemotherapy was given. Ten years after the initial resection, surveillance imaging identified new and enhancing nodules, leading to another gross total resection. This specimen showed areas similar to the original tumor, but also high-grade foci with oligodendroglial morphology, increased cellularity, palisading necrosis, microvascular proliferation, and up to 13 mitotic figures per 10 high power fields. Ancillary studies the status by sequencing showed wild-type of the isocitrate dehydrogenase 1 (IDH1), IDH2, and human histone 3.3 (H3F3A) genes, and BRAF studies were negative for mutation or rearrangement. Fluorescence in situ hybridization (FISH) showed codeletion of 1p and 19q limited to the high-grade regions. By immunohistochemistry there was loss of nuclear alpha-thalassemia mental retardation syndrome, X-linked (ATRX) expression only in the high-grade region. Next-generation sequencing showed an fibroblast growth factor receptor receptor 1 (FGFR1) kinase domain internal tandem duplication in three resection specimens. ATRX mutation in the high-grade tumor was confirmed by sequencing which showed a frameshift mutation (p.R1427fs), while the apparent 1p/19q-codeletion by FISH was due to loss of chromosome arm 1p and only partial loss of 19q. Exceptional features of this case include the temporal lobe location, 1p/19q loss by FISH without true whole-arm codeletion, and anaplastic transformation associated with ATRX mutation without radiation or chemotherapy

Resolution of inflammation: Mechanisms and opportunity for drug development

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Uncovering Instabilities in Variational-Quantum Deep Q-Networks

Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of training time to converge. Recent work has started to approach this problem through the lens of quantum computing, which promises theoretical speed-ups for several traditionally hard tasks. In this work, we examine a class of hybrid quantum-classical RL algorithms that we collectively refer to as variational quantum deep Q-networks (VQ-DQN). We show that VQ-DQN approaches are subject to instabilities that cause the learned policy to diverge, study the extent to which this afflicts reproduciblity of established results based on classical simulation, and perform systematic experiments to identify potential explanations for the observed instabilities. Additionally, and in contrast to most existing work on quantum reinforcement learning, we execute RL algorithms on an actual quantum processing unit (an IBM Quantum Device) and investigate differences in behaviour between simulated and physical quantum systems that suffer from implementation deficiencies. Our experiments show that, contrary to opposite claims in the literature, it cannot be conclusively decided if known quantum approaches, even if simulated without physical imperfections, can provide an advantage as compared to classical approaches. Finally, we provide a robust, universal and well-tested implementation of VQ-DQN as a reproducible testbed for future experiments.Comment: Authors Maja Franz, Lucas Wolf, Maniraman Periyasamy contributed equally (name order randomised). To be published in the Journal of The Franklin Institut

Activation of conventional protein kinase C (PKC) is critical in the generation of human neutrophil extracellular traps

BACKGROUND: Activation of NADPH oxidase is required for neutrophil extracellular trap (NET) formation. Protein kinase C (PKC) is an upstream mediator of NADPH oxidase activation and thus likely to have a role in NET formation. METHODS: Pharmacological inhibitors were used to block PKC activity in neutrophils harvested from healthy donor blood. RESULTS: Pan PKC inhibition with Ro-31-8220 (p<0.001), conventional PKC inhibition with Go 6976 (p<0.001) and specific PKCβ inhibition with LY333531 (p<0.01) blocked NET formation in response to PMA. Inhibition of novel and atypical PKC had no effect. LY333531 blocked NET induction by the diacylglycerol analogue OAG (conventional PKC activator) (p<0.001). CONCLUSIONS: Conventional PKCs have a prominent role in NET formation. Furthermore PKCβ is the major isoform implicated in NET formation