Online Knowledge Base Research Articles

Countering underproduction of peer produced goods

Peer produced goods, such as online knowledge bases and free/libre open source software rely on contributors who often choose their tasks regardless of consumer needs. These goods are susceptible to underproduction: when popular goods are relatively low quality. Although underproduction is a common feature of peer production, very little is known about how to counteract it. We use a detailed longitudinal dataset from English Wikipedia to show that more experienced contributors—including those who contribute without an account—tend to contribute to underproduced goods. A within-person analysis shows that contributors’ efforts shift toward underproduced goods over time. These findings illustrate the value of retaining contributors in peer production, including those contributing without accounts, as a means to counter underproduction.

OP09 Developing A Patient And Consumer Training Tool Explaining Health Technology Assessment And Patient/Consumer Participation: The French Experience

IntroductionThe French National Authority for Health’s (HAS) 2019-2024 strategic workplan called for “making public involvement a priority.” This project was designed within the roadmap validated in 2021; “Strengthening public involvement in health technology assessment (HTA) at the HAS”, including an action of building a means of training patient organizations for their contribution. The project’s overall objective was to develop with patients and consumers a first training tool, representing an online knowledge base targeting French patients and consumers to explain the HAS HTA process and assist their participation in these assessments.MethodsThree stages were designed to meet this objective. Firstly, an international benchmark was performed of available online HTA training tools for patients and consumers, notably those used by HTA bodies and European and international patient and consumer groups (PCGs). Secondly, an internal HAS search for e-learning tools, was conducted to identify whether they could meet the training needs of French patients and consumers. Finally, the training tool was developed via a working group composed of patients and HAS scientific officers.ResultsThe benchmark identified 82 online training tools selected according to the specified inclusion criteria. Sixteen international HTA agencies, nine European and international PCGs and 13 other bodies provided online HTA training tools for patients and consumers during the research period, but no journal articles identified such tools. Eleven formats and 12 key themes, divided into two main categories were identified: important content related to HTA, and important content related to public involvement in HTA. The HAS search for e-learning tools resulted in internal e-learning tools offered for clinical experts not meeting the needs and preferences of patients and consumers. Finally, HAS based its training tool development on these preferences and needs to create a PowerPoint in two blocks of modules covering the two main categories above (six modules in total).ConclusionsFrench patients and consumers preferences and needs for a HTA training tool were inspired by the international benchmark, dividing key themes into two main categories: important content related to HTA, and important content related to public involvement in HTA. This resulted in HAS development of two blocks of modules in PowerPoint format covering these two categories.

ELGA Terminology Server for Clinical Decision Support: A Case-Study Using an Existing Knowledge Base, CDS Hooks and FHIR.

There are many medical knowledge bases with potential for supporting medical professionals in their decision-making during routine care, yet usage of these sources remains low. Standardized linking of Clinical Decision Support (CDS) applications and existing medical knowledge bases is not a common practice. Using existing eHealth standards to increase the utilization of knowledge bases and implement a prototype. Linking an existing online knowledge base via a FHIR CodeSystem supplement to the Austrian national EHR (ELGA) terminology server and accessing these data using CDS Hooks and FHIR. We tested the approach by incorporating photosensitivity data of medications into a local copy of the Austrian terminology server. These data are directly used by a CDS Hooks compliant CDS service. The Austrian Terminology Server could be an important interface to access existing knowledge bases from within EHR systems. FHIR and CDS Hooks could lead the way for a simple and open integration of CDS services into EHR systems.

Improving a Library FAQ: Assessment and Reflection of the First Year’s Use

ABSTRACT In 2020, the Leonard Lief Library created a searchable online knowledge base (FAQs) as a complement to virtual reference during the library’s pandemic-related closure. One year of search query data was used to assess the online knowledge base. This paper discusses the assessment’s findings and planned improvements to the FAQs. A content analysis of user queries revealed what users are seeking in the knowledge base. The study examined the actions taken by users after conducting a search to determine the knowledge base’s success rate. The knowledge base was successful in answering user questions almost half of the time. The top three query categories were access, non-library, and instructional. The frequency of access-related queries was expected, due to COVID-19 library building closure. The prevalence of questions about other campus units was unexpected. This finding suggests a perception of the academic library as a source of campus information and supports including this type of information in the library FAQs. This study adds to the body of assessment research within reference services, an area not well represented in the LIS literature. The methodology employed provides a model for assessment of online FAQs that can be adopted by other libraries.

Pulmonary hazard identifications of Graphene family nanomaterials: Adverse outcome pathways framework based on toxicity mechanisms.

Graphene-family nanomaterials (GFNs) are revolutionary new nanomaterials that have attracted significant attention in the field of nanomaterials, but the ensuing problems lie in the potential threats to public health and the ecosystem caused by these nanomaterials. From the perspective of GFN-related health risk assessments, this study reviews the current status of GFN-induced pathological lung events with a focus on the damage caused to different biological moieties (molecular, cellular, tissue, and organ) and the mechanistic relationships between different toxic endpoints. These multiple sites of damage were matched with existing adverse outcome pathways (AOPs) in an online knowledge base to obtain available molecular initiation events (MIEs), key events (KEs), and adverse outcomes (AOs). Among them, the MIEs were discussed in combination with the structure-activity relationship due to the correlation between toxicity and physical and chemical properties of GFNs. Based on the collection of information regarding MIEs, Kes, and AOs in addition to upstream and downstream causal extrapolation, the AOP framework for GFN-induced pulmonary toxicity was developed, highlighting the possible mechanisms of GFN-induced lung damage. This review intended to combine AOP with classic toxicological methods with a view to rapidly and accurately establishing a nanotoxicology infrastructure so as to contribute to public health risk assessment strategies through iteration from and animal models up to the population level.

An Open-Access Toolkit for Collaborative, Community-Informed Dictionaries

ABSTRACT: In this article, we discuss the development of a relational lexicography framework and an open-access toolkit for collaborative, community-informed dictionaries. We explain how the relational lexicography toolkit supports envisioning, developing, and publishing dictionaries that meet the cultural, linguistic, and educational goals of Indigenous communities who, despite ongoing language shift, are working to strengthen their languages. This framework recognizes the many relationships that are present in community-based language projects, including relationships between speakers, dialects, academics, communities, and the dictionary itself. The toolkit, which comprises two online Knowledgebase of Indigenous language dictionaries and lexicography technologies, documents how these relationships have been represented in existing work and provides a centralized platform to refer to and compare resources. Overall, this article provides background context on our methodology, project development, aspects of the resulting resources, and the anticipated benefit of creating such an open-access framework in support of community-based lexicography.

Q-NET – a new scholarly network on quantitative wood anatomy

Quantitative wood anatomy (QWA) is a dynamic research approach of increasing interest that can provide answers to a wide range of research questions across different disciplines. However, the lack of common protocols and knowledge gaps hinder the realisation of the full potential of QWA. Therefore, we established the new community-based network Q-NET to provide an open interdisciplinary platform for exchange and research around QWA. Q-NET (https://qwa-net.com) combines an online knowledge and exchange base with virtual workshops. The first two workshops each attracted more than 125 participants from around the world, demonstrating the community's interest in QWA and this virtual way of networking and collaborating. Indeed, virtual networks such as Q-NET could increase the inclusiveness, efficiency and sustainability of scientific collaboration while providing additional training and teaching opportunities for early career scientists, both of which complement in-person conferences and workshops.

Cross-language article linking with deep neural network based paragraph encoding

Cross-language article linking (CLAL), the task of generating links between articles in different languages from different encyclopedias, is critical for facilitating sharing among online knowledge bases. Some previous CLAL research has been done on creating links among Wikipedia wikis, but much of this work depends heavily on simple language patterns and encyclopedia format or metadata. In this paper, we propose a new CLAL method based on deep learning paragraph embeddings to link English Wikipedia articles with articles in Baidu Baike, the most popular online encyclopedia in mainland China. To measure article similarity for link prediction, we employ several neural networks with attention mechanisms, such as CNN and LSTM, to train paragraph encoders that create vector representations of the articles’ semantics based only on article text, rather than link structure, as input data. Using our “Deep CLAL” method, we compile a data set consisting of Baidu Baike entries and corresponding English Wikipedia entries. Our approach does not rely on linguistic or structural features and can be easily applied to other language pairs by using pre-trained word embeddings, regardless of whether the two languages are on the same encyclopedia platform.

Comprior: facilitating the implementation and automated benchmarking of prior knowledge-based feature selection approaches on gene expression data sets

BackgroundReproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness.ResultsWe present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance.ConclusionComprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness.

Spiking neural networks and hippocampal function: A web-accessible survey of simulations, modeling methods, and underlying theories

Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The intensively studied neuron type circuitry of the hippocampus is a particularly conducive substrate for spiking neural models. Here we present an online knowledge base of spiking neural network simulations of hippocampal functions. First, we overview theories involving the hippocampal formation in subjects such as spatial representation, learning, and memory. Then we describe an original literature mining process to organize published reports in various key aspects, including: (i) subject area (e.g., navigation, pattern completion, epilepsy); (ii) level of modeling detail (Hodgkin-Huxley, integrate-and-fire, etc.); and (iii) theoretical framework (attractor dynamics, oscillatory interference, self-organizing maps, and others). Moreover, every peer-reviewed publication is also annotated to indicate the specific neuron types represented in the network simulation, establishing a direct link with the Hippocampome.org portal. The web interface of the knowledge base enables dynamic content browsing and advanced searches, and consistently presents evidence supporting every annotation. Moreover, users are given access to several types of statistical reports about the collection, a selection of which is summarized in this paper. This open access resource thus provides an interactive platform to survey spiking neural network models of hippocampal functions, compare available computational methods, and foster ideas for suitable new directions of research.

Resourcing, annotating, and analysing synthetic peptides of SARS-CoV-2 for immunopeptidomics and other immunological studies.

SARS‐CoV‐2 has caused a significant ongoing pandemic worldwide. A number of studies have examined the T cell mediated immune responses against SARS‐CoV‐2, identifying potential T cell epitopes derived from the SARS‐CoV‐2 proteome. Such studies will aid in identifying targets for vaccination and immune monitoring. In this study, we applied tandem mass spectrometry and proteomic techniques to a library of ∼40,000 synthetic peptides, in order to generate a large dataset of SARS‐CoV‐2 derived peptide MS/MS spectra. On this basis, we built an online knowledgebase, termed virusMS (https://virusms.erc.monash.edu/), to document, annotate and analyse these synthetic peptides and their spectral information. VirusMS incorporates a user‐friendly interface to facilitate searching, browsing and downloading the database content. Detailed annotations of the peptides, including experimental information, peptide modifications, predicted peptide‐HLA (human leukocyte antigen) binding affinities, and peptide MS/MS spectral data, are provided in virusMS.

Use of online knowledge base in primary health care and correlation to health care quality: an observational study

BackgroundEvidence-based information available at the point of care improves patient care outcomes. Online knowledge bases can increase the application of evidence-based medicine and influence patient outcome data which may be captured in quality registries. The aim of this study was to explore the effect of use of an online knowledge base on patient experiences and health care quality.MethodsThe study was conducted as a retrospective, observational study of 24 primary health care centers in Sweden exploring their use of an online knowledge base. Frequency of use was compared to patient outcomes in two national quality registries. A socio-economic Care Need Index was applied to assess whether the burden of care influenced the results from those quality registries. Non-parametric statistical methods and linear regression were used.ResultsFrequency of knowledge base use showed two groups: frequent and non-frequent users, with a significant use difference between the groups (p < 0.001). Outcome data showed significant higher values for all seven National Primary Care Patient Survey dimensions in the frequent compared to the non-frequent knowledge base users (p < 0.001), whereas 10 out of 11 parameters in the National Diabetes Register showed no differences between the groups (p > 0.05). Adjusting for Care Need Index had almost no effect on the outcomes for the groups.ConclusionsFrequent users of a national online knowledge base received higher ratings on patient experiences, but figures on health care quality in diabetes showed near to no correlation. The findings indicate that some effects may be attributed to the use of knowledge bases and requires a controlled evaluation.

Smart Education — The Necessity And Prospect Of Big Data Mining And Artificial Intelligence Technology In Art Education

smart education refers to a new education form and education mode relying on Internet technology, big data mining, artificial intelligence (AI) technology and mobile communication technology to realize online, platform, convenient, modular, accurate, and even mobile and fragmented learning knowledge and skills. This is a big trend. The education form of traditional art colleges is old-fashioned, conservative and lack of innovative means to adapt to it. It is imperative to improve the guidance, systematicness and convenience of art education curriculum by using new technology and new means. However, it is not very beneficial to simply transfer the curriculum and teaching materials under the offline learning mode to the Internet for all art students. Therefore, we put forward the concept and Prospect of "smart education". In short, smart education is the comprehensive development and utilization of online education platform, knowledge base, artificial intelligence (AI) and big data mining technology.

An online Paper Authoring Tool (PAT) to improve reporting of, and synthesis of evidence from, trials in behavioral sciences.

The Science of Behavior Change project represents a major advance in the way we approach the study of behavior and behavior change; the protocols in this special issue reflect the innovative approach to intervention development. Digital technology is transforming the way we conduct science and can greatly assist with developing protocols, reporting studies, and evidence synthesis. The journal Addiction has developed an online Paper Authoring Tool (PAT) for reporting full-scale randomized controlled trials that could also be used for reporting protocols and early phase trials. PAT aims to help authors ensure that they include all the required information and present it in a way that is clear and consistent in terms of language and phrasing. It also generates a computer-readable record that should greatly facilitate automation of evidence synthesis. PAT is intended to represent the first step in creation of a supportive ecosystem for the conduct of science, linking grant applications, study protocols, study reports, measures, reviews and study data in a coordinated online knowledge base. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

DES-ROD: Exploring Literature to Develop New Links between RNA Oxidation and Human Diseases.

Normal cellular physiology and biochemical processes require undamaged RNA molecules. However, RNAs are frequently subjected to oxidative damage. Overproduction of reactive oxygen species (ROS) leads to RNA oxidation and disturbs redox (oxidation-reduction reaction) homeostasis. When oxidation damage affects RNA carrying protein-coding information, this may result in the synthesis of aberrant proteins as well as a lower efficiency of translation. Both of these, as well as imbalanced redox homeostasis, may lead to numerous human diseases. The number of studies on the effects of RNA oxidative damage in mammals is increasing by year due to the understanding that this oxidation fundamentally leads to numerous human diseases. To enable researchers in this field to explore information relevant to RNA oxidation and effects on human diseases, we developed DES-ROD, an online knowledgebase that contains processed information from 298,603 relevant documents that consist of PubMed abstracts and PubMed Central full-text articles. The system utilizes concepts/terms from 38 curated thematic dictionaries mapped to the analyzed documents. Researchers can explore enriched concepts, as well as enriched pairs of putatively associated concepts. In this way, one can explore mutual relationships between any combinations of two concepts from used dictionaries. Dictionaries cover a wide range of biomedical topics, such as human genes and proteins, pathways, Gene Ontology categories, mutations, noncoding RNAs, enzymes, toxins, metabolites, and diseases. This makes insights into different facets of the effects of RNA oxidation and the control of this process possible. The usefulness of the DES-ROD system is demonstrated by case studies on some known information, as well as potentially novel information involving RNA oxidation and diseases. DES-ROD is the first knowledgebase based on text and data mining that focused on the exploration of RNA oxidation and human diseases.

Tear and Crumble: Deterioration Processes in Skins and Hides in Mammal Collections

Abstract In the mammal collection of the Museum für Naturkunde Berlin (MfN), Germany a serious but inconspicuous deterioration of mammal skins and hides has been detected. The tear strength has been decreasing until the skins are falling apart, risking permanent loss of valuable specimens. At the MfN, about 80% of the 30,000 skins are affected. Although this phenomenon has been known by taxidermists for some time, there are very few publications on the subject. In this study, we surveyed the literature and conducted interviews with collections and leather industry professionals to understand the extent and potential causes of skin deterioration. In addition, analyses of skins in the collections of the MfN and the ZFMK (Bonn, Germany) showed that more than 80% of the tested skins had a very low tear strength. The tear strength appears correlated with the pH value and age of the skin. Our findings suggest that surplus acid from residual fat, preservation methods, or external sources such as air pollution might be a primary source of the degradation. Future steps should include further research on the chemical processes involved in deterioration, treatment options for threatened skins, and development of best practices, protocols for documentation, and development of a publicly available online knowledge base for museum skin preparation, preservation, and storage methods.

Application of Economic Evaluation to Assess Feasibility for Reimbursement of Genomic Testing as Part of Personalized Medicine Interventions.

Background: The incorporation of genomic testing into clinical practice constitutes an opportunity to improve patients’ lives, as it makes possible the implementation of innovative, individualized clinical interventions that maximize efficacy and/or minimize the risk of adverse drug reactions. In order to ensure equal access to genomic testing for all patients, the costs associated with these tests should be reimbursed by their respective national healthcare systems. Given that funding for the public health sector is decreasing in real terms, it is of paramount importance that the emerging interventions are thoroughly evaluated both in terms of their clinical effectiveness and their full economic cost. Objective: The aim of this study was to identify those genome-guided interventions that could be adopted and reimbursed by national healthcare systems. Further, we recorded the underlying factors determining the broad adoption of genome-guided interventions in clinical practice, in order to identify potential reimbursement criteria. Methods: We performed a systematic review of published (PubMed-listed) scientific articles on the economic evaluation of those individualized clinical interventions that include genomic tests. Information on genomic tests reimbursed by the US Medicare program was also included. Subsequently, we correlated the regulatory guidance given for the interventions collated in our systematic review with the corresponding economic evaluation results and policies of the Medicare program. Regulatory guidance information was collected from the PharmGKB online knowledgebase and the Clinical Pharmacogenetics Implementation Consortium (CPIC). Results: Most of the included studies constitute cost-utility analyses, in which the outcome of the interventions has been measured in quality-adjusted life years (QALYs) whereas an estimate of the total cost has been based upon direct medical cost data. Favorable economic evaluation results, as well as concrete evidence demonstrating the clinical utility of pre-emptive genotyping, are considered as prerequisites for the broad adoption and reimbursement of the costs incurred during genomic testing. Indicatively, pre-emptive HLA-B*5701 and TPMT testing before administration of abacavir and azathioprine, respectively, is reimbursed by Medicare based on both economic and efficacy evidence. Likewise, the medical necessary screening for MMR and BRCA1/2 genes are reimbursed for high-risk populations. Conclusions: Our findings further underline the need for further cost-utility analyses within different national healthcare systems, in order to promote the reimbursement of the cost of innovative genome-guided therapeutic interventions.

A curated knowledgebase on endocrine disrupting chemicals and their biological systems-level perturbations.

Human well-being can be affected by exposure to several chemicals in the environment. One such group is endocrine disrupting chemicals (EDCs) that can perturb the hormonal homeostasis leading to adverse health effects. In this work, we have developed a detailed workflow to identify EDCs with supporting evidence of endocrine disruption in published experiments in humans or rodents. Thereafter, this workflow was used to manually evaluate more than 16,000 published research articles and identify 686 potential EDCs with published evidence in humans or rodents. Importantly, we have compiled the observed adverse effects or endocrine-specific perturbations along with the dosage information for the potential EDCs from their supporting published experiments. Subsequently, the potential EDCs were classified based on the type of supporting evidence, their environmental source and their chemical properties. Additional compiled information for potential EDCs include their chemical structure, physicochemical properties, predicted ADMET properties and target genes. In order to enable future research based on this compiled information on potential EDCs, we have built an online knowledgebase, Database of Endocrine Disrupting Chemicals and their Toxicity profiles (DEDuCT), accessible at: https://cb.imsc.res.in/deduct/. After building this comprehensive resource, we have performed a network-centric analysis of the chemical space and the associated biological space of target genes of EDCs. Specifically, we have constructed two networks of EDCs using our resource based on similarity of chemical structures or target genes. Ensuing analysis revealed a lack of correlation between chemical structure and target genes of EDCs. Though our detailed results highlight potential challenges in developing predictive models for EDCs, the compiled information in our resource will undoubtedly enable future research in the field, especially, those focussed towards mechanistic understanding of the systems-level perturbations caused by EDCs.

PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.

Post-translational modifications (PTMs) play very important roles in various cell signaling pathways and biological process. Due to PTMs' extremely important roles, many major PTMs have been studied, while the functional and mechanical characterization of major PTMs is well documented in several databases. However, most currently available databases mainly focus on protein sequences, while the real 3D structures of PTMs have been largely ignored. Therefore, studies of PTMs 3D structural signatures have been severely limited by the deficiency of the data. Here, we develop PRISMOID, a novel publicly available and free 3D structure database for a wide range of PTMs. PRISMOID represents an up-to-date and interactive online knowledge base with specific focus on 3D structural contexts of PTMs sites and mutations that occur on PTMs and in the close proximity of PTM sites with functional impact. The first version of PRISMOID encompasses 17145 non-redundant modification sites on 3919 related protein 3D structure entries pertaining to 37 different types of PTMs. Our entry web page is organized in a comprehensive manner, including detailed PTM annotation on the 3D structure and biological information in terms of mutations affecting PTMs, secondary structure features and per-residue solvent accessibility features of PTM sites, domain context, predicted natively disordered regions and sequence alignments. In addition, high-definition JavaScript packages are employed to enhance information visualization in PRISMOID. PRISMOID equips a variety of interactive and customizable search options and data browsing functions; these capabilities allow users to access data via keyword, ID and advanced options combination search in an efficient and user-friendly way. A download page is also provided to enable users to download the SQL file, computational structural features and PTM sites' data. We anticipate PRISMOID will swiftly become an invaluable online resource, assisting both biologists and bioinformaticians to conduct experiments and develop applications supporting discovery efforts in the sequence-structural-functional relationship of PTMs and providing important insight into mutations and PTM sites interaction mechanisms. The PRISMOID database is freely accessible at http://prismoid.erc.monash.edu/. The database and web interface are implemented in MySQL, JSP, JavaScript and HTML with all major browsers supported.

Literature-Based Enrichment Insights into Redox Control of Vascular Biology.

In cellular physiology and signaling, reactive oxygen species (ROS) play one of the most critical roles. ROS overproduction leads to cellular oxidative stress. This may lead to an irrecoverable imbalance of redox (oxidation-reduction reaction) function that deregulates redox homeostasis, which itself could lead to several diseases including neurodegenerative disease, cardiovascular disease, and cancers. In this study, we focus on the redox effects related to vascular systems in mammals. To support research in this domain, we developed an online knowledge base, DES-RedoxVasc, which enables exploration of information contained in the biomedical scientific literature. The DES-RedoxVasc system analyzed 233399 documents consisting of PubMed abstracts and PubMed Central full-text articles related to different aspects of redox biology in vascular systems. It allows researchers to explore enriched concepts from 28 curated thematic dictionaries, as well as literature-derived potential associations of pairs of such enriched concepts, where associations themselves are statistically enriched. For example, the system allows exploration of associations of pathways, diseases, mutations, genes/proteins, miRNAs, long ncRNAs, toxins, drugs, biological processes, molecular functions, etc. that allow for insights about different aspects of redox effects and control of processes related to the vascular system. Moreover, we deliver case studies about some existing or possibly novel knowledge regarding redox of vascular biology demonstrating the usefulness of DES-RedoxVasc. DES-RedoxVasc is the first compiled knowledge base using text mining for the exploration of this topic.