The rockefeller university

Severe COVID-19 is characterized by persistent lung inflammation, inflammatory cytokine production, viral RNA and a sustained interferon (IFN) response, all of which are recapitulated and required for pathology in the SARS-CoV-2-infected MISTRG6-hACE2 humanized mouse model of COVID-19, which has a human immune system(1-20). Blocking either viral replication with remdesivir(21-23) or the downstream IFN-stimulated cascade with anti-IFNAR2 antibodies in vivo in the chronic stages of disease attenuates the overactive immune inflammatory response, especially inflammatory macrophages. Here we show that SARS-CoV-2 infection and replication in lung-resident human macrophages is a critical driver of disease. In response to infection mediated by CD16 and ACE2 receptors, human macrophages activate inflammasomes, release interleukin 1 (IL-1) and IL-18, and undergo pyroptosis, thereby contributing to the hyperinflammatory state of the lungs. Inflammasome activation and the accompanying inflammatory response are necessary for lung inflammation, as inhibition of the NLRP3 inflammasome pathway reverses chronic lung pathology. Notably, this blockade of inflammasome activation leads to the release of infectious virus by the infected macrophages. Thus, inflammasomes oppose host infection by SARS-CoV-2 through the production of inflammatory cytokines and suicide by pyroptosis to prevent a productive viral cycle.

Planting new forests has received scientific and political attention as a measure to mitigate climate change. Large, new forests have been planted in places like China and Ethiopia and, over time, a billion hectares could become available globally for planting new forests. Sustainable management of forests, which are available to wood production, has received less attention despite these forests covering at least two billion hectares globally. Better management of existing forests would improve forest growth and help mitigate climate change by increasing the forest carbon (C) stock, by storing C in forest products, and by generating wood-based materials substituting fossil C based materials or other CO2-emission-intensive materials. Some published research assumes a trade-off between the timber harvested from existing forests and the stock of C in those forest ecosystems, asserting that both cannot increase simultaneously. We tested this assumption using the uniquely detailed forest inventory data available from Finland, Norway and Sweden, hereafter denoted northern Europe. We focused on the period 1960 - 2017, that saw little change in the total area covered by forests in northern Europe. At the start of the period, rotational forestry practices began to diffuse, eventually replacing selective felling management systems as the most common management practice. Looking at data over the period we find that despite significant increases in timber and pulp wood harvests, the growth of the forest C stock accelerated. Over the study period, the C stock of the forest ecosystems in northern Europe increased by nearly 70%, while annual timber harvests increased at the about 40% over the same period. This increase in the forest C stock was close to on par with the CO2-emissions from the region (other greenhouse gases not included). Our results suggest that the important effects of management on forest growth allows the forest C stock and timber harvests to increase simultaneously. The development in northern Europe raises the question of how better forest management can improve forest growth elsewhere around the globe while at the same time protecting biodiversity and preserving landscapes.

Background Convalescent plasma (CP) has been widely used to treat COVID-19 and is under study. However, the variability in the current clinical trials has averted its wide use in the current pandemic. We aimed to evaluate the safety and efficacy of CP in severe coronavirus disease 2019 (COVID-19) in the early stages of the disease. Methods A randomized controlled clinical study was conducted on 101 patients admitted to the hospital with confirmed severe COVID-19. Most participants had less than 14 days from symptoms onset and less than seven days from hospitalization. Fifty patients were assigned to receive CP plus standard therapy (ST), and 51 were assigned to receive ST alone. Participants in the CP arm received two doses of 250 mL each, transfused 24 h apart. All transfused plasma was obtained from "super donors" that fulfilled the following criteria: titers of anti-SARS-CoV-2 S1 IgG >= 1:3200 and IgA >= 1:800 antibodies. The effect of transfused anti-IFN antibodies and the SARS-CoV-2 variants at the entry of the study on the overall CP efficacy was evaluated. The primary outcomes were the reduction in viral load and the increase in IgG and IgA antibodies at 28 days of follow-up. The per-protocol analysis included 91 patients. Results An early but transient increase in IgG anti-S1-SARS-CoV-2 antibody levels at day 4 post-transfusion was observed (Estimated difference [ED], - 1.36; 95% CI, - 2.33 to - 0.39; P = 0.04). However, CP was not associated with viral load reduction in any of the points evaluated. Analysis of secondary outcomes revealed that those patients in the CP arm disclosed a shorter time to discharge (ED adjusted for mortality, 3.1 days; 95% CI, 0.20 to 5.94; P = 0.0361) or a reduction of 2 points on the WHO scale when compared with the ST group (HR adjusted for mortality, 1.6; 95% CI, 1.03 to 2.5; P = 0.0376). There were no benefits from CP on the rates of intensive care unit admission (HR, 0.82; 95% CI, 0.35 to 1.9; P = 0.6399), mechanical ventilation (HR, 0.66; 95% CI, 0.25 to 1.7; P = 0.4039), or mortality (HR, 3.2; 95% CI, 0.64 to 16; P = 0.1584). Anti-IFN antibodies and SARS-CoV-2 variants did not influence these results. Conclusion CP was not associated with viral load reduction, despite the early increase in IgG anti-SARS-CoV-2 antibodies. However, CP is safe and could be a therapeutic option to reduce the hospital length of stay. Trial registration NCT04332835

Exome sequencing on tens of thousands of parent-proband trios has identified numerous deleterious de novo mutations (DNMs) and implicated risk genes for many disorders. Recent studies have suggested shared genes and pathways are enriched for DNMs across multiple disorders. However, existing analytic strategies only focus on genes that reach statistical significance for multiple disorders and require large trio samples in each study. As a result, these methods are not able to characterize the full landscape of genetic sharing due to polygenicity and incomplete penetrance. In this work, we introduce EncoreDNM, a novel statistical framework to quantify shared genetic effects between two disorders characterized by concordant enrichment of DNMs in the exome. EncoreDNM makes use of exome-wide, summary-level DNM data, including genes that do not reach statistical significance in single-disorder analysis, to evaluate the overall and annotation-partitioned genetic sharing between two disorders. Applying EncoreDNM to DNM data of nine disorders, we identified abundant pairwise enrichment correlations, especially in genes intolerant to pathogenic mutations and genes highly expressed in fetal tissues. These results suggest that EncoreDNM improves current analytic approaches and may have broad applications in DNM studies.

Sarcomas are rare tumours with many different subtypes and clinical outcomes; a broader knowledge of their genetic features is required. Here, the authors analyse 2138 soft tissue and bone sarcomas across 45 subtypes using MSK-IMPACT targeted sequencing and find genomic groups that are distinct from histological subgroups. The genetic, biologic, and clinical heterogeneity of sarcomas poses a challenge for the identification of therapeutic targets, clinical research, and advancing patient care. Because there are > 100 sarcoma subtypes, in-depth genetic studies have focused on one or a few subtypes. Herein, we report a comparative genetic analysis of 2,138 sarcomas representing 45 pathological entities. This cohort is prospectively analyzed using targeted sequencing to characterize subtype-specific somatic alterations in targetable pathways, rates of whole genome doubling, mutational signatures, and subtype-agnostic genomic clusters. The most common alterations are in cell cycle control and TP53, receptor tyrosine kinases/PI3K/RAS, and epigenetic regulators. Subtype-specific associations include TERT amplification in intimal sarcoma and SWI/SNF alterations in uterine adenosarcoma. Tumor mutational burden, while low compared to other cancers, varies between and within subtypes. This resource will improve sarcoma models, motivate studies of subtype-specific alterations, and inform investigations of genetic factors and their correlations with treatment response.

The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb(-1), collected with the CMS detector at the CERN LHC, at root s = 13 TeV. The hidden sector is hypothesized to couple to the standard model (SM) via a heavy leptophobic Z' mediator produced as a resonance in proton-proton collisions. The mediator decay results in two "semivisible" jets, containing both visible matter and invisible dark matter. The final state therefore includes moderate missing energy aligned with one of the jets, a signature ignored by most dark matter searches. No structure in the dijet transverse mass spectra compatible with the signal is observed. Assuming the Z' boson has a universal coupling of 0.25 to the SM quarks, an inclusive search, relevant to any model that exhibits this kinematic behavior, excludes mediator masses of 1.5-4.0 TeV at 95% confidence level, depending on the other signal model parameters. To enhance the sensitivity of the search for this particular class of hidden sector models, a boosted decision tree (BDT) is trained using jet substructure variables to distinguish between semivisible jets and SM jets from background processes. When the BDT is employed to identify each jet in the dijet system as semivisible, the mediator mass exclusion increases to 5.1 TeV, for wider ranges of the other signal model parameters. These limits exclude a wide range of strongly coupled hidden sector models for the first time.

In theoretical biology, robustness refers to the ability of a biological system to function properly even under perturbation of basic parameters (e.g., temperature or pH), which in mathematical models is reflected in not needing to fine-tune basic parameter constants; flexibility refers to the ability of a system to switch functions or behaviors easily and effortlessly. While there are extensive explorations of the concept of robustness and what it requires mathematically, understanding flexibility has proven more elusive, as well as also elucidating the apparent opposition between what is required mathematically for models to implement either. In this paper we address a number of arguments in theoretical neuroscience showing that both robustness and flexibility can be attained by systems that poise themselves at the onset of a large number of dynamical bifurcations, or dynamical criticality, and how such poising can have a profound influence on integration of information processing and function. Finally, we examine critical map lattices, which are coupled map lattices where the coupling is dynamically critical in the sense of having purely imaginary eigenvalues. We show that these map lattices provide an explicit connection between dynamical criticality in the sense we have used and "edge of chaos" criticality.

Environmental perturbations during the first years of life are a major factor in psychiatric diseases. Phencyclidine (PCP), a drug of abuse, has psychomimetic effects, and neonatal subchronic administration of PCP in rodents leads to long-term behavioral changes relevant for schizophrenia. The cerebellum is increasingly recognized for its role in diverse cognitive functions. However, little is known about potential cerebellar changes in models of schizophrenia. Here, we analyzed the characteristics of the cerebellum in the neonatal subchronic PCP model. We found that, while the global cerebellar cytoarchitecture and Purkinje cell spontaneous spiking properties are unchanged, climbing fiber/Purkinje cell synaptic connectivity is increased in juvenile mice. Neonatal subchronic administration of PCP is accompanied by increased cFos expression, a marker of neuronal activity, and transient modification of the neuronal surfaceome in the cerebellum. The largest change observed is the overexpression of Ctgf, a gene previously suggested as a biomarker for schizophrenia. This neonatal increase in Ctgf can be reproduced by increasing neuronal activity in the cerebellum during the second postnatal week using chemogenetics. However, it does not lead to increased climbing fiber/Purkinje cell connectivity in juvenile mice, showing the complexity of PCP action. Overall, our study shows that administration of the drug of abuse PCP during the developmental period of intense cerebellar synaptogenesis and circuit remodeling has long-term and specific effects on Purkinje cell connectivity and warrants the search for this type of synaptic changes in psychiatric diseases.