Supplementary material from "Risk factors for stereotypic behaviour in captive ungulates"

Behavioural needs are highly motivated actions critical to a species' survival and reproduction. Prolonged restriction of these behaviours can lead to stereotypic behaviours (SB) in captive animals, and this is particularly common in ungulate species. While risk factors for SB have been suggested for some ungulates, no study has integrated these findings to identify which aspects of ungulates’ wild behavioural biology and captive husbandry are potential drivers for SB across this clade. We collated SB data from 15 236 individuals across 38 ungulate species from 95 sources, and determined species' wild/free-ranging behaviour from 559 additional studies. Bayesian-phylogenetic statistical methods showed that ungulate behavioural needs relating to foraging and mating are particularly affected by captive environments, with promiscuous and browsing species showing the greatest prevalence of SB. Concentrate-only diets and lack of ad libitum feed substrates were also associated with high SB prevalence. This study identifies which ungulates are better suited to captive environments and which species require targeted husbandry, enrichment and breeding protocols in order to meet their behavioural needs. Our approach of applying Bayesian-phylogenetic inference to factors influencing SB within a clade can be used to identify other intrinsic and extrinsic risk factors of reduced animal health and welfare

Key Areas For Conserving United States\u27 Biodiversity Likely Threatened By Future Land Use Change

A major challenge for biodiversity conservation is to mitigate the effects of future environmental change, such as land use, in important areas for biodiversity conservation. In the United States, recent conservation efforts by The Nature Conservancy and partners have identified and mapped the nation\u27s Areas of Biodiversity Significance (ABS), representing the best remaining habitats for the full diversity of native species and ecosystems, and thus the most important and suitable areas for the conservation of native biodiversity. Our goal was to understand the potential consequences of future land use changes on the nation\u27s ABS, and identify regions where ABS are likely to be threatened due to future land use expansion. For this, we used an econometric-based model to forecast land use changes between 2001 and 2051 across the conterminous U. S. under alternative scenarios of future land use change. Our model predicted a total of similar to 100,000 to 160,000 km(2) of natural habitats within ABS replaced by urban, crop and pasture expansion depending on the scenario (5% to 8% habitat loss across the conterminous U.S.), with some regions experiencing up to 30% habitat loss. The majority of the most threatened ABS were located in the Eastern half of the country. Results for our different scenarios were generally fairly consistent, but some regions exhibited notable difference from the baseline under specific policies and changes in commodity prices. Overall, our study suggests that key areas for conserving United States\u27 biodiversity are likely threatened by future land use change, and efforts trying to preserve the ecological and conservation values of ABS will need to address the potential intensification of human land uses

Characterisation of the transcriptome and proteome of SARS-CoV-2 reveals a cell passage induced in-frame deletion of the furin-like cleavage site from the spike glycoprotein

Background SARS-CoV-2 is a recently emerged respiratory pathogen that has significantly impacted global human health. We wanted to rapidly characterise the transcriptomic, proteomic and phosphoproteomic landscape of this novel coronavirus to provide a fundamental description of the virus’s genomic and proteomic potential. Methods We used direct RNA sequencing to determine the transcriptome of SARS-CoV-2 grown in Vero E6 cells which is widely used to propagate the novel coronavirus. The viral transcriptome was analysed using a recently developed ORF-centric pipeline. Allied to this, we used tandem mass spectrometry to investigate the proteome and phosphoproteome of the same virally infected cells. Results Our integrated analysis revealed that the viral transcripts (i.e. subgenomic mRNAs) generally fitted the expected transcription model for coronaviruses. Importantly, a 24 nt in-frame deletion was detected in over half of the subgenomic mRNAs encoding the spike (S) glycoprotein and was predicted to remove a proposed furin cleavage site from the S glycoprotein. Tandem mass spectrometry identified over 500 viral peptides and 44 phosphopeptides in virus-infected cells, covering almost all proteins predicted to be encoded by the SARS-CoV-2 genome, including peptides unique to the deleted variant of the S glycoprotein. Conclusions Detection of an apparently viable deletion in the furin cleavage site of the S glycoprotein, a leading vaccine target, shows that this and other regions of SARS-CoV-2 proteins may readily mutate. The furin site directs cleavage of the S glycoprotein into functional subunits during virus entry or exit and likely contributes strongly to the pathogenesis and zoonosis of this virus. Our data emphasises that the viral genome sequence should be carefully monitored during the growth of viral stocks for research, animal challenge models and, potentially, in clinical samples. Such variations may result in different levels of virulence, morbidity and mortality

LayoutLM: Pre-training of Text and Layout for Document Image Understanding

Pre-training techniques have been verified successfully in a variety of NLP tasks in recent years. Despite the widespread use of pre-training models for NLP applications, they almost exclusively focus on text-level manipulation, while neglecting layout and style information that is vital for document image understanding. In this paper, we propose the \textbf{LayoutLM} to jointly model interactions between text and layout information across scanned document images, which is beneficial for a great number of real-world document image understanding tasks such as information extraction from scanned documents. Furthermore, we also leverage image features to incorporate words' visual information into LayoutLM. To the best of our knowledge, this is the first time that text and layout are jointly learned in a single framework for document-level pre-training. It achieves new state-of-the-art results in several downstream tasks, including form understanding (from 70.72 to 79.27), receipt understanding (from 94.02 to 95.24) and document image classification (from 93.07 to 94.42). The code and pre-trained LayoutLM models are publicly available at \url{https://aka.ms/layoutlm}.Comment: KDD 202

Economic-based Projections Of Future Land Use In The Conterminous United States Under Alternative Policy Scenarios

The article presents a study which constructs and parameterizes an econometric model of land-use change to project future land use to the year 2051 at a fine spatial scale across the conterminous U.S. under several alternative land-use policy scenarios. It parameterizes the econometric model of land-use change with the National Resource Inventory (NRI) 1992 and 1997 land-use data for 844 000 sample points

RNA-binding proteins ZFP36L1 and ZFP36L2 promote cell quiescence.

Progression through the stages of lymphocyte development requires coordination of the cell cycle. Such coordination ensures genomic integrity while cells somatically rearrange their antigen receptor genes [in a process called variable-diversity-joining (VDJ) recombination] and, upon successful rearrangement, expands the pools of progenitor lymphocytes. Here we show that in developing B lymphocytes, the RNA-binding proteins (RBPs) ZFP36L1 and ZFP36L2 are critical for maintaining quiescence before precursor B cell receptor (pre-BCR) expression and for reestablishing quiescence after pre-BCR-induced expansion. These RBPs suppress an evolutionarily conserved posttranscriptional regulon consisting of messenger RNAs whose protein products cooperatively promote transition into the S phase of the cell cycle. This mechanism promotes VDJ recombination and effective selection of cells expressing immunoglobulin-μ at the pre-BCR checkpoint.This work was funded by the Biotechnology and Biological Sciences Research Council, a Medical Research Council CASE studentship with GSK, an MRC centenary award (A.G) and project grants from Bloodwise. DJH was supported by a Medical Research Council Clinician Scientist FellowshipThis is the author accepted manuscript. The final version is available from the American Association for the Advancement of Science via http://dx.doi.org/10.1126/science.aad597

Accelerated expansion from ghost-free bigravity: a statistical analysis with improved generality

We study the background cosmology of the ghost-free, bimetric theory of gravity. We perform an extensive statistical analysis of the model using both frequentist and Bayesian frameworks and employ the constraints on the expansion history of the Universe from the observations of supernovae, the cosmic microwave background and the large scale structure to estimate the model's parameters and test the goodness of the fits. We explore the parameter space of the model with nested sampling to find the best-fit chi-square, obtain the Bayesian evidence, and compute the marginalized posteriors and mean likelihoods. We mainly focus on a class of sub-models with no explicit cosmological constant (or vacuum energy) term to assess the ability of the theory to dynamically cause a late-time accelerated expansion. The model behaves as standard gravity without a cosmological constant at early times, with an emergent extra contribution to the energy density that converges to a cosmological constant in the far future. The model can in most cases yield very good fits and is in perfect agreement with the data. This is because many points in the parameter space of the model exist that give rise to time-evolution equations that are effectively very similar to those of the $\Lambda$CDM. This similarity makes the model compatible with observations as in the $\Lambda$CDM case, at least at the background level. Even though our results indicate a slightly better fit for the $\Lambda$CDM concordance model in terms of the $p$-value and evidence, none of the models is statistically preferred to the other. However, the parameters of the bigravity model are in general degenerate. A similar but perturbative analysis of the model as well as more data will be required to break the degeneracies and constrain the parameters, in case the model will still be viable compared to the $\Lambda$CDM.Comment: 42 pages, 9 figures; typos corrected in equations (2.12), (2.13), (3.7), (3.8) and (3.9); more discussions added (footnotes 5, 8, 10 and 13) and abstract, sections 4.2, 4.3 and 5 (conclusions) modified in response to referee's comments; references added; acknowledgements modified; all results completely unchanged; matches version accepted for publication in JHE

COVID-19 patients share common, corticosteroid-independent features of impaired host immunity to pathogenic molds

Patients suffering from coronavirus disease-2019 (COVID-19) are susceptible to deadly secondary fungal infections such as COVID-19-associated pulmonary aspergillosis and COVID-19-associated mucormycosis. Despite this clinical observation, direct experimental evidence for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-driven alterations of antifungal immunity is scarce. Using an ex-vivo whole blood stimulation assay, we challenged blood from twelve COVID-19 patients with Aspergillus fumigatus and Rhizopus arrhizus antigens and studied the expression of activation, maturation, and exhaustion markers, as well as cytokine secretion. Compared to healthy controls, T-helper cells from COVID-19 patients displayed increased expression levels of the exhaustion marker PD-1 and weakened A. fumigatus - and R. arrhizus -induced activation. While baseline secretion of proinflammatory cytokines was massively elevated, whole blood from COVID-19 patients elicited diminished release of T-cellular (e.g., IFN-γ, IL-2) and innate immune cell-derived (e.g., CXCL9, CXCL10) cytokines in response to A. fumigatus and R. arrhizus antigens. Additionally, samples from COVID-19 patients showed deficient granulocyte activation by mold antigens and reduced fungal killing capacity of neutrophils. These features of weakened anti-mold immune responses were largely decoupled from COVID-19 severity, the time elapsed since diagnosis of COVID-19, and recent corticosteroid uptake, suggesting that impaired anti-mold defense is a common denominator of the underlying SARS-CoV-2 infection. Taken together, these results expand our understanding of the immune predisposition to post-viral mold infections and could inform future studies of immunotherapeutic strategies to prevent and treat fungal superinfections in COVID-19 patients

Non-verbal sound processing in the primary progressive aphasias

Little is known about the processing of non-verbal sounds in the primary progressive aphasias. Here, we investigated the processing of complex non-verbal sounds in detail, in a consecutive series of 20 patients with primary progressive aphasia [12 with progressive non-fluent aphasia; eight with semantic dementia]. We designed a novel experimental neuropsychological battery to probe complex sound processing at early perceptual, apperceptive and semantic levels, using within-modality response procedures that minimized other cognitive demands and matching tests in the visual modality. Patients with primary progressive aphasia had deficits of non-verbal sound analysis compared with healthy age-matched individuals. Deficits of auditory early perceptual analysis were more common in progressive non-fluent aphasia, deficits of apperceptive processing occurred in both progressive non-fluent aphasia and semantic dementia, and deficits of semantic processing also occurred in both syndromes, but were relatively modality specific in progressive non-fluent aphasia and part of a more severe generic semantic deficit in semantic dementia. Patients with progressive non-fluent aphasia were more likely to show severe auditory than visual deficits as compared to patients with semantic dementia. These findings argue for the existence of core disorders of complex non-verbal sound perception and recognition in primary progressive aphasia and specific disorders at perceptual and semantic levels of cortical auditory processing in progressive non-fluent aphasia and semantic dementia, respectively