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Development of Computational Models and Platforms for Multicellular Development and Preclinical Therapeutic Screening.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Development of Computational Models and Platforms for Multicellular Development and Preclinical Therapeutic Screening./
作者:	Huizar, Francisco J.
面頁冊數:	1 online resource (419 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-08, Section: B.
Contained By:	Dissertations Abstracts International84-08B.
標題:	Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30000308click for full text (PQDT)
ISBN:	9798368438818

Development of Computational Models and Platforms for Multicellular Development and Preclinical Therapeutic Screening.
Huizar, Francisco J.

Development of Computational Models and Platforms for Multicellular Development and Preclinical Therapeutic Screening. - 1 online resource (419 pages)

Source: Dissertations Abstracts International, Volume: 84-08, Section: B.

Thesis (Ph.D.)--University of Notre Dame, 2023.

Includes bibliographical references

With the emanation of big data, there is an ever-increasing need for advanced quantitative, computational, and statistical approaches to comprehensively study biology. From dynamical models, data processing, high-throughput screening, to high-dimensional data analysis, computational tools and pipelines are revolutionizing the landscape of biological research and medicine. However, there are still many challenges associated with harnessing the data revolution in computational biology. More specifically, efforts to develop computational, simulation-based models of multicellular development and high-throughput preclinical therapeutic screening assays are broadly needed to provide insight into novel treatment approaches in modern medicine.The work herein describes the development of experimental platforms, modeling tools, and statistical approaches to expand upon and drive novel discoveries in multicellular models of organ formation and preclinical therapeutic development. This dissertation builds upon the existing resources available to study crosstalk in developmental biology, identify therapeutic targets of interest, and evaluate efficacy of novel small molecule therapeutics. In this dissertation, Drosophila melanogaster is used as a model organism to develop computational and high-throughput screening platforms to advance the state-of-the-art in each field.Chapter 1 reviews combined experimental and computational efforts to piece together physiological aspects of pattern formation in developmental biology. Colleagues and I stress the need for increased quantitative, dynamical, and systems-based studies to gain a deeper understanding of morphogenetic processes in multicellular development and disease. Attempting to address several of the outstanding questions posed in Chapter 1, a quantitative image-analysis pipeline for decoding organ-level calcium (Ca2+) signaling (Chapter 2) and a mechanistic model that links Ca2+ signaling to emergent spatiotemporal classes of signaling dynamics (Chapter 3) were developed. A fluorescent Ca2+ sensor, GCaMP6f was used in developing Drosophila wing discs to experimentally demonstrate that spatially patterned Ca2+ signal dynamics correlate with differential growth. Through power transformations and regression techniques, we discovered that integrated Ca2+ signaling contains a power-law scaling relationship with tissue size. We observed four unique classes of Ca2+ signatures both ex vivo and in vivo during third instar wing disc development: 1) single cell Ca2+ spikes, 2) intercellular Ca2+ transients, 3) intercellular Ca2+ waves, and 4) a global fluttering pattern. A mechanistic computational model was developed to recapitulate the experimental findings and to define key conditions that reproduce the observed Ca2+ signatures. Based on in silico simulations and experimental validation, we propose the existence of two subpopulations of cells within developing tissues that are connected through gap junction communication. The characteristics of "initiator cells" that induce Ca2+ signals and "standby cells" that propagate Ca2+ signals dictate classes of Ca2+ signatures observed in silico. Together, the analysis pipeline and mechanistic model of Ca2+ signaling enabled elucidation on how Ca2+ signaling dynamics integrate upstream input to mediate multiple response outputs in developing organs.Nuclear factors of activated T-cells (NFATs) are a family of Ca2+-dependent transcription factors that play critical roles in transcription of genes regulating morphogenesis and development. NFATc1, a promoter of cell proliferation and migration, is established as a regulator of vertebrate development. A serine/threonine protein kinase, DYRK1A, regulates nuclear occupancy of NFATc1 in cells, wherein DYRK1A phosphorylated NFATc1 is exported from the cell nucleus. The rate at which NFATc1 is exported enables discrimination between brief and sustained Ca2+ signals. Therefore, DYRK1A dysregulation may disrupt Ca2+-induced transcription of genes crucial for development. In Chapter 4, we explore the role of DYRK1A overexpression as a neurodegenerative and cancer-related therapeutic target. A combination of in vitro, in vivo, and in silico approaches were used to identify three new classes of N-heterocyclic inhibitors of DYRK1A. In silico molecular modeling simulations were performed to inspire the generation of a library of potential small molecule inhibitors of DYRK1A. A high-throughput therapeutic efficacy platform was then designed and implemented using Drosophila, that substantiated lead candidates identified in an in vitro screening. Standardized mean differences of inhibitor-fed Drosophila overexpressing the DYRK1A homolog, minibrain, were compared to a wildtype group that were fed DYRK1A inhibitors. Cohen's d statistic and pooled standard deviations demonstrated that even the most potent DYRK1A inhibitor identified was not exceedingly detrimental to the wildtype group, while still favorably rescuing minibrain overexpression phenotypes. The resulting in vivo to in vitro correspondence of the findings validate the synthesized architectural motifs as lead candidates for further evaluation and optimization as safe and effective DYRK1A inhibitors. Although discovery of the novel DYRK1A inhibitor classes is promising, the study relied heavily on a single metric of analysis for in vivo evaluation of the DYRK1A inhibitors: total area of the Drosophila melanogaster wing.To overcome this limitation for future studies and. (Abstract shortened by ProQuest).

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798368438818Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Computational modelIndex Terms--Genre/Form:

542853
Electronic books.

Development of Computational Models and Platforms for Multicellular Development and Preclinical Therapeutic Screening.
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This dissertation builds upon the existing resources available to study crosstalk in developmental biology, identify therapeutic targets of interest, and evaluate efficacy of novel small molecule therapeutics. In this dissertation, Drosophila melanogaster is used as a model organism to develop computational and high-throughput screening platforms to advance the state-of-the-art in each field.Chapter 1 reviews combined experimental and computational efforts to piece together physiological aspects of pattern formation in developmental biology. Colleagues and I stress the need for increased quantitative, dynamical, and systems-based studies to gain a deeper understanding of morphogenetic processes in multicellular development and disease. Attempting to address several of the outstanding questions posed in Chapter 1, a quantitative image-analysis pipeline for decoding organ-level calcium (Ca2+) signaling (Chapter 2) and a mechanistic model that links Ca2+ signaling to emergent spatiotemporal classes of signaling dynamics (Chapter 3) were developed. A fluorescent Ca2+ sensor, GCaMP6f was used in developing Drosophila wing discs to experimentally demonstrate that spatially patterned Ca2+ signal dynamics correlate with differential growth. Through power transformations and regression techniques, we discovered that integrated Ca2+ signaling contains a power-law scaling relationship with tissue size. We observed four unique classes of Ca2+ signatures both ex vivo and in vivo during third instar wing disc development: 1) single cell Ca2+ spikes, 2) intercellular Ca2+ transients, 3) intercellular Ca2+ waves, and 4) a global fluttering pattern. A mechanistic computational model was developed to recapitulate the experimental findings and to define key conditions that reproduce the observed Ca2+ signatures. Based on in silico simulations and experimental validation, we propose the existence of two subpopulations of cells within developing tissues that are connected through gap junction communication. The characteristics of "initiator cells" that induce Ca2+ signals and "standby cells" that propagate Ca2+ signals dictate classes of Ca2+ signatures observed in silico. Together, the analysis pipeline and mechanistic model of Ca2+ signaling enabled elucidation on how Ca2+ signaling dynamics integrate upstream input to mediate multiple response outputs in developing organs.Nuclear factors of activated T-cells (NFATs) are a family of Ca2+-dependent transcription factors that play critical roles in transcription of genes regulating morphogenesis and development. NFATc1, a promoter of cell proliferation and migration, is established as a regulator of vertebrate development. A serine/threonine protein kinase, DYRK1A, regulates nuclear occupancy of NFATc1 in cells, wherein DYRK1A phosphorylated NFATc1 is exported from the cell nucleus. The rate at which NFATc1 is exported enables discrimination between brief and sustained Ca2+ signals. Therefore, DYRK1A dysregulation may disrupt Ca2+-induced transcription of genes crucial for development. In Chapter 4, we explore the role of DYRK1A overexpression as a neurodegenerative and cancer-related therapeutic target. A combination of in vitro, in vivo, and in silico approaches were used to identify three new classes of N-heterocyclic inhibitors of DYRK1A. In silico molecular modeling simulations were performed to inspire the generation of a library of potential small molecule inhibitors of DYRK1A. A high-throughput therapeutic efficacy platform was then designed and implemented using Drosophila, that substantiated lead candidates identified in an in vitro screening. Standardized mean differences of inhibitor-fed Drosophila overexpressing the DYRK1A homolog, minibrain, were compared to a wildtype group that were fed DYRK1A inhibitors. Cohen's d statistic and pooled standard deviations demonstrated that even the most potent DYRK1A inhibitor identified was not exceedingly detrimental to the wildtype group, while still favorably rescuing minibrain overexpression phenotypes. The resulting in vivo to in vitro correspondence of the findings validate the synthesized architectural motifs as lead candidates for further evaluation and optimization as safe and effective DYRK1A inhibitors. Although discovery of the novel DYRK1A inhibitor classes is promising, the study relied heavily on a single metric of analysis for in vivo evaluation of the DYRK1A inhibitors: total area of the Drosophila melanogaster wing.To overcome this limitation for future studies and. (Abstract shortened by ProQuest).
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