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Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1 , 2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3 – 5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7 , 8 and is critical for integrating self-motion (path integration) 6 , 7 , 9 and planning direct trajectories to goals (vector-based navigation) 7 , 10 , 11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments—optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7 , 10 , 11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments. Grid-like representations emerge spontaneously within a neural network trained to self-localize, enabling the agent to take shortcuts to destinations using vector-based navigation.

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions “How does the Earth system respond to forcing?” and “What are the origins and consequences of systematic model biases?” and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions.How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?

Among hospitalized patients with Covid-19, treatment with dexamethasone resulted in lower 28-day mortality than usual care, according to the level of respiratory support the patients were receiving, indicating a possible correlation between efficacy and the stage of infection.

Pancreatic cancer is not caused by a specific series of genetic alterations that occur sequentially but by one, or few, catastrophic events that result in simultaneous oncogenic genetic rearrangements, giving rise to highly aggressive tumours. Pancreatic cancer genome evolution Pancreatic cancer is a highly aggressive tumour type. With a view to examining the evolution of rapid tumour progression in this cancer, this paper presents an analysis of more than a hundred tumour-enriched whole-genome sequences from primary and metastatic pancreas cancers obtained from collaborating hospitals in Canada and the United States of America. Challenging a traditional model of progressive evolution based on ordered mutations in several genes, the authors find support for a role of complex rearrangements and chromothripsis in pancreatic cancer progression, which suggests that the genomic instability that marks this cancer may be explained by a punctuated equilibrium model. Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development 1 . The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations 2 , 3 , 4 , 5 ( KRAS , followed by CDKN2A , then TP53 and SMAD4 ); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage 2 , 5 , 6 , 7 , 8 , 9 , indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage 10 . However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection 11 , suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory 12 . In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols and because of the large climate variability presently limits confidence in attribution of observed changes.

Genetic variation for disease resistance is present in salmonid fish; however, the molecular basis is poorly understood, and biomarkers of disease susceptibility/resistance are unavailable. Previously, we selected a line of rainbow trout for high survival following standardized challenge with Flavobacterium psychrophilum ( Fp ), the causative agent of bacterial cold water disease. The resistant line (ARS-Fp-R) exhibits over 60 percentage points higher survival compared to a reference susceptible line (ARS-Fp-S). To gain insight into the differential host response between genetic lines, we compared the plasma proteomes from day 6 after intramuscular challenge. Pooled plasma from unhandled, PBS-injected, and Fp -injected groups were simultaneously analyzed using a TMT 6-plex label, and the relative abundance of 513 proteins was determined. Data are available via ProteomeXchange, with identifier PXD041308, and the relative protein abundance values were compared to mRNA measured from a prior, whole-body RNA-seq dataset. Our results identified a subset of differentially abundant intracellular proteins was identified, including troponin and myosin, which were not transcriptionally regulated, suggesting that these proteins were released into plasma following pathogen-induced tissue damage. A separate subset of high-abundance, secreted proteins were transcriptionally regulated in infected fish. The highest differentially expressed protein was a C1q family member (designated complement C1q-like protein 3; C1q-LP3) that was upregulated over 20-fold in the infected susceptible line while only modestly upregulated, 1.8-fold, in the infected resistant line. Validation of biomarkers was performed using immunoassays and C1q-LP3, skeletal muscle troponin C, cathelcidin 2, haptoglobin, leptin, and growth and differentiation factor 15 exhibited elevated concentration in susceptible line plasma. Complement factor H-like 1 exhibited higher abundance in the resistant line compared to the susceptible line in both control and challenged fish and thus was a baseline differentiator between lines. C1q-LP3 and STNC were elevated in Atlantic salmon plasma following experimental challenge with Fp . In summary, these findings further the understanding of the differential host response to Fp and identifies salmonid biomarkers that may have use for genetic line evaluation and on-farm health monitoring.

Background The objective of this study was to investigate cellular bioenergetics in primary skin fibroblasts derived from patients with amyotrophic lateral sclerosis (ALS) and to determine if they can be used as classifiers for patient stratification. Methods We assembled a collection of unprecedented size of fibroblasts from patients with sporadic ALS (sALS, n  = 171), primary lateral sclerosis (PLS, n  = 34), ALS/PLS with C9orf72 mutations ( n  = 13), and healthy controls ( n  = 91). In search for novel ALS classifiers, we performed extensive studies of fibroblast bioenergetics, including mitochondrial membrane potential, respiration, glycolysis, and ATP content. Next, we developed a machine learning approach to determine whether fibroblast bioenergetic features could be used to stratify patients. Results Compared to controls, sALS and PLS fibroblasts had higher average mitochondrial membrane potential, respiration, and glycolysis, suggesting that they were in a hypermetabolic state. Only membrane potential was elevated in C9Orf72 lines. ATP steady state levels did not correlate with respiration and glycolysis in sALS and PLS lines. Based on bioenergetic profiles, a support vector machine (SVM) was trained to classify sALS and PLS with 99% specificity and 70% sensitivity. Conclusions sALS, PLS, and C9Orf72 fibroblasts share hypermetabolic features, while presenting differences of bioenergetics. The absence of correlation between energy metabolism activation and ATP levels in sALS and PLS fibroblasts suggests that in these cells hypermetabolism is a mechanism to adapt to energy dissipation. Results from SVM support the use of metabolic characteristics of ALS fibroblasts and multivariate analysis to develop classifiers for patient stratification.

Abstract Rationale “Noninfectious” pulmonary complications are significant causes of morbidity and mortality after allogeneic hematopoietic cell transplant. Early-onset viral reactivations or infections are common after transplant. Whether the first-onset viral infection causes noninfectious pulmonary complications is unknown. Objectives To determine whether the first-onset viral infection within 100 days after transplant predisposes to development of noninfectious pulmonary complications. Methods We performed a retrospective review of 738 allogeneic hematopoietic cell transplant patients enrolled from 2005 to 2011. We also established a novel bone marrow transplantation mouse model to test whether herpesviral reactivation after transplant causes organ injury. Measurements and Main Results First-onset viral infections with human herpesvirus 6 or Epstein-Barr virus within 100 days after transplant increase the risk of developing idiopathic pneumonia syndrome (adjusted hazard ratio [aHR], 5.52; 95% confidence interval [CI], 1.61–18.96; P = 0.007; and aHR, 9.21; 95% CI, 2.63–32.18; P = 0.001, respectively). First infection with human cytomegalovirus increases risk of bronchiolitis obliterans syndrome (aHR, 2.88; 95% CI, 1.50–5.55; P = 0.002) and grade II–IV acute graft-versus-host disease (aHR, 1.59; 95% CI, 1.06–2.39; P = 0.02). Murine roseolovirus, a homolog of human herpesvirus 6, can also be reactivated in the lung and other organs after bone marrow transplantation. Reactivation of murine roseolovirus induced an idiopathic pneumonia syndrome–like phenotype and aggravated acute graft-versus-host disease. Conclusions First-onset herpesviral infection within 100 days after allogeneic hematopoietic cell transplant increases risk of pulmonary complications. Experimentally reactivating murine roseolovirus causes organ injury similar to phenotypes seen in human transplant recipients.

BackgroundThe past two decades have witnessed a surge in the use of cervical spine joint procedures including joint injections, nerve blocks and radiofrequency ablation to treat chronic neck pain, yet many aspects of the procedures remain controversial.MethodsIn August 2020, the American Society of Regional Anesthesia and Pain Medicine and the American Academy of Pain Medicine approved and charged the Cervical Joint Working Group to develop neck pain guidelines. Eighteen stakeholder societies were identified, and formal request-for-participation and member nomination letters were sent to those organizations. Participating entities selected panel members and an ad hoc steering committee selected preliminary questions, which were then revised by the full committee. Each question was assigned to a module composed of 4–5 members, who worked with the Subcommittee Lead and the Committee Chairs on preliminary versions, which were sent to the full committee after revisions. We used a modified Delphi method whereby the questions were sent to the committee en bloc and comments were returned in a non-blinded fashion to the Chairs, who incorporated the comments and sent out revised versions until consensus was reached. Before commencing, it was agreed that a recommendation would be noted with >50% agreement among committee members, but a consensus recommendation would require ≥75% agreement.ResultsTwenty questions were selected, with 100% consensus achieved in committee on 17 topics. Among participating organizations, 14 of 15 that voted approved or supported the guidelines en bloc, with 14 questions being approved with no dissensions or abstentions. Specific questions addressed included the value of clinical presentation and imaging in selecting patients for procedures, whether conservative treatment should be used before injections, whether imaging is necessary for blocks, diagnostic and prognostic value of medial branch blocks and intra-articular joint injections, the effects of sedation and injectate volume on validity, whether facet blocks have therapeutic value, what the ideal cut-off value is for designating a block as positive, how many blocks should be performed before radiofrequency ablation, the orientation of electrodes, whether larger lesions translate into higher success rates, whether stimulation should be used before radiofrequency ablation, how best to mitigate complication risks, if different standards should be applied to clinical practice and trials, and the indications for repeating radiofrequency ablation.ConclusionsCervical medial branch radiofrequency ablation may provide benefit to well-selected individuals, with medial branch blocks being more predictive than intra-articular injections. More stringent selection criteria are likely to improve denervation outcomes, but at the expense of false-negatives (ie, lower overall success rate). Clinical trials should be tailored based on objectives, and selection criteria for some may be more stringent than what is ideal in clinical practice.