Design and Implementation of an Ontology for Measurement Terminology in Digital Calibration Certificates.

Digital Calibration Certificates (DCCs) are a key focus in metrology digitalization, necessitating that they satisfy the criteria for machine readability and understandability. Current DCCs are machine-readable, but they are still missing the essential semantic information required for machine understandability. This shortfall is particularly notable in the lack of a dedicated semantic ontology for measurement terminologies. This paper proposes a domain ontology for measurement terminologies named the OMT (Ontology for Measurement Terminology), using a foundation of metrological terms from standards like the International Vocabulary of Metrology (VIM), the Guide to the Expression of Uncertainty in Measurement (GUM), and JJF1001. It also incorporates insights from models such as the SI Reference Point, the Simple Knowledge Organization System (SKOS), and the DCC Schema. The methodology was guided by Stanford's Seven-Step Method, ensuring a systematic development process tailored to the needs of metrological semantics. Through semantic expression capability verification and SPARQL query validations, the OMT has been confirmed to possess essential machine readability and understandability features. It has been successfully integrated into version 3.2.1 of DCCs across ten representative domains. This integration demonstrates an effective method for ensuring that DCCs are machine-readable and capable of interoperating within digital environments, thereby advancing the research in metrology digitization.

Multiomics Analysis of the PHLDA Gene Family in Different Cancers and Their Clinical Prognostic Value.

The PHLDA (pleckstrin homology-like domain family) gene family is popularly known as a potential biomarker for cancer identification, and members of the PHLDA family have become considered potentially viable targets for cancer treatments. The PHLDA gene family consists of PHLDA1, PHLDA2, and PHLDA3. The predictive significance of PHLDA genes in cancer remains unclear. To determine the role of pleckstrin as a prognostic biomarker in human cancers, we conducted a systematic multiomics investigation. Through various survival analyses, pleckstrin expression was evaluated, and their predictive significance in human tumors was discovered using a variety of online platforms. By analyzing the protein-protein interactions, we also chose a collection of well-known functional protein partners for pleckstrin. Investigations were also carried out on the relationship between pleckstrins and other cancers regarding mutations and copy number alterations. The cumulative impact of pleckstrin and their associated genes on various cancers, Gene Ontology (GO), and pathway analyses were used for their evaluation. Thus, the expression profiles of PHLDA family members and their prognosis in various cancers may be revealed by this study. During this multiomics analysis, we found that among the PHLDA family, PHLDA1 may be a therapeutic target for several cancers, including kidney, colon, and brain cancer, while PHLDA2 can be a therapeutic target for cancers of the colon, esophagus, and pancreas. Additionally, PHLDA3 may be a useful therapeutic target for ovarian, renal, and gastric cancer.

Inflammation and immunological disarrays are associated with acute exercise in type 2 diabetes.

Objective: Type 2 diabetes (T2D) is the most common metabolic disorder that is associated with insulin resistance. The aim of the present study is to discover details of the molecular mechanism of exercise on control or progress of diabetic condition in patients via network analysis. Methods: Gene expression profiles of patients with T2D before and after doing exercise are retrieved from Gene Expression Omnibus (GEO) and are pre-evaluated by the GEO2R program. Data are studied based on expression values, regulatory relationships between the differentially expressed genes (DEGs), gene ontology analyses, and protein-protein interaction PPI network analysis. Results: A number of 118 significant DEGs were identified and classified based on fold change (FC) values as most dysregulated genes and dysregulated individuals. Action map analysis revealed that 18 DEGs appeared as the critical genes. Gene ontology analysis showed that 24 DEGs are connected to at least four pathways. JUN, IL6, IL1B, PTGS2, FOS, MYC, ATF3, CXCL8, EGR1, EGR2, NR4A1, PLK3, TTN, and UCP3 were identified as central DEGs. Conclusion: Finally; JUN, IL6, IL1B, PTGS2, FOS, ATF3, CXCL8, EGR1, and EGR2 were introduced as the critical targeted genes by exercise. Since the critical genes after exercise are upregulated and mostly are known as the risk factors of T2D, it can be concluded that unsuitable exercise can develop diabetic conditions in patients. Acute exercise-induced inflammation and immune disturbances seem to be associated with the development of T2D in patients.

An Ontology-Based Decision Support System for Tailored Clinical Nutrition Recommendations for Patients With Chronic Obstructive Pulmonary Disease: Development and Acceptability Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a chronic condition among the main causes of morbidity and mortality worldwide, representing a burden on health care systems. Scientific literature highlights that nutrition is pivotal in respiratory inflammatory processes connected to COPD, including exacerbations. Patients with COPD have an increased risk of developing nutrition-related comorbidities, such as diabetes, cardiovascular diseases, and malnutrition. Moreover, these patients often manifest sarcopenia and cachexia. Therefore, an adequate nutritional assessment and therapy are essential to help individuals with COPD in managing the progress of the disease. However, the role of nutrition in pulmonary rehabilitation (PR) programs is often underestimated due to a lack of resources and dedicated services, mostly because pneumologists may lack the specialized training for such a discipline. OBJECTIVE: This work proposes a novel knowledge-based decision support system to support pneumologists in considering nutritional aspects in PR. The system provides clinicians with patient-tailored dietary recommendations leveraging expert knowledge. METHODS: The expert knowledge-acquired from experts and clinical literature-was formalized in domain ontologies and rules, which were developed leveraging the support of Italian clinicians with expertise in the rehabilitation of patients with COPD. Thus, by following an agile ontology engineering methodology, the relevant formal ontologies were developed to act as a backbone for an application targeted at pneumologists. The recommendations provided by the decision support system were validated by a group of nutrition experts, whereas the acceptability of such an application in the context of PR was evaluated by pneumologists. RESULTS: A total of 7 dieticians (mean age 46.60, SD 13.35 years) were interviewed to assess their level of agreement with the decision support system's recommendations by evaluating 5 patients' health conditions. The preliminary results indicate that the system performed more than adequately (with an overall average score of 4.23, SD 0.52 out of 5 points), providing meaningful and safe recommendations in compliance with clinical practice. With regard to the acceptability of the system by lung specialists (mean age 44.71, SD 11.94 years), the usefulness and relevance of the proposed solution were extremely positive-the scores on each of the perceived usefulness subscales of the technology acceptance model 3 were 4.86 (SD 0.38) out of 5 points, whereas the score on the intention to use subscale was 4.14 (SD 0.38) out of 5 points. CONCLUSIONS: Although designed for the Italian clinical context, the proposed system can be adapted for any other national clinical context by modifying the domain ontologies, thus providing a multidisciplinary approach to the management of patients with COPD.

A Proteomics Approach Identifies RREB1 as a Crucial Molecular Target of Imidazo-Pyrazole Treatment in SKMEL-28 Melanoma Cells.

Cutaneous melanoma is the most dangerous and deadly form of human skin malignancy. Despite its rarity, it accounts for a staggering 80% of deaths attributed to cutaneous cancers overall. Moreover, its final stages often exhibit resistance to drug treatments, resulting in unfavorable outcomes. Hence, ensuring access to novel and improved chemotherapeutic agents is imperative for patients grappling with this severe ailment. Pyrazole and its fused systems derived thereof are heteroaromatic moieties widely employed in medicinal chemistry to develop effective drugs for various therapeutic areas, including inflammation, pain, oxidation, pathogens, depression, and fever. In a previous study, we described the biochemical properties of a newly synthesized group of imidazo-pyrazole compounds. In this paper, to improve our knowledge of the pharmacological properties of these molecules, we conduct a differential proteomic analysis on a human melanoma cell line treated with one of these imidazo-pyrazole derivatives. Our results detail the changes to the SKMEL-28 cell line proteome induced by 24, 48, and 72 h of 3e imidazo-pyrazole treatment. Notably, we highlight the down-regulation of the Ras-responsive element binding protein 1 (RREB1), a member of the zinc finger transcription factors family involved in the tumorigenesis of melanoma. RREB1 is a downstream element of the MAPK pathway, and its activation is mediated by ERK1/2 through phosphorylation.

Identifying Molecular Pathophysiology and Potential Therapeutic Options in Iatrogenic Tracheal Stenosis.

INTRODUCTION: While most patients with iatrogenic tracheal stenosis (ITS) respond to endoscopic ablative procedures, approximately 15% experience a recalcitrant, recurring disease course that is resistant to conventional management. We aimed to explore genetic profiles of patients with recalcitrant ITS to understand underlying pathophysiology and identify novel therapeutic options. METHODS: We collected 11 samples of granulation tissue from patients with ITS and performed RNA sequencing. We identified the top 10 most highly up- and down-regulated genes and cellular processes that these genes corresponded to. For the most highly dysregulated genes, we identified potential therapeutic options that favorably regulate their expression. RESULTS: The dysregulations in gene expression corresponded to hyperkeratinization (upregulation of genes involved in keratin production and keratinocyte differentiation) and cellular proliferation (downregulation of cell cycle regulating and pro-apoptotic genes). Genes involved in retinoic acid (RA) metabolism and signaling were dysregulated in a pattern suggesting local cellular RA deficiency. Consequently, RA also emerged as the most promising potential therapeutic option for ITS, as it favorably regulated seven of the ten most highly dysregulated genes. CONCLUSION: This is the first study to characterize the role of hyperkeratinization and dysregulations in RA metabolism and signaling in the disease pathophysiology. Given the ability of RA to favorably regulate key genes involved in ITS, future studies must explore its efficacy as a potential therapeutic option for patients with recalcitrant ITS.

Genetic Analysis of Egg Production Traits in Luhua Chickens: Insights from a Multi-Trait Animal Model and a Genome-Wide Association Study.

Egg production plays a pivotal role in the economic viability of hens. To analyze the genetic rules of egg production, a total of 3151 Luhua chickens were selected, the egg production traits including egg weight at first laying (Start-EW), egg weight at 43 weeks (EW-43), egg number at 43 weeks (EN-43), and total egg number (EN-All) were recorded. Then, the effects of related factors on egg production traits were explored, using a multi-trait animal model for genetic parameter estimation and a genome-wide association study (GWAS). The results showed that body weight at first egg (BWFE), body weight at 43 weeks (BW-43), age at first egg (AFE), and seasons had significant effects on the egg production traits. Start-EW and EW-43 had moderate heritability of 0.30 and 0.21, while EN-43 and EN-All had low heritability of 0.13 and 0.16, respectively. Start-EW exhibited a robust positive correlation with EW-43, while Start-EW was negatively correlated with EN-43 and EN-All. Furthermore, gene ontology (GO) results indicated that Annexin A2 (ANXA2) and Frizzled family receptor 7 (FZD7) related to EW-43, Cyclin D1 (CCND1) and A2B adenosine receptor (ADORA2B) related to EN-All, and have been found to be mainly involved in metabolism and growth processes, and deserve more attention and further study. This study contributes to accelerating genetic progress in improving low heritability egg production traits in layers, especially in Luhua chickens.

FABP4 Is an Indispensable Factor for Regulating Cellular Metabolic Functions of the Human Retinal Choroid.

The purpose of the current study was to elucidate the physiological roles of intraocularly present fatty acid-binding protein 4 (FABP4). Using four representative intraocular tissue-derived cell types, including human non-pigmented ciliary epithelium (HNPCE) cells, retinoblastoma (RB) cells, adult retinal pigment epithelial19 (ARPE19) cells and human ocular choroidal fibroblast (HOCF) cells, the intraocular origins of FABP4 were determined by qPCR analysis, and the intracellular functions of FABP4 were investigated by seahorse cellular metabolic measurements and RNA sequencing analysis using a specific inhibitor for FABP4, BMS309403. Among these four different cell types, FABP4 was exclusively expressed in HOCF cells. In HOCF cells, both mitochondrial and glycolytic functions were significantly decreased to trace levels by BMS309403 in a dose-dependent manner. In the RNA sequencing analysis, 67 substantially up-regulated and 94 significantly down-regulated differentially expressed genes (DEGs) were identified in HOCF cells treated with BMS309403 and those not treated with BMS309403. The results of Gene Ontology enrichment analysis and ingenuity pathway analysis (IPA) revealed that the DEGs were most likely involved in G-alpha (i) signaling, cAMP-response element-binding protein (CREB) signaling in neurons, the S100 family signaling pathway, visual phototransduction and adrenergic receptor signaling. Furthermore, upstream analysis using IPA suggested that NKX2-1 (thyroid transcription factor1), HOXA10 (homeobox A10), GATA2 (gata2 protein), and CCAAT enhancer-binding protein A (CEBPA) were upstream regulators and that NKX homeobox-1 (NKX2-1), SFRP1 (Secreted frizzled-related protein 1) and TREM2 (triggering receptor expressed on myeloid cells 2) were causal network master regulators. The findings in this study suggest that intraocularly present FABP4 originates from the ocular choroid and may be a critical regulator for the cellular homeostasis of non-adipocyte HOCF cells.

Common Cause Versus Dynamic Mutualism: An Empirical Comparison of Two Theories of Psychopathology in Two Large Longitudinal Cohorts.

Mental disorders are among the leading causes of global disease burden. To respond effectively, a strong understanding of the structure of psychopathology is critical. We empirically compared two competing frameworks, dynamic-mutualism theory and common-cause theory, that vie to explain the development of psychopathology. We formalized these theories in statistical models and applied them to explain change in the general factor of psychopathology (p factor) from early to late adolescence (N = 1,482) and major depression in middle adulthood and old age (N = 6,443). Change in the p factor was better explained by mutualism according to model-fit indices. However, a core prediction of mutualism was not supported (i.e., predominantly positive causal interactions among distinct domains). The evidence for change in depression was more ambiguous. Our results support a multicausal approach to understanding psychopathology and showcase the value of translating theories into testable statistical models for understanding developmental processes in clinical sciences.

Building ontology-based temporal databases for data reuse: An applied example on hospital organizational structures.

Keeping track of data semantics and data changes in the databases is essential to support retrospective studies and the reproducibility of longitudinal clinical analysis by preventing false conclusions from being drawn from outdated data. A knowledge model combined with a temporal model plays an essential role in organizing the data and improving query expressiveness across time and multiple institutions. This paper presents a modelling framework for temporal relational databases using an ontology to derive a shareable and interoperable data model. The framework is based on: OntoRela an ontology-driven database modelling approach and Unified Historicization Framework a temporal database modelling approach. The method was applied to hospital organizational structures to show the impact of tracking organizational changes on data quality assessment, healthcare activities and data access rights. The paper demonstrated the usefulness of an ontology to provide a formal, interoperable, and reusable definition of entities and their relationships, as well as the adequacy of the temporal database to store, trace, and query data over time.

Advances in big data and omics: Paving the way for discovery in childhood epilepsies.

The insights gained from big data and omics approaches have transformed the field of childhood genetic epilepsy. With an increasing number of individuals receiving genetic testing for seizures, we are provided with an opportunity to identify clinically relevant subgroups and extract meaningful observations from this large-scale clinical data. However, the volume of data from electronic medical records and omics (e.g., genomics, transcriptomics) is so vast that standardized methods, such as the Human Phenotype Ontology, are necessary for reliable and comprehensive characterization. Here, we explore the integration of clinical and omics data, highlighting how these approaches pave the way for discovery in childhood epilepsies.

Transcriptome analysis in various cell lines exposed to nitric oxide.

Nitric oxide (NO) plays a physiological role in signal transduction and excess or chronic NO has toxic effects as an inflammatory mediator. NO reversibly forms protein S-nitrosylation and exerts toxicological functions related to disease progression. DNA methyltransferases, epigenome-related enzymes, are inhibited in enzymatic activity by S-nitrosylation. Therefore, excess or chronic NO exposure may cause disease by altering gene expression. However, the effects of chronic NO exposure on transcriptome are poorly understood. Here, we performed transcriptome analysis of A549, AGS, HEK293T, and SW48 cells exposed to NO (100 µM) for 48 hr. We showed that the differentially expressed genes were cell-specific. Gene ontology analysis showed that the functional signature of differentially expressed genes related to cell adhesion or migration was upregulated in several cell lines. Gene set enrichment analysis indicated that NO stimulated inflammation-related gene expression in various cell lines. This finding supports previous studies showing that NO is closely involved in inflammatory diseases. Overall, this study elucidates the pathogenesis of NO-associated inflammatory diseases by focusing on changes in gene expression.

The link between ancient whole-genome duplications and cold adaptations in the Caryophyllaceae.

PREMISE: The Caryophyllaceae (the carnation family) have undergone multiple transitions into colder climates and convergence on cushion plant adaptation, indicating that they may provide a natural system for cold adaptation research. Previous research has suggested that putative ancient whole-genome duplications (WGDs) are correlated with niche shifts into colder climates across the Caryophyllales. Here, we explored the genomic changes potentially involved in one of these discovered shifts in the Caryophyllaceae. METHODS: We constructed a data set combining 26 newly generated transcriptomes with 45 published transcriptomes, including 11 cushion plant species across seven genera. With this data set, we inferred a dated phylogeny for the Caryophyllaceae and mapped ancient WGDs and gene duplications onto the phylogeny. We also examined functional groups enriched for gene duplications related to the climatic shift. RESULTS: The ASTRAL topology was mostly congruent with the current consensus of relationships within the family. We inferred 15 putative ancient WGDs in the family, including eight that have not been previously published. The oldest ancient WGD (ca. 64.4-56.7 million years ago), WGD1, was found to be associated with a shift into colder climates by previous research. Gene regions associated with ubiquitination were overrepresented in gene duplications retained after WGD1 and those convergently retained by cushion plants in Colobanthus and Eremogone, along with other functional annotations. CONCLUSIONS: Gene family expansions induced by ancient WGDs may have contributed to the shifts to cold climatic niches in the Caryophyllaceae. Transcriptomic data are crucial resources that help unravel heterogeneity in deep-time evolutionary patterns in plants.

Comparative transcriptome profile of embryos at different developmental stages derived from somatic cell nuclear transfer (SCNT) and in-vitro fertilization (IVF) in riverine buffalo (Bubalus bubalis).

Somatic cell nuclear transfer (SCNT) is a very important reproductive technology with many diverse applications, such as fast multiplication of elite animals, the production of transgenic animals and embryonic stem (ES) cells. However, low cloning efficiency, a low live birth rate and the abnormally high incidence of abnormalities in the offspring born are attributed to incomplete or aberrant nuclear reprogramming. In SCNT embryos, the aberrant expression pattern of the genes throughout embryonic development is responsible for the incomplete nuclear reprogramming. The present study was carried out to identify the differential gene expression (DEGs) profile and molecular pathways of the SCNT and IVF embryos at different developmental stages (2 cell, 8 cell and blastocyst stages). In the present study, 1164 (2 cell), 1004 (8 cell) and 530 (blastocyst stage) DEGs were identified in the SCNT embryos as compared to IVF embryos. In addition, several genes such as ZEB1, GDF1, HSF5, PDE3B, VIM, TNNC, HSD3B1, TAGLN, ITGA4 and AGMAT were affecting the development of SCNT embryos as compared to IVF embryos. Further, Gene Ontology (GO) and molecular pathways analysis suggested, SCNT embryos exhibit variations compared to their IVF counterparts and affected the development of embryos throughout the different developmental stages. Apart from this, q-PCR analysis of the GDF1, TMEM114, and IGSF22 genes were utilized to validate the RNA-seq data. These findings contribute valuable insights about the different genes and molecular pathways underlying SCNT embryo development and offer crucial information for improving SCNT efficiency.

Unveiling the mysteries: Functional insights into hypothetical proteins from Bacteroides fragilis 638R.

Humans benefit from a vast community of microorganisms in their gastrointestinal tract, known as the gut microbiota, numbering in the tens of trillions. An imbalance in the gut microbiota known as dysbiosis, can lead to changes in the metabolite profile, elevating the levels of toxins like Bacteroides fragilis toxin (BFT), colibactin, and cytolethal distending toxin. These toxins are implicated in the process of oncogenesis. However, a significant portion of the Bacteroides fragilis genome consists of functionally uncharacterized and hypothetical proteins. This study delves into the functional characterization of hypothetical proteins (HPs) encoded by the Bacteroides fragilis genome, employing a systematic in silico approach. A total of 379 HPs were subjected to a BlastP homology search against the NCBI non-redundant protein sequence database, resulting in 162 HPs devoid of identity to known proteins. CDD-Blast identified 106 HPs with functional domains, which were then annotated using Pfam, InterPro, SUPERFAMILY, SCANPROSITE, SMART, and CATH. Physicochemical properties, such as molecular weight, isoelectric point, and stability indices, were assessed for 60 HPs whose functional domains were identified by at least three of the aforementioned bioinformatic tools. Subsequently, subcellular localization analysis was examined and the gene ontology analysis revealed diverse biological processes, cellular components, and molecular functions. Remarkably, E1WPR3 was identified as a virulent and essential gene among the HPs. This study presents a comprehensive exploration of B. fragilis HPs, shedding light on their potential roles and contributing to a deeper understanding of this organism's functional landscape.

Advances in Inflammatory Bowel Disease Diagnostics: Machine Learning and Genomic Profiling Reveal Key Biomarkers for Early Detection.

This study, utilizing high-throughput technologies and Machine Learning (ML), has identified gene biomarkers and molecular signatures in Inflammatory Bowel Disease (IBD). We could identify significant upregulated or downregulated genes in IBD patients by comparing gene expression levels in colonic specimens from 172 IBD patients and 22 healthy individuals using the GSE75214 microarray dataset. Our ML techniques and feature selection methods revealed six Differentially Expressed Gene (DEG) biomarkers (VWF, IL1RL1, DENND2B, MMP14, NAAA, and PANK1) with strong diagnostic potential for IBD. The Random Forest (RF) model demonstrated exceptional performance, with accuracy, F1-score, and AUC values exceeding 0.98. Our findings were rigorously validated with independent datasets (GSE36807 and GSE10616), further bolstering their credibility and showing favorable performance metrics (accuracy: 0.841, F1-score: 0.734, AUC: 0.887). Our functional annotation and pathway enrichment analysis provided insights into crucial pathways associated with these dysregulated genes. DENND2B and PANK1 were identified as novel IBD biomarkers, advancing our understanding of the disease. The validation in independent cohorts enhances the reliability of these findings and underscores their potential for early detection and personalized treatment of IBD. Further exploration of these genes is necessary to fully comprehend their roles in IBD pathogenesis and develop improved diagnostic tools and therapies. This study significantly contributes to IBD research with valuable insights, potentially greatly enhancing patient care.

Genotyping-by-Sequencing Analysis Reveals Associations between Agronomic and Oil Traits in Gamma Ray-Derived Mutant Rapeseed (Brassica napus L.).

Rapeseed (Brassica napus L.) holds significant commercial value as one of the leading oil crops, with its agronomic features and oil quality being crucial determinants. In this investigation, 73,226 single nucleotide polymorphisms (SNPs) across 95 rapeseed mutant lines induced by gamma rays, alongside the original cultivar ('Tamra'), using genotyping-by-sequencing (GBS) analysis were examined. This study encompassed gene ontology (GO) analysis and a genomewide association study (GWAS), thereby concentrating on agronomic traits (e.g., plant height, ear length, thousand-seed weight, and seed yield) and oil traits (including fatty acid composition and crude fat content). The GO analysis unveiled a multitude of genes with SNP variations associated with cellular processes, intracellular anatomical structures, and organic cyclic compound binding. Through GWAS, we detected 320 significant SNPs linked to both agronomic (104 SNPs) and oil traits (216 SNPs). Notably, two novel candidate genes, Bna.A05p02350D (SFGH) and Bna.C02p22490D (MDN1), are implicated in thousand-seed weight regulation. Additionally, Bna.C03p14350D (EXO70) and Bna.A09p05630D (PI4Kα1) emerged as novel candidate genes associated with erucic acid and crude fat content, respectively. These findings carry implications for identifying superior genotypes for the development of new cultivars. Association studies offer a cost-effective means of screening mutants and selecting elite rapeseed breeding lines, thereby enhancing the commercial viability of this pivotal oil crop.

Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.

BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity of cancer vaccine data significantly impedes effective integration and analysis. While CanVaxKB serves as a pioneering database for over 670 manually annotated cancer vaccines, it is important to distinguish that a database, on its own, does not offer the structured relationships and standardized definitions found in an ontology. Recognizing this, we expanded the Vaccine Ontology (VO) to include those cancer vaccines present in CanVaxKB that were not initially covered, enhancing VO's capacity to systematically define and interrelate cancer vaccines. RESULTS: An ontology design pattern (ODP) was first developed and applied to semantically represent various cancer vaccines, capturing their associated entities and relations. By applying the ODP, we generated a cancer vaccine template in a tabular format and converted it into the RDF/OWL format for generation of cancer vaccine terms in the VO. '12MP vaccine' was used as an example of cancer vaccines to demonstrate the application of the ODP. VO also reuses reference ontology terms to represent entities such as cancer diseases and vaccine hosts. Description Logic (DL) and SPARQL query scripts were developed and used to query for cancer vaccines based on different vaccine's features and to demonstrate the versatility of the VO representation. Additionally, ontological modeling was applied to illustrate cancer vaccine related concepts and studies for in-depth cancer vaccine analysis. A cancer vaccine-specific VO view, referred to as "CVO," was generated, and it contains 928 classes including 704 cancer vaccines. The CVO OWL file is publicly available on: http://purl.obolibrary.org/obo/vo/cvo.owl , for sharing and applications. CONCLUSION: To facilitate the standardization, integration, and analysis of cancer vaccine data, we expanded the Vaccine Ontology (VO) to systematically model and represent cancer vaccines. We also developed a pipeline to automate the inclusion of cancer vaccines and associated terms in the VO. This not only enriches the data's standardization and integration, but also leverages ontological modeling to deepen the analysis of cancer vaccine information, maximizing benefits for researchers and clinicians. AVAILABILITY: The VO-cancer GitHub website is: https://github.com/vaccineontology/VO/tree/master/CVO .

A data extraction template for the behaviour change intervention ontology.

Background: The Behaviour Change Intervention Ontology (BCIO) aims to improve the clarity, completeness and consistency of reporting within intervention descriptions and evidence synthesis. However, a recommended method for transparently annotating intervention evaluation reports using the BCIO does not currently exist. This study aimed to develop a data extraction template for annotating using the BCIO. Methods: The BCIO data extraction template was developed in four stages: i) scoping review of papers citing component ontologies within the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template. Results: A prototype data extraction template using Microsoft Excel was developed based on BCIO annotations from 14 papers. The 'BCIO data extraction template v1' was produced following piloting and revision, incorporating a facility for user feedback. Discussion: This data extraction template provides a single, accessible resource to extract all necessary characteristics of behaviour change intervention scenarios. It can be used to annotate the presence of BCIO entities for evidence synthesis, including systematic reviews. In the future, we will update this template based on feedback from the community, additions of newly published ontologies within the BCIO, and revisions to existing ontologies.

Behaviour change interventions are often reported in an inconsistent and incomplete manner in study reports. This makes it difficult to build knowledge and predict outcomes. There is a need for a shared language to describe behaviour change interventions. This need was met using 'ontologies', which are classification systems that represent knowledge in a standardised way. The Behaviour Change Intervention Ontology (BCIO) has been developed to describe the different aspects of interventions in a way that is precise enough for computers as well as humans to 'read' study findings. The BCIO can be used to extract information from study reports for evidence synthesis, such as systematic literature reviews. To meet the need for a resource for annotating (coding) study reports according to the BCIO, we developed a data extraction template. The template was developed in four stages: i) reviewing existing papers using the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template. The resulting resource is an accessible, easy-to-use template to assist with specifying the content of published papers reporting interventions and their evaluation. The template will be updated based on user feedback and future revisions to the BCIO.

Translating motivational interviewing for the HPV vaccine into a computable ontology model for automated AI conversational interaction.

Human papillomavirus (HPV) vaccinations are lower than expected. To protect the onset of head and neck cancers, innovative strategies to improve the rates are needed. Artificial intelligence may offer some solutions, specifically conversational agents to perform counseling methods. We present our efforts in developing a dialogue model for automating motivational interviewing (MI) to encourage HPV vaccination. We developed a formalized dialogue model for MI using an existing ontology-based framework to manifest a computable representation using OWL2. New utterance classifications were identified along with the ontology that encodes the dialogue model. Our work is available on GitHub under the GPL v.3. We discuss how an ontology-based model of MI can help standardize/formalize MI counseling for HPV vaccine uptake. Our future steps will involve assessing MI fidelity of the ontology model, operationalization, and testing the dialogue model in a simulation with live participants.