Science Background Research Articles

Artificial Intelligence and Theology

This bibliographic essay provides a starting point for theological librarians to engage the history, anthropology, ethics, theology of artificial intelligence. What it shows is that despite seeming to appear ex nihilio, artificial intelligence for writing has a long history, profound ethical consequences beyond academic integrity, and latent theology. While theological librarians may or may not have the computer science background necessary to engage the technicalities of AI, they certainly have the disciplinary knowledge and skill to engage the topic in a meaningful and theological way.

Automatic detection for bioacoustic research: a practical guide from and for biologists and computer scientists.

Recent years have seen a dramatic rise in the use of passive acoustic monitoring (PAM) for biological and ecological applications, and a corresponding increase in the volume of data generated. However, data sets are often becoming so sizable that analysing them manually is increasingly burdensome and unrealistic. Fortunately, we have also seen a corresponding rise in computing power and the capability of machine learning algorithms, which offer the possibility of performing some of the analysis required for PAM automatically. Nonetheless, the field of automatic detection of acoustic events is still in its infancy in biology and ecology. In this review, we examine the trends in bioacoustic PAM applications, and their implications for the burgeoning amount of data that needs to be analysed. We explore the different methods of machine learning and other tools for scanning, analysing, and extracting acoustic events automatically from large volumes of recordings. We then provide a step-by-step practical guide for using automatic detection in bioacoustics. One of the biggest challenges for the greater use of automatic detection in bioacoustics is that there is often a gulf in expertise between the biological sciences and the field of machine learning and computer science. Therefore, this review first presents an overview of the requirements for automatic detection in bioacoustics, intended to familiarise those from a computer science background with the needs of the bioacoustics community, followed by an introduction to the key elements of machine learning and artificial intelligence that a biologist needs to understand to incorporate automatic detection into their research. We then provide a practical guide to building an automatic detection pipeline for bioacoustic data, and conclude with a discussion of possible future directions in this field.

On the Billefjorden fault zone in Garmdalen, central Spitsbergen: implications for the mapping of major fault zones during geological fieldwork and for the tectonic history of Svalbard

Background The present contribution reexamines the geometry of a segment of a presumably long-lived fault in Svalbard, the Balliolbreen Fault segment of the Billefjorden Fault Zone, along which presumably two basement terranes of Svalbard accreted in the early–mid Paleozoic after thousands of kilometers strike-slip displacement. Methods We performed structural fieldwork to Billefjorden in central Spitsbergen and interpreted satellite images. Results Field observations demonstrate that the Balliolbreen Fault formed as a top-west thrust fault in the early Cenozoic and that weak sedimentary units such as shales of the Lower Devonian Wood Bay Formation and coals of the uppermost Devonian–Mississippian Billefjorden Group partitioned deformation, resulting in significant contrast in deformation intensity between stratigraphic units. For example, tight early Cenozoic folds are localized in shales of the Wood Bay Formation and contemporaneous top-west brittle–ductile thrusts within coals of the Billefjorden Group, whereas Pennsylvanian deposits of the Hultberget (and/or Ebbadalen?) Formation are simply folded into gentle open folds. Rheological contrasts also resulted in the development of décollements locally, e.g., between tightly folded strata of the Wood Bay Formation and Billefjorden Group and flat-lying, brecciated limestone-dominated strata of the Wordiekammen Formation. Despite the limited quality and continuity of outcrops in the area, the eastward-thickening character (i.e., away from the fault) of Pennsylvanian deposits of the Hultberget, Ebbadalen, and Minkinfjellet formations suggests that the fault did not act as a normal fault in Pennsylvanian times. Conclusions The study suggests that strain partitioning of early Cenozoic Eurekan contraction alone may explain the deformation patterns in Paleozoic rock units in central Spitsbergen, i.e., that Late Devonian Svalbardian contraction is not required, and that a major segment of the Billefjorden Fault Zone formed in the early Cenozoic. The present work illustrates the crucial need for interdisciplinary approaches and composite educational backgrounds in science.

Using flux theory in dynamic omics data sets to identify differentially changing signals using DPoP

BackgroundDerivative profiling is a novel approach to identify differential signals from dynamic omics data sets. This approach applies variable step-size differentiation to time dynamic omics data. This work assumes that there is a general omics derivative that is a useful and descriptive feature of dynamic omics experiments. We assert that this omics derivative, or omics flux, is a valuable descriptor that can be used instead of, or with, fold change calculations.ResultsThe results of derivative profiling are compared to established methods such as Multivariate Adaptive Regression Splines, significance versus fold change analysis (Volcano), and an adjusted ratio over intensity (M/A) analysis to find that there is a statistically significant similarity between the results. This comparison is repeated for transcriptomic and phosphoproteomic expression profiles previously characterized in Aspergillus nidulans. This method has been packaged in an open-source, GUI-based MATLAB app, the Derivative Profiling omics Package (DPoP). Gene Ontology (GO) term enrichment has been included in the app so that a user can automatically/programmatically describe the over/under-represented GO terms in the derivative profiling results using domain specific knowledge found in their organism’s specific GO database file. The advantage of the DPoP analysis is that it is computationally inexpensive, it does not require fold change calculations, it describes both instantaneous as well as overall behavior, and it achieves statistical confidence with signal trajectories of a single bio-replicate over four or more points.ConclusionsWhile we apply this method to time dynamic transcriptomic and phosphoproteomic datasets, it is a numerically generalizable technique that can be applied to any organism and any field interested in time series data analysis. The app described in this work enables omics researchers with no computer science background to apply derivative profiling to their data sets, while also allowing multidisciplined users to build on the nascent idea of profiling derivatives in omics.

PSVII-30 Assessing writing and visual models as a pedagogical strategy for creating individual learning paths in animal nutrition

Abstract Self-directed learning harnesses intrinsic drive of students to create and preserve knowledge fostering comprehension of broader concepts and real-world applicability. Principles of animal nutrition, a required course in animal science curricula nationwide, is foundational to sustainable management of livestock and companion animals. Mastery of the principles governing nutrient digestion and metabolism is imperative as students progress into upper-level classes and pursue careers in the agriculture field. In this study, 304 students, enrolled in an upper-level animal nutrition class were invited to participate in an honors contract, entailing the completion of the “Explorer” project to earn honors credit. Throughout the semester, students (n = 27) researched a unique herbivore or omnivore, to create novel visual models illustrating nutrient digestion and metabolism (e.g., carbohydrates, lipids, proteins). We hypothesized that explaining these processes and models through writing would build confidence and proficiency in lecture material. The honors cohort convened weekly for 1 h sessions on campus; meetings offered scientific writing seminars, collaborative brainstorming activities, and project feedback. A Likert scale survey was generated and administered using Qualtrics software during the last weekly meeting to those who completed the “Explorer” project (88.8% response rate). Additionally, participating students completed a learning reflection addressing prompts regarding engagement, critical thinking, comparison with lecture writing assignments, and proposed design modifications. An open coding methodology was employed, utilizing MAXQDA Analytics Pro (Version 24.1.0) to analyze reflections qualitatively. Subsequently, the AI assist feature was used to enhance inter-coder reliability by generating summaries and sub-codes that aided in the exploration of common themes across reflections. Our analysis revealed that writing to learn in a nutrition course provided an authentic avenue for scientific expression, fostering skills such as communication, time management, research, comprehension of literature, and effective citation usage. Information gathering improved confidence in their ability to interpret and integrate concepts from lectures and external sources. Incorporating group activities and peer-reviews bolstered project efficacy, motivating students to revise, incorporate feedback, and consider alternative perspectives iteratively. Moreover, the learner-generated drawing enhanced critical thinking by encouraging students to dissect processes thoroughly. In conclusion, the combination of creating visual models alongside written explanations proved highly effective in simplifying complex nutritional concepts, facilitating deeper comprehension, and providing a high-impact learning experience. Future research should focus on peer teaching following similar writing activities to further improve student engagement and foster avenues for autonomy. Efforts should be made to encourage participation from a more diverse range of students that represent all backgrounds in animal science.

Introduction to the Special Issue: Family Science Careers Through the Eyes of Theory

This manuscript is part of a special issue of Family Science Review entitled Family Science Careers Through the Eyes of Theory, edited by Raeann Hamon, Ph.D., CFLE. The authors of these deliberately unconventional manuscripts were asked to select and describe a career that a professional with a family science background might pursue. After outlining the professional role, authors reflected upon the family theories that most influence the way they approach their work and perform their professional duties. Authors briefly review the scholarly literature on selected family theories, provide case studies or work scenarios as illustrations of theory in action, and discuss the strengths and weaknesses of the theories in their unique professional contexts. The Special Issue articles are designed to be used individually or in combination, and feature articles about careers in early intervention, special education, family court, child life, and higher education.

The role of technology belief, perceived risk and initial trust in users’ acceptance of urban air mobility: An empirical case in China

Urban Air Mobility (UAM) is poised to revolutionize transportation, necessitating an assessment of public acceptance before broad commercial adoption. This study presents the Urban Air Mobility Acceptance Model (UAM-AM), which draws from the Technology Acceptance Model (TAM) and underscores the crucial role of initial trust, technology belief and perceived risk. The UAM-AM is validated using Structural Equation Modeling (SEM) based on 544 questionnaires for the first time in China. The findings highlight the significant impact of perceived ease of use and perceived usefulness on acceptance, uncovering a complex interplay with the intention to utilize UAM services. Notably, initial trust emerges as a foundational factor, influencing attitudes directly or indirectly through perceived ease of use and perceived usefulness. Moreover, the research identifies technology belief and perceived risk as fundamental drivers of initial trust. Examination of demographic segments reveals a heightened technology belief among individuals with backgrounds in science, indicative of a more favorable attitude towards UAM adoption. In closing, the paper presents recommendations for policymakers, service providers, and eVTOL manufacturers to formulate effective strategies that promote public acceptance during the initial phases of UAM deployment.

Interest in science and mathematics teaching among non-science/mathematics initial teacher education candidates

ABSTRACT Many countries are experiencing teacher shortages, with particularly long-standing issues in attraction and retention in secondary science and mathematics. Policy initiatives often focus on science and mathematics undergraduates, with the aim of encouraging them to consider teaching by offering scholarships into teacher education or fast-tracking into employment permanency. However, those who have already chosen to teach in non-science and mathematics teaching specialisations have already shown their interest in teaching and form a pool of candidates that may potentially be recruited into science and mathematics teaching pathways. While these non-science and mathematics teacher candidates could have the capacity to address in part longstanding science and mathematics teacher shortages, there is a lack of research examining their motivations from the perspective of initiatives that may attract them into science and mathematics teaching, and little that examines their science and mathematics backgrounds. We sought to address these gaps by surveying 349 initial teacher education (ITE) students from four Australian universities, examining their career motivations, interest in science and mathematics teaching, and science and mathematics backgrounds. We explored perceived barriers to secondary science and mathematics teaching, and responses to potential policy initiatives. We found that 61% of non-science/mathematics ITE candidates indicated high interest in secondary science or mathematics pathways. Policy options such as support for science and mathematics retraining after several years of teaching in their current subject area or level, were selected as likely to support this choice. Our results suggest considerable capacity for policymakers and tertiary institutions to design initiatives that may attract non-science/mathematics ITE candidates into science and mathematics teaching.

Cultivating Excellence: Future-Proofing Medical Affairs with Tailored Talent Programs.

In today's rapidly growing healthcare landscape, the role of Medical Affairs within pharmaceutical companies has transitioned from a traditional support function into a strategic one. Amidst acute challenges such as evolving globalization, digitization, and healthcare trends, effective talent development and professional standards in Medical Affairs emerge as a pivotal cornerstone to future-proof pharmaceutical companies. This article explores strategies, perspectives, and best practices for enhancing talent development with medical or natural sciences background in the field of Medical Affairs. From the historical development of Medical Affairs, we cover current challenges and provide a comprehensive approach to talent development strategies of next-generation talents in Medical Affairs. Drawing upon current literature and personal experiences, we discuss various aspects relevant for designing targeted training programs, fostering interdisciplinary collaboration, and enhancing both technical and soft skills essential for success in Medical Affairs roles. Furthermore, we highlight the significance of company-internal rotational programs in exposing talents to different facets of Medical Affairs. We advocate for a flexible and individualized approach to talent development, allowing next-generation talents to pursue personal interests and contribute to innovative projects. Overall, this article offers practical recommendations for pharmaceutical companies aiming to optimize their local talent development initiatives in Medical Affairs and align them with the evolving needs of the healthcare landscape.

Science Instructional Coaches: Characteristics, Contexts, Beliefs, and Community

ABSTRACT Instructional coaching has emerged as a promising form of professional development for teachers. However, little is known about the background, contexts, professional responsibilities, and beliefs of instructional coaches who work with science teachers. This mixed-methods study focused on instructional coaches in secondary schools across the United States to understand the experiences these coaches bring to the role and what activities they participate in that support science teaching. Coaches’ goals for their work and tensions with the institution’s goals were also explored, as well as their beliefs about science teaching. Results suggest that three types of coaches may support science teaching, depending on the content expertise of the coach (science or not) and the focus of their role (content-specific or general). Teacher support by instructional coaches with science backgrounds is evident through their support of effective science teaching strategies. However, this support may not extend to pushing teachers to develop reform-based science teaching practices, as the results showed that most of these instructional coaches did not hold reform-based views of science teaching. The goal of relationship building and the coaches’ work as trust-builders emerged as a critical factor in the coaches’ abilities to support teachers’ pedagogical development. Implications for the field are discussed.

Living labs in agrifood studies: An opportunity to revisit fundamental questions about participatory research?

The use of the term ‘living lab’ is now widespread, and in agrifood studies has been incorporated into research funding requirements. However, the methodological skills and prerequisites for successful living labs are not particularly well articulated. Based on our experience (five national and EU research projects) and our research backgrounds in (interdisciplinary) social science and participatory research, we highlight several risks associated with the use of living labs in agrifood studies without having the resources, reflectivity or skills required. These risks include: 1) imposing predefined agendas that are masked as participatory processes, 2) placing an overemphasis on confidentiality or knowledge sharing, and 3) getting lost in researcher roles. We argue that there is a need to discuss and improve understanding of these risks in order to produce successful living labs in agrifood studies, as well as avoid conceptual dilution or confusion.

Design of Point-of-Care Ultrasound Device to be Used in At-Home Setting-A Holistic Approach.

The primary purpose of this work was to design and implement a compact, battery-powered, fully wearable applicator for delivering therapeutic low-frequency (20-40 kHz), low-intensity (100 mW/cm2 ISPTP) (LFLI) ultrasound to enable treatment of chronic wounds in home setting. Such a device does not currently exist, and in addition to engineering aspects associated with electromechanical design, its implementation requires a novel approach involving consideration of feedback received not only from healthcare professionals but also caregivers. One strong motivation for the novel design approach is to enable individuals with chronic wounds to enhance self-care management of wounds in the home setting instead of a hospital or outpatient clinic setting. In the home setting, the device may be exposed to physical maltreatment, requiring precautions with respect to its sturdiness. Although the holistic approach presented has been applied to the design of an applicator for chronic wounds, the design considerations and execution are transferable to any device targeted for home use. The implementation exemplified here examines transformation of an early, relatively fragile design into a robust, time-programmable, safe tool. The modification, which includes comprehensive reconfiguration and redesign of the electronics driving a piezoelectric transducer, is presented along with methodology devised with the field feedback obtained from focus groups. This feedback evinced that in addition to electrical engineering, an extensive background in mechanical engineering, material science, biology, and clinical practice is needed to fabricate an end-user friendly, quality-of-life improving, ergonomic device.

A comprehensive workflow for optimizing RNA-seq data analysis

BackgroundCurrent RNA-seq analysis software for RNA-seq data tends to use similar parameters across different species without considering species-specific differences. However, the suitability and accuracy of these tools may vary when analyzing data from different species, such as humans, animals, plants, fungi, and bacteria. For most laboratory researchers lacking a background in information science, determining how to construct an analysis workflow that meets their specific needs from the array of complex analytical tools available poses a significant challenge.ResultsBy utilizing RNA-seq data from plants, animals, and fungi, it was observed that different analytical tools demonstrate some variations in performance when applied to different species. A comprehensive experiment was conducted specifically for analyzing plant pathogenic fungal data, focusing on differential gene analysis as the ultimate goal. In this study, 288 pipelines using different tools were applied to analyze five fungal RNA-seq datasets, and the performance of their results was evaluated based on simulation. This led to the establishment of a relatively universal and superior fungal RNA-seq analysis pipeline that can serve as a reference, and certain standards for selecting analysis tools were derived for reference. Additionally, we compared various tools for alternative splicing analysis. The results based on simulated data indicated that rMATS remained the optimal choice, although consideration could be given to supplementing with tools such as SpliceWiz.ConclusionThe experimental results demonstrate that, in comparison to the default software parameter configurations, the analysis combination results after tuning can provide more accurate biological insights. It is beneficial to carefully select suitable analysis software based on the data, rather than indiscriminately choosing tools, in order to achieve high-quality analysis results more efficiently.

Re-thinking of arsiparis as records and archives professional in Indonesia

Background of the study: To be able to manage archival documents according to applicable standards, organizations need professional and competent arsiparis. Professionalism and competence are represented in the qualification and requirements in the recruitment process. Purpose: This paper aims to present the results of a mapping study of the qualification and special requirement for arsiparis, also analyzes the implications of these aspects for the reinforcement of arsiparis profiles Method: this paper uses an inductive qualitative approach, with the data analysis process by content analysis Findings: Formal educational qualification are still dominant in archival science major, although many opportunities are also for individuals with non-archival science backgrounds. Job experience in archives and records management is also recommended to acquire by individual who wants to be arsiparis. However, these have implications for the arsiparis’ profile which tends to be interpreted that archives and records management can be done by anyone. Conclusion: The authors give three recommends. First, confirming educational qualification limits; second, limiting the scope of arsiparis taskforce, and strengthening the independence of professional associations.

Breaking barriers: CEOs STEM educational background and corporate climate change disclosure

PurposeThis study aims to investigate the association between chief executive officer (CEO) educational backgrounds in science, technology, engineering and mathematics (STEM) and climate change disclosure within Indonesian companies.Design/methodology/approachUsing data spanning from 2017 to 2022 from all publicly traded companies, the study uses ordinary least squares with fixed effects and robust standard error to evaluate the proposed hypothesis. In addition, a series of endogeneity tests are incorporated to bolster the robustness of the findings.FindingsThe study reveals that CEOs with a STEM educational background are more inclined to participate in corporate climate change disclosure compared to their counterparts with a non-STEM background. These results emphasize the significant role CEO educational backgrounds play in shaping a company’s approach to sustainability, specifically in the realm of climate change disclosure. The insights gleaned from this research hold valuable implications for various stakeholders, including top management and investors aiming to enhance corporate sustainability. Recognizing the influence of CEO characteristics, particularly a STEM educational background, proves pivotal in improving corporate climate change disclosure. Stakeholders can leverage this understanding to formulate and implement effective strategies toward realizing a company’s sustainability vision.Originality/valueNotably, this study stands out as it was conducted within the context of Indonesia, a nation actively encouraging nonsocial graduates to assume crucial positions within the Republic of Indonesia.

A Practical tutorial on Explainable AI Techniques

The past years have been characterized by an upsurge in opaque automatic decision support systems, such as Deep Neural Networks (DNNs). Although DNNs have great generalization and prediction abilities, it is difficult to obtain detailed explanations for their behaviour. As opaque Machine Learning models are increasingly being employed to make important predictions in critical domains, there is a danger of creating and using decisions that are not justifiable or legitimate. Therefore, there is a general agreement on the importance of endowing DNNs with explainability. EXplainable Artificial Intelligence (XAI) techniques can serve to verify and certify model outputs and enhance them with desirable notions such as trustworthiness, accountability, transparency and fairness. This guide is intended to be the go-to handbook for anyone with a computer science background aiming to obtain an intuitive insight from Machine Learning models accompanied by explanations out-of-the-box. The article aims to rectify the lack of a practical XAI guide by applying XAI techniques in particular day-to-day models, datasets and use-cases. In each chapter, the reader will find a description of the proposed method as well as one or several examples of use with Python notebooks. These can be easily modified in order to be applied to specific applications. We also explain what the prerequisites are for using each technique, what the user will learn about them, and which tasks they are aimed at.

Using summary tables to introduce principal component analysis in an elementary data science course

AbstractThis article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging due to the potential abstraction of multivariate datasets, and especially when students have a minimal background in statistics or data science. This method aims to help teachers bridge the gap between basic descriptive statistics and the more advanced concepts of PCA; this is done by disregarding mathematical optimization, while emphasizing the use of summary tables and the programming language R. The focus is on implementing this method in an introductory tertiary data science course; however, it may potentially be used in higher level courses, and across a variety of disciplines.

Use of basic programming tools to foster programming logic in university students with school preparation other than computer science

Teaching programming logic to students who do not have a background in computer science is challenging, as the instructor has to awaken problem-solving, critical thinking, and logical reasoning skills Several programming tools have been created to teach coding concepts to computer science students of different ages. However, these tools are not well designed to meet the challenge of teaching programming to new developers who come with school training in other areas such as accounting, management, etc. Therefore, this research focused on analyzing the importance of the application of online programming tools to students starting college who come with a school background in an area other than technology. A pre/post experimental design was carried out with 82 first-level students of the Technical University of Ambato in the careers of Systems and Electronics. The results revealed that 45% of the students increased their levels of application and analysis in programming processes. In addition, the research revealed that students who come from a background other than computer science agree with the integration of online programming tools from the first level of university entrance since this method helps to improve their learning capacity.

Therapeutic inhibition of biomechanically-activated YAP-TAZ signaling prevents vein graft atherosclerosis

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Rembrandt Institute for Cardiovascular Sciences Background Venous bypass grafts may have limited patency due to excessive intimal hyperplasia and accelerated atherosclerosis. YAP-TAZ signaling regulates cellular responses to biomechanical cues, such as disturbed flow or vessel distention as seen in vein grafts. YAP activation leads to inflammation and angiogenesis, which both contribute to vein graft atherosclerosis. Inhibition of YAP-TAZ attenuates naive atherogenesis, but its potential to inhibit intraplaque angiogenesis and reduce vein graft atherosclerosis has not been explored. Methods Saphenous vein progenitor cells (SVPs) were subjected to mechanical strain in vitro to assess YAP activation. IHC to assess YAP-expression was performed on vein grafts from pigs as well as ex vivo cultured human saphenous veins. Furthermore, YAP-IHC was performed on murine vein grafts from hypercholesterolemic ApoE3*Leiden mice harvested at early, mid- and late-stage disease timepoints to assess optimal treatment window. In a separate experiment, mice (n=11-13/group) underwent bypass surgery and were treated with the FDA-approved YAP-TAZ inhibitor Verteporfin (50 mg/kg) or vehicle 3 times/week from day 10 until sacrifice (day 28). Ultrasound was used to longitudinally quantify vascular remodeling. Vein grafts were harvested and processed for morphometric and compositional analysis. Results Mechanical strain induced activation of YAP and its downstream targets (Ctgf, Cyr61) in SVPs, which was inhibited by Verteporfin (confirmed by WB, IP and qPCR). Moreover, YAP was abundantly expressed in pig vein graft lesions, whilst Verteporfin blocked YAP expression in ex vivo cultured human saphenous veins after exposure to disturbed flow. In addition, YAP was increasingly expressed during vein graft lesion development in mice, reaching its peak around day 14, which coincides with the initiation of intraplaque angiogenesis. Furthermore, YAP was predominantly expressed in luminal and adventitial endothelial cells. Analysis of ultrasound demonstrated that Verteporfin prevented vein graft thickening in mice over time. End-point histology revealed that the intima/media ratio was significantly decreased by Verteporfin treatment (37%, p=0.001). Intraplaque angiogenesis was also reduced (34%, p=0.002), whilst neovessel maturation was improved upon verteporfin treatment. The vessel wall ACTA2 content was reduced (42%, p=0.023), whilst collagen was not altered between both groups, indicating that Verteporfin diminished the fibroproliferative response without affecting vessel wall stability. Conclusion Verteporfin inhibited YAP-TAZ activation induced by mechanical strain in vitro (SVPs) as well as ex vivo (cultured human saphenous veins). In vivo, Verteporfin treatment resulted in a significant decrease of vein graft atherosclerosis and intraplaque angiogenesis. Therefore, therapeutic targeting of YAP-TAZ using Verteporfin might be a new candidate to improve vein graft patency.

Lenti-viral overexpression of RhoGEF Trio reduces CD8 T cell extravasation into atherosclerotic vein graft lesions in mice

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Rembrandt Institute for Cardiovascular Sciences Background In advanced atherosclerotic plaques, such as vein graft lesions, neovessels grow into the hypoxic plaque. This intraplaque angiogenic neovessels lack proper endothelial cell-cell junctions and are therefore susceptible to extravasation of leukocytes, which results in inflammation and atherosclerosis. T cells are the largest leukocyte subset found in atherosclerotic plaques and are key drivers of inflammation and plaque progression. RhoGEF Trio improves endothelial barrier function by strengthening endothelial cell-cell junctions in vitro, but its effect on T cell transmigration and its therapeutic potential to impede atherogenesis remains unknown. Methods ApoE3*Leiden mice (n=10/group) underwent bypass surgery in which a donor caval vein was interpositioned into the arterial circulation at the site of the right common carotid artery. Immediately post-operatively, a pluronic gel containing either GFP-Lentivirus (LV) (control) or Trio-GFP-LV (Trio) was locally applied around the vein graft to induce local overexpression of Trio. At post-op day 28, vein grafts were harvested and processed for morphometric and compositional analysis of the atherosclerotic lesions. Additionally, CD4 and CD8 T cells were isolated from healthy human donors and used in vitro to assess the role of Trio on trans-endothelial migration over in vitro-cultured HUVECs. Results At post-op day 28, both luminal and neovessel endothelial cells were GFP positive indicating successful transfection. CD8 T cell infiltration into the atherosclerotic plaque was reduced in the Trio group (45%, p=0.0426), whilst plaque size and the number of neovessels were unaffected. Mechanistically, we observed that adherence of CD8, but not CD4 T cells to the endothelial monolayer was reduced in vitro upon transfection with Trio-LV. This resulted in a decrease in the absolute number of transmigrated CD8 T cells (56%, p=0.0197), whilst the number of transmigrated CD4 T cells was unaffected. Interestingly, CD8 T cells exhibited no difference trans-/paracellular diapedesis, whilst for CD4 T cells Trio overexpression induced transcellular, rather than paracellular, transmigration. Conclusions LV transfection of vein grafts by local application of a pluronic gel holds promise a therapeutic strategy to improve bypass surgery outcomes. LV transfection with RhoGEF Trio did reduce CD8 T cell transmigration (in vivo and in vitro), but not CD4 T cell transmigration (in vitro) into the atherosclerotic plaque, whilst plaque size was not affected. Ongoing investigations focus on the effect of Trio on micro-vascular leakage as well as infiltration of other immune cells into the plaque.