Early IFNγ-Mediated and Late Perforin-Mediated Suppression of Pathogenic CD4 T Cell Responses Are Both Required for Inhibition of Demyelinating Disease by CNS-Specific Autoregulatory CD8 T Cells

Pathogenesis of immune-mediated demyelinating diseases like multiple sclerosis (MS) is thought to be governed by a complex cellular interplay between immunopathogenic and immunoregulatory responses. We have previously shown that central nervous system (CNS)-specific CD8 T cells have an unexpected protective role in the mouse model of MS, experimental autoimmune encephalomyelitis (EAE). In this study, we interrogated the suppressive potential of PLP178-191-specific CD8 T cells (PLP-CD8). Here, we show that PLP-CD8, when administered post-disease onset, rapidly ameliorated EAE progression, and suppressed PLP178-191-specific CD4 T cell responses as measured by delayed-type hypersensitivity (DTH). To accomplish DTH suppression, PLP-CD8 required differential production of perforin and IFNγ. Perforin was not required for the rapid suppressive action of these cells, but was critical for maintenance of optimal longer term DTH suppression. Conversely, IFNγ production by PLP-CD8 was necessary for swift DTH suppression, but was less significant for maintenance of longer term suppression. These data indicate that CNS-specific CD8 T cells employ an ordered regulatory mechanism program over a number of days in vivo during demyelinating disease and have mechanistic implications for this immunotherapeutic approach

Capturing contentiousness: Constructing the contentious terms in context corpus

Recent initiatives by cultural heritage institutions in addressing outdated and offensive language used in their collections demonstrate the need for further understanding into when terms are problematic or contentious. This paper presents an annotated dataset of 2,715 unique samples of terms in context, drawn from a historical newspaper archive, collating 21,800 annotations of contentiousness from expert and crowd workers. We describe the contents of the corpus by analysing inter-rater agreement and differences between experts and crowd workers. In addition, we demonstrate the potential of the corpus for automated detection of contentiousness. We show that a simple classifier applied to the embedding representation of a target word provides a better than baseline performance in predicting contentiousness. We find that the term itself and the context play a role in whether a term is considered contentious

Collodictyon—An Ancient Lineage in the Tree of Eukaryotes

The current consensus for the eukaryote tree of life consists of several large assemblages (supergroups) that are hypothesized to describe the existing diversity. Phylogenomic analyses have shed light on the evolutionary relationships within and between supergroups as well as placed newly sequenced enigmatic species close to known lineages. Yet, a few eukaryote species remain of unknown origin and could represent key evolutionary forms for inferring ancient genomic and cellular characteristics of eukaryotes. Here, we investigate the evolutionary origin of the poorly studied protist Collodictyon (subphylum Diphyllatia) by sequencing a cDNA library as well as the 18S and 28S ribosomal DNA (rDNA) genes. Phylogenomic trees inferred from 124 genes placed Collodictyon close to the bifurcation of the “unikont” and “bikont” groups, either alone or as sister to the potentially contentious excavate Malawimonas. Phylogenies based on rDNA genes confirmed that Collodictyon is closely related to another genus, Diphylleia, and revealed a very low diversity in environmental DNA samples. The early and distinct origin of Collodictyon suggests that it constitutes a new lineage in the global eukaryote phylogeny. Collodictyon shares cellular characteristics with Excavata and Amoebozoa, such as ventral feeding groove supported by microtubular structures and the ability to form thin and broad pseudopods. These may therefore be ancient morphological features among eukaryotes. Overall, this shows that Collodictyon is a key lineage to understand early eukaryote evolution

Eukaryotic richness in the abyss: insights from pyrotag sequencing

Background: The deep sea floor is considered one of the most diverse ecosystems on Earth. Recent environmental DNA surveys based on clone libraries of rRNA genes confirm this observation and reveal a high diversity of eukaryotes present in deep-sea sediment samples. However, environmental clone-library surveys yield only a modest number of sequences with which to evaluate the diversity of abyssal eukaryotes. Methodology/Principal Findings: Here, we examined the richness of eukaryotic DNA in deep Arctic and Southern Ocean samples using massively parallel sequencing of the 18S ribosomal RNA (rRNA) V9 hypervariable region. In very small volumes of sediments, ranging from 0.35 to 0.7 g, we recovered up to 7,499 unique sequences per sample. By clustering sequences having up to 3 differences, we observed from 942 to 1756 Operational Taxonomic Units (OTUs) per sample. Taxonomic analyses of these OTUs showed that DNA of all major groups of eukaryotes is represented at the deep-sea floor. The dinoflagellates, cercozoans, ciliates, and euglenozoans predominate, contributing to 17%, 16%, 10%, and 8% of all assigned OTUs, respectively. Interestingly, many sequences represent photosynthetic taxa or are similar to those reported from the environmental surveys of surface waters. Moreover, each sample contained from 31 to 71 different metazoan OTUs despite the small sample volume collected. This indicates that a significant faction of the eukaryotic DNA sequences likely do not belong to living organisms, but represent either free, extracellular DNA or remains and resting stages of planktonic species. Conclusions/Significance: In view of our study, the deep-sea floor appears as a global DNA repository, which preserves genetic information about organisms living in the sediment, as well as in the water column above it. This information can be used for future monitoring of past and present environmental changes.French ANR Aquaparadox; ANR DeepOases; Swiss National Science Foundation [31003A-125372]; WM Keck foundationinfo:eu-repo/semantics/publishedVersio

Improving language model predictions via prompts enriched with knowledge graphs

Despite advances in deep learning and knowledge graphs (KGs), using language models for natural language understanding and question answering remains a challenging task. Pre-trained language models (PLMs) have shown to be able to leverage contextual information, to complete cloze prompts, next sentence completion and question answering tasks in various domains. Unlike structured data querying in e.g. KGs, mapping an input question to data that may or may not be stored by the language model is not a simple task. Recent studies have highlighted the improvements that can be made to the quality of information retrieved from PLMs by adding auxiliary data to otherwise naive prompts. In this paper, we explore the effects of enriching prompts with additional contextual information leveraged from the Wikidata KG on language model performance. Specifically, we compare the performance of naive vs. KG-engineered cloze prompts for entity genre classification in the movie domain. Selecting a broad range of commonly available Wikidata properties, we show that enrichment of cloze-style prompts with Wikidata information can result in a significantly higher recall for the investigated BERT and RoBERTa large PLMs. However, it is also apparent that the optimum level of data enrichment differs between models

New worlds in political science

Political science’ is a ‘vanguard’ field concerned with advancing generic knowledge of political processes, while a wider ‘political scholarship’ utilising eclectic approaches has more modest or varied ambitions. Political science nonetheless necessarily depends upon and is epistemologically comparable with political scholarship. I deploy Boyer's distinctions between discovery, integration, application and renewing the profession to show that these connections are close woven. Two sets of key challenges need to be tackled if contemporary political science is to develop positively. The first is to ditch the current unworkable and restrictive comparative politics approach, in favour of a genuinely global analysis framework. Instead of obsessively looking at data on nation states, we need to seek data completeness on the whole (multi-level) world we have. A second cluster of challenges involves looking far more deeply into political phenomena; reaping the benefits of ‘digital-era’ developments; moving from sample methods to online census methods in organisational analysis; analysing massive transactional databases and real-time political processes (again, instead of depending on surveys); and devising new forms of ‘instrumentation’, informed by post-rational choice theoretical perspectives