Bioinformatics Commons^™

Urobiome Screening For Antimicrobial Peptides Against Uropathogenic Escherichia Coli, Jennifer Jones

ORBioM (Open Research BioSciences Meeting)

BACKGROUND: Urinary tract infections (UTIs) are one of the most common bacterial infections worldwide. As global incidences of UTIs caused by multidrug resistant bacteria continue to increase, so too does the demand for novel antimicrobial therapies.

Due to its relatively understudied nature, the urinary microbiome represents a niche with an untapped source of potentially novel antimicrobials (e.g., bacteriocins). Improvements to bacterial culturing and sequencing techniques have highlighted these potential alternative treatments and control strategies to target antibiotic resistant uropathogenic E. coli (UPEC).

METHODS: Expanded quantitative urine culture (EQUC) was used to culture bacterial isolates from mid-stream urine samples. Urinary isolates …

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 …

Exploration Of Potential Natural Inhibitors Against Kras-G12d In Pancan: Protein Centered Pharmacophore Htvs Approach., Anupam Dhasmana, Swati Dhasmana, Sudhir Kotnala, Vivek Kumar Kashyap, Sheema Khan, Murali M. Yallapu, Meena Jaggi, Subhash C. Chuahan

Research Symposium

Background: As per key statistics of American Cancer Society 2021, Pancreatic Cancer (PanCan) affects around 60,430 persons a year in the U.S. and is tricky to diagnose & treat. Studies revealed that African Americans have a 50–90% higher incidence of PanCan compared to other ethnic groups. Oncogenic KRAS mutation is the signature genetic incident in the progression and development of PDAC. KRAS is the most common protein which is 95% times mutated in PDAC condition. By considering this alarming situation our group is now focused on to develop therapeutic portfolio against KRAS-G12D mutation associated PanCan by using high through-put virtual …

Cell-Based Experimental Evidence To The Anti-Covid-19 Potential Of Ashwagandha And Honeybee Propolis Ingredients, Renu Wadhwa, Durai Sundar, Yoshiyuki Ishida, Keiji Terao, Sunil C. Kaul

Research Symposium

Background: The COVID-19 pandemic emerged in December 2019 by a novel strain of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) has led to new endeavours in repurposing of existing drugs, anti-COVID-19 vaccine and drug development. Natural products, due to their general safety and wider availability, have attracted research and public attention. In this study, we report anti-COVID potential of compounds from honeybee propolis and Ayurvedic herb, Ashwagandha. Effect of active ingredients was studied on human cell surface receptors (ACE-2:Angiotensin Converting Enzyme-2/Spike protein and TMPRSS2:Transmembrane Protease Serine 2), critical for virus infection and virus main protease (Mpro, essential for virus replication), …

Comparative Analysis Of The Effects Of Actual Versus Assumed Opioid Experience On The Regulation Of Ventral Striatal Opioid Receptor Gene Expression, Indu Mithra Madhuranthakam, Martin Job

Rowan-Virtua Research Day

Rationale: We conducted experiments to assess the effect of prior opioid experience on gene expression changes. We compared the current experimenter-imposed short versus extended-access conditions of opioid self-administration and developed a new quantitative method to determine their effectiveness in identifying the role of opioid experience in regulating opioid receptor expression levels in the ventral striatum (VS) using an oxycodone self-administration/abstinence model.

Methods: In this study, male Sprague-Dawley rats (n=36) were trained for 20 days to self-administer oxycodone at 0.1 mg/kg/infusion under short access (n=15, or saline as controls n=3, for 3h/day) or extended access (n=15, or saline as controls n=3, …

Intellectual Disability Related To De Novo Germline Loss Of The Distal End Of The P-Arm Of Chromosome 17: A Case Report, Eden Pope, Matthew Huertas, Amar Paul, Braden Cunningham, Matthew Jennings, Ryan Perry, Stephanie Chavez, John A. Kriak, Kyle B. Bills, David W. Sant

Annual Research Symposium

Hypothesis/Purpose: In this report we present a case of a 20-year-old female with congenital intellectual disability, stunted growth, and hypothyroidism. Competitive genetic hybridization (CHG) revealed a loss of 17p13.3, and the deletion was not present in either parent. This deletion has not previously been characterized, but mutations on the p-arm of chromosome 17 are responsible for Miller-Dieker Syndrome and Isolated Lissencephaly Sequence, both of which share symptoms in common with the patient.

Methods: Peripheral mononuclear cells (PBMCs) were used for karyotyping and competitive genetic hybridization (CHG). Bioinformatic analysis was carried out using the Genome Data Viewer (ncbi.nlm.nih.gov/genome/gdv).

Results: Karyotype was …

Vitamin C Contributes To Epigenetic Regulation Of Genes Related To Diabetic Retinopathy In Retinal Endothelial Cells, Elizabeth L. Turner, Jonathon Reynolds, Walker Kay, Marianne Becnel, Matthew Conway, Alexander Kim, John A. Kriak, Kyle B. Bills, David W. Sant

Annual Research Symposium

No abstract provided.

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 …