CasPEDIA Database: a functional classification system for class 2 CRISPR-Cas enzymes.

CRISPR-Cas enzymes enable RNA-guided bacterial immunity and are widely used for biotechnological applications including genome editing. In particular, the Class 2 CRISPR-associated enzymes (Cas9, Cas12 and Cas13 families), have been deployed for numerous research, clinical and agricultural applications. However, the immense genetic and biochemical diversity of these proteins in the public domain poses a barrier for researchers seeking to leverage their activities. We present CasPEDIA (http://caspedia.org), the Cas Protein Effector Database of Information and Assessment, a curated encyclopedia that integrates enzymatic classification for hundreds of different Cas enzymes across 27 phylogenetic groups spanning the Cas9, Cas12 and Cas13 families, as well as evolutionarily related IscB and TnpB proteins. All enzymes in CasPEDIA were annotated with a standard workflow based on their primary nuclease activity, target requirements and guide-RNA design constraints. Our functional classification scheme, CasID, is described alongside current phylogenetic classification, allowing users to search related orthologs by enzymatic function and sequence similarity. CasPEDIA is a comprehensive data portal that summarizes and contextualizes enzymatic properties of widely used Cas enzymes, equipping users with valuable resources to foster biotechnological development. CasPEDIA complements phylogenetic Cas nomenclature and enables researchers to leverage the multi-faceted nucleic-acid targeting rules of diverse Class 2 Cas enzymes.

Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictions.

Wikipedia, the largest encyclopedia ever created, is a global initiative driven by volunteer contributions. When the COVID-19 pandemic broke out and mobility restrictions ensued across the globe, it was unclear whether contributions to Wikipedia would decrease in the face of the pandemic, or whether volunteers would withstand the added stress and increase their contributions to accommodate the growing readership uncovered in recent studies. We analyze [Formula: see text] million edits contributed from 2018 to 2020 across twelve Wikipedia language editions and find that Wikipedia's global volunteer community responded resiliently to the pandemic, substantially increasing both productivity and the number of newcomers who joined the community. For example, contributions to the English Wikipedia increased by over [Formula: see text] compared to the expectation derived from pre-pandemic data. Our work sheds light on the response of a global volunteer population to the COVID-19 crisis, providing valuable insights into the behavior of critical online communities under stress.

A general method for estimating the prevalence of influenza-like-symptoms with Wikipedia data.

Influenza is an acute respiratory seasonal disease that affects millions of people worldwide and causes thousands of deaths in Europe alone. Estimating in a fast and reliable way the impact of an illness on a given country is essential to plan and organize effective countermeasures, which is now possible by leveraging unconventional data sources like web searches and visits. In this study, we show the feasibility of exploiting machine learning models and information about Wikipedia's page views of a selected group of articles to obtain accurate estimates of influenza-like illnesses incidence in four European countries: Italy, Germany, Belgium, and the Netherlands. We propose a novel language-agnostic method, based on two algorithms, Personalized PageRank and CycleRank, to automatically select the most relevant Wikipedia pages to be monitored without the need for expert supervision. We then show how our model can reach state-of-the-art results by comparing it with previous solutions.

Measuring the quality of scientific references in Wikipedia: an analysis of more than 115M citations to over 800 000 scientific articles.

Wikipedia is a widely used online reference work which cites hundreds of thousands of scientific articles across its entries. The quality of these citations has not been previously measured, and such measurements have a bearing on the reliability and quality of the scientific portions of this reference work. Using a novel technique, a massive database of qualitatively described citations, and machine learning algorithms, we analyzed 1 923 575 Wikipedia articles which cited a total of 824 298 scientific articles in our database and found that most scientific articles cited by Wikipedia articles are uncited or untested by subsequent studies, and the remainder show a wide variability in contradicting or supporting evidence. Additionally, we analyzed 51 804 643 scientific articles from journals indexed in the Web of Science and found that similarly most were uncited or untested by subsequent studies, while the remainder show a wide variability in contradicting or supporting evidence.

Knowledge translation: Cochrane, Wikipedia and students initiatives. / Transferencia del conocimiento: Cochrane, Wikipedia e iniciativas con estudiantes.

Cochrane is an international collaboration whose mission is to promote evidence-based decision-making on health. This is done by conducting high-quality, relevant and accessible systematic reviews, as well as through other forms of summarized scientific evidence. Knowledge translation promotes the real use of scientific knowledge and Cochrane has been developing various projects within this theme. One of those projects includes a collaboration with Wikipedia to improve the quality of information provided in the medical articles published in this digital encyclopaedia. This article summarizes the main characteristics of these initiatives.

Cochrane es una colaboración internacional cuya misión es promover la toma de decisiones sobre salud basada en la evidencia, mediante la realización de revisiones sistemáticas de alta calidad, relevantes y accesibles; así como a través de otros formatos en los cuales se resumen las evidencias científicas que se generan a partir de la ejecución de las revisiones sistemáticas Cochrane. La transferencia del conocimiento (Knowledge translation) promueve el uso real del conocimiento científico y Cochrane ha impulsado diversos proyectos con esta temática. Uno de ellos consiste en un convenio con Wikipedia para la mejora de la calidad de los artículos relacionados con la salud que se encuentran en esta enciclopedia digital. En este artículo se resumen las características principales de estas iniciativas.

Adding evidence of the effects of treatments into relevant Wikipedia pages: a randomised trial.

OBJECTIVES: To investigate the effects of adding high-grade quantitative evidence of outcomes of treatments into relevant Wikipedia pages on further information-seeking behaviour by the use of routinely collected data. SETTING: Wikipedia, Cochrane summary pages and the Cochrane Library. DESIGN: Randomised trial. PARTICIPANTS: Wikipedia pages which were highly relevant to up-to-date Cochrane Schizophrenia systematic reviews that contained a Summary of Findings table. INTERVENTIONS: Eligible Wikipedia pages in the intervention group were seeded with tables of best evidence of the effects of care and hyperlinks to the source Cochrane review. Eligible Wikipedia pages in the control group were left unchanged. MAIN OUTCOME MEASURES: Routinely collected data on access to the full text and summary web page (after 12 months). RESULTS: We randomised 70 Wikipedia pages (100% follow-up). Six of the 35 Wikipedia pages in the intervention group had the tabular format deleted during the study but all pages continued to report the same data within the text. There was no evidence of effect on either of the coprimary outcomes: full-text access adjusted ratio of geometric means 1.30, 95% CI: 0.71 to 2.38; page views 1.14, 95% CI: 0.6 to 2.13. Results were similar for all other outcomes, with exception of Altmetric score for which there was some evidence of clear effect (1.36, 95% CI: 1.05 to 1.78). CONCLUSIONS: The pursuit of fair balance within Wikipedia healthcare pages is impressive and its reach unsurpassed. For every person who sought and clicked the reference on the 'intervention' Wikipedia page to seek more information (the primary outcome), many more are likely to have been informed by the page alone. Enriching Wikipedia content is, potentially, a powerful way to improve health literacy and it is possible to test the effects of seeding pages with evidence. This trial should be replicated, expanded and developed. TRIAL REGISTRATION NUMBER: IRCT2017070330407N2.

The Quality and Readability of English Wikipedia Anatomy Articles.

Forty anatomy articles were sampled from English Wikipedia and assessed quantitatively and qualitatively. Quantitatively, each article's edit history was analyzed by Wikipedia X-tools, references and media were counted manually, and two readability indices were used to evaluate article readability. This analysis revealed that each article was updated 8.3 ± 6.8 times per month, and referenced with 33.5 ± 24.3 sources, such as journal articles and textbooks. Each article contained on average 14.0 ± 7.6 media items. The readability indices including: (1) Flesch-Kincaid Grade Level Readability Test and (2) Flesch Reading Ease Readability Formula demonstrated that the articles had low readability and were more appropriate for college students and above. Qualitatively, the sampled articles were evaluated by experts using a modified DISCERN survey. According to the modified DISCERN, 13 articles (32.5%), 24 articles (60%), 3 articles (7.5%), were rated as "good," "moderate," and "poor," respectively. There were positive correlations between the DISCERN score and the number of edits (r = 0.537), number of editors (r = 0.560), and article length (r = 0.536). Strengths reported by the panel included completeness and coverage in 11 articles (27.5%), anatomical details in 10 articles (25%), and clinical details in 5 articles (12.5%). The panel also noted areas which could be improved, such as providing missing information in 28 articles (70%), inaccuracies in 10 articles (25%), and lack or poor use of images in 17 articles (42.5%). In conclusion, this study revealed that many Wikipedia anatomy articles were difficult to read. Each article's quality was dependent on edit frequency and article length. Learners and students should be cautious when using Wikipedia articles for anatomy education due to these limitations.

Teaching Evidence-Based Medicine to Medical Students Using Wikipedia as a Platform.

PROBLEM: While ideal curricular structures for effective teaching of evidence-based medicine (EBM) have not been definitively determined, optimal strategies ensure that EBM teaching is interactive and clinically based, aligns with major trends in education and health care, and uses longitudinally integrated, whole-task activities. APPROACH: The authors developed a longitudinal, semester-long project, embedded in a first-year medicine course, through which they taught EBM using Wikipedia as a platform. Students worked individually and in small groups to choose a medicine-related Wikipedia article, identify information gaps, search for high-quality resources, appraise the sources, and incorporate the new information into the article (i.e., by editing Wikipedia). Students also applied their new appraisal skills to critique a second article. The authors used an online tool to track and record student editing, and they obtained qualitative data on student perceptions of the project via survey. Duplicate marking of a sample of assignments was performed using the Valid Assessment of Learning in Undergraduate Education critical thinking rubric developed by Finley and Rhodes. OUTCOMES: In fall 2017, 101 students made over 1,000 unique edits to 16 online Wikipedia articles, adding over 10,000 words. Through thematic analysis of qualitative data, the authors highlighted several aspects of the project that students appreciated, as well as barriers related to completing their projects. Correlation of the 17 consenting students' final assignments with the critical thinking rubric supports the assignment structure as a tool for assessing critical thinking. NEXT STEPS: This authentic task adheres to the principles of high-quality EBM instruction and could be implemented by a variety of health care educational programs. Modifications to the delivery model are underway to address challenges identified.

Continuing medical and student education in dermatology during the coronavirus pandemic - a major challenge.

Continuing medical education (CME) is the essential basis for student teaching and for training and further development of physicians. Without it, modern and adequate patient care is unthinkable. Recently, the coronavirus pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARSCoV2), forced the entire medical community to change its usual habits of advanced medical training, teaching and learning. As a result, digital training and teaching via social media, online medical encyclopedias, web-based learning platforms and educational podcasts moved to the fore. Here, we give an overview on current concepts for online medical education, with special consideration of dermatology.

Collectively biased representations of the past: Ingroup Bias in Wikipedia articles about intergroup conflicts.

Individuals tend to present their own group (the ingroup) in a systematically more favourable way (ingroup bias). By examining socially negotiated and publicly accessible Wikipedia articles about intergroup conflicts, we investigated ingroup bias at a collective level. Specifically, we compared articles about the same intergroup conflicts (e.g., the Falklands War) in the corresponding language versions of Wikipedia (e.g., the Spanish and English Wikipedia articles about the Falklands War). Study 1 featured a content coding of translated Wikipedia articles by trained raters, which showed that articles systematically presented the ingroup in a more favourable way (e.g., Argentina in the Spanish article and the United Kingdom in the English article) and, in reverse, the outgroup as more immoral and more responsible for the conflict. These findings were replicated and extended in Study 2, which was limited to the lead sections of articles but included considerably more conflicts and many participants instead of a few trained coders. This procedure allowed for separate analyses for each conflict, which showed considerable variance in the results pattern with a stronger ingroup bias for (1) more recent conflicts and (2) conflicts in which the proportion of ingroup members among the top editors was larger. Finally, a third study ruled out that these effects were driven by translations or the raters' own nationality. Therefore, this paper is the first to demonstrate ingroup bias in Wikipedia - a finding that is of practical as well as theoretical relevance as we outline in the discussion.

Wikipedia: Why is the common knowledge resource still neglected by academics?

Wikipedia is by far the largest online encyclopedia, and the number of errors it contains is on par with the professional sources even in specialized topics such as biology or medicine. Yet, the academic world is still treating it with great skepticism because of the types of inaccuracies present there, the widespread plagiarism from Wikipedia, and historic biases, as well as jealousy regarding the loss of the knowledge dissemination monopoly. This article argues that it is high time not only to acknowledge Wikipedia's quality but also to start actively promoting its use and development in academia.

Is Wikipedia a complete and accurate source for musculoskeletal anatomy?

PURPOSE: Wikipedia is a popular online encyclopedia generating over 5.4 billion visits per month, and it is also a common resource for the general public and professionals for medical information. The goal of this study is to determine the accuracy and completeness of Wikipedia as a resource for musculoskeletal anatomy. METHODS: The origin, insertion, innervation, and function of all muscles of the upper and lower extremities as detailed on Wikipedia was compared to the available corresponding information in Grant's Atlas of Anatomy (14th edition). Entries were scored for both accuracy and completeness. Descriptive statistics were calculated and associations between and within entries for accuracy and completeness were assessed by McNemar's tests. Information on Wikipedia's references was also collected. RESULTS: Overall, data on Wikipedia was 97.6% complete and 98.8% accurate when compared to Grant's Atlas of Anatomy. 78.6% of all entries were fully complete and accurate, with 15.3% of entries containing one error and 6.1% containing two errors. There were no associations between or within entries' accuracy and completeness. Only 62% of references from Wikipedia included were from academic sources. CONCLUSIONS: Musculoskeletal anatomy entries on Wikipedia are imperfect; they have inaccurate and missing information. Furthermore, a considerable proportion of references cited in entries are from poorly identified sources. While Wikipedia is an easily accessible resource for a large number of people and much of the anatomic information is appropriate, it cannot be considered to be an equivalent resource when compared to anatomic texts.

Early onset of structural inequality in the formation of collaborative knowledge in all Wikimedia projects.

The Wikimedia project, including Wikipedia, is one of the largest communal data sets and has served as a representative medium to convey collective knowledge in the twenty-first century. Researchers have believed that the analysis of these collaborative digital data sets provides a unique window into the processes of collaborative knowledge formation; yet, in reality, most previous studies have usually focused on its narrow subsets. Here, by analysing all 863 Wikimedia projects (various types and in different languages), we find evidence for a universal growth pattern in communal data formation. We observe that inequality arises early in the development of Wikimedia projects and stabilizes at high levels. To understand the mechanism behind the observed structural inequality, we develop an agent-based model that considers the characteristics of the editors and successfully reproduces the empirical results. Our findings from the Wikimedia projects data, along with other types of collaboration data, such as patents and academic papers, show that a small number of editors have a disproportionately large influence on the formation of collective knowledge. This analysis offers insights into how various collaboration environments can be sustained in the future.

The wisdom of polarized crowds.

As political polarization in the United States continues to rise1-3, the question of whether polarized individuals can fruitfully cooperate becomes pressing. Although diverse perspectives typically lead to superior team performance on complex tasks4,5, strong political perspectives have been associated with conflict, misinformation and a reluctance to engage with people and ideas beyond one's echo chamber6-8. Here, we explore the effect of ideological composition on team performance by analysing millions of edits to Wikipedia's political, social issues and science articles. We measure editors' online ideological preferences by how much they contribute to conservative versus liberal articles. Editor surveys suggest that online contributions associate with offline political party affiliation and ideological self-identity. Our analysis reveals that polarized teams consisting of a balanced set of ideologically diverse editors produce articles of a higher quality than homogeneous teams. The effect is most clearly seen in Wikipedia's political articles, but also in social issues and even science articles. Analysis of article 'talk pages' reveals that ideologically polarized teams engage in longer, more constructive, competitive and substantively focused but linguistically diverse debates than teams of ideological moderates. More intense use of Wikipedia policies by ideologically diverse teams suggests institutional design principles to help unleash the power of polarization.

[Medicine in Croatian Lexicography and Encyclopaedistics] / Medicina u hrvatskoj leksikografiji i enciklopedici

Due to the undeniable importance of medicine in human life, the authors explore the level of attentiveness given to medical topics since the beginnings of Croatian lexicography and encyclopaedistics in the 16th century until today. Specific emphasis is put on the activities of the Miroslav Krleza Institute of Lexicography, as the only Croatian institution which has been systematically involved in the field of lexicography and encyclopaedistics for almost 70 years. The representation and importance of medicine have been established in three ways. Firstly, by chronologically presenting medical terms and topics in the works of Croatian lexicography and encyclopaedistics from the 16th to the 19th century. Subsequently, by systemizing and analysing medical publications published in the 20th century, especially the ones created by the Institute. Lastly, by reviewing the presence of medical terms and topics in other Institute's publications, especially in the Croatian Encyclopaedia. The study shows that medicine has been well represented in Croatian lexicographic and encyclopaedic works, which have played a significant role in establishing Croatian medical terminology and adding to systematization of knowledge in the field of medicine. The authors conclude that lexicography and encyclopaedistics in Croatia have paid adequate attention to medical topics, as well as mirrored the interest of professional and broader community towards medicine.

Altered levels of focal adhesion and extracellular matrix-receptor interacting proteins were identified in Hailey-Hailey disease by quantitative iTRAQ proteome analysis.

Benign chronic familial pemphigus or Hailey-Hailey disease (HHD, OMIM 169600) is a rare, autosomal dominant blistering skin disorder characterized by suprabasal cell separation (acantholysis) of the epidermis. To date, the proteomic changes in skin lesions from HHD patients has not been reported yet. In this study, a sample of skin lesions from HHD patients was collected for isobaric tags for relative and absolute quantitation to analyze proteome changes compared with unaffected individuals. The 134 differentially expressed proteins were assigned to at least one Gene Ontology term, and 123 annotated proteins with significant matches were assigned to 187 known metabolic or signaling pathways listed in the Kyoto Encyclopedia of Genes and Genomes. Most of the altered proteins in skin lesions of HHD patients were enriched in pathways involved in the PI3K-Akt signaling, focal adhesion, extracellular matrix (ECM)-receptor interaction, and protein digestion and absorption, such as collagen family members, microfibril-associated glycoprotein 4 and plakophilin. The changes of proteins related to cell adhesion, ECM-receptor interaction, and protein folding and glycosylation suggested that strategy targeted to alter cell junction and extracellular microenvironment might provide a potential treatment for HHD.

Integrating Wikipedia Articles and Images into an Information Resource for Radiology Patients.

Wikipedia-an open-access online encyclopedia-contains a large number of medically relevant articles and images that may help supplement glossaries of radiology terms. We sought to determine the extent to which concepts from a large online radiology glossary developed as part of the Patient-Oriented Radiology Reporter (PORTER) initiative could be mapped to relevant Wikipedia web pages and images using automated or semi-automated approaches. The glossary included 4090 concepts with their definitions; the concept's preferred name and lexical variants, such as plurals, adjectival forms, synonyms, and abbreviations, yielded a total of 13,030 terms. Of the 4090 concepts, 3063 (74.9%) had a corresponding English-language Wikipedia page identified by automated search with subsequent manual review. We applied the MediaWiki application programming interface (API) to generate web-service calls to identify the images from each concept's corresponding Wikipedia page; three reviewers selected relevant images to associate with the glossary's concepts. Licensing terms for the images were reviewed. For 800 randomly sampled concepts that had associated Wikipedia pages, 362 distinct images were identified from the MediaWiki library and matched to 404 concepts (51%). Three images (1%) had unspecified licensing terms; the rest were in the public domain or available via a Creative Commons license. Wikipedia and the MediaWiki library offer a large collection of medical articles and images that can be incorporated into an online lay-language glossary of radiology terms though a semi-automated approach.