VACE Winners Announced! 5th Annual CCTS "60-second Poster Pitch" Competition
April 2022 (Lexington, KY) - The 17th Annual CCTS Spring Conference was held in conjunction with the College of Dentistry Research Day, College of Nursing Scholarship Showcase, College of Public Health Research Day and the College of Health Sciences Research Day. The Von Allmen Center for Entrepreneurship was excited to be part of the conference, hosting the 5th Annual "60-second Poster Pitch" Competition on April 5th, 2022. These awards were generously sponsored by the Institute for the Study of Free Enterprise in the Gatton College of Business & Economics. Congratulations to the winners!
1st Place - $750
Sydney Gordon | Center for Oral Health Research, University of Kentucky College of Dentistry
Poster Title: "Anti-inflammatory properties of Functionalized Mesoporous Silica Nanoparticles loaded with Quercetin"
New and more efficient drug delivery systems are needed as adjunctive therapy to prevent and treat periodontal disease. Mesoporous silica nanoparticles (MSNPs) are showing great potential in drug delivery to prevent and/or treat disease due to their biocompatibility properties and increased surface area, which allows higher loading amounts and prolonged and sustained delivery of therapeutic compounds. The purpose of our study was to evaluate cytotoxic effect, cellular internalization, and anti-inflammatory properties of MSNPs functionalized with aminopropyl groups and titania (MSNPs-AT) and loaded with quercetin in human oral epithelial cells (OECs). OKF6 cell cultures were exposed to different concentrations of unloaded MSNPs-AT or loaded with quercetin. Cell cytotoxicity was tested by WST-1, MSNPs-AT internalization by OECs and oral epithelium organotypic cultures was evaluated by fluorescence microscopy, and anti-inflammatory properties determined by cytokine production (IL-6, IL-8, GM-CSF) in OKF6 cell supernatants after exposure to Actinomyces naeslundii. Cell viability was not significantly affected by quercetin, unloaded MSNPs-AT, or MSNPs-AT loaded with quercetin. MSNPs-AT loaded with quercetin were successfully internalized by OECs as early as four hours and exhibited better anti-inflammatory effect when compared to quercetin alone (p≤0.01). These findings suggest that MSNPs-AT loaded with quercetin can be efficiently and rapidly internalized by OECs in cell cultures and regulate the production of pro-inflammatory chemokines/cytokines without compromising cell viability. Efficiency of internalization/translocation of similar amounts of MSNPs-AT was lower in stratified oral epithelium. Future studies testing functionalized MSNPs loaded with antibiotics are warranted to test their effect in controlling intracellular bacterial infections of OECs.
2nd Place - $500
Jennifer Castle, MD | Department of Surgery, University of Kentucky and Markey Cancer Center
Poster Title: "Inhibition of de Novo and Salvage Pathways for dNTP Synthesis Enhances Sensitivity to Ionizing Radiation in Pancreatic Neuroendocrine Tumor Cells"
Ionizing radiation is a promising treatment for neuroendocrine tumors (NETs). However, these tumors confer radioresistance via DNA repair, which is dependent on the production of deoxynucleoside triphosphates (dNTPs). We investigated inhibitors of two enzymes in the production of dNTPs as radiosensitizers in NETs. Methods: CellTiter-Glo (Promega) luminescent assay established drug sensitivities of two pancreatic-NET cell-lines (BON and QGP1) for triapine (ribonucleotide reductase inhibitor; RNRi) and three ataxia-telangiectasia-and-rad3- related inhibitors (ATRi: AZD6738, VX-970, and BAY1895344). Synergy models determined synergism of drug combinations with scores greater than zero. Clonogenic assays were performed with sulforhodamine B. Immunoblots were used to assess apoptosis and ATR activation following treatment. Results: BON cells are more sensitive to all agents compared to QGP-1 (BON vs QGP1: triapine 2.8µM vs 6.3µM, AZD6738 0.9µM vs 6.1µM, VX-970 239nM vs 2.4µM, BAY1895344 81nM vs 1.1µM). Loewe synergy models found BAY1895344 and triapine to be synergistic with scores of 9.89 in BON and 15.91 in QGP-1 cells (p-values<0.0001). BAY1895344 is more efficacious when combined with IR in both BON (IC50 : 150nM 0Gy versus 19nM 2Gy) and QGP1 cells (IC50: 277nM 0Gy versus 93nM2Gy). Immunoblot demonstrated greater apoptosis with combination treatments as well as activation of the ATR pathway with IR and triapine and subsequent inhibition with an ATRi. Conclusion: The treatment of GEP-NET cell lines with inhibitors that block dNTP production markedly sensitize these cells to subsequent IR. The combination of IR with an ATRi and an RNRi is a potentially effective treatment modality for NETs.
3rd Place - $250
Samaneh Rabienia Haratbar | University of Kentucky College of Engineering, Department of Biomedical Engineering
Poster Title: "A Machine Learning Approach for the Prediction of Retinopathy of Prematurity (ROP) in Preterm Infants"
Retinopathy of prematurity (ROP) is a leading cause of visual impairment in preterm infants. Predicting ROP plays a vital role in preventing vision loss. The objective of this study is to employ a machine learning algorithm with influencing factors (e.g., gestational age, birth weight, small for gestational age) as inputs to predict ROP. Methods: Data were collected from 230 preterm infants (23 0/7 to 34 6/7 weeks gestation) at the Kentucky Children's Hospital, including 200 infants without ROP and 30 infants with ROP. A logistic regression-based model for predictive analysis was used to predict ROP. Model training was performed using seven independent variables including gestational age, birth weight, small for gestational age, gender, prenatal steroids, cesarean section, and multiple gestation. All analyses were performed using Python program and a data analysis tool of Pandas. The model performance was examined using a metrics including the sensitivity, specificity, area under the receiver operating characteristic curve (ROC), and harmonic mean of the model’s precision (F-score). Results: Our logistic regression model predicts the ROP with the sensitivity of 0.74, specificity of 0.83, area under ROC of 0.86, and F-score of 0.52. Among seven independent variables, gestational age is the most significant factor for ROP prediction, which meets the clinical expectation. Conclusions: With the promising logistic regression model established in this pilot study, we are now adding other influencing factors such as intermittent hypoxemia for better prediction and management of ROP.
Judges Choice Award - $100
Mehrana Mohtasebi | University of Kentucky College of Engineering, Department of Biomedical Engineering
Poster Title: "Noncontact Optical Assessment of Disrupted Cerebral Functional Connectivity in a Piglet Model of Transient Ischemic Stroke"
Perinatal ischemic stroke results from the lack of blood supply to brain tissue, possibly leading to cerebral ischemic/hypoxic stress, neurological disorder, and brain network impairment. Preterm infants with ischemic stroke are prone to alterations in cerebral blood flow (CBF) and associated spontaneous low-frequency oscillations (LFOs). However, there are no established noninvasive imaging methods for continuous monitoring of CBF alterations at the bedside in neonatal intensive care units (NICUs). An innovative camera-based speckle contrast diffuse correlation tomography (scDCT) technology has been recently developed in our laboratory, which enables noncontact, noninvasive, and high-density 3D imaging of CBF distributions in cerebral cortex. In the present study, the capability of scDCT technique for 3D imaging of CBF distributions in a neonatal piglet model of transient ischemic stroke was demonstrated. Moreover, power spectral density analyses of LFOs and the network connections over the brain were assessed before and after the induction of acute ischemic stroke. The stroke resulted in a substantial decrease in CBF, attenuations in resting-state LFOs over the LFO frequency band (0.01–0.08 Hz), and functional connectivity disruptions in motor and somatosensory cortices. This pilot study demonstrated the feasibility and safety of scDCT for noninvasive detection of resting-state LFO alteration and functional connectivity disruption after stroke. We are currently testing this fully noncontact scDCT technology for 3D imaging of brain hemodynamics in the NICU, with the ultimate goal of instantly evaluating and managing brain injury/health to improve the clinical decision and outcome.
