Browsing by Author "Tischbein, Maeve"

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    Abnormal mineralization of the Ts65Dn Down syndrome mouse appendicular skeleton begins during embryonic development in a Dyrk1a-independent manner
    (Elsevier, 2015-05) Blazek, Joshua D.; Malik, Ahmed M.; Tischbein, Maeve; Arbones, Maria L.; Moore, Clara S.; Roper, Randall J.; Biology, School of Science
    The relationship between gene dosage imbalance and phenotypes associated with Trisomy 21, including the etiology of abnormal bone phenotypes linked to Down syndrome (DS), is not well understood. The Ts65Dn mouse model for DS exhibits appendicular skeletal defects during adolescence and adulthood but the developmental and genetic origin of these phenotypes remains unclear. It is hypothesized that the postnatal Ts65Dn skeletal phenotype originates during embryonic development and results from an increased Dyrk1a gene copy number, a gene hypothesized to play a critical role in many DS phenotypes. Ts65Dn embryos exhibit a lower percent bone volume in the E17.5 femur when compared to euploid embryos. Concomitant with gene copy number, qPCR analysis revealed a  ~1.5 fold increase in Dyrk1a transcript levels in the Ts65Dn E17.5 embryonic femur as compared to euploid. Returning Dyrk1a copy number to euploid levels in Ts65Dn, Dyrk1a+/− embryos did not correct the trisomic skeletal phenotype but did return Dyrk1a gene transcript levels to normal. The size and protein expression patterns of the cartilage template during embryonic bone development appear to be unaffected at E14.5 and E17.5 in trisomic embryos. Taken together, these data suggest that the dosage imbalance of genes other than Dyrk1a is involved in the development of the prenatal bone phenotype in Ts65Dn embryos.
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    Leveraging artificial intelligence to summarize abstracts in lay language for increasing research accessibility and transparency
    (Oxford University Press, 2024) Shyr, Cathy; Grout, Randall W.; Kennedy, Nan; Akdas, Yasemin; Tischbein, Maeve; Milford, Joshua; Tan, Jason; Quarles, Kaysi; Edwards, Terri L.; Novak, Laurie L.; White, Jules; Wilkins, Consuelo H.; Harris, Paul A.; Pediatrics, School of Medicine
    Objective: Returning aggregate study results is an important ethical responsibility to promote trust and inform decision making, but the practice of providing results to a lay audience is not widely adopted. Barriers include significant cost and time required to develop lay summaries and scarce infrastructure necessary for returning them to the public. Our study aims to generate, evaluate, and implement ChatGPT 4 lay summaries of scientific abstracts on a national clinical study recruitment platform, ResearchMatch, to facilitate timely and cost-effective return of study results at scale. Materials and methods: We engineered prompts to summarize abstracts at a literacy level accessible to the public, prioritizing succinctness, clarity, and practical relevance. Researchers and volunteers assessed ChatGPT-generated lay summaries across five dimensions: accuracy, relevance, accessibility, transparency, and harmfulness. We used precision analysis and adaptive random sampling to determine the optimal number of summaries for evaluation, ensuring high statistical precision. Results: ChatGPT achieved 95.9% (95% CI, 92.1-97.9) accuracy and 96.2% (92.4-98.1) relevance across 192 summary sentences from 33 abstracts based on researcher review. 85.3% (69.9-93.6) of 34 volunteers perceived ChatGPT-generated summaries as more accessible and 73.5% (56.9-85.4) more transparent than the original abstract. None of the summaries were deemed harmful. We expanded ResearchMatch's technical infrastructure to automatically generate and display lay summaries for over 750 published studies that resulted from the platform's recruitment mechanism. Discussion and conclusion: Implementing AI-generated lay summaries on ResearchMatch demonstrates the potential of a scalable framework generalizable to broader platforms for enhancing research accessibility and transparency.