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Molecular Mechanisms Of Opioid Use Disorder In Human Brain Models, Emily Mendez 2024 The Texas Medical Center Library

Molecular Mechanisms Of Opioid Use Disorder In Human Brain Models, Emily Mendez

Dissertations & Theses (Open Access)

Opioid use disorder (OUD) is a national and global public health crisis with no end in sight. While studies from animal models hint at widespread epigenetic and transcriptomic alterations of opioid drugs, the molecular consequences of long-term exposure to opioid drugs in human brain is still unclear, and human-centered translational models are necessary to discern the human cell type-specific effects of OUD.

Using postmortem brain Brodmann area 9 (BA9) from the UTHealth Brain Collection for Research on Psychiatric Disorders, I identified angiogenic gene networks perturbed in the RNA and protein of OUD subjects, as well as downregulation of many neuron-correlated …


Integrative Genomic Insights Into Coral Resilience: Adaptive And Acclimatory Responses To Seasonal Environmental Shifts, Tasnim Ghanim 2024 American University in Cairo

Integrative Genomic Insights Into Coral Resilience: Adaptive And Acclimatory Responses To Seasonal Environmental Shifts, Tasnim Ghanim

Theses and Dissertations

Coral reefs, critical to marine biodiversity and coastal protection, face escalating threats from climate change-related phenomena such as ocean warming. This warming is leading to widespread thermal stress that contributes to coral bleaching and infectious disease in corals, leading to the disruption of marine ecosystems and the economies that depend on them. Focusing on the brain coral Platygyra daedalea, known for its thermal resilience in the Persian Arabian Gulf—a region that exemplifies the extreme stressors of climate change—our study aims to dissect the genetic, transcriptomic, and microbiological underpinnings of coral survival in high-temperature environments predicted for the end of …


Investigating The Phytochemicals In Sargassum (Brown Algae) Against The Therapeutic Targets Of Oral Squamous Cell Carcinoma Metastasized From Breast: An Approach, MAHEMA S 2024 Roseman University of Health Sciences

Investigating The Phytochemicals In Sargassum (Brown Algae) Against The Therapeutic Targets Of Oral Squamous Cell Carcinoma Metastasized From Breast: An Approach, Mahema S

Annual Research Symposium

ABSTRACT:

Purpose: Oral metastases are relatively rare. In women, the most common oral metastases originate from breast cancer, the most diagnosed malignancy, and the second leading cause of death. Sargassum is a genus of brown algae which exhibits its natural therapeutic potential with anticancer properties. This study aimed to identify a therapeutic target for OSCC metastasized from breast cancer through network pharmacology and to evaluate potent phytochemicals against the identified target.

Methods: DEGs associated with OSCC and breast cancer were obtained from the Gene Expression Omnibus. The upregulated DEGs were then intersected to identify common targets between OSCC and BC. …


Interplay Of Periodontal Bacterial Metabolites In The Progression Of Coronary Artery Disease: A System Biological Approach, Janakiraman V 2024 Roseman University of Health Sciences

Interplay Of Periodontal Bacterial Metabolites In The Progression Of Coronary Artery Disease: A System Biological Approach, Janakiraman V

Annual Research Symposium

Purpose:

The purpose of this study is to investigate the intricate relationship between periodontal disease (PD) and coronary artery disease (CAD), as evidenced by epidemiological associations. Metalloproteinase inhibitor (TIMP1) plays a pivotal role in cellular signaling, differentiation, cell death, and migration by binding to target metalloproteinases, forming complexes with other molecules (collagenases) to inactivate them. However, the expression of TIMP1 is reduced in both PD and CAD, leading to an upregulation of other metalloproteinases. This research explores the hypothesis that metabolites released from (Porphyromonas gingivalis), a prevalent bacterium in atherosclerotic patients, may inhibit TIMP1, thereby influencing CAD progression. …


A Reliable Diabetic Retinopathy Grading Via Transfer Learning And Ensemble Learning With Quadratic Weighted Kappa Metric, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei 2024 College of Saint Benedict/Saint John's University

A Reliable Diabetic Retinopathy Grading Via Transfer Learning And Ensemble Learning With Quadratic Weighted Kappa Metric, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei

Computer Science Faculty Publications

The most common eye infection in people with diabetes is diabetic retinopathy (DR). It might cause blurred vision or even total blindness. Therefore, it is essential to promote early detection to prevent or alleviate the impact of DR. However, due to the possibility that symptoms may not be noticeable in the early stages of DR, it is difficult for doctors to identify them. Therefore, numerous predictive models based on machine learning (ML) and deep learning (DL) have been developed to determine all stages of DR. However, existing DR classification models cannot classify every DR stage or use a computationally heavy …


Protein-Protein Interactions In Cell Cycle Proteins: An In Silico Investigation Of Two Important Players, Andriele Eichner 2024 The Graduate Center, City University of New York

Protein-Protein Interactions In Cell Cycle Proteins: An In Silico Investigation Of Two Important Players, Andriele Eichner

Dissertations, Theses, and Capstone Projects

The examination of the cell cycle carries significant implications for the biology, health, and overall existence of all living things. These implications span from the development and growth of these organisms to the aging process and cancer, as well as the potential of stem cell therapies to repair diseases and injuries. Numerous proteins of the cell cycle are essential for cellular division and proliferation and are widely conserved over the course of evolution. In this work, we aimed to investigate the molecular processes of protein-protein interactions in cell cycle proteins, centering on two key players: Cdc6 in budding yeast and …


Toward Improved Global Food Security: Uncovering How Tomatoes Fight Root-Knot Nematodes, Chingyan H. Huang 2024 Purdue University

Toward Improved Global Food Security: Uncovering How Tomatoes Fight Root-Knot Nematodes, Chingyan H. Huang

The Journal of Purdue Undergraduate Research

No abstract provided.


Exploring The Evolution Of Callose Synthase In Green Plants, Giovanna Durante 2024 Purdue University

Exploring The Evolution Of Callose Synthase In Green Plants, Giovanna Durante

The Journal of Purdue Undergraduate Research

No abstract provided.


Elastin-Like Polypeptide As A Model To Study Intrinsically Disordered Proteins, Sadegh Majdi 2024 Rowan University

Elastin-Like Polypeptide As A Model To Study Intrinsically Disordered Proteins, Sadegh Majdi

Theses and Dissertations

The elastin-like polypeptide (ELP) is a well-studied structural protein that is easily amenable to amino acid (AA) sequence modifications and has the potential to yield a wide variety of uses in bioengineering and biomedical applications. One unique property of ELP is the inclusion of intrinsically disordered domains (IDP) within the structure that allow for its diversity of physical properties. While it is generally understood that amino acid sequence dictates protein folding arrangements, the contributions of specific amino acid sequences to the intrinsic disorder of ELP has yet to be fully resolved. Therefore, identifying the contributions of specific amino acid sequences …


A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin LI, Hanchao YU 2024 Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China

A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin Li, Hanchao Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of biotechnology and information technology has brought life sciences into a new era of data explosion. The traditional life science research paradigm struggles to reveal the fundamental rules of complex biological systems from rapidly growing biological big data. As artificial intelligence continues to achieve disruptive breakthroughs in life science, a new paradigm driven by AI is emerging. This study delves into typical examples of life science research driven by AI, proposes the concept and key elements of the new life science research paradigm, elaborates on the cutting-edge of life science research under this new paradigm, and discusses …


Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas 2024 University of Kentucky

Molecular Understanding And Design Of Deep Eutectic Solvents And Proteins Using Computer Simulations And Machine Learning, Usman Lame Abbas

Theses and Dissertations--Chemical and Materials Engineering

Hydrophobic deep eutectic solvents (DESs) have emerged as excellent extractants. A major challenge is the lack of an efficient tool to discover DES candidates. Currently, the search relies heavily on the researchers’ intuition or a trial-and-error process, which leads to a low success rate or bypassing of promising candidates. DES performance depends on the heterogeneous hydrogen bond environment formed by multiple hydrogen bond donors and acceptors. Understanding this heterogeneous hydrogen bond environment can help develop principles for designing high performance DESs for extraction and other separation applications. This work investigates the structure and dynamics of hydrogen bonds in hydrophobic DESs …


Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman 2024 Virginia Commonwealth University

Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman

Undergraduate Research Posters

Early intervention in Alzheimer's is vital for treatment. The earlier a professional can detect symptoms and make a diagnosis the earlier a prognosis can be implemented. With the prevalence of data in our day-to-day world combined with Artificial intelligence (AI), utilizing both for machine learning can pave the way for more accurate and efficient detection of Alzheimer's and other neurodegenerative diseases. AI combined with Machine learning (ML) increases diagnostic efficiency and reduces human errors, making it a valuable resource for physicians and clinicians alike. With the increasing amount of data processing and image interpretation required, the ability to use AI …


Model-Based Deep Autoencoders For Clustering Single-Cell Rna Sequencing Data With Side Information, Xiang Lin 2023 New Jersey Institute of Technology

Model-Based Deep Autoencoders For Clustering Single-Cell Rna Sequencing Data With Side Information, Xiang Lin

Dissertations

Clustering analysis has been conducted extensively in single-cell RNA sequencing (scRNA-seq) studies. scRNA-seq can profile tens of thousands of genes' activities within a single cell. Thousands or tens of thousands of cells can be captured simultaneously in a typical scRNA-seq experiment. Biologists would like to cluster these cells for exploring and elucidating cell types or subtypes. Numerous methods have been designed for clustering scRNA-seq data. Yet, single-cell technologies develop so fast in the past few years that those existing methods do not catch up with these rapid changes and fail to fully fulfil their potential. For instance, besides profiling transcription …


Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia 2023 Brigham Young University

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …


A Computational Exploration: Docking Analysis Of Compounds From Foeniculum Vulgare As Potential Aromatase Inhibitors For Endometriosis Candidate Therapy, Dwi Anita Suryandari, Puji Sari, Hadi Sunaryo, Khaerunissa Anbar Istiadi 2023 Department of Biology, Faculty of Medicine, Universitas Indonesia, Indonesia

A Computational Exploration: Docking Analysis Of Compounds From Foeniculum Vulgare As Potential Aromatase Inhibitors For Endometriosis Candidate Therapy, Dwi Anita Suryandari, Puji Sari, Hadi Sunaryo, Khaerunissa Anbar Istiadi

Indonesian Journal of Medical Chemistry and Bioinformatics

Aromatase inhibitors (AI) have controlling symptoms and size of endometriotic implants, making them a promising second-line therapy for endometriosis treatment.pretreatment with letrozole, an AI, combined with leuprolide acetate and resveratrol has been found to improve in vitro fertilization (IVF) outcomes in women mild endometriosis.in this study we screening and analysis of ten phenolic compounds from Foeniculum vulgare using molecular docking with Mcole server.from this results showed that three phenolic trans resveratrol (TR), caempherol coumaril (CC) have low gibbs energy compare with resveratrol (R). The binding modalities of compound TR and compound R were hydrogen-bonding between the hydroxyl and oxygen atom …


Dna Methylation-Based Epigenetic Biomarkers In Cell-Type Deconvolution And Tumor Tissue Of Origin Identification, Ze Zhang 2023 Dartmouth College

Dna Methylation-Based Epigenetic Biomarkers In Cell-Type Deconvolution And Tumor Tissue Of Origin Identification, Ze Zhang

Dartmouth College Ph.D Dissertations

DNA methylation is an epigenetic modification that regulates gene expression and is essential to establishing and preserving cellular identity. Genome-wide DNA methylation arrays provide a standardized and cost-effective approach to measuring DNA methylation. When combined with a cell-type reference library, DNA methylation measures allow the assessment of underlying cell-type proportions in heterogeneous mixtures. This approach, known as DNA methylation deconvolution or methylation cytometry, offers a standardized and cost-effective method for evaluating cell-type proportions. While this approach has succeeded in discerning cell types in various human tissues like blood, brain, tumors, skin, breast, and buccal swabs, the existing methods have major …


Using In Silico Tools To Analyze The 5ʹ Untranslated Regions Of The Alcohol Dehydrogenase Gene From Arabidopsis Thaliana And Omega Sequence, Reza Mohammadhassan, Tina Asadishad 2023 Plant Science Department, Amino Techno Gene Private Virtual Institute, Tehran 1495845983, Iran

Using In Silico Tools To Analyze The 5ʹ Untranslated Regions Of The Alcohol Dehydrogenase Gene From Arabidopsis Thaliana And Omega Sequence, Reza Mohammadhassan, Tina Asadishad

Makara Journal of Science

The 5ʹ ends of protein-encoding genes contain 5ʹ untranslated regions (5ʹUTRs), which can effectively participate in regulating gene expression. The 5ʹUTRs of Arabidospis thaliana–derived alcohol dehydrogenase gene (AtADH) and omega (Ω) sequence from tobacco mosaic virus (TMV) are the most effective enhancers in biotechnology. In this study, bioinformatics techniques were employed to analyze the characteristics of the above sequences. After 5ʹUTR sequence collection, the inner ribosome entrance sites; small RNA (sRNA) target sequences; nucleotide contents; and upstream start and stop codons, ORFs, and coding DNA sequences of the Ω sequence and AtADH 5ʹUTR were identified. Moreover, the …


Investigating The Impact Of Transcription On Mutation Rates, Sarah Patterson 2023 Mississippi State University

Investigating The Impact Of Transcription On Mutation Rates, Sarah Patterson

Theses and Dissertations

tRNA genes are highly transcribed and perform one of the most fundamental cellular functions. Although a universal pattern observed across all three domains of life is that highly transcribed genes tend to evolve slowly, tRNA genes have been shown previously to evolve rapidly. This rapid sequence evolution could result from relaxed selection, increased mutation rate, or a combination of both. Here, we use mutation-accumulation line sequencing data to show that tRNA genes accumulate more mutations than other gene types. Our results indicate that this elevated mutation rate is a consequence of both elevated transcription-associated mutagenesis and a lack of transcription-coupled …


Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone 2023 University of Nebraska-Lincoln

Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2024–

The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …


Determining The Effects Of Glycocalyx Modifications On The Electrophysical Properties Of Human Mesenchymal Stem Cells, Rominna E. Valentine Ico 2023 California State University - San Bernardino

Determining The Effects Of Glycocalyx Modifications On The Electrophysical Properties Of Human Mesenchymal Stem Cells, Rominna E. Valentine Ico

Electronic Theses, Projects, and Dissertations

Human mesenchymal stem cells (hMSCs) have gained popularity in clinical trials due to their multipotent differentiation characteristics, ability to secrete bioactive molecules, migrate into diseased or damaged tissues, and their immunosuppressive properties. HMSC cultures are heterogeneous, containing stem cells, partially differentiated progenitor cells, and fully differentiated cells. One of the major challenges with hMSCs therapeutic potential is the inability to select specific cell subpopulations due to an insufficient number of biomarkers. Often the biomarkers used, like those for fluorescence-activated cell sorting, are not sufficient to define hMSCs because they overlap with other cell types. Consequently, there is a need to …


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