2023

2023 ISEF Finalists from CKRSEF

Please note that some of these finalists qualified to ISEF from the KY State Science Fair

MATH028 - Hereditary Atomicity and ACCPThe relationship between atomicity and ACCP, two properties measuring the way elements factor in integral domains, is central to abstract factorization theory. It is known that all integral domains satisfying ACCP are atomic and that the converse does not hold, but this connection is not fully understood, and few examples of atomic integral domains not satisfying ACCP have been found. Two related properties, hereditary atomicity and hereditary ACCP, were recently introduced with the aim of better understanding this complex relationship, and it is conjectured that they are equivalent. In this project, hereditary atomicity and hereditary ACCP were investigated further for specific classes of integral domains and in the more general context of monoids. The conjecture that hereditary atomicity and hereditary ACCP are equivalent was proved for torsion-free monoids and certain types of integral domains with polynomial-like structure. These results establish the validity of the conjecture for several important classes of monoids and integral domains and provide methods for approaching the general case.

BCHM019 - Cathepsin B Links Exercise and Stroke RecoveryIn the United States, a stroke occurs every 40 seconds. 60% of strokes will occur in females and 87% will be ischemic strokes. One modifiable risk factor for stroke severity, and subsequently stroke recovery, is exercise. Consistent exercise prior to stroke onset (i.e. exercise preconditioning), has been shown to reduce stroke severity; however, the mechanisms mediating this positive effect are largely unknown. Cathepsin B (CTSB) is a cysteine protease that increases in the blood with exercise and can cross the blood brain barrier. It plays a role in extracellular matrix remodeling and maintenance and derives the neuroprotective and pro-angiogenic protein Lg3 from its pro-peptide perlecan. This study uses brain samples from sedentary and exercise preconditioned ischemic stroke-induced female CTSB knockout mice (mice that cannot produce CTSB) to investigate if CTSB is necessary for exercise preconditioning to reduce stroke severity. Histology was performed to measure infarct volumes and capillary density. Capillary density data analysis is in progress, but no significant difference in infarct volumes was found between the sedentary and exercise CTSB knockout mouse cohorts, supporting the idea that CTSB mediates exercise preconditioning’s neuroprotective role in stroke. This adds a positive dimension to this protein’s role in disease, as prior research found CTSB to be harmful in epilepsy, increasing epileptic episode severity, and help mediate COVID-19 infection by cleaving the SARS-CoV-2 spike protein.

CBIO036 - Gene Signatures for Drug Resistant EpilepsyOne in twenty-six people worldwide develops epilepsy during their lifetime, including myself. Around 30% of epilepsy patients are nonresponsive to medication. It is important to identify these patients using less invasive and low-cost methods. This study aims to use gene expression profiles derived from blood cells to identify potential gene signatures to predict drug response in epilepsy patients. To determine whether expression profile changes in blood samples can reflect epilepsy pathogenesis, a weighted gene coexpression network analysis (WGCNA) was performed using samples from drug-naive epilepsy patients and healthy controls. A differentially expressed network was identified through this analysis, suggesting a link between epileptogenesis and gene expression in blood samples. Patients with epilepsy were grouped based on 3 medications: Carbamazepine, Valproate, and Phenytoin. Responders and non-responders were compared with each other, establishing a list of differentially expressed genes. The lists were also analyzed with pathway enrichment and gene ontology analyses. Pathways enriched in all three drug groups were identified. Gene ontology analysis identified Regulation of Response to Biotic Stimulus as commonly enriched across all 3 gene lists. It has been reported that ‘Regulation of Response to Biotic Stimulus’ was related to the immune system. This result suggests an association between drug-resistant epilepsy and the immune system. In conclusion, multiple differentially expressed genes, pathways, and ontologies were identified from the expression profiles derived from blood samples of epilepsy patients. These gene signatures have the potential to be utilized as a biomarker to predict drug response in epilepsy patients.

TMED034 - MicroRNA Classification of Tumor BiopsiesWith respect to evaluating biopsies for cancer diagnosis, a pressing yet often sidelined issue is that of anatomical pathology errors. Due to the image-based nature of biopsy examinations and the variation between cell appearances, the current process for verifying and diagnosing cancers has been characterized with a high level of inconsistencies between clinical opinions, and at times, incorrect diagnosis. In a substantial number of these cases, pathological errors have resulted in detriments to patient treatment outcomes. As such, this project sought to develop an efficient and robust molecular framework to evaluate biopsies in a way that is safeguarded against pathological mistakes caused by human error. Specifically, dimensional compression by denoising autoencoder (DAE) neural networks and tree-based ensemble classification via XG-Boost, were utilized to both learn the key microRNA features of each neoplasm, and then classify the tumors based on the molecular features. microRNAs were selected as the target molecule due to their short length and role in regulating cell growth and differentiation. Classification between all neoplasms demonstrated an overall accuracy of 94.01%, and the binary classifications between tumorous cells and normal cells was highly discriminant, with many neoplasm types correctly classified at close to 100%. The high sensitivity between all neoplasms, and more importantly, between normal and neoplastic cells based on their miRNA profile presents a promising verification method for biopsies. If applied in a clinical setting, this computational-molecular framework has the potential to serve as a cost-effective baseline for biopsy purity and validation for pathologists, improving patient treatment outcomes.

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