Browsing by Subject "Scholarly Concentration"
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ItemImplementation of an Annual Education Day to Foster Medical Education Scholarship in a Regional Campus System(2023-04-19) Kochhar, Komal; Soleimani, Leila A; Byrne, Bobbi J; Stefanidis, Dimitrios; Pettit, Katie E; Zakeri, Bita H; Denny, Kim; Brokaw, James J; Wallach, Paul MPurpose/Background The Indiana University School of Medicine (IUSM) employs a large geographically distributed system of medical education comprised of 8 regional medical campuses statewide and the main medical campus in Indianapolis. An inherent challenge of operating such a large multi-campus educational system is being able to provide professional development opportunities for all our medical educators across the state. Design/Methods To address the professional development challenge in a large multi-campus system, our steering committee planned an inaugural “Education Day” in 2020, which attracted proposals of educational innovations and scholarship from across the statewide system. After a peer-review process, the accepted proposals were scheduled for oral and poster presentations, workshops and small groups sessions, and themed sessions. A keynote address was given by a nationally recognized medical educator. The day ended with an awards ceremony for “best” faculty, staff, and student presentations. The Education Days were held in-person on the Indianapolis campus in 2020 and 2022; and it was held virtually in 2021. Outcomes/Results Across the 3 Education Days: ~250 registrants participated each year ~130 proposals were received each year; in 2022, we included an additional 40 proposals from medical students statewide regarding their Scholarly Concentration projects1 80% of the post-event respondents rated Education Day as excellent/very good 87% strongly agreed/agreed (SA/A) they were better able to collaborate with other IUSM medical educators 79% SA/A they were better able to identify best practices in medical education 72% SA/A they were better able to publish educational outcomes data To facilitate statewide dissemination, the presentations were archived in the University’s ScholarWorks Digital Repository.2 Strengths/Limitations IUSM’s Annual Education Day has established itself as a successful venue to share educational best practices and to forge new collaborations. Feasibility/Transferability Although the time and resources required for a successful Education Day are substantial, this event can be replicated elsewhere. ItemMethod Development Involving Modeling Bacterial Metabolite Regulation of Vaginal Epithelial Cell Signaling in Bacterial Vaginosis(2022-04-28) Trinh, Alan; Brubaker, DouglasBACKGROUND Bacterial vaginosis, which is the imbalance of normal vaginal microbiota, contributes to preterm delivery, vaginitis, and decreased drug efficacy. Despite metronidazole efficacy in reducing BV contributing organisms, BV continues to recur in 50% of patients. Previous studies showing imidazole propionate’s role in the pathogenesis of type II diabetes suggest that similar metabolite-regulated pathways in vaginal microbiomes may be the key in pathogenesis of uterine diseases such as BV. Thus, the purpose of this study was to observe the relationship between vaginal metabolites, host or microbiome-derived, and transcriptomic responses in vaginal epithelial tissues stratified by vaginal microbiome composition (“microbiome group”). The hypothesis was that differences in vaginal microbiome composition result in differential regulation of metabolite-host pathway functional relationships. METHODS Transcript levels and metabolite concentrations precollected from 23 East African women were processed and analyzed via R. Transcriptomic data were converted into KEGG pathway enrichment scores via ssGSEA2.0, a package within R. Enrichment scores were correlated (Spearman) with metabolite levels by microbiome group and lactobacillus dominant phenotypes, and relationships were visualized via Heatmap3 and Cytoscape. RESULTS The results showed varying strengths in correlation among metabolites and KEGG pathway enrichment scores after filtering for strong correlations (R > |0.5|) and significance (p< 0.05). Nonlactobacillus dominant microbiomes showed fewer strongly associated metabolite-KEGG pathway relationships compared to the lactobacillus dominant microbiome group, specifically the imidazole-related networks. CONCLUSIONS In this study, variations in significant correlations among metabolites and KEGG pathways suggests that microbiome diversity may contribute to how metabolites regulate host pathways in vaginal epithelial cells. The reduced pathway interactions observed in imidazole compounds suggests that dysregulation may contribute to recurrence of bacterial vaginosis. This method of modelling could be used to characterize the regulation of critical pathways associated with the pathogenesis of bacterial vaginosis. ItemSystems Modeling of Gut Microbiome Regulation of Estrogen Receptor Beta Signaling in Ulcerative Colitis(2023-04-28) Trinh, Alan; Munoz, Javier; Cross, Tzu-Wen; Brubaker, DougIntroduction: The pathogenesis of ulcerative colitis (UC), a chronic inflammatory disorder, involves interactions between gut microbiome dysbiosis, epithelial cell barrier disruption, and immune hyperactivity. Men are 20% more likely to develop UC and 60% more likely to progress to colitis-associated cancer than women. A possible explanation for this may be the anti-inflammatory and epithelial-protective role of estrogen via estrogen receptor beta (ESR2) in the gut. However, extracting insights into how microbiomes regulate host cell signaling is challenged by high-dimensional data integrations across kingdoms and the need to extract interpretable biological information from complex models. To address these challenges and understand microbiome regulation of ESR2 signaling, we developed a partial least squares path modeling (PLS-PM)-inspired microbiome multi-omic modeling framework. Materials and Methods: Gut metabolomic, colorectal transcriptomic, and stool 16S rRNA-seq data from unique UC or non-IBD controls subjects (n=35) were obtained from the Inflammatory Bowel Disease Multi-Omics Database. Single sample gene set enrichment analysis was used to calculate pathway scores for genes up or down-regulated by ESR2 (ESR2UP/ESR2DN respectively).Latent variables (LV) obtained via regularized sparse partial least square regression (sPLSR) mdoels were extracted and used as predictors in two linear regression meta-models with dependent variables of ESR2UP or ESR2DN scores, and independent variables in each model consisting of patient LV scores on metabolites and 16S LVs along with sex and UC status. Significance testing on regression coefficients identified LV interactions synergistically predictive of ER Beta pathway activity. Results and Discussion: The first two LVs from each single-omic sPLSR models were extracted to create terms in the multi-omic meta-model accounting for sex and disease status. The meta-model was predictive of ESR2UP pathway score, implicating UC status (p=0.046), microbiota LV1 (p=0.0006), metabolites LV2 (p=0.045), and interactions of metabolite LV1:microbiota LV1 (p=0.003), microbiota LV1:UC (p=0.0008), and microbiota LV2:sex (p=0.019) in predicting ESR2UP pathway status. For ESR2DN, the 16S model clustered by ESR2DN activity while the metabolomic model clustering was best illustrated by disease status. The ESR2DN meta-model was predictive of ESR2DN pathway activity, implicating main effects of microbiota LV1 (p =0.004), metabolites LV2 (p=0.004), and diagnosis and the interaction effects of metabolites LV1:microbiota LV1 (p=0.005), microbiota LV1:UC (p=0.014), microbiota LV2:sex (p=0.017), and metabolites LV2:UC (p=0.035) in predicting ESR2DN pathway status. Acesulfame, an artificial sweetener, and oxymetazoline, a nasal decongestant, were some of the metabolites predicted by our model to have a differential effect on ESR2 activity based on patient sex. The metabolites predicted in our models are tested in cancer cell lines to understand estrogen regulatory effects on inflammation observed in UC. Method developed in this study can be applied to gain insight regarding regulation of signaling pathways in pathologies not limited to UC. Conclusions: We demonstrate the effectiveness of a PLS-PM based method for modeling relationships between host signaling and microbiome multi-omics data via this investigation of ER Beta activity in UC patients. We quantified significant multi-omic microbiome interactions with disease status and sex that impact ER Beta signaling which may aid in identifying new microbiome-targeted UC therapeutics stratified by sex-specific disease characteristics.