Curation Process Research Articles

Microbe Finder (MiFi®): Implementation of an Interactive Pathogen Detection Tool in Metagenomic Sequence Data.

Agricultural high throughput diagnostics need to be fast, accurate and have multiplexing capacity. Metagenomic sequencing is being widely evaluated for plant and animal diagnostics. Bioinformatic analysis of metagenomic sequence data has been a bottleneck for diagnostic analysis due to the size of the data files. Most available tools for analyzing high-throughput sequencing (HTS) data require that the user have computer coding skills and access to high-performance computing. To overcome constraints to most sequencing-based diagnostic pipelines today, we have developed Microbe Finder (MiFi®). MiFi® is a web application for quick detection and identification of known pathogen species/strains in raw, unassembled HTS metagenomic data. HTS-based diagnostic tools developed through MiFi® must pass rigorous validation, which is outlined in this manuscript. MiFi® allows researchers to collaborate in the development and validation of HTS-based diagnostic assays using MiProbe™, a platform used for developing pathogen-specific e-probes. Validated e-probes are made available to diagnosticians through MiDetect™. Here we describe the e-probe development, curation and validation process of MiFi® using grapevine pathogens as a model system. MiFi® can be used with any pathosystem and HTS platform after e-probes have been validated.

Nontargeted Analysis of Face Masks: Comparison of Manual Curation to Automated GCxGC Processing Tools.

Masks constructed of a variety of materials are in widespread use due to the COVID-19 pandemic, and people are exposed to chemicals inherent in the masks through inhalation. This work aims to survey commonly available mask materials to provide an overview of potential exposure. A total of 19 mask materials were analyzed using a nontargeted analysis two-dimensional gas chromatography (GCxGC)-mass spectrometric (MS) workflow. Traditionally, there has been a lack of GCxGC-MS automated high-throughput screening methods, resulting in trade-offs with throughput and thoroughness. This work addresses the gap by introducing new machine learning software tools for high-throughput screening (Floodlight) and subsequent pattern analysis (Searchlight). A recursive workflow for chemical prioritization suitable for both manual curation and machine learning is introduced as a means of controlling the level of effort and equalizing sample loading while retaining key chemical signatures. Manual curation and machine learning were comparable with the mask materials clustering into three groups. The majority of the chemical signatures could be characterized by chemical class in seven categories: organophosphorus, long chain amides, polyethylene terephthalate oligomers, n-alkanes, olefins, branched alkanes and long-chain organic acids, alcohols, and aldehydes. The olefin, branched alkane, and organophosphorus components were primary contributors to clustering, with the other chemical classes having a significant degree of heterogeneity within the three clusters. Machine learning provided a means of rapidly extracting the key signatures of interest in agreement with the more traditional time-consuming and tedious manual curation process. Some identified signatures associated with plastics and flame retardants are potential toxins, warranting future study to understand the mask exposure route and potential health effects.

CTD anatomy: Analyzing chemical-induced phenotypes and exposures from an anatomical perspective, with implications for environmental health studies

The Comparative Toxicogenomics Database (CTD) is a freely available public resource that curates and interrelates chemical, gene/protein, phenotype, disease, organism, and exposure data. CTD can be used to address toxicological mechanisms for environmental chemicals and facilitate the generation of testable hypotheses about how exposures affect human health. At CTD, manually curated interactions for chemical-induced phenotypes are enhanced with anatomy terms (tissues, fluids, and cell types) to describe the physiological system of the reported event. These same anatomy terms are used to annotate the human media (e.g., urine, hair, nail, blood, etc.) in which an environmental chemical was assayed for exposure. Currently, CTD uses more than 880 unique anatomy terms to contextualize over 255,000 chemical-phenotype interactions and 167,000 exposure statements. These annotations allow chemical-phenotype interactions and exposure data to be explored from a novel, anatomical perspective. Here, we describe CTD’s anatomy curation process (including the construction of a controlled, interoperable vocabulary) and new anatomy webpages (that coalesce and organize the curated chemical-phenotype and exposure data sets). We also provide examples that demonstrate how this feature can be used to identify system- and cell-specific chemical-induced toxicities, help inform exposure data, prioritize phenotypes for environmental diseases, survey tissue and pregnancy exposomes, and facilitate data connections with external resources. Anatomy annotations advance understanding of environmental health by providing new ways to explore and survey chemical-induced events and exposure studies in the CTD framework.

Cancer Registry Coding via Hybrid Neural Symbolic Systems in the Cross-Hospital Setting

Cancer registries are critical databases for cancer research whose maintenance requires various types of domain knowledge with labor-intensive data curation. In order to facilitate the curation process with high quality in a timely manner, we developed a hybrid neural symbolic system for cancer registry coding. Unlike previous works which mainly worked on the dataset collected from one hospital or formulated the task as text classification problems, we collaborated with two medical centers in Taiwan to compile a cross-hospital corpus and applied neural networks to extract cancer registry variables described in unstructured pathology reports along with expert systems for generating registry coding. We conducted experiments to study the feasibility of the proposed hybrid for the task of cancer registry coding and compare its performance with state-of-the-art non-hybrid approaches. Furthermore, cross-hospital experiments were performed to study the advantages and limitations of transfer learning for processing reports from different sources. The experiment results demonstrated that the proposed hybrid neural symbolic system is a robust approach which works well across hospitals and outperformed classification-based baselines by F-scores of 0.13~0.27. Compared to the baseline models, the F-scores of the proposed approaches are apparently higher when fewer training instances were used. All methods benefited from the transferred parameters learned from the source dataset, but the results suggest that it is a better strategy to transfer the learned knowledge through the concept recognition task followed by the symbolic expert system to address the task of cancer registry coding.

The Science Library: Curation and visualization of a science gateway repository

SummaryScientific publications from a group or consortium often form a coherent larger body of work with underlying threads and relationships. Rich social, structural, and topical networks between authors and organizations can be identified, and to convey these we have created the publicly available “Science Library” as a user‐centric, interactive portal. A key consideration in this endeavor is rapid and efficient curation of the corpus of publications, both in terms of assuring quality, as well minimizing the effort required. For this to be sustainable it must offer substantial benefits to the community and avoid excessive operational cost through cumbersome or complex processes. We describe the agility of the Science Library implementation as a controlled natural language (CNL) semantic knowledge graph and describe the different roles within the community to ensure efficient curation, validation, and provenance of the content. By describing the process of curation and validation, alongside the CNL‐based definition of the model we show how relatively non‐technical users are able to interact with, and contribute to the Science Library. This provides an extensible approach, initially based around digital library and virtual community capabilities, that can be applied more broadly to support other desired capabilities of Science Gateways.

DATA CURATION DAN RESEARCH DATA MANAGEMENT UNTUK TERWUJUDNYA INTEGRASI DATA RISET DI INDONESIA

Indonesia is actively supporting the research process that is conducted in their research institutions, by providing research funds for them. Many research institutions in Indonesia work in the similar field and their funding could also come from the same source. Based on that reason, there is a need to evaluate the data curation and research data management processes at Indonesian research institutions. The purposes of this research are to evaluate the existing research data conditions at several research institutions, issues associated with research data management, standards and tools to support the implementation of research data management, also finding a way to achieve research data integration for research institutions in Indonesia. Interviews were used as the method to gain data from several research institutions in Indonesia then it was analysed with the qualitative data analysis. Ultimately, the result shows that data access problem, data collection and awareness of researcher are the main complexities of the research data management process. While policies and regulations on research data management are considered important by research institutions to guide them along the process. The result also shows that integration between research institutions could be achieved by using supporting tools and protocols such as OAI-PMH (The Open Archives Initiative Protocol for Metadata Harvesting) and API (Application Programming Interface), integrated system and standard data format.

Desafios e estratégias para a gestão de coleções de remanescentes humanos na Amazônia

Neste texto destacamos a situação das coleções formadas por remanescentes de corpos humanos recuperados de contextos arqueológicos na Amazônia. Os desafios de conservação e acondicionamento desses acervos se relacionam tanto a fatores técnicos quanto a prática arqueológica em si. Através do histórico de pesquisa dos remanescentes humanos do sítio Curiaú Mirim – I, AP, desde sua escavação até a recente revisão dos processos curatoriais, desejamos observar problemas comuns a instituições e coleções na Amazônia. As soluções e reflexões apresentadas, embora não esgotem o problema, apontam para a importância dos processos curatoriais para a gestão desses acervos. Ademais, debatemos a necessidade de profissionais especializados, de abordagens mais éticas sobre materiais sensíveis e de fortalecimento das redes de colaboração entre pessoas e instituições.

Measurement Recorder: developing a useful tool for making species descriptions that produces computable phenotypes.

To use published phenotype information in computational analyses, there have been efforts to convert descriptions of phenotype characters from human languages to ontologized statements. This postpublication curation process is not only slow and costly, it is also burdened with significant intercurator variation (including curator–author variation), due to different interpretations of a character by various individuals. This problem is inherent in any human-based intellectual activity. To address this problem, making scientific publications semantically clear (i.e. computable) by the authors at the time of publication is a critical step if we are to avoid postpublication curation. To help authors efficiently produce species phenotypes while producing computable data, we are experimenting with an author-driven ontology development approach and developing and evaluating a series of ontology-aware software modules that would create publishable species descriptions that are readily useable in scientific computations. The first software module prototype called Measurement Recorder has been developed to assist authors in defining continuous measurements and reported in this paper. Two usability studies of the software were conducted with 22 undergraduate students majoring in information science and 32 in biology. Results suggest that participants can use Measurement Recorder without training and they find it easy to use after limited practice. Participants also appreciate the semantic enhancement features. Measurement Recorder’s character reuse features facilitate character convergence among participants by 48% and have the potential to further reduce user errors in defining characters. A set of software design issues have also been identified and then corrected. Measurement Recorder enables authors to record measurements in a semantically clear manner and enriches phenotype ontology along the way. Future work includes representing the semantic data as Resource Description Framework (RDF) knowledge graphs and characterizing the division of work between authors as domain knowledge providers and ontology engineers as knowledge formalizers in this new author-driven ontology development approach.

Fitness for Use of Data Objects Described with Quality Maturity Matrix at Different Phases of Data Production

Fitness for use information should be stored to enable easy identification of data objects that are suitable for re-use – a feature which can only be assessed by the data user. With the described Quality Maturity Matrix (QMM), we want to provide a metric for a discrete measurement of the fitness for use of data objects. We use the data maturity to describe the degree of formalization and standardization of the data with respect to the quality of data and metadata. The data objects mature as they pass through the different post-production steps where they undergo different curation measures. The higher the maturity and the level in the QMM, the easier is it for the user to judge the appropriateness of the data for a possible re-use. For our development of the Quality Maturity Matrix we link the maturity levels to the five phases concept, production/processing, project collaboration/intended use, long-term archiving, and impact re-use. Each of the five levels is measured with regard to the four criteria consistency, completeness, accessibility, and accuracy. For the description we use the terms of the Open Archival Information System (OAIS). We relate our data focused QMM to some existing maturity matrices which put the focus on the maturity of the curation process rather than of the data objects themselves. In addition, we make an attempt to establish a connection between the QMM criteria of data assessment and the FAIR Data principles.

Effect of Platelet-Rich Plasma Injection on Mild or Moderate Carpal Tunnel Syndrome: An Updated Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Objective To evaluate efficacy of platelet-rich plasma (PRP) injection in carpal tunnel syndrome (CTS), we conducted this meta-analysis, as well as proposed a protocol for its application in curative processes. Methods All randomized controlled trials (RCTs) of PRP for the management of mild or moderate CTS were included in this study. Database search was conducted from study inception to July 2020, including PubMed, Embase, Web of Science, and Cochrane Library. We used visual analogue scores (VAS) and the Boston Carpal Tunnel Questionnaire (BCTQ) as evaluation tools for primary outcomes. Second outcomes comprised cross-sectional area (ΔCSA) and electrophysiological indexes including distal motor latency (DML), sensory peak latency (SPL), motor nerve conduction velocity (MNCV), sensory nerve conduction velocity (SNCV), compound muscle action potential (CMAP), and sensory nerve action potential (SNAP). The pooled data were analyzed using RevMan 5.3. Subgroup and sensitivity analyses were conducted with the evidence of heterogeneity. Egger' test was used to investigate publication bias. Results 9 RCTs were finally screened out with 434 patients included. Control groups comprised corticosteroid injection in 5 trials, saline injection in 1 trial, and splint in 3 trials. At the 1st month after follow-up, only ΔCSA between the PRP group and the control group showed significant difference (P < 0.05). In the 3rd month, there were statistically significant differences in VAS, BCTQ, SPL, SNCV, and ΔCSA between two groups (P < 0.05), while no statistically significant differences were found in the remaining outcomes. In the 6th month, there were statistically significant differences at BCTQ (P < 0.05) in primary outcomes and ΔCSA (P < 0.05) in secondary outcomes between two groups. As to adverse events in PRP injection, only one study reported increased pain sensation within 48 h after injections. Conclusion This systematic review and meta-analysis demonstrates that the PRP could be effective for mild to moderate CTS and superior to traditional conservative treatments in improving pain and function and reducing the swelling of the median nerve for a mid-long-term effect. To some extent, the electrophysiological indexes also improved after PRP injection compared with others conservative treatments.

Archiving an Epidemic: Art, AIDS, and the Queer Chicanx Avant-Garde

Archiving an Epidemic: Art, AIDS, and the Queer Chicanx Avant-Garde

MATCOR, a program for the cross-validation of material properties between databases

Data analytics approaches are increasingly often used to facilitate property-specific materials discovery. The uncertainties in these approaches can be greatly affected by the fidelity of the data sets that are used to train the data models. Therefore, data curation is an essential step for obtaining well-constrained model predictions. This can be a challenging task, especially for data sets that are too large for human quality control. We developed MATCOR, an open source, user-friendly, easily adaptable software to facilitate the data curation process. MATCOR processes lists of material identifiers in either AFLOW or Materials Project format and searches for the best matching materials entry in the other database. This is a non-trivial task due to differences in labeling and/or non-unique usage of material labels. MATCOR uses a combination of characteristics such space group, compound formula, crystal structure and use of Hubbard-U to provide the best possible comparison between databases. The capabilities of MATCOR are demonstrated for density, elastic properties, magnetic properties, and band gap correlations between AFLOW and Materials Project. We find that density shows the highest correlation among the tested properties, 93% of verified densities agree to within ±2%. Bulk- and shear-moduli showed deviations of less than ±10% for 80.6% and 65.1% of the materials, respectively. The classification of materials as non-magnetic/paramagnetic and metallic/gapped are consistent among the two databases for 91% and 69% of the materials, respectively. These examples show that MATCOR can be used to automate and thereby accelerate the data curation process prior to materials discovery through data analytical models.

From selling songs to engineering experiences: exploring the competitive strategies of music streaming platforms

ABSTRACT Economic, cultural, social, and political life is being increasingly shaped by digital platforms including social networking sites (Facebook), streaming services (Netflix) and sharing platforms (AirBnB). While social scientists have tracked the rapid emergence of platforms and developed useful conceptualisations about what they are and how they operate, surprisingly little attention has been paid to the nature of platform competition or the experiences of users. To address these gaps, this paper focuses on the illustrative case of recorded music, where platforms, including Spotify and Apple Music, face intense competition due to similarities in price and content. Drawing on 42 semi-structured interviews, 20 app ‘walk-alongs’ with Spotify users and an analysis of 120 documents (industry reports, trade magazines, press releases and news articles), it demonstrates how the basis of competition has shifted from content, price and curation to the engineering of compelling experiences that harness the unique and interconnected affordances of platformisation. The paper nuances our understanding of the dynamic and contingent nature of platforms, the processes of datafication and curation underpinning their interventions in markets and everyday life, the geographies of these virtual distribution and consumption channels, and the ways in which users imagine, value, and experience music streaming platforms.

Lists of Chemical Warfare Agents and Precursors from International Nonproliferation Frameworks: Structural Annotation and Chemical Fingerprint Analysis.

To support efforts to stem the proliferation of chemical weapons (CWs), we have curated and structurally annotated CW-control lists from three key international nonproliferation frameworks: the Chemical Weapons Convention (CWC), the Australia Group (AG), and the Wassenaar Arrangement. The curated lists are available as web tables at the Costanzi Research website (https://costanziresearch.com/cw-control-lists/). The annotations include manually curated 2D structural images, which provide a means to appreciate at a glance the similarities and differences between different entries, as well as downloadable 2D structures, in two different formats and three different structural identifiers, namely, simplified molecular-input line-entry system, standard InChI, and standard InChIKey, which are intended to provide a platform for cheminformatics analyses. The tables also include links to National Center for Biotechnology Information's PubChem and National Institute of Standards and Technology's Chemistry WebBook cards, hence providing prompt access to a wealth of physicochemical, analytical chemistry, and toxicological information. To showcase the importance of structural annotations, we discuss a discrepancy in a CW-control list covering the defoliant Agent Orange, which we identified through our curation process, and propose a solution to address it. Moreover, we present the results of chemical fingerprinting analyses, through which we clustered the entries of the three CW-control lists under study into structurally related groups and studied the overlaps between the three lists. As an application of this study, we examine the recent updates of CWC Schedule 1 and the AG precursors list, highlighting the relationships between the two amendments and proposing the possible addition of further chemicals. Our research is intended to facilitate the communication between scientific advisors and policymakers as well as the work of chemists and cheminformaticians involved in the CW nonproliferation field. Ultimately, we seek to provide tools to bolster the control of CWs and support the global efforts to rid the world of this category of weapons.

Forming a method for the integral estimation of interface quality in automated systems based on the quantitative and qualitative indicators

Informatization is considered an integral part of the functioning of the present-day society, which changes the nature of human-computer interaction and interface. It was substantiated that the interface quality determines the success of software marketing. It was shown that quality is estimated by both quantitative and qualitative indicators. Their calculation is complicated because of the lack of an analytical model of usability. Two Euclidean norms in the form of the root mean square value and the largest value of the modulus of the set of attribute values were proposed for continuous factor attributes. The problem was reduced to a geometric inequality by applying development into the Maclaurin series and a three-level comparator. Expressions of the upper and lower boundaries of the generalized index of interface quality represented through a set of attribute estimates were obtained. Expressions of the maximum possible absolute and relative errors represented by the method of recurrent approximation through the first and second derivative of the trend were substantiated. Representation of data in a plane with one common axis turned by a certain angle was applied which enabled fast viewing of all planes. It was shown that when all attributes have a quantitative dimension, it is sufficient to apply one norm to estimate the generalized index. However, in the case of quantitative and qualitative estimations, consecutive application of norms for the root mean square and the maximum possible value of the module solves the problem of comprehensive generalized estimation of interface quality. Experimental study of estimation of the generalized quality of the user interfaces for the MedInfoService medical information system which covers automation of curative treatment processes in outpatient clinics and hospitals was presented.

Genetic diversity of MHC-B in 12 chicken populations in Korea revealed by single-nucleotide polymorphisms.

This study used a single-nucleotide polymorphism (SNP) panel to characterise the diversity in the major histocompatibility complex B region (MHC-B) in 12 chicken populations in Korea. Samples were genotyped for 96 MHC-B SNPs using an Illumina GoldenGate genotyping assay. The MHC-B SNP haplotypes were predicted using 58 informative SNPs and a coalescence-based Bayesian algorithm implemented by the PHASE program and a manual curation process. In total, 117 haplotypes, including 24 shared and 93 unique haplotypes, were identified. The unique haplotype numbers ranged from 0 in Rhode Island Red to 32 in the Korean native commercial chicken population 2 ("Hanhyup-3ho"). Population and haplotype principal component analysis (PCA) indicated no clear population structure based on the MHC haplotypes. Three haplotype clusters (A, B, C) segregated in these populations highlighted the relationship between the haplotypes in each cluster. The sequences from two clusters (B and C) overlapped, whereas the sequences from the third cluster (A) were very different. Overall, native breeds had high genetic diversity in the MHC-B region compared with the commercial breeds. This highlights their immune capabilities and genetic potential for resistance to many different pathogens.

Abstract 5456: Clinical validation of NAVIFY® Mutation Profiler for solid tumor NGS variant interpretation

Abstract Introduction: Next-Generation Sequencing (NGS) is a standard of care for identifying actionable mutations in solid tumors. Data analysis and adjudication of variants is a significant barrier to NGS adoption in community settings. NAVIFY® Mutation Profiler (NMP) is a cloud-based software that provides curation, annotation, interpretation and reporting of somatic genomic variants identified by NGS. NMP is agnostic to the sample prep, target enrichment, sequencing, and secondary analysis and will accept Variant Call File (VCF) and BAM (Binary Alignment/Map) files. It provides information on genomic variants based on published literature, public annotations, medical guidelines, drug labels and results of clinical trials. The software reports a tiered classification based on modified AMP guidelines, to aid in interpretation of detected variants, inform available therapies, and create a report. To validate accuracy and reproducibility of the NMP software and curation process when used by the intended users, a usability study was performed. Methods: 15 VCF files were prepared, including 12 semi-contrived VCF files across 4 different solid tumor types (3 lung, 3 colon, 3 melanoma and 3 breast). Each file contained on average 8 variants, 4 AMP Tier I variants (strong clinical significance) and 4 non-Tier I variants including SNVs, Indels, Fusions and CNVs. In addition, each case had filtered out variants (based on a variant allele frequency (VAF) &amp;lt;1% or a read depth &amp;lt; 500) with 1 case containing ~9000 and 2 cases containing ~500 filtered out variants. There were 3 VCF files designed to create error messages (1 &amp;gt; 10,000 variants, 1 VAF filter value missing, 1 incorrect reference genome). The study was performed at 3 external sites with 1, 2, and 3 users (total 6 users). Users downloaded the files onto their computers and processed them according to the instructions provided. Results: Correct variant call lists 100% (486/486), variant call list after filter modification 100% (42/42). Most critical was user agreement of Tier classification (Tier I vs. non-Tier I) for a pre-defined filter set: 99.6% (484/486). One user reclassified a MET amplification (lung case) from Tier I to Tier II and one user reclassified a BRAF V600D mutation (colon case) from Tier II to Tier I. In addition, the three cases designed to produce error messages all failed NMP processing: 100% (18/18). Conclusions: NAVIFY® Mutation Profiler is a robust automated solution for variant reporting. The annotation, curation and interpretation provided is highly concordant with molecular genetics experts. With the increasing number of known clinically relevant variants, software capable of automatically identifying and accurately interpreting variants promises to decrease the manual review time necessary to account for and inform on relevant variants. Citation Format: Sidney Alexander Scudder, Anoop Grewal, Lisha Capucion, Guili Zhang, Leonid Formin, Shuba Krishna, Xi Decker, Joanie Chung. Clinical validation of NAVIFY® Mutation Profiler for solid tumor NGS variant interpretation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5456.

Genome-Scale Metabolic Model of Xanthomonas phaseoli pv. manihotis: An Approach to Elucidate Pathogenicity at the Metabolic Level.

Xanthomonas phaseoli pv. manihotis (Xpm) is the causal agent of cassava bacterial blight, the most important bacterial disease in this crop. There is a paucity of knowledge about the metabolism of Xanthomonas and its relevance in the pathogenic process, with the exception of the elucidation of the xanthan biosynthesis route. Here we report the reconstruction of the genome-scale model of Xpm metabolism and the insights it provides into plant–pathogen interactions. The model, iXpm1556, displayed 1,556 reactions, 1,527 compounds, and 890 genes. Metabolic maps of central amino acid and carbohydrate metabolism, as well as xanthan biosynthesis of Xpm, were reconstructed using Escher (https://escher.github.io/) to guide the curation process and for further analyses. The model was constrained using the RNA-seq data of a mutant of Xpm for quorum sensing (QS), and these data were used to construct context-specific models (CSMs) of the metabolism of the two strains (wild type and QS mutant). The CSMs and flux balance analysis were used to get insights into pathogenicity, xanthan biosynthesis, and QS mechanisms. Between the CSMs, 653 reactions were shared; unique reactions belong to purine, pyrimidine, and amino acid metabolism. Alternative objective functions were used to demonstrate a trade-off between xanthan biosynthesis and growth and the re-allocation of resources in the process of biosynthesis. Important features altered by QS included carbohydrate metabolism, NAD(P)+ balance, and fatty acid elongation. In this work, we modeled the xanthan biosynthesis and the QS process and their impact on the metabolism of the bacterium. This model will be useful for researchers studying host–pathogen interactions and will provide insights into the mechanisms of infection used by this and other Xanthomonas species.

How concerns about former or future partners influence virtual possession management: Examining relational curation in the relational dissolution model

ABSTRACT As relational partners document their romantic relationships in mediated contexts, they must manage virtual relational possessions to determine what should be kept or deleted, particularly following a breakup. Using the Relational Dissolution Model, this study examines keeping and deleting behaviors through the lens of a newly proposed process – relational curation. Collegiate participants (N = 234) who had experienced a breakup were recruited to complete an online survey. Findings showed that when individuals based their possession decisions on their relationship with their former partner, they were more likely to keep possessions; whereas, when individuals based their possession decisions on their relationship with a potential future partner, they were more likely to delete possessions. By further clarifying the role of former and future relationships in keeping and deleting decisions, the results further delineate the dissolution processes of grave-dressing, relational curation, and resurrection.

Extraction of radiographic findings from unstructured thoracoabdominal computed tomography reports using convolutional neural network based natural language processing.

Heart failure (HF) is a major cause of morbidity and mortality. However, much of the clinical data is unstructured in the form of radiology reports, while the process of data collection and curation is arduous and time-consuming. We utilized a machine learning (ML)-based natural language processing (NLP) approach to extract clinical terms from unstructured radiology reports. Additionally, we investigate the prognostic value of the extracted data in predicting all-cause mortality (ACM) in HF patients. This observational cohort study utilized 122,025 thoracoabdominal computed tomography (CT) reports from 11,808 HF patients obtained between 2008 and 2018. 1,560 CT reports were manually annotated for the presence or absence of 14 radiographic findings, in addition to age and gender. Thereafter, a Convolutional Neural Network (CNN) was trained, validated and tested to determine the presence or absence of these features. Further, the ability of CNN to predict ACM was evaluated using Cox regression analysis on the extracted features. 11,808 CT reports were analyzed from 11,808 patients (mean age 72.8 ± 14.8 years; 52.7% (6,217/11,808) male) from whom 3,107 died during the 10.6-year follow-up. The CNN demonstrated excellent accuracy for retrieval of the 14 radiographic findings with area-under-the-curve (AUC) ranging between 0.83-1.00 (F1 score 0.84-0.97). Cox model showed the time-dependent AUC for predicting ACM was 0.747 (95% confidence interval [CI] of 0.704-0.790) at 30 days. An ML-based NLP approach to unstructured CT reports demonstrates excellent accuracy for the extraction of predetermined radiographic findings, and provides prognostic value in HF patients.