Interrogation Of Data Research Articles

VCAb: a web-tool for structure-guided exploration of antibodies.

Effective responses against immune challenges require antibodies of different isotypes performing specific effector functions. Structural information on these isotypes is essential to engineer antibodies with desired physico-chemical features of their antigen-binding properties, and optimal developability as potential therapeutics. In silico mutational scanning profiles on antibody structures would further pinpoint candidate mutations for enhancing antibody stability and function. Current antibody structure databases lack consistent annotations of isotypes and structural coverage of 3D antibody structures, as well as computed deep mutation profiles. The V and C region bearing antibody (VCAb) web-tool is established to clarify these annotations and provides an accessible resource to facilitate antibody engineering and design. VCAb currently provides data on 7,166 experimentally determined antibody structures including both V and C regions from different species. Additionally, VCAb provides annotations of species and isotypes with numbering schemes applied. These information can be interactively queried or downloaded in batch. VCAb is implemented as a R shiny application to enable interactive data interrogation. The online application is freely accessible https://fraternalilab.cs.ucl.ac.uk/VCAb/. The source code to generate the database and the online application is available open-source at https://github.com/Fraternalilab/VCAb.

‘It’s a bit tough when you’re just trying to have fun’: gendered practices of school sport surfing in France and California

ABSTRACT The provision of sports opportunities for youths in schools has expanded beyond traditional competitive offerings, with activities such as skateboarding and surfing now considered important avenues for youth development. This trend follows the recent expansion of action or ‘lifestyle’ sports provision into various community and educational contexts. This paper concomitantly explores how surfing, in particular, is now being formally utilised by schools as a viable sporting opportunity for both boys and girls. Research is lacking in terms of understanding how activities such as surfing may promote specific gender relations. This line of research is critical given that surfing in its unstructured format typically privileges masculine ideals and codes of practice, with women being considered secondary participants. In this paper, then, we highlight data findings about gender relations based on a study of boys’ and girls’ surfing programmes located in coastal regions of California and France. Through our interrogation of semi-structured interview and field observation data, we illustrate how school-based programmes that incorporate surfing served to reproduce gendered hierarchies and power relationships during training sessions and competitions.

RETROFITTING OUTDATED PYRANOMETER FOR IoT INTEGRATION TOWARDS A CIRCULAR ECONOMY MODEL

An innovative way of applying the circular economy concept in the obsolete research equipment domain is by repairing and upgrading critical subcomponents of the initial equipment, for reuse purposes. Thus, a large percentage of environmental waste is reduced, resulting from the whole process of manufacturing a brand new modern one, along with the implied purchasing costs, while serving its intended purpose simultaneously. The whole re-engineering process produces increased overall cost efficiency, by massively reducing the raw material requirements, the electrical energy consumption for design and manufacture, and the resulting waste material. In this respect, the article addresses the inherent issues in retrofitting an old model analog signal pyranometer, designed in the ‘90s. The upgrade initiative aims to massively increase the digital processing speed, the quality, and the quantity of the data acquisition, while also providing an integrated local storage solution and wireless access through a designated IP address using a web interface, for data interrogation in real-time. All these are done at low costs, with market-available materials, to avoid any high expenses related to acquiring new ones.

GenIA, the Genetic Immunology Advisor database for inborn errors of immunity

BackgroundTo date, no publicly accessible platform captures and synthesizes all the layered dimensions of genotypic, phenotypic and mechanistic information published in the field of inborn errors of immunity (IEI). Such a platform would represent the extensive and complex landscape of IEIs and could increase the diagnostic rate in patients with suspected IEI, which remains unacceptably low. ObjectiveTo create an expertly curated, patient-centered, multi-dimensional IEI database that enables aggregation and sophisticated data interrogation and promotes involvement from diverse stakeholders across the community. MethodsThe database structure was designed following a subject-centered model and written in SQL. The web application is written in PHP, HTML, CSS and JavaScript. All data stored in GenIA is extracted by manually reviewing published research articles. ResultsWe completed data collection and curation for 24 pilot genes. Using these data, we exemplify how GenIA can provide quick access to a structured, longitudinal, more thorough, comprehensive and up-to-date IEI knowledge than currently existing databases, such as ClinGen, HPO, ClinVar or OMIM, with which GenIA intends to dovetail. ConclusionsGenIA strives to accurately capture the extensive genetic, mechanistic, and phenotypic heterogeneity found across IEIs, as well as genetic paradigms and diagnostic pitfalls associated with individual genes and conditions. The IEI community's involvement will help promote GenIA as an enduring resource that supports and improves knowledge-sharing, research, diagnosis and care for patients with genetic immune disease.

Poly(imidazolyliden-yl)borato Complexes of Tungsten: Mapping Steric vs. Electronic Features of Facially Coordinating Ligands.

A convenient synthesis of [HB(HImMe)3](PF6)2 (ImMe = N-methylimidazolyl) is decribed. This salt serves in situ as a precursor to the tris(imidazolylidenyl)borate Li[HB(ImMe)3] pro-ligand upon deprotonation with nBuLi. Reaction with [W(≡CC6H4Me-4)(CO)2(pic)2(Br)] (pic = 4-picoline) affords the carbyne complex [W(≡CC6H4Me-4)(CO)2{HB(ImMe)3}]. Interrogation of experimental and computational data for this compound allow a ranking of familiar tripodal and facially coordinating ligands according to steric (percentage buried volume) and electronic (νCO) properties. The reaction of [W(≡CC6H4Me-4)(CO)2{HB(ImMe)3}] with [AuCl(SMe2)] affords the heterobimetallic semi-bridging carbyne complex [WAu(μ-CC6H4Me-4)(CO)2(Cl){HB(ImMe)3}].

Natural history of cardiac findings in mucopolysaccharidosis type I: report from an international registry.

Mucopolysaccharidosis type I is an inborn error of glycosaminoglycan catabolism with phenotypes ranging from severe (Hurler syndrome) to attenuated (Hurler-Scheie and Scheie syndromes). Cardiovascular involvement is common and contributes significantly to morbidity and mortality. We conducted a retrospective analysis of the prevalence and natural history of cardiac abnormalities in treatment-naïve individuals enrolled in the international Mucopolysaccharidosis Type I Registry. Interrogation of echocardiography data (presence of cardiac valve regurgitation and/or stenosis; measurements of left ventricular chamber dimensions in diastole and systole, diastolic left ventricular posterior wall and interventricular septal thicknesses and ventricular systolic function (shortening fraction)) showed that mitral regurgitation was the most common and earliest finding for individuals with both severe (58.3%, median age 1.2 years) and attenuated (74.2%, median age 8.0 years) disease. Left-sided valve stenosis was also common in individuals with attenuated disease (mitral 30.3%; aortic 25%). Abnormal ventricular wall and septal thickness (Z-scores ≥2) were observed early in both phenotypes. Z-scores for diastolic left ventricular posterior wall and interventricular septal thicknesses increased with age in the severe phenotype (annualised slopes of 0.2777 [p = 0.037] and 0.3831 [p = 0.001], respectively); a similar correlation was not observed in the attenuated phenotype (annualised slopes of -0.0401 [p = 0.069] and -0.0029 [p = 0.875], respectively). Decreased cardiac ventricular systolic function (defined as shortening fraction <28%) was uncommon but, when noted, was more frequent in infants with the severe phenotype. While cardiac abnormalities occur early in both severe and attenuated mucopolysaccharidosis type I, the pattern of valve dysfunction and progression of ventricular abnormalities vary by phenotype.

A Game-Theoretical Approach to Clinical Decision Making with Immersive Visualisation

Cancer is a disease characterised by changes in combinations of genes within affected tumour cells. The deep understanding of genetic activity afforded to cancer specialists through complex genomics data analytics has advanced the clinical management of cancer by using deep machine learning algorithms and visualisation. However, most of the existing works do not integrate intelligent decision-making aids that can guide users in the analysis and exploration processes. This paper contributes a novel strategy that applies game theory within a VR-enabled immersive visualisation system designed as the decision support engine to mimic real-world interactions between stakeholders within complex relationships, in this case cancer clinicians. Our focus is to apply game theory to assist doctors in the decision-making process regarding the treatment options for rare-cancer patients. Nash Equilibrium and Social Optimality strategy profiles were used to facilitate complex analysis within the visualisation by inspecting which combination of genes and dimensionality reduction methods yields the best survival rate and by investigating the treatment protocol to form new hypotheses. Using a case simulation, we demonstrate the effectiveness of game theory in guiding the analyst with a patient cohort data interrogation system as compared to an analyst without a decision support system. Particularly, the strategy profile (t-SNE method and DNMT3B_ZBTB46_LAPTM4B gene) gains the highest payoff for the two doctors.

Teaching listening in middle schools: perceptions of practice

Abstract This qualitative case study first examined middle school teacher perceptions of practice regarding L2 listening instruction and, from these, proposes guidelines to favour L2 listening development. Novice middle-school teachers from Chile (n = 14) were guided within semi-structured interviews to reflect on their own L2 listening teaching practices in public and semi-private school classrooms. Verbal reports were transcribed and analysed using thematic analysis techniques and underwent systematic interrogation of qualitative data. The results show an overemphasis on teacher preference for task completion to the detriment of developing listening strategies. We present results and provide guidelines for teachers to integrate features of a metacognitive instruction approach to listening.

An Open-Source Framework for Mass Calculation of Antibody-Based Therapeutic Molecules.

Biotherapeutic masses are a means of verifying identity and structural integrity. Mass spectrometry (MS) of intact proteins or protein subunits provides an easy analytical tool for different stages of biopharmaceutical development. The protein's identity is confirmed when the experimental mass from MS is within a pre-defined mass error range of the theoretical mass. While several computational tools exist for the calculation of protein and peptide molecular weights, they either were not designed for direct application to biotherapeutic entities, have access limitations due to paid licenses, or require uploading protein sequences to host servers. We have developed a modular mass calculation routine that enables the easy determination of the average or monoisotopic masses and elemental compositions of therapeutic glycoproteins, including monoclonal antibodies (mAb), bispecific antibodies (bsAb), and antibody-drug conjugates (ADC). The modular nature of this Python-based calculation framework will allow the extension of this platform to other modalities such as vaccines, fusion proteins, and oligonucleotides in the future, and this framework could also be useful for the interrogation of top-down mass spectrometry data. By creating an open-source standalone desktop application with a graphical user interface (GUI), we hope to overcome the restrictions around use in environments where proprietary information cannot be uploaded to web-based tools. This article describes the algorithms and application of this tool, mAbScale, to different antibody-based therapeutic modalities.

Semi-automated detection of rangeland runoff and erosion control berms using high-resolution topography data

An inventory of topographic modifications is essential to addressing their impacts on hydrological and morphological processes in human-altered watersheds. However, such inventories are generally lacking. This study presents two workflows for semi-automatic detection of linear earthen runoff and erosion control berms in rangelands using high-resolution topographic data. The workflows consist of initial object identification by applying either morphological grayscale reconstruction (MGR) or the Geomorphon (GEO) method, followed by identification refinements through filters based on objects’ horizontal and vertical information. Three sites were selected within the Altar Valley, Arizona, in the southwestern United States. One site was used for developing workflows and optimizing filter thresholds, and the other two sites were used to validate workflows. The results showed that: 1) The MGR-based workflow methodology could produce final precision and detection rates of up to 92% and 75%, respectively, and take less than 5 s for a 10.1 km2 site; 2) The workflow based on the MGR method yielded greater identification accuracy than did the GEO workflow; 3) Object length, orientation, and eccentricity were important characteristics for identifying earthen berms, and are sensitive to general channel flow direction and berm shape; 4) Manual interrogation of topographic data and imagery can significantly improve identification precision rates. The proposed workflows will be useful for developing inventories of runoff and erosion control structures in support of sustainable rangeland management.

Storing paediatric genomic data for sequential interrogation across the lifespan

Genomic sequencing (GS) is increasingly used in paediatric medicine to aid in screening, research and treatment. Some health systems are trialling GS as a first-line test in newborn screening programmes....

PO-455617-3 NOVEL PRECISION GENETIC APPROACH IMPROVES DIAGNOSIS AND RISK STRATIFICATION IN LONG QT SYNDROME TYPE 5

Type 5 long QT syndrome (LQT5) is a subtype of long QT syndrome caused by loss of function variants in KCNE1 encoding a key potassium channel function-modifying subunit. LQT5 cases are rare and incompletely penetrant, so it has been controversial whether KCNE1 variants are disease-causing or risk-modifying. We identified 9 local LQT5 probands carrying the D76N KCNE1 variant, the most common variant implicated in LQT5. To test the hypothesis that these probands shared a recent common ancestor and to identify other potential D76N carriers in BioVU, our biobank that links electronic health records to DNA data. We used dense genomic arrays and identity-by-descent (IBD)-based genotype inference to identify shared chromosomal segments in the 9 probands and 3 first-degree relatives, and across BioVU. We determined penetrance (QTc > 490 msec) and the relationship of penetrance to a 1.1 million SNP QT interval polygenic risk score (PRS) in all mutation carriers. IBD analysis identified large (>1 cM) shared chromosomal segments across 8 of the 9 probands, indicating a shared common ancestor approximately 4-5 generations ago. Interrogation of array data in 69,879 European ancestry subjects in BioVU identified a further 26 subjects sharing the same large chromosomal segment, and sequencing confirmed D76N carrier status in 22 subjects, all previously undiagnosed. One BioVU subject had a history of sotalol-induced Torsades de Pointes. We found that among the 34 D76N carriers, QT intervals were prolonged compared to >32,000 BioVU controls free of heart disease or QT prolonging drugs, and that penetrance for QTc>490 was 44%. Among carriers, the QTc PRS was associated with severe QT prolongation. Detection of large shared chromosomal segments around KCNE1 enabled us to define a local founder event, identify previously undiagnosed carriers, demonstrate the contribution of polygenic risk to monogenic disease penetrance, and to further establish LQT5 as a primary arrhythmia disorder. The analysis of distant relatedness is a promising new approach to identify undiagnosed cases of genetic diseases.

Middle Palaeolithic occupation of the southern North Sea Basin: evidence from the Sandscaping sediments emplaced on the beach between Bacton and Walcott, Norfolk, UK

ABSTRACTDuring the summer of 2019, the Bacton to Walcott Coastal Management Scheme involved the emplacement on to the foreshore of 1.8 million cubic metres of sand and gravel dredged from the submerged sediments of the Palaeo‐Yare in the southern North Sea 11 km off Great Yarmouth. During the following 2‐year period, an active group of collectors identified Palaeolithic artefacts eroding from these sediments, including Levallois cores and flakes, and cordiform handaxes. In this paper, we present an analysis of the lithic artefacts, and consider the relationships between the different elements of the assemblage. We discuss its significance in the context of the Middle Palaeolithic record of northwest Europe and the light it shines on the human occupation of the submerged landscape of the southern North Sea during the later Middle Pleistocene. Interrogation of beach survey data shows the reworking of these sediments to the southeast towards Happisburgh where archaeologically significant exposures of the Cromer Forest‐bed Formation are located. The implications of the introduction of a Middle Palaeolithic assemblage to this stretch of the North Norfolk Coast are considered, highlighting the importance of continuing dialogue between researchers, local authorities and local communities for capturing information and monitoring this critical Palaeolithic resource.

Participant-specific interrogation of population-based data to predict cognitive decline from neuropsychiatric symptoms and neuroimaging biomarkers: A machine learning approach (P12-6.001)

<h3>Objective:</h3> Develop machine learning (ML) models to predict decline in global cognition and attention from neuroimaging biomarkers of Alzheimer’s disease (AD) and neuropsychiatric symptoms (NPS). <h3>Background:</h3> ML is increasingly being used in brain aging research. <h3>Design/Methods:</h3> We developed four ML models (support vector machine, Gaussian process, random forest, Naïve Bayes) to predict z-scored global cognition and attention domain changes between first and last study visits of each participant. We used a stepwise approach to develop the prediction models by: 1) including AD biomarkers (PiB- &amp; FDG-PET), education, and APOE ɛ4 status; followed by 2) adding measures of depression (Beck Depression Inventory-II; BDI-II), and anxiety (Beck Anxiety Inventory; BAI); then 3) adding 12 NPS including NPS severity as measured by Neuropsychiatric Inventory Questionnaire (NPI-Q). <h3>Results:</h3> Data from 777 cognitively unimpaired (CU) participants for the outcome of global cognition z-score, and 795 CU participants for the outcome of attention z-score was available. 80% of the sample was randomly used to train the model, which was blind tested on the remaining 20%. For global cognition, the best model was able to predict 78% of participants with decreasing z-score using AD biomarkers, education, and APOE ɛ4 status. Adding BDI-II and BAI improved the prediction to 87%; and adding 12 NPS further improved the prediction to 96% of participants with decreasing z-scores. Including NPS severity did not improve the model’s performance. For the attention domain, the best model predicted 89% of participants with decreasing z-score using AD biomarkers, education, and APOE ɛ4 status. After adding BDI-II and BAI measurements, the model was able to predict 97% of participants with decreasing z-scores. Adding 12 NPS, and NPI severity only marginally improved the model’s performance to 98%. <h3>Conclusions:</h3> ML has the potential to successfully predict global and domain-specific cognitive decline in community-dwelling persons, with NPS improving prediction compared to AD neuroimaging biomarkers alone. <b>Disclosure:</b> Mr. Shah has nothing to disclose. Jeremy Syrjanen has nothing to disclose. Dr. Krell-Roesch has nothing to disclose. The institution of Walter Kremers has received research support from Biogen. Dr. Vemuri has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Miller Medical Communications Inc.. The institution of Dr. Vemuri has received research support from NIH. The institution of Dr. Vassilaki has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for F. Hoffmann-La Roche Ltd . Dr. Vassilaki has stock in Abbott Laboratories. Dr. Vassilaki has stock in Johnson and Johnson. Dr. Vassilaki has stock in Medtronic. Dr. Vassilaki has stock in Amgen. Dr. Vassilaki has stock in AbbVie. Dr. Vassilaki has stock in Merck. The institution of Dr. Vassilaki has received research support from NIH. The institution of Dr. Vassilaki has received research support from European Union/ St. Anne’s University Hospital Brno, Czech Republic. The institution of an immediate family member of Dr. Vassilaki has received research support from Avobis Bio, LLC. Dr. Petersen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Roche. Dr. Petersen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Merck. Dr. Petersen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Genentech. Dr. Petersen has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Nestle. Dr. Petersen has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genentech, Inc.. Dr. Petersen has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Roche, Inc.. Dr. Petersen has received publishing royalties from a publication relating to health care. Dr. Petersen has received publishing royalties from a publication relating to health care. The institution of Dr. Forzani has received research support from NIH. The institution of Dr. Forzani has received research support from NSF. Dr. Forzani has received intellectual property interests from a discovery or technology relating to health care. Dr. Forzani has received personal compensation in the range of $100,000-$499,999 for serving as a Professor with Arizona State University. Dr. Wu has nothing to disclose. The institution of Dr. Geda has received research support from NIH.

The development of high school students’ statistical literacy across grade level

The capacity to interrogate data with critical thinking is a strong predictor of statistical literacy (SL). This data interrogation, from the data consumers’ perspective, incorporates four complex response skills: interpreting, communicating, evaluating, and decision-making, and those skills are strongly supported by students’ appreciation of three interrelated knowledge components (text and context, representation, and statistical-mathematical knowledge). Due to the need to be critical data-information readers, students’ SL should develop during their formal schooling. The aim of this paper was to investigate differences in SL between Indonesian year 9 and year 12 students and between female and male students. The same test was administered to 48 year 9 students (50% females) and 48 year 12 students (50% females) from 16 different schools in Indonesia. Findings revealed that the highest percentage of year 9 and 12 students demonstrated evidence of consistent but non-critical thinking (level 4), suggesting that they exhibited their statistical knowledge but not in critical ways. There were 42% of year 9 students showing limited statistical thinking (levels 1 to 3) compared to 17% of year 12 students. Furthermore, while there were no significant gender differences in students’ SL and its all skills, the study shows significant grade level differences in overall SL as well as in its skills except interpreting. Implications of this study include the development of a framework that provides a coherent assessment of students’ SL from a data consumers’ perspective, along with suggestions for classroom teaching.

Abstract P2-20-01: Patient-derived triple-negative breast cancer organoids as a platform for glucocorticoid receptor- mediated mechanisms of immunotherapy response and resistance

Abstract Background: In early-stage triple-negative breast cancer (TNBC), high glucocorticoid receptor (GR) expression correlates with worse relapse-free survival across TNBC subtypes, induces oncogenic gene expression and tumor cell survival, and potentiates anti-inflammatory or an anti-immunogenic phenotype. Immune checkpoint therapy has increased pathologic complete response rates in the neoadjuvant setting, however response to immunotherapy remains modest overall and the explanatory mechanisms for this phenomenon are incompletely understood. We sought a three-dimensional model of the TNBC immune microenvironment using patient-derived organoids (PDOs) that capture tumor heterogeneity, partially recapitulates tumor microenvironment, and can be established for longer-term in vitro/in-vivo translational study after exposure to immunotherapy. We hypothesize that during chemoimmunotherapy treatment of early-stage triple-negative breast cancer, high glucocorticoid receptor activity mediates an immunosuppressive phenotype and glucocorticoid receptor modulation can restore anti-tumor immunity. Methods and Results: We are successfully growing 5 PDOs out of 8 surgically resectedion samples tumors from patients with early-stage triple-negative breast cancer treated with chemotherapy vs. chemoimmunotherapy as per KEYNOTE-522. Interrogation of complementary TNBC cell line data revealed that GR activation downregulates the expression of immune checkpoint genes (PD-L1, B7-H3, B7-H4), while GR knockdown or treatment with a selective GR modulator restores expression of these immune checkpoint genes. TNBC-intrinsic GR activation increases the proportion of regulatory T cells vs. CD8+ T cells. In a coculture system of TNBC spheroids and T cells, GR activation in TNBC results in decreased activated CD8+ CD137+ T cells and use of the selective GR modulator increases the proportion of activated CD8+ CD137+ T cells. Conclusions and Future Directions: In early-stage triple-negative breast cancer, GR activation downregulates expression of immune checkpoint genes and reduction of GR activity restores expression. In a coculture system that recapitulates T cell repertoire found in triple-negative breast cancer, tumor-intrinsic GR activation results in increased regulatory T cell population and reduction of GR activity increases activated CD8+ CD137+ T cells. Ongoing analyses of TNBC organoid-immune coculture systems modeling high GR states will be used to (i) define cooperativity amongst immune checkpoint proteins in costimulation vs. coinhibition of anti-tumor responses and (ii) define novel pairs of receptor-ligands amongst TNBC:CD8+ vs. TNBC:Treg vs. CD8+:Treg as discovery of potential new therapeutic targets. Citation Format: Christine Shiang, Candace Frerich, Ishrat Durdana, Cheryl Lewis, Lynda B. Bennett, Carlos Arteaga, Suzanne D. Conzen. Patient-derived triple-negative breast cancer organoids as a platform for glucocorticoid receptor- mediated mechanisms of immunotherapy response and resistance [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-20-01.

Integration of mRNA and protein expression data for the identification of potential biomarkers associated with pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most death-dealing tumors, with a tremendously poor prognosis. Here, we, through interrogation of mRNA and protein data combined with a system biology approach, identified several key genes, functional processes, and pathways that can have critical roles in PDAC. We detected an interesting module related to the clinical traits that enriched in the ribosome, hematopoietic cell lineage, and cell adhesion molecules-related pathways. We also identified several hub genes in important modules that are associated with immune system processes. The results also indicated some lncRNAs, such as FAM30A, and MIR223HG with essential functions that are involved in PDAC. Additionally, five genes, including CD53, ITGAL, WDFY4, TLX1, and LMAN1L were screened by survival analysis and can be considered as candidate biomarkers or therapeutic targets. According to our strategy, the findings of this study may provide a better understanding of the molecular mechanisms and suggest potential prognostic and therapeutic targets for PDAC.

Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset

ObjectivesWe involved public and professional stakeholders to assess a novel data interrogation tool, the Neonatal Health Intelligence Tool, for a National Data Asset, the National Neonatal Research Database.MethodsWe recruited parents,...

Correlations and associations between fluid‐based and morphometric imaging biomarkers through interrogation and integration of data and analysis across two data platforms

AbstractBackgroundThe Global Alzheimer’s Association Interactive Network (GAAIN) and the Critical Path for Alzheimer’s Disease (CPAD) Consortium have undertaken a collaborative effort to establish a mechanism that can help evaluate the relationship between fluid‐based, morphometric imaging biomarkers and clinical trajectories of disease progression, across datasets and analyses pipelines housed by CPAD and GAAIN. Additionally, this collaboration will demonstrate the feasibility of bidirectional integration of data management models and will guide development of a federated image analysis pipeline model across these two platforms.MethodTo enable interoperability, GAAIN’s original architecture is expanded to accommodate the LONI brain structural imaging pipeline. Under this new framework, GAAIN researchers can initiate brain imaging‐related analyses on their servers directly from GAAIN’s graphical interface with the results integrating back into GAAIN for further analyses. Feasibility was demonstrated for the determination of correlations for CPAD’s biomarker and imaging volumetric data. GAAIN’s brain imaging pipeline was executed on CPAD data, allowing for quantification of volumetric images. In turn, blood and volumetric data were inserted in GAAIN allowing further evaluation and analyses.ResultBased on the results, we provide guidelines for a future framework for a federated analysis model that can be utilized from GAAIN and CPAD to establish relationships between blood and brain markers. In this model, for a cohort of interest, analyses of relevant brain marker data can be remotely done in CPAD servers via GAAINs’ federated platform after which results can be inserted back to GAAIN alongside CPAD’s blood marker data. The full capabilities of this federated model will be explored in subsequent work.ConclusionAs data sharing becomes increasingly prominent and mature, the partnership between GAAIN and CPAD will yield ever greater benefits and knowledge and will continue to grow and evolve in response to the changing Alzheimer’s disease landscape. As such, it represents a non‐exclusive door for researchers to make use of the data sets and advanced analytical tools and is intended to leverage the unique competencies of these organizations and lead to the continued evolution of bringing meaningful and high‐impact advances in Alzheimer’s disease.

Interprofessional education programs to foster the use of Learning Health Systems

Healthcare management continues to worsen, with process inefficiencies, wastage, unsafe practices and accordingly, non-optimal patient care. The concept of the Learning Health Systems (LHS) demonstrates the potential for the utilisation of health data in real time, through rapid and continuous cycles of data interrogation, implementation of insights into practice, and eventually practice change (Friedman &amp; Flynn, 2019). Yet, the lack of appropriately skilled workforce results in an inability to leverage existing data to design innovative solutions. We identified a need to develop tailored professional development programs to foster skilled interdisciplinary learning communities in the healthcare workforce, as well as digital health champions that understand each other’s roles and capabilities, to collaboratively solve these complex problems. Thus, we have developed multiple educational programs of work, including a professional development short course and a year-long Academy Fellowship program, to teach LHS principles. The short course is wholly online, open to interdisciplinary professionals working in the digital health arena. To foster interprofessional learning, we assigned participants into working groups of five interprofessional members, who worked together and shared knowledge, perspectives and experiences in workshop activities throughout the 13-week course. We employed a flipped classroom approach, utilising various eLearning tools such as crowdsourced evidence synthesis Mind Maps; Jupyter Notebooks for hands on data interrogation, data visualisation and interpretation of machine learning models; clinical process modelling software (LucidChart); and virtual care platform for prototype testing digital health solutions (Datos), which showcasing the potential of technology. We undertook a mixed methods evaluation, to determine the utility and success of our programming. This framework consisted of pre and post-surveys with identical measures of self-efficacy, ratings scales for engagement, usefulness, applicability and value for various aspects of the course. Participants were also invited to participate in a semi-structured interview post course. This allowed a deeper dive into themes relating to utility, barriers, recommendations for future applicability, and evolving digital health identity. The evaluation results demonstrated that participants found the teaching model useful, engaging, applicable and valuable to their daily tasks and workplace LHS projects. Self-efficacy scales revealed a significant increase in perceive confidence. From interviews and analysis of free text responses, we discovered that the program gave participants a shared language and common understanding to converse with other interprofessional peers; transformed their perceptions of their role and the potential of data and technologies; provided a framework to organise their transformation plans; and finally provided a toolkit to refer to and operate from. The most notable observation from the LHS Academy Fellows, was a significant increase in the number of fellows identifying themselves as leaders at the end of their foundational coursework compared to at the start of the program. It is clear that in order to transform healthcare systems to their full potential, it requires a workforce with an understanding of LHS and the potential of data driven approaches, as well as an appreciation for the need for diversly skilled learning communities to tackle these problems together.