Medicine and Health Sciences Commons^™

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Precise Method To Identify Kinase Drug Targets In Complex Diseases: The First Step Towards Sustainable And Effective Treatment, Hasbanny Irisson, Marzieh Ayati

Research Symposium

Background: Kinases are enzymes that have proven to be important drug targets due to their role in critical biological mechanisms such as phosphorylation. Phosphorylation happens when a kinase catalyzes the transfer of a phosphate group to a protein in a phosphorylated site, which then becomes known as the substrate of the kinase. Any dysregulation of protein phosphorylation causes a wide range of complex diseases including cancer. Thus, discovering the links between kinases and their substrates (i.e. predicting kinase-substrate associations (KSAs)) is crucial in developing effective and sustainable treatments. Presently, less than 5% of phosphorylated sites have an associated kinase, and …

An Ngqd Based Diagnostic Tool For Pancreatic Cancer, Ryan Ketan Ajgaonkar, Bong Lee, Alina Valimukhametova, Anton Naumov, Giridhar Akkaraju

Research Symposium

Background: Pancreatic cancer remains difficult to detect at early stages which contributes to a poor five-yearsurvival rate. Therefore, early detection approaches based on novel technologies should be explored to address this critical health issue. Nanomaterials have recently emerged as frontrunners for diagnostic applications due to their small size in the 1-100 nm range, which facilitates one-on-one interactions with a variety of biomolecules like oligonucleotides and makes them suitable for a plethora of detection and delivery applications. In this work, the presence of specific pancreatic cancer miRNA (pre-miR-132) is detected utilizing the fluorescence properties of highly biocompatible nitrogen-doped graphene quantum dots …

Photodynamic Therapy Agents: The Power Of Mjöllnir To Eradicate Cancer, Sidney M. Hopper

Honors College Theses

After its discovery back in the 1900s, photosensitizers became a critical study for potential treatments and cures for medical issues, including cancer. It was discovered that porphyrins appeared to target and accumulate in proliferating cells, and to reach the cells, a certain wavelength of light with maximum absorbance associated with the porphyrin was necessary to achieve cell death. Photodynamic therapy involves making use of porphyrins or metalloporphyrins as activators when exposed to such light. When activated, these compounds generate reactive oxygen species (ROS), such as HO- or O2-, which can react with nucleic acids found in DNA and RNA. In …

The Discovery And Characterization Of Novel Potent 5-Substituted 3, 3’, 4’, 7-Tetramethoxyflavonoid Dna Triplex Specific Binding Ligands, Vanessa Marie Rangel

University of the Pacific Theses and Dissertations

Chemotherapy works by killing fast dividing cells. Unfortunately, these drugs are not specific to cancer tissue and can damage normal cells. Chemotherapy is like taking poison and hoping it kills the cancer cells before it kills you. As an alternative, many researchers have investigated the use of antigene therapy to selectively target cancer causing genes to avoid off target effects. Although promising, the theory is limited by the stability of the triplex structure. Here, we report the discovery of potent triplex binding ligands derived from the natural product quercetin. Chemical derivatives of 5-substituted 3, 3’, 4’, 7-tetramethoxyquercetin derivatives were characterized …

Para-Methoxybenzylidene Acetal-Protected D-Glucosamine Derivatives As Ph-Responsive Gelators And Their Applications For Drug Delivery, Jonathan Bietsch, Logan Baker, Anna Duffney, Alice Mao, Mary Foutz, Cheandri Ackermann, Guijun Wang

Chemistry & Biochemistry Faculty Publications

Carbohydrate-based low molecular weight gelators (LMWGs) are compounds with the capability to self-assemble into complex molecular networks within a solvent, leading to solvent immobilization. This process of gel formation depends on noncovalent interactions, including Van der Waals, hydrogen bonding, and π–π stacking. Due to their potential applications in environmental remediation, drug delivery, and tissue engineering, these molecules have emerged as an important area of research. In particular, various 4,6-O-benzylidene acetal-protected D-glucosamine derivatives have shown promising gelation abilities. In this study, a series of C-2-carbamate derivatives containing a para-methoxy benzylidene acetal functional group were synthesized and characterized. These compounds exhibited good …

Msdrp: A Deep Learning Model Based On Multisource Data For Predicting Drug Response, Haochen Zhao, Xiaoyu Zhang, Qichang Zhao, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict drug response in vitro. However, most of these methods capture drug features based on a single drug description (e.g. drug structure), without considering the relationships between drugs and biological entities (e.g. target, diseases, and side effects). Moreover, most of these methods collect features separately for drugs and cell lines but fail to consider the pairwise interactions between drugs and cell …

Cancer Incidence And Stage At Diagnosis Among People With Psychotic Disorders: Systematic Review And Meta-Analysis., Jared C Wootten, Joshua C Wiener, Phillip S Blanchette, Kelly K. Anderson

Epidemiology and Biostatistics Publications

Research regarding the incidence of cancer among people with psychotic disorders relative to the general population is equivocal, although the evidence suggests that they have more advanced stage cancer at diagnosis. We conducted a systematic review and meta-analysis to examine the incidence and stage at diagnosis of cancer among people with, relative to those without, psychotic disorders. We searched the MEDLINE, EMBASE, PsycINFO, and CINAHL databases. Articles were included if they reported the incidence and/or stage at diagnosis of cancer in people with psychotic disorders. Random effects meta-analyses were used to determine risk of cancer and odds of advanced stage …

Cancer Incidence And Stage At Diagnosis Among People With Recent-Onset Psychotic Disorders: A Retrospective Cohort Study Using Health Administrative Data From Ontario, Canada., Jared C Wootten, Lucie Richard, Phillip S Blanchette, Joshua C. Wiener, Kelly K. Anderson

Epidemiology and Biostatistics Publications

OBJECTIVE: Prior evidence on the relative risk of cancer among people with psychotic disorders is equivocal. The objective of this study was to compare incidence and stage at diagnosis of cancer for people with psychotic disorders relative to the general population.

METHOD: We constructed a retrospective cohort of people with a first diagnosis of non-affective psychotic disorder and a comparison group from the general population using linked health administrative databases in Ontario, Canada. The cohort was followed for incident diagnoses of cancer over a 25-year period. We used Poisson and logistic regression models to compare cancer incidence and stage at …

Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi

Electrical & Computer Engineering Faculty Publications

Plasma medicine refers to the application of nonequilibrium plasmas at approximately body temperature, for therapeutic purposes. Nonequilibrium plasmas are weakly ionized gases which contain charged and neutral species and electric fields, and emit radiation, particularly in the visible and ultraviolet range. Medically-relevant cold atmospheric pressure plasma (CAP) sources and devices are usually dielectric barrier discharges and nonequilibrium atmospheric pressure plasma jets. Plasma diagnostic methods and modelling approaches are used to characterize the densities and fluxes of active plasma species and their interaction with surrounding matter. In addition to the direct application of plasma onto living tissue, the treatment of liquids …

The Effects Of Paclitaxel On Cellular Migration And The Cytoskeleton, Ashley Salguero-Gonzalez

Thinking Matters Symposium

In a clinical setting, some patients are exposed to an anti-cancer chemotherapy agent, paclitaxel. Cancerous cells undergo rapid, continuous cell division without control. Chemotherapy treatments try to slow and stop the uncontrollable cell division cycles and eliminate cancerous cells in the process. Paclitaxel serves as a treatment for some types of cancers, including lung, melanoma, bladder, and esophageal. Because it targets the cytoskeleton, paclitaxel can also influence cell migration. This project utilizes a cellular migration assay and an immunohistochemistry assay to analyze the effects of paclitaxel on the movement of cells and on the cytoskeleton of neuroglia rat cells with …

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

Combination Chemo-Pdt Ionic Nanomedicines As Enhanced Therapeutics For Cancer, Samantha Macchi

Arkansas Women in STEM Conference

Cancer remains as one of the leading causes of death in humans worldwide. Nanotechnology has made great strides in improving treatment for the disease. This work describes a simplistic approach to design self-assembled combination nanomedicines. A facile one-step ion exchange reaction is utilized to combine a chemotherapeutic (phosphonium) cation and photodynamic therapeutic (porphyrin) anion. An aqueous nanomedicine is prepared from the hydrophobic ionic combination drug via a single-step reprecipitation method. Upon conversion to ionic combination drug, improved photophysical properties of porphyrin were observed. These characteristics subsequently led to increased photodynamic therapeutic activity of nanomedicines—explained by greater singlet oxygen quantum yield. …

A Review Of Monte Carlo Methods And Their Application In Medical Physics For Simulating Radiation Transport, Joe Shields

Honors Theses and Capstones

Monte Carlo methods are used to calculate statistical behavior through the use of random number generators and probability density functions. They have been used extensively in medical physics for research in radiotherapy, designing technology, dosimetry, and advanced clinical applications. This paper provides a background on Monte Carlo methods and a review of radiation therapy physics and dosimetry. Additionally, there is a discussion of the different ways Monte Carlo methods are used in medical physics as well as a review of current research related to Monte Carlo methods. The final portion of this paper contains my own Monte Carlo simulation using …

System Measurements For X-Ray Phase And Diffraction Imaging, Erik Wolfgang Tripi

Legacy Theses & Dissertations (2009 - 2024)

In medical imaging, X rays are used to look inside the body to find fractures in bones, abnormal masses, cavities in teeth, and so on. What makes X rays so good at looking at these types of structures is the X ray’s penetration power. When imaging soft tissue to search for tumors, X-ray images tend to have difficulty performing well. The reason for this is that the background structures, such as fat or fibro glandular tissue have similar absorption coefficients as the tumor. Mammography tends to have a high false positive rate and can miss tumors entirely as well. There …

Clinical Diagnosis Support With Convolutional Neural Network By Transfer Learning, Spencer Fogleman, Jeremy Otsap, Sangrae Cho

SMU Data Science Review

Breast cancer is prevalent among women in the United States. Breast cancer screening is standard but requires a radiologist to review screening images to make a diagnosis. Diagnosis through the traditional screening method of mammography currently has an accuracy of about 78% for women of all ages and demographics. A more recent and precise technique called Digital Breast Tomosynthesis (DBT) has shown to be more promising but is less well studied. A machine learning model trained on DBT images has the potential to increase the success of identifying breast cancer and reduce the time it takes to diagnose a patient, …

Synergistic Anticancer Response Of Curcumin And Piperine Loaded Lignin-G-P (Nipam-Co-Dmaema) Gold Nanogels Against Glioblastoma Multiforme, Xinyi Zhao, Bilal Javad, Daxing Cui, James Curtin, Furong Tian

Articles

Glioblastoma multiforme (GBM) is the most aggressive and commonly diag- 11 nosed brain cancer and presents a strong resistance to routine chemotherapeutic drugs. 12 The present study involves the synthesis of Lignin-g- p (NIPAM-co-DMAEMA) gold 13 nanogel, loaded with curcumin and piperine to treat GBM. The application has three 14 functions: (1) overcome the limitations of biodistribution, (2) enhance the toxicity of an- 15 ticancer drugs against GBM, (3) identify the uptake pathway. Atom transfer radical 16 polymerization was used to synthesize the Lignin-g-PNIPAM network, crosslinked with 17 the gold nanoparticles (GNPs) to self-assemble into nanogels. The size distribution and …

Development Of Biomaterials For Drug Delivery, Raquel De Castro

Graduate Theses and Dissertations

Drug delivery systems (DDS) have highly evolved in the last decades with the development of hydrogels and nanoparticles. However, high systemic uptake, side effects, low bioavailability, and encapsulation efficiency continue to be a major hurdle faced by such DDSs.

Nanoparticles and hydrogels can be specifically designed for targeted DDSs to mitigate some of the problems. This dissertation aimed to design two DDSs for ocular drug delivery and one for cancer treatment. The first project sought to develop chitosan nanoparticles (Cs-NP) using PEGDA as a copolymer to encapsulate gentamicin (GtS) for ocular drug delivery. Cs-NPs contain positive charges that can interact …

Mixture Model Approaches To Integrative Analysis Of Multi-Omics Data And Spatially Correlated Genomic Data, Ziqiao Wang

Dissertations & Theses (Open Access)

Integrative genomic data analysis is a powerful tool to study the complex biological processes behind a disease. Statistical methods can model the interrelationships of the involved gene activities through jointly analyzing multiple types of genomic data from different platforms (vertical integration), or improve the power of a study through aggregating the same type of genomic data across studies (horizontal integration). In this dissertation, we propose statistical methods and strategies for integrative multi-omics data in association analysis of disease phenotypes, with an emphasis on cancer applications.

We develop a new strategy based on horizontal integration by leveraging publicly available datasets into …

Bibliometric Analysis Of Named Entity Recognition For Chemoinformatics And Biomedical Information Extraction Of Ovarian Cancer, Vijayshri Khedkar, Charlotte Fernandes, Devshi Desai, Mansi R, Gurunath Chavan Dr, Sonali Tidke Dr., M. Karthikeyan Dr.

Library Philosophy and Practice (e-journal)

With the massive amount of data that has been generated in the form of unstructured text documents, Biomedical Named Entity Recognition (BioNER) is becoming increasingly important in the field of biomedical research. Since currently there does not exist any automatic archiving of the obtained results, a lot of this information remains hidden in the textual details and is not easily accessible for further analysis. Hence, text mining methods and natural language processing techniques are used for the extraction of information from such publications.Named entity recognition, is a subtask that comes under information extraction that focuses on finding and categorizing specific …

Biophysical Characterization Of The Par-4 Tumor Suppressor: Evidence Of Structure Outside The Coiled Coil Domain And Interactions With Platinum Chemotherapeutics, Andrea Megan Clark

Chemistry & Biochemistry Theses & Dissertations

Prostate apoptosis response-4 (Par-4) is an apoptosis-inducing tumor suppressor protein. Full-length Par-4 has previously been shown to be a predominantly intrinsically disordered protein (IDP) under neutral conditions, with significant regular secondary structure evident only within the C-terminal coiled coil domain. However, IDPs can gain ordered structure through the process of induced folding, which often occurs under non-neutral conditions. Previous work has shown that the Par-4 leucine zipper, which is a subset of the C-terminal coiled coil domain, is disordered under neutral conditions, but forms a dimeric coiled coil at acidic pH. Increase in ionic strength was also shown to increase …

Limitations Of Transformers On Clinical Text Classification, Shang Gao, Mohammed Alawad, Michael Todd Young, John Gounley, Noah Schaefferkoetter, Hong-Jun Yoon, Xiao-Cheng Wu, Eric B. Durbin, Jennifer Doherty, Antoinette Stroup, Linda Coyle, Georgia D. Tourassi

Kentucky Cancer Registry Faculty Publications

Bidirectional Encoder Representations from Transformers (BERT) and BERT-based approaches are the current state-of-the-art in many natural language processing (NLP) tasks; however, their application to document classification on long clinical texts is limited. In this work, we introduce four methods to scale BERT, which by default can only handle input sequences up to approximately 400 words long, to perform document classification on clinical texts several thousand words long. We compare these methods against two much simpler architectures -- a word-level convolutional neural network and a hierarchical self-attention network -- and show that BERT often cannot beat these simpler baselines when classifying …

Association Of Incident Cancer To Low-Value Care And Healthcare Cost Burden Among Elderly Medicare Beneficiaries, Chibuzo Iloabuchi

Graduate Theses, Dissertations, and Problem Reports

In the United States (US), 25% of healthcare spending is considered wasteful because it is spent reimbursing low-value care. Low-value care is the utilization of healthcare services, medical tests, and procedures that have unclear or no clinical benefit to patients but still exposes them to risk. World-wide, low-value care imposes a significant economic burden on patients, payers, governments, and society. Cancer care among older adults > 65 years is one of the biggest drivers of healthcare expenditure in the US and accounts for nearly 40% of all spending, and low-value care among cancer patients is prevalent and contributes to the financial …

Design, Synthesis, And Anticancer Properties Of Ru(Ii) Complexes With Organometallic, “Expanded” Bipyridine, And O,O’-Chelating Ligands, Raphael Ryan

Theses and Dissertations--Chemistry

Cancer is a worldwide public health crisis that requires new and improved drugs to be developed to extend survival rates and improve quality of life for the patient. Platinum-based drugs are used in approximately 50% of cancer treatment regimens. These drugs are highly effective in many kinds of cancer; however, cancers can develop platinum resistance and these drugs have troubling side effects that reduced their use and efficacy. To overcome these disadvantages, many other metals have been studied for their anticancer properties. Notably, the anticancer properties of ruthenium-based agents have drawn considerable attention with multiple ruthenium complexes entering clinical trials. …

Integrated Multiparametric Radiomics And Informatics System For Characterizing Breast Tumor Characteristics With The Oncotypedx Gene Assay, Michael A. Jacobs, Christopher B. Umbricht, Vishwa S. Parekh, Riham H. El Khouli, Leslie Cope, Katarzyna J. Macura, Susan Harvey, Antonio C. Wolff

Radiology Faculty Publications

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained …

Personalized Medicine: The Use Of Biomarkers And Molecularly Targeted Therapies For Patient Care And Cancer Intervention, Wafa Asad, Emily Schmitt Lavin

Mako: NSU Undergraduate Student Journal

Personalized medicine and targeted therapy have been emerging fields of study for the remediation and inhibition of cancer. Personalized medicine in the treatment of cancer involves using genetic, immune, and proteomic profiling to provide therapeutic options as well as prognostic background for every patient and their tumor’s genetic mutations. Targeted therapies allow researchers and medical personnel alike to determine the appropriate treatment for a patient based on the molecular basis and mechanistic actions of a cancerous tumor. The overall significance of this study was to express how these treatments use biomarkers to pinpoint the location, and severity of the cancer, …

Statistical Methods For Resolving Intratumor Heterogeneity With Single-Cell Dna Sequencing, Alexander Davis

Dissertations & Theses (Open Access)

Tumor cells have heterogeneous genotypes, which drives progression and treatment resistance. Such genetic intratumor heterogeneity plays a role in the process of clonal evolution that underlies tumor progression and treatment resistance. Single-cell DNA sequencing is a promising experimental method for studying intratumor heterogeneity, but brings unique statistical challenges in interpreting the resulting data. Researchers lack methods to determine whether sufficiently many cells have been sampled from a tumor. In addition, there are no proven computational methods for determining the ploidy of a cell, a necessary step in the determination of copy number. In this work, software for calculating probabilities from …

Epidemiology Of Cancers In Men Who Have Sex With Men (Msm): A Protocol For Umbrella Review Of Systematic Reviews, Manoj Kumar Honaryar, Yelena Tarasenko, Maribel Almonte, Vitaly Smelov

Department of Biostatistics, Epidemiology, and Environmental Health Sciences Faculty Publications

While earlier studies on men having sex with men (MSM) tended to examine infection-related cancers, an increasing number of studies have been focusing on effects of sexual orientation on other cancers and social and cultural causes for cancer disparities. As a type of tertiary research, this umbrella review (UR) aims to synthesize findings from existing review studies on the effects of sexual orientation on cancer. Relevant peer-reviewed systematic reviews (SRs) will be identified without date or language restrictions using MEDLINE, Cochrane Database of Systematic Reviews, and the International Prospective Register for Systematic Reviews, among others. The research team members will …

A Web-Based, Positive Emotion Skills Intervention For Enhancing Posttreatment Psychological Well-Being In Young Adult Cancer Survivors (Empower): Protocol For A Single-Arm Feasibility Trial, John M. Salsman, Laurie E. Mclouth, Michael Cohn, Janet A. Tooze, Mia Sorkin, Judith T. Moskowitz

Behavioral Science Faculty Publications

BACKGROUND: Adolescent and young adult cancer survivors (AYAs) experience clinically significant distress and have limited access to supportive care services. Interventions to enhance psychological well-being have improved positive affect and reduced depression in clinical and healthy populations but have not been routinely tested in AYAs.

OBJECTIVE: The aim of this protocol is to (1) test the feasibility and acceptability of a Web-based positive emotion skills intervention for posttreatment AYAs called Enhancing Management of Psychological Outcomes With Emotion Regulation (EMPOWER) and (2) examine proof of concept for reducing psychological distress and enhancing psychological well-being.

METHODS: The intervention development and testing are …

Using Case-Level Context To Classify Cancer Pathology Reports, Shang Gao, Mohammed Alawad, Noah Schaefferkoetter, Lynne Penberthy, Xiao-Cheng Wu, Eric B. Durbin, Linda Coyle, Arvind Ramanathan, Georgia Tourassi

Kentucky Cancer Registry Faculty Publications

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence-for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We …