Biomedical Engineering and Bioengineering Commons^™

Integrated Rules Classifier For Predicting Pathogenic Non-Synonymous Single Nucleotide Variants In Human, Ahmed Barakat Hosseny, Marwa Said Hassan, A A. Shalan, Shymaa Khamis, M I. Dessouky

Basic Science Engineering

The most prevalent kind of genetic variants in humans are non-synonymous single nucleotide variants (nsSNVs). Several prediction tools have been launched to forecast the effect of amino acid substitutes on human protein function. These tools sort variants as pathogenic or neutral. We developed an Integrated Rules Classifier (Integration Score through JRip “ISTJRip”), which integrates the four individual tools that are publicly available; iFish, Mutation Assessor, FATHMM, and SIFT-based on the JRip machine learning technique. Additionally, we compared the ISTJRip approach with the other three created integration classifiers; Integration Score through J48 “ISTJ48”, Integration Score through RF “ISTRF”, and Integration …

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

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 …

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 …

In Silico Prediction Of Sodium-Glucose Co-Transporter-2 (Sglt2) Inhibition Activity By Allium Fistulosum Compound Based On Skelspheres Molecular Descriptor, Rudy Heryanto, Aryo Tedjo, Dimas Noor

Indonesian Journal of Medical Chemistry and Bioinformatics

The Sodium-Glucose co-transporter-2 (SGLT2) inhibitor represents a novel agent for the treatment of type 2 diabetes. Drugs of this class function by inhibiting glucose reabsorption in the kidneys, thereby controlling blood glucose levels. It is known that SGLT2 inhibitors activate the AMPK signaling pathway by increasing the expression and activity of AMP-activated protein kinase (AMPK). In vivo tests have demonstrated that ethanolic and aqueous extracts of Welsh onion leaves (Allium fistulosum L) can reduce body weight, liver weight, adipocyte size, and enhance AMP-activated protein kinase (AMPK) expression. In this study, the inhibitory activity (IC50) of compounds within Allium fistulosum against …

Metabolomic Insights Into Tuberculosis: Machine Learning Approaches For Biomarker Identification, Miftahul Khair Akbar, Arief Aulia Rahman

Indonesian Journal of Medical Chemistry and Bioinformatics

The lung parenchyma is largely impacted by the infectious condition known as pulmonary tuberculosis (pulmonary TB) when the immune system creates a wall around the germs in the lungs, a tiny, hard bulge known as a tubercle develops, earning the disease the name tuberculosis. Although the majority of TB germs target the lungs, they can also harm other bodily organs. The identification of TB biomarkers, which are crucial for diagnosis, treatment monitoring, risk analysis, and prognosis, has been the subject of extensive research. Differences in metabolites between normal cells and tuberculosis are considered to be able to support the diagnosis …

Visual Complexity Of The Time-Frequency Image Pinpoints The Epileptogenic Zone: An Unsupervised Deep-Learning Tool To Analyze Interictal Intracranial Eeg, Sarvagya Gupta

Graduate Masters Theses

Epilepsy, a prevalent neurological disorder characterized by recurrent seizures, continues to pose significant challenges in diagnosis and treatment, particularly among children. Despite substantial advancements in medical technology and treatment modalities, localization of the part of brain that causes seizures (Epileptogenic Zone) remains a difficult task. Intracranial EEG (iEEG) is often used to estimate the epileptogenic zone (EZ) in children with drugresistant epilepsy (DRE) and target it during surgery. Conventionally, iEEG signals are inspected in the time domain by human experts aiming to locate epileptiform activity.

Visual scrutiny of the iEEG time-frequency (TF) images can be an alternative way to review …

Serum Metabolomic Profiling For Colorectal Cancer Using Machine Learning, Ria Nur Puspa Sari, Diah Balqis Ikfi Hidayati, Arleni Bustami

Indonesian Journal of Medical Chemistry and Bioinformatics

Background: Colorectal cancer is one of the deadliest diseases with a high prevalence worldwide and is characterized by the appearance of adenomatous polyps in the colon mucosa which are at high risk of developing into colorectal cancer. This study aims to use serum metabolites as promising non-invasive biomarkers for colorectal cancer detection and prognostication. Differences in serum metabolites in patients with adenomatous polyps, colorectal cancer, and healthy controls are considered to be able to support the prognosis of colorectal cancer. Methods: Metabolite dataset is taken from the Metabolomic Workbench. Analysis and validation are carried out in silico using machine learning …

Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego

Electrical & Computer Engineering Theses & Dissertations

World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …

Assesment Of Structure, Function, And Microevolutionary Dynamics Of Extrachromosomal Circular Dna In Chinese Hamster Ovary Cells, Dylan Chitwood

All Dissertations

Chinese hamster ovary (CHO) cell lines are among the most popular expression hosts used in biopharmaceutical manufacturing due to relative ease of culture, capacity to perform human-like post-translational modifications, and non-susceptibility to viruses. However, the intrinsic plasticity of the CHO genome can lead to undesired genetic rearrangements, phenotypic shifts, reduced product quality, and early culture termination that prevents continuous biomanufacturing. A characteristic of plastic and unstable genomes that is poorly understood in CHO cells is extrachromosomal circular DNA (eccDNA). EccDNAs are focal amplifications of the genome that reside in the extranuclear space. These plasmid-like entities are structurally complex and are …

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

Therapeutic Options For Covid-19: Drug Repurposing Of Serine Protease Inhibitor Against Tmprss2, Mohammad Wildan Abiyyi, Surya Dwira, Arleni Bustami, Linda Erlina

Indonesian Journal of Medical Chemistry and Bioinformatics

The SARS-Coronavirus 2 (SARS-CoV-2) outbreak is a serious global public health threat. Researchers around the world are conducting mass research to control this epidemic, starting from the discovery of vaccines, to new drugs that have specific activities as antivirals. Drug repurposing is a potential method of using drugs with known activity for reuse as COVID-19 therapy. This method has the advantage that it can reduce costs and also the duration in the development of potential drugs. The initial step in drug repurposing can be done computationally to determine the effectiveness and specificity of the drug on the target protein. Molecular …

Virtual Screening On Indonesian Herbal Compounds As Sars-Cov-2 Spike (S2) Glycoprotein Inhibitors: Pharmacophore Modelling & Molecular Docking Approaches, Syailendra Karuna Sugito, Artha Uli Cristina, Putri Saskia Harimurti, Gabriella Regita Cendani, Fauzi Azhar Insani, Linda Erlina, Rafika Indah Paramita, Fadilah Fadilah

Indonesian Journal of Medical Chemistry and Bioinformatics

Background: There are still no specific treatments for coronavirus disease (COVID-19) until present days. Several studies have been conducted to determine whether herbal medicine can be an option to be used as a definitive medicine for COVID-19. S2 subunit of spike protein which is responsible for SARS-CoV-2 entry to the host cell, is a potential drug target to inhibit the viral infection. In this study, we aimed to find some compounds from the HerbalDB database that have potential as SARS-CoV-2 spike (S2) glycoprotein inhibitor.

Methods: The 6LXT protein was used as the target protein. The procedure in this study consisted …

Development And Validation Of A Three-Dimensional Optical Imaging System For Chest Wall Deformity Measurement, Nahom Kidane

Electrical & Computer Engineering Theses & Dissertations

Congenital chest wall deformities (CWD) are malformations of the thoracic cage that become more pronounced during early adolescence. Pectus excavatum (PE) is the most common CWD, characterized by an inward depression of the sternum and adjacent costal cartilage. A cross-sectional computed tomography (CT) image is mainly used to calculate the chest thoracic indices. Physicians use the indices to quantify PE deformity, prescribe surgical or non-surgical therapies, and evaluate treatment outcomes. However, the use of CT is increasingly causing physicians to be concerned about the radiation doses administered to young patients. Furthermore, radiographic indices are an unsafe and expensive method of …

Analysis And Visualization Of Molecular Docking 2hi4 Protein, Innas Widiasti

Indonesian Journal of Medical Chemistry and Bioinformatics

The crystal structure of the human microsomal complex P450 1A2 with alpha-naphthoflavone, a cytochrome P450 (CYP) enzyme is particularly important, as it is abundant in the human liver and alters a more diverse xenobiotic array than any other group of metabolic enzymes. CYP1A2 is abundantly found in the liver and involved in the metabolism of about 10% of clinically used drugs metabolized by CYP enzymes. The current drug discovery and development mostly uses high-throughput screening (HTS). However, this regular method is time-consuming and costly. To address the issue, an advanced drug discovery and development method namely chemical compound database screening …

Development Of The Assessment Of Clinical Prediction Model Transportability (Apt) Checklist, Sean Chonghwan Yu

McKelvey School of Engineering Theses & Dissertations

Clinical Prediction Models (CPM) have long been used for Clinical Decision Support (CDS) initially based on simple clinical scoring systems, and increasingly based on complex machine learning models relying on large-scale Electronic Health Record (EHR) data. External implementation – or the application of CPMs on sites where it was not originally developed – is valuable as it reduces the need for redundant de novo CPM development, enables CPM usage by low resource organizations, facilitates external validation studies, and encourages collaborative development of CPMs. Further, adoption of externally developed CPMs has been facilitated by ongoing interoperability efforts in standards, policy, and …

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 …

The Low Abundance Of Cpg In The Sars-Cov-2 Genome Is Not An Evolutionarily Signature Of Zap, Ali Afrasiabi, Hamid Alinejad-Rokny, Azad Khosh, Mostafa Rahnama, Nigel Lovell, Zhenming Xu, Diako Ebrahimi

Plant Pathology Faculty Publications

The zinc finger antiviral protein (ZAP) is known to restrict viral replication by binding to the CpG rich regions of viral RNA, and subsequently inducing viral RNA degradation. This enzyme has recently been shown to be capable of restricting SARS-CoV-2. These data have led to the hypothesis that the low abundance of CpG in the SARS-CoV-2 genome is due to an evolutionary pressure exerted by the host ZAP. To investigate this hypothesis, we performed a detailed analysis of many coronavirus sequences and ZAP RNA binding preference data. Our analyses showed neither evidence for an evolutionary pressure acting specifically on CpG …

Framework For The Evaluation Of Perturbations In The Systems Biology Landscape And Inter-Sample Similarity From Transcriptomic Datasets — A Digital Twin Perspective, Mariah Marie Hoffman

Dissertations and Theses

One approach to interrogating the complexities of human systems in their well-regulated and dysregulated states is through the use of digital twins. Digital twins are virtual representations of physical systems that are descriptive of an individual's state of health, an object fundamentally related to precision medicine. A key element for building a functional digital twin type for a disease or predicting the therapeutic efficacy of a potential treatment is harmonized, machine-parsable domain knowledge. Hypothesis-driven investigations are the gold standard for representing subsystems, but their results encompass a limited knowledge of the full biosystem. Multi-omics data is one rich source of …

Classifying Electrocardiogram With Machine Learning Techniques, Hillal Jarrar

Master's Theses

Classifying the electrocardiogram is of clinical importance because classification can be used to diagnose patients with cardiac arrhythmias. Many industries utilize machine learning techniques that consist of feature extraction methods followed by Naive- Bayesian classification in order to detect faults within machinery. Machine learning techniques that analyze vibrational machine data in a mechanical application may be used to analyze electrical data in a physiological application. Three of the most common feature extraction methods used to prepare machine vibration data for Naive-Bayesian classification are the Fourier transform, the Hilbert transform, and the Wavelet Packet transform. Each machine learning technique consists of …

Bone Quality And Fractures In Women With Osteoporosis Treated With Bisphosphonates For 1 To 14 Years, Hartmut H. Malluche, Jin Chen, Florence Lima, Lucas J. Liu, Marie-Claude Monier-Faugere, David A. Pienkowski

Internal Medicine Faculty Publications

Oral bisphosphonates are the primary medication for osteoporosis, but concerns exist regarding potential bone-quality changes or low-energy fractures. This cross-sectional study used artificial intelligence methods to analyze relationships among bisphosphonate treatment duration, a wide variety of bone-quality parameters, and low-energy fractures. Fourier transform infrared spectroscopy and histomorphometry quantified bone-quality parameters in 67 osteoporotic women treated with oral bisphosphonates for 1 to 14 years. Artificial intelligence methods established two models relating bisphosphonate treatment duration to bone-quality changes and to low-energy clinical fractures. The model relating bisphosphonate treatment duration to bone quality demonstrated optimal performance when treatment durations of 1 to 8 …

Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook

Undergraduate Research and Scholarship Symposium

Single-nucleotide polymorphisms (SNPs) are variations in the genome where one base pair can differ between individuals.¹ SNPs occur throughout the genome and can correlate to a disease-state if they occur in a functional region of DNA.¹According to the central dogma of molecular biology, any variation in the DNA sequence will have a direct effect on the RNA sequence and will potentially alter the identity or conformation of a protein product. A single RNA molecule, due to intramolecular base pairing, can acquire a plethora of 3-D conformations that are described by its structural ensemble. One SNP, rs12477830, which …

Differentiating Human Embryonic Stem Cells In Micropatterns To Study Cell Fate Specification And Morphogenetic Events During Gastrulation, Kyaw Thu Minn

McKelvey School of Engineering Theses & Dissertations

During mammalian embryogenesis, the first major lineage segregation occurs when embryonic epiblast, and extraembryonic trophectoderm and hypoblast arise in the blastocyst. In the next fundamental and conserved phase of animal embryogenesis known as gastrulation, extraembryonic cells provide signals to epiblast to instruct embryonic patterning, and epiblast gives rise to germ layers ectoderm, mesoderm, and endoderm, that will establish all embryonic tissues. Proper specification and morphogenesis of germ layers during gastrulation is vital for correct embryonic development. Due to ethical and legal restrictions limiting human embryo studies, human gastrulation is poorly understood. Our knowledge of human gastrulation has largely been derived …

A Note From The Editor, Daphne Fauber

Ideas: Exhibit Catalog for the Honors College Visiting Scholars Series

This piece is a letter from Daphne Fauber, the editor of this issue of Ideas. In the letter, the editor introduces the work of Dr. Paschalis Gkoupidenis as well as the moment in time in which his Visiting Scholars talk occurs.

Β-Amyloid And Tau Drive Early Alzheimer's Disease Decline While Glucose Hypometabolism Drives Late Decline, Tyler C. Hammond, Xin Xing, Chris Wang, David Ma, Kwangsik Nho, Paul K. Crane, Fanny Elahi, David A. Ziegler, Gongbo Liang, Qiang Cheng, Lucille M. Yanckello, Nathan Jacobs, Ai-Ling Lin

Sanders-Brown Center on Aging Faculty Publications

Clinical trials focusing on therapeutic candidates that modify β-amyloid (Aβ) have repeatedly failed to treat Alzheimer’s disease (AD), suggesting that Aβ may not be the optimal target for treating AD. The evaluation of Aβ, tau, and neurodegenerative (A/T/N) biomarkers has been proposed for classifying AD. However, it remains unclear whether disturbances in each arm of the A/T/N framework contribute equally throughout the progression of AD. Here, using the random forest machine learning method to analyze participants in the Alzheimer’s Disease Neuroimaging Initiative dataset, we show that A/T/N biomarkers show varying importance in predicting AD development, with elevated biomarkers of Aβ …

Transcriptomic Analysis Of Cytokine-Treated Tissue-Engineered Cartilage As An In Vitro Model Of Osteoarthritis, Jiehan Li

McKelvey School of Engineering Theses & Dissertations

Osteoarthritis (OA), as the most common form of arthritis and a leading cause of disability worldwide, currently has no disease-modifying drugs. Inflammation plays an important role in cartilage degeneration in OA, and pro-inflammatory cytokines, IL-1β and TNF-α, have been shown to induce degradative changes along with aberrant gene expression in chondrocytes, the only resident cells in cartilage. The goal of this study was to further understand the transcriptomic regulation of tissue-engineered cartilage in response to inflammatory cytokines using an in vitro miPSC model system. We performed RNA sequencing for the IL-1β or TNF-α treated tissue-engineered cartilage derived from murine iPSCs, …

Impedance Analysis Of Tissues In Nspef Treatment For Cancer Therapy, Edwin Ayobami Oshin

Biomedical Engineering Theses & Dissertations

Nanosecond pulsed electric field (nsPEF) for cancer therapy is characterized by applications of high voltage pulses with low pulsed energy to induce non-thermal effects on tissues such as tumor ablation. It nonthermally treats tissues via electroporation. Electroporation is the increase in permeabilization of a cell membrane due to the application of high pulsed electric field. The objective of this study was to investigate the effect of nsPEF on tissue by monitoring the tissue’s impedance in real-time. Potato slices (both untreated and electroporated), and tumors extracted from female BALBc mice were studied. 100ns, 1-10kV pulses were applied to the tissues using …

Scalable Profiling And Visualization For Characterizing Microbiomes, Camilo Valdes

FIU Electronic Theses and Dissertations

Metagenomics is the study of the combined genetic material found in microbiome samples, and it serves as an instrument for studying microbial communities, their biodiversities, and the relationships to their host environments. Creating, interpreting, and understanding microbial community profiles produced from microbiome samples is a challenging task as it requires large computational resources along with innovative techniques to process and analyze datasets that can contain terabytes of information.

The community profiles are critical because they provide information about what microorganisms are present in the sample, and in what proportions. This is particularly important as many human diseases and environmental disasters …

A Discrete-Event Simulation Approach For Modeling Human Body Glucose Metabolism, Buket Aydas

Theses and Dissertations

This dissertation describes CarbMetSim (Carbohydrate Metabolism Simulator), a discrete-event simulator that tracks the blood glucose level of a person in response to a timed sequence of diet and exercise activities. CarbMetSim implements broader aspects of carbohydrate metabolism in human beings with the objective of capturing the average impact of various diet/exercise activities on the blood glucose level. Key organs (stomach, intestine, portal vein, liver, kidney, muscles, adipose tissue, brain and heart) are implemented to the extent necessary to capture their impact on the production and consumption of glucose. Key metabolic pathways (glucose oxidation, glycolysis and gluconeogenesis) are accounted for by …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …