Guidelines and definitions for research on epithelial-mesenchymal transition.

Epithelial-mesenchymal transition (EMT) encompasses dynamic changes in cellular organization from epithelial to mesenchymal phenotypes, which leads to functional changes in cell migration and invasion. EMT occurs in a diverse range of physiological and pathological conditions and is driven by a conserved set of inducing signals, transcriptional regulators and downstream effectors. With over 5,700 publications indexed by Web of Science in 2019 alone, research on EMT is expanding rapidly. This growing interest warrants the need for a consensus among researchers when referring to and undertaking research on EMT. This Consensus Statement, mediated by 'the EMT International Association' (TEMTIA), is the outcome of a 2-year-long discussion among EMT researchers and aims to both clarify the nomenclature and provide definitions and guidelines for EMT research in future publications. We trust that these guidelines will help to reduce misunderstanding and misinterpretation of research data generated in various experimental models and to promote cross-disciplinary collaboration to identify and address key open questions in this research field. While recognizing the importance of maintaining diversity in experimental approaches and conceptual frameworks, we emphasize that lasting contributions of EMT research to increasing our understanding of developmental processes and combatting cancer and other diseases depend on the adoption of a unified terminology to describe EMT.

Staying Afloat in the Rising Tide of Science.

New York Times columnist and science writer Carl Zimmer discusses the challenges of effectively communicating with the public about science.

Role play with large language models.

As dialogue agents become increasingly human-like in their performance, we must develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. Here we foreground the concept of role play. Casting dialogue-agent behaviour in terms of role play allows us to draw on familiar folk psychological terms, without ascribing human characteristics to language models that they in fact lack. Two important cases of dialogue-agent behaviour are addressed this way, namely, (apparent) deception and (apparent) self-awareness.

A nomenclature consensus for nervous system organoids and assembloids.

Self-organizing three-dimensional cellular models derived from human pluripotent stem cells or primary tissue have great potential to provide insights into how the human nervous system develops, what makes it unique and how disorders of the nervous system arise, progress and could be treated. Here, to facilitate progress and improve communication with the scientific community and the public, we clarify and provide a basic framework for the nomenclature of human multicellular models of nervous system development and disease, including organoids, assembloids and transplants.

Liquid-liquid phase separation in biology.

Cells organize many of their biochemical reactions in non-membrane compartments. Recent evidence has shown that many of these compartments are liquids that form by phase separation from the cytoplasm. Here we discuss the basic physical concepts necessary to understand the consequences of liquid-like states for biological functions.

The rhomboid-like superfamily: molecular mechanisms and biological roles.

The rhomboid proteases were first discovered as regulators of Drosophila EGF receptor signaling; soon after, it was recognized that they represented the founder members of a widespread family of intramembrane serine proteases conserved in all kingdoms. More recently still, the family was promoted to a superfamily, encompassing a wide variety of distantly related proteins. One of the surprises has been that many members of the rhomboid-like superfamily are not active proteases. Given the size of this clan, and its relatively recent discovery, there is still much to learn. Nevertheless, we already understand much about how rhomboid proteases perform their surprising function of cleaving transmembrane domains. We also already know that members of the rhomboid-like superfamily participate in biological functions as diverse as growth factor signaling, mitochondrial dynamics, inflammation, parasite invasion, and the machinery of protein quality control. Their potential medical significance is now becoming apparent in several areas.

Universal nomenclature for oxytocin-vasotocin ligand and receptor families.

Oxytocin (OXT; hereafter OT) and arginine vasopressin or vasotocin (AVP or VT; hereafter VT) are neurotransmitter ligands that function through specific receptors to control diverse functions1,2. Here we performed genomic analyses on 35 species that span all major vertebrate lineages, including newly generated high-contiguity assemblies from the Vertebrate Genomes Project3,4. Our findings support the claim5 that OT (also known as OXT) and VT (also known as AVP) are adjacent paralogous genes that have resulted from a local duplication, which we infer was through DNA transposable elements near the origin of vertebrates and in which VT retained more of the parental sequence. We identified six major oxytocin-vasotocin receptors among vertebrates. We propose that all six of these receptors arose from a single receptor that was shared with the common ancestor of invertebrates, through a combination of whole-genome and large segmental duplications. We propose a universal nomenclature based on evolutionary relationships for the genes that encode these receptors, in which the genes are given the same orthologous names across vertebrates and paralogous names relative to each other. This nomenclature avoids confusion due to differential naming in the pre-genomic era and incomplete genome assemblies, furthers our understanding of the evolution of these genes, aids in the translation of findings across species and serves as a model for other gene families.

Examining linguistic shifts between preprints and publications.

Preprints allow researchers to make their findings available to the scientific community before they have undergone peer review. Studies on preprints within bioRxiv have been largely focused on article metadata and how often these preprints are downloaded, cited, published, and discussed online. A missing element that has yet to be examined is the language contained within the bioRxiv preprint repository. We sought to compare and contrast linguistic features within bioRxiv preprints to published biomedical text as a whole as this is an excellent opportunity to examine how peer review changes these documents. The most prevalent features that changed appear to be associated with typesetting and mentions of supporting information sections or additional files. In addition to text comparison, we created document embeddings derived from a preprint-trained word2vec model. We found that these embeddings are able to parse out different scientific approaches and concepts, link unannotated preprint-peer-reviewed article pairs, and identify journals that publish linguistically similar papers to a given preprint. We also used these embeddings to examine factors associated with the time elapsed between the posting of a first preprint and the appearance of a peer-reviewed publication. We found that preprints with more versions posted and more textual changes took longer to publish. Lastly, we constructed a web application (https://greenelab.github.io/preprint-similarity-search/) that allows users to identify which journals and articles that are most linguistically similar to a bioRxiv or medRxiv preprint as well as observe where the preprint would be positioned within a published article landscape.

Unsupervised word embeddings capture latent knowledge from materials science literature.

The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the materials research community has come from structured property databases1,2, which encompass only a small fraction of the knowledge present in the research literature. Beyond property values, publications contain valuable knowledge regarding the connections and relationships between data items as interpreted by the authors. To improve the identification and use of this knowledge, several studies have focused on the retrieval of information from scientific literature using supervised natural language processing3-10, which requires large hand-labelled datasets for training. Here we show that materials science knowledge present in the published literature can be efficiently encoded as information-dense word embeddings11-13 (vector representations of words) without human labelling or supervision. Without any explicit insertion of chemical knowledge, these embeddings capture complex materials science concepts such as the underlying structure of the periodic table and structure-property relationships in materials. Furthermore, we demonstrate that an unsupervised method can recommend materials for functional applications several years before their discovery. This suggests that latent knowledge regarding future discoveries is to a large extent embedded in past publications. Our findings highlight the possibility of extracting knowledge and relationships from the massive body of scientific literature in a collective manner, and point towards a generalized approach to the mining of scientific literature.

Genenames.org: the HGNC resources in 2023.

The HUGO Gene Nomenclature Committee (HGNC) assigns unique symbols and names to human genes. The HGNC database (www.genenames.org) currently contains over 43 000 approved gene symbols, over 19 200 of which are assigned to protein-coding genes, 14 000 to pseudogenes and nearly 9000 to non-coding RNA genes. The public website, www.genenames.org, displays all approved nomenclature within Symbol Reports that contain data curated by HGNC nomenclature advisors and links to related genomic, clinical, and proteomic information. Here, we describe updates to our resource, including improvements to our search facility and new download features.

Fungal names: a comprehensive nomenclatural repository and knowledge base for fungal taxonomy.

Fungal taxonomy is a complex and rapidly changing subject, which makes proper naming of fungi challenging for taxonomists. A registration platform with a standardized and information-integrated database is a powerful tool for efficient research on fungal taxonomy. Fungal Names (FN, https://nmdc.cn/fungalnames/; launched in 2011) is one of the three official fungal nomenclatural repositories authorized by the International Nomenclature Committee for Fungi (NCF). Currently, FN includes >567 000 taxon names from >10 000 related journals and books published since 1596 and covers >147 000 collection records of type specimens/illustrations from >5000 preserving agencies. FN is also a knowledge base that integrates nomenclature information with specimens, culture collections and herbaria/fungaria, publications and taxonomists, and represents a summary of the history and recent advances in fungal taxonomy. Published fungal names are categorized based on well-accepted nomenclature rules and can be readily searched with different keywords and strategies. In combination with a standardized name checking tool and a sequence alignment-based identification package, FN makes the registration and typification of nomenclatural novelties of fungi convenient and accurate.

Standardised definitions and diagnostic criteria for extranodal extension detected on histopathological examination in head and neck cancer: Head and Neck Cancer International Group consensus recommendations.

Detection of extranodal extension on histopathology in surgically treated head and neck squamous cell carcinoma indicates poor prognosis. However, there is no consensus on the diagnostic criteria, interpretation, and reporting of histology detected extranodal extension, which has contributed to conflicting evidence in the literature, and likely clinical inconsistency. The Head and Neck Cancer International Group conducted a three-round modified Delphi process with a group of 19 international pathology experts representing 15 national clinical research groups to generate consensus recommendations for histology detected extranodal extension diagnostic criteria. The expert panel strongly agreed on terminology and diagnostic features for histology detected extranodal extension and soft tissue metastasis. Moreover, the panel reached consensus on reporting of histology detected extranodal extension and on nodal sampling. These consensus recommendations, endorsed by 19 organisations representing 34 countries, are a crucial development towards standardised diagnosis and reporting of histology detected extranodal extension, and more accurate data collection and analysis.

Criteria for the diagnosis of extranodal extension detected on radiological imaging in head and neck cancer: Head and Neck Cancer International Group consensus recommendations.

Extranodal extension of tumour on histopathology is known to be a negative prognostic factor in head and neck cancer. Compelling evidence suggests that extranodal extension detected on radiological imaging is also a negative prognostic factor. Furthermore, if imaging detected extranodal extension could be identified reliably before the start of treatment, it could be used to guide treatment selection, as patients might be better managed with non-surgical approaches to avoid the toxicity and cost of trimodality therapy (surgery, chemotherapy, and radiotherapy together). There are many aspects of imaging detected extranodal extension that remain unresolved or are without consensus, such as the criteria to best diagnose them and the associated terminology. The Head and Neck Cancer International Group conducted a five-round modified Delphi process with a group of 18 international radiology experts, representing 14 national clinical research groups. We generated consensus recommendations on the terminology and diagnostic criteria for imaging detected extranodal extension to harmonise clinical practice and research. These recommendations have been endorsed by 19 national and international organisations, representing 34 countries. We propose a new classification system to aid diagnosis, which was supported by most of the participating experts over existing systems, and which will require validation in the future. Additionally, we have created an online educational resource for grading imaging detected extranodal extensions.

Evasins: Tick Salivary Proteins that Inhibit Mammalian Chemokines.

Ticks are hematophagous arachnids that parasitize mammals and other hosts, feeding on their blood. Ticks secrete numerous salivary factors that enhance host blood flow or suppress the host inflammatory response. The recruitment of leukocytes, a hallmark of inflammation, is regulated by chemokines, which activate chemokine receptors on the leukocytes. Ticks target this process by secreting glycoproteins called Evasins, which bind to chemokines and prevent leukocyte recruitment. This review describes the recent discovery of numerous Evasins produced by ticks, their classification into two structural and functional classes, and the efficacy of Evasins in animal models of inflammatory diseases. The review also proposes a standard nomenclature system for Evasins and discusses the potential of repurposing or engineering Evasins as therapeutic anti-inflammatory agents.