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Sulfhemoglobinemia And Methemoglobinemia Following Acetaminophen Overdose, Justin A Seltzer, Irvan Bubic, Garret A Winkler, Nathan A Friedman, Jessica Bagby, Christian A Tomaszewski, Richard F Clark, Allyson Kreshak, Daniel R Lasoff

Faculty, Staff and Student Publications

INTRODUCTION: Though acetaminophen overdoses are common, acetaminophen induced methemoglobinemia is rare and it is thought to be due to oxidative stress from reactive metabolites. However, few prior cases of sulfhemoglobinemia in the setting of acetaminophen overdose have been reported. We report a case of mixed methemoglobinemia and sulfhemoglobinemia in the setting of a large, isolated acetaminophen ingestion.

CASE REPORT: A 30-year-old African American male presented after intentionally ingesting 50 tablets of 500 mg acetaminophen two days prior. He was cyanotic and tachypneic. Peripheral oxygen saturation was 78 % on room air and minimally improved with high-flow oxygen. He was noted …

Dimensionality Reduction And Louvain Agglomerative Hierarchical Clustering For Cluster-Specified Frequent Biomarker Discovery In Single-Cell Sequencing Data, Soumita Seth, Saurav Mallik, Tapas Bhadra, Zhongming Zhao

Faculty, Staff and Student Publications

The major interest domains of single-cell RNA sequential analysis are identification of existing and novel types of cells, depiction of cells, cell fate prediction, classification of several types of tumor, and investigation of heterogeneity in different cells. Single-cell clustering plays an important role to solve the aforementioned questions of interest. Cluster identification in high dimensional single-cell sequencing data faces some challenges due to its nature. Dimensionality reduction models can solve the problem. Here, we introduce a potential cluster specified frequent biomarkers discovery framework using dimensionality reduction and hierarchical agglomerative clustering Louvain for single-cell RNA sequencing data analysis. First, we pre-filtered …

Explanation-Driven Deep Learning Model For Prediction Of Brain Tumour Status Using Mri Image Data, Loveleen Gaur, Mohan Bhandari, Tanvi Razdan, Saurav Mallik, Zhongming Zhao

Faculty, Staff and Student Publications

Cancer research has seen explosive development exploring deep learning (DL) techniques for analysing magnetic resonance imaging (MRI) images for predicting brain tumours. We have observed a substantial gap in explanation, interpretability, and high accuracy for DL models. Consequently, we propose an explanation-driven DL model by utilising a convolutional neural network (CNN), local interpretable model-agnostic explanation (LIME), and Shapley additive explanation (SHAP) for the prediction of discrete subtypes of brain tumours (meningioma, glioma, and pituitary) using an MRI image dataset. Unlike previous models, our model used a dual-input CNN approach to prevail over the classification challenge with images of inferior quality …

Breast Cancer Detection: Shallow Convolutional Neural Network Against Deep Convolutional Neural Networks Based Approach, Himanish Shekhar Das, Akalpita Das, Anupal Neog, Saurav Mallik, Kangkana Bora, Zhongming Zhao

Faculty, Staff and Student Publications

Introduction: Of all the cancers that afflict women, breast cancer (BC) has the second-highest mortality rate, and it is also believed to be the primary cause of the high death rate. Breast cancer is the most common cancer that affects women globally. There are two types of breast tumors: benign (less harmful and unlikely to become breast cancer) and malignant (which are very dangerous and might result in aberrant cells that could result in cancer).

Methods: To find breast abnormalities like masses and micro-calcifications, competent and educated radiologists often examine mammographic images. This study focuses on computer-aided diagnosis to help …

The Wnt/Β-Catenin Pathway Regulates Expression Of The Genes Involved In Cell Cycle Progression And Mitochondrial Oxidative Phosphorylation In The Postmitotic Cardiac Myocytes, Melis Olcum, Sirisha M Cheedipudi, Leila Rouhi, Siyang Fan, Hyun-Hwan Jeong, Zhongming Zhao, Priyatansh Gurha, Ali J Marian

Faculty, Staff and Student Publications

INTRODUCTION: Aging is associated with cardiac myocyte loss, sarcopenia, and cardiac dysfunction. Adult cardiac myocytes are postmitotic cells with an insufficient proliferative capacity to compensate for myocyte loss. The canonical WNT (cWNT) pathway is involved in the regulation of cell cycle reentry in various cell types. The effects of the cWNT pathway on the expression of genes involved in cell cycle reentry in the postmitotic cardiac myocytes are unknown.

AIM: The aim of the study was to identify genes whose expression is regulated by the β-catenin, the indispensable component to the cWNT signaling, in the postmitotic myocytes.

METHODS AND RESULTS: …

Prediction Of Intensive Care Unit Admission (>24h) After Surgery In Elective Noncardiac Surgical Patients Using Machine Learning Algorithms, Lan Lan, Fangwei Chen, Jiawei Luo, Mengjiao Li, Xuechao Hao, Yao Hu, Jin Yin, Tao Zhu, Xiaobo Zhou

Faculty, Staff and Student Publications

BACKGROUND: To develop a highly discriminative machine learning model for the prediction of intensive care unit admission (>24h) using the easily available preoperative information from electronic health records. An accurate prediction model for ICU admission after surgery is of great importance for surgical risk assessment and appropriate utilization of ICU resources.

METHOD: Data were collected retrospectively from a large hospital, comprising 135,442 adult patients who underwent surgery except for cardiac surgery between 1 January 2014, and 31 July 2018 in China. Multiple existing predictive machine learning algorithms were explored to construct the prediction model, including logistic regression, random forest, …

Prediction Of Fluid Intelligence From T1-W Mri Images: A Precise Two-Step Deep Learning Framework, Mingliang Li, Mingfeng Jiang, Guangming Zhang, Yujun Liu, Xiaobo Zhou

Faculty, Staff and Student Publications

The Adolescent Brain Cognitive Development (ABCD) Neurocognitive Prediction Challenge (ABCD-NP-Challenge) is a community-driven competition that challenges competitors to develop algorithms to predict fluid intelligence scores from T1-w MRI images. In this work, a two-step deep learning pipeline is proposed to improve the prediction accuracy of fluid intelligence scores. In terms of the first step, the main contributions of this study include the following: (1) the concepts of the residual network (ResNet) and the squeeze-and-excitation network (SENet) are utilized to improve the original 3D U-Net; (2) in the segmentation process, the pixels in symmetrical brain regions are assigned the same label; …

Distinguish Bipolar And Major Depressive Disorder In Adolescents Based On Multimodal Neuroimaging: Results From The Adolescent Brain Cognitive Development Stud, Yujun Liu, Kai Chen, Yangyang Luo, Jiqiu Wu, Qu Xiang, Li Peng, Jian Zhang, Weiling Zhao, Mingliang Li, Xiaobo Zhou

Faculty, Staff and Student Publications

BACKGROUND: Major depressive disorder and bipolar disorder in adolescents are prevalent and are associated with cognitive impairment, executive dysfunction, and increased mortality. Early intervention in the initial stages of major depressive disorder and bipolar disorder can significantly improve personal health.

METHODS: We collected 309 samples from the Adolescent Brain Cognitive Development study, including 116 adolescents with bipolar disorder, 64 adolescents with major depressive disorder, and 129 healthy adolescents, and employed a support vector machine to develop classification models for identification. We developed a multimodal model, which combined functional connectivity of resting-state functional magnetic resonance imaging and four anatomical measures of …

Multiplexed Engineering And Precision Gene Editing In Cellular Immunotherapy, Alexander Biederstädt, Gohar Shahwar Manzar, May Daher

Faculty, Staff and Student Publications

The advent of cellular immunotherapy in the clinic has entirely redrawn the treatment landscape for a growing number of human cancers. Genetically reprogrammed immune cells, including chimeric antigen receptor (CAR)-modified immune effector cells as well as T cell receptor (TCR) therapy, have demonstrated remarkable responses across different hard-to-treat patient populations. While these novel treatment options have had tremendous success in providing long-term remissions for a considerable fraction of treated patients, a number of challenges remain. Limited

Re-Thinking Therapeutic Development For Cns Metastatic Disease, Chantal Saberian, Michael A Davies

Faculty, Staff and Student Publications

There has been unprecedented progress in the development of systemic therapies for patients with metastatic melanoma over the last decade. There is now tremendous potential and momentum to further and markedly reduce the impact of this disease. However, developing more effective treatments for metastases to the CNS remains a critical challenge for patients with melanoma. Melanoma patients with active CNS metastases have largely been excluded from both early-phase and registration trials for all currently approved targeted and immune therapies for this disease. While this exclusion has generally been justified in clinical research due to concerns about poor prognosis, lack of …

Deep Learning Auto-Segmentation Of Cervical Skeletal Muscle For Sarcopenia Analysis In Patients With Head And Neck Cancer, Mohamed A Naser, Kareem A Wahid, Aaron J Grossberg, Brennan Olson, Rishab Jain, Dina El-Habashy, Cem Dede, Vivian Salama, Moamen Abobakr, Abdallah S R Mohamed, Renjie He, Joel Jaskari, Jaakko Sahlsten, Kimmo Kaski, Clifton D Fuller

Faculty, Staff and Student Publications

Background/purpose: Sarcopenia is a prognostic factor in patients with head and neck cancer (HNC). Sarcopenia can be determined using the skeletal muscle index (SMI) calculated from cervical neck skeletal muscle (SM) segmentations. However, SM segmentation requires manual input, which is time-consuming and variable. Therefore, we developed a fully-automated approach to segment cervical vertebra SM.

Materials/methods: 390 HNC patients with contrast-enhanced CT scans were utilized (300-training, 90-testing). Ground-truth single-slice SM segmentations at the C3 vertebra were manually generated. A multi-stage deep learning pipeline was developed, where a 3D ResUNet auto-segmented the C3 section (33 mm window), the middle slice of the …

Evaluation Of Deep Learning-Based Multiparametric Mri Oropharyngeal Primary Tumor Auto-Segmentation And Investigation Of Input Channel Effects: Results From A Prospective Imaging Registry, Kareem A Wahid, Sara Ahmed, Renjie He, Lisanne V Van Dijk, Jonas Teuwen, Brigid A Mcdonald, Vivian Salama, Abdallah S R Mohamed, Travis Salzillo, Cem Dede, Nicolette Taku, Stephen Y Lai, Clifton D Fuller, Mohamed A Naser

Faculty, Staff and Student Publications

Background/purpose: Oropharyngeal cancer (OPC) primary gross tumor volume (GTVp) segmentation is crucial for radiotherapy. Multiparametric MRI (mpMRI) is increasingly used for OPC adaptive radiotherapy but relies on manual segmentation. Therefore, we constructed mpMRI deep learning (DL) OPC GTVp auto-segmentation models and determined the impact of input channels on segmentation performance.

Materials/methods: GTVp ground truth segmentations were manually generated for 30 OPC patients from a clinical trial. We evaluated five mpMRI input channels (T2, T1, ADC, Ktrans, Ve). 3D Residual U-net models were developed and assessed using leave-one-out cross-validation. A baseline T2 model was compared to mpMRI models (T2 + T1, …

Epithelial Immunomodulation By Aerosolized Toll-Like Receptor Agonists Prevents Allergic Inflammation In Airway Mucosa In Mice, David L Goldblatt, Gabriella Valverde Ha, Shradha Wali, Vikram V Kulkarni, Michael K Longmire, Ana M Jaramillo, Rosha P Chittuluru, Adrienne Fouts, Margarita Martinez-Moczygemba, Jonathan T Lei, David P Huston, Michael J Tuvim, Burton F Dickey, Scott E Evans

Faculty, Staff and Student Publications

Allergic asthma is a chronic inflammatory respiratory disease associated with eosinophilic infiltration, increased mucus production, airway hyperresponsiveness, and airway remodeling. Epidemiologic data reveal that the prevalence of allergic sensitization and associated diseases has increased in the twentieth century. This has been hypothesized to be partly due to reduced contact with microbial organisms (the hygiene hypothesis) in industrialized society. Airway epithelial cells, once considered a static physical barrier between the body and the external world, are now widely recognized as immunologically active cells that can initiate, maintain, and restrain inflammatory responses, such as those that mediate allergic disease. Airway epithelial cells …

Comparison Of Three Exercise Interventions With And Without Gemcitabine Treatment On Pancreatic Tumor Growth In Mice: No Impact On Tumor Infiltrating Lymphocytes, Priti Gupta, Charles F Hodgman, Claudia Alvarez-Florez, Keri L Schadler, Melissa M Markofski, Daniel P O'Connor, Emily C Lavoy

Faculty, Staff and Student Publications

Exercise has been shown to slow pancreatic tumor growth, but whether exercise interventions of differing volume or intensity yield differential effects on tumor outcomes is unknown. In this study, we compared three exercise training interventions implemented with and without chemotherapy on pancreatic tumor growth in mice. Methods: Male C57BL/6 mice (6-8 weeks old) were subcutaneously inoculated with pancreatic ductal adenocarcinoma tumor cells (PDAC 4662). Upon tumor detection, mice received gemcitabine 15 mg/kg intraperitoneally 3 days/week and were assigned to exercise: high volume continuous exercise (HVCE), low volume continuous exercise (LVCE), high intensity interval training (HIIT), or sedentary (SED). HVCE ran …

B Cells Are Required To Generate Optimal Anti-Melanoma Immunity In Response To Checkpoint Blockade, Shubhra Singh, Jason Roszik, Neeraj Saini, Vipul Kumar Singh, Karishma Bavisi, Zhiqiang Wang, Long T Vien, Zixi Yang, Suprateek Kundu, Richard E Davis, Laura Bover, Adi Diab, Sattva S Neelapu, Willem W Overwijk, Kunal Rai, Manisha Singh

Faculty, Staff and Student Publications

Immunotherapies such as checkpoint blockade therapies are known to enhance anti-melanoma CD8+ T cell immunity, but only a fraction of patients treated with these therapies achieve durable immune response and disease control. It may be that CD8+ T cells need help from other immune cells to generate effective and long-lasting anti-tumor immunity or that CD8+ T cells alone are insufficient for complete tumor regression and cure. Melanoma contains significant numbers of B cells; however, the role of B cells in anti-melanoma immunity is controversial. In this study, B16 melanoma mouse models were used to determine the role of B cells …

Automated Segmentation Of Colorectal Liver Metastasis And Liver Ablation On Contrast-Enhanced Ct Images, Brian M Anderson, Bastien Rigaud, Yuan-Mao Lin, A Kyle Jones, Hynseon Christine Kang, Bruno C Odisio, Kristy K Brock

Faculty, Staff and Student Publications

Objectives: Colorectal cancer (CRC), the third most common cancer in the USA, is a leading cause of cancer-related death worldwide. Up to 60% of patients develop liver metastasis (CRLM). Treatments like radiation and ablation therapies require disease segmentation for planning and therapy delivery. For ablation, ablation-zone segmentation is required to evaluate disease coverage. We hypothesize that fully convolutional (FC) neural networks, trained using novel methods, will provide rapid and accurate identification and segmentation of CRLM and ablation zones.

Methods: Four FC model styles were investigated: Standard 3D-UNet, Residual 3D-UNet, Dense 3D-UNet, and Hybrid-WNet. Models were trained on 92 patients from …

The Other Legacy Of Qasim Amin: The View From 1908, Hoda Yousef

Faculty Publications

No abstract provided.

The Religious Communication Approach And Political Behavior, Paul Djupe, Jacob R. Neiheisel

Faculty Publications

No abstract provided.

Book Review: Transforming Print: Collection Development And Management For Our Connected Future, Debra Andreadis

Faculty Publications

No abstract provided.

Divine Attribution? The Interaction Of Religious And Secular Beliefs On Climate Change Attitudes, Paul Djupe, Ryan P. Burge

Faculty Publications

No abstract provided.

Effects Of Co-Incubation Of Lps-Stimulated Raw 264.7 Macrophages On Leptin Production By 3t3-L1 Adipocytes: A Method For Co-Incubating Distinct Adipose Tissue Cell Lines, Cristina Caldari, Jordan Beck

Faculty Publications

No abstract provided.

Both Consumptive And Non-Consumptive Effects Of Predators Impact Mosquito Populations And Have Implications For Disease Transmission, Marie C. Russell, Catherine M. Herzog, Zachary Gajewski, Chloe Ramsay, Andy Mccall

Faculty Publications

No abstract provided.

Toward Liquid Cell Quantum Sensing: Ytterbium Complexes With Ultra-Narrow Absorption, Ashley J. Shin, Changling Zhao, Yi Shen, Claire E. Dickerson, Timothy Luke Atallah

Faculty Publications

No abstract provided.

Local Biodiversity Change Reflects Interactions Among Changing Abundance, Evenness, And Richness, Shane A. Blowes, Gergana N. Daskalova, Maria Dornelas, Thore Engel, Nicholas J. Gotelli, Anne E. Magurran, Ines S. Martins, Brian Mcgill, Daniel J. Mcglinn, Alban Sagouis, Hideyasu Shimadzu, Sarah R. Supp, Jonathan M. Chase

Faculty Publications

No abstract provided.

“You Don’T Belong In Nashville!”: Politics, Country Music, And The Reception Of Robert Altman’S Nashville, Dan Blim

Faculty Publications

Robert Altman’s film Nashville (1975) generated a prodigious amount of press commentary following its release. Early on, critics praised the film, but a disappointing box office led many to assume a split between big-city liberal audiences and small-town conservative audiences. Subsequent press coverage connected this divide to both the film’s politics and its use and portrayal of country music, as political pundits, music critics, country music stars, and general audiences weighed in. This essay situates the reception of the film within a shifting country music industry, which was growing increasingly aligned with the Republican Party and increasingly suspicious of new …

Growth In Snapping Turtle, Chelydra Serpentina (Testudines: Chelydridae) In Northern Indiana, John B. Iverson, Geoffrey R. Smith, Jessica E. Rettig

Faculty Publications

No abstract provided.

Exploring The Sexual Literacies Of Denison University Students, Ellie Gutmann

Student Scholarship

No abstract provided.

Friendship In College Students: Examining Changes In Time Perspective And Emotional Closeness, Blake H. Glatley

Student Scholarship

No abstract provided.

Meet The Staff

The Synapse: Intercollegiate science magazine

No abstract provided.

Left On Red: The Chemistry Of Color, Rebecca Fenselau, Kayla Bertholf

The Synapse: Intercollegiate science magazine

No abstract provided.