Digital Commons Network^™

The Response Of Dual-Leucine Zipper Kinase (Dlk) To Nocodazole: Evidence For A Homeostatic Cytoskeletal Repair Mechanism, Laura Devault, Chase Mateusiak, John Palucki, Michael Brent, Jeffrey Milbrandt, Aaron Diantonio

2020-Current year OA Pubs

Genetic and pharmacological perturbation of the cytoskeleton enhances the regenerative potential of neurons. This response requires Dual-leucine Zipper Kinase (DLK), a neuronal stress sensor that is a central regulator of axon regeneration and degeneration. The damage and repair aspects of this response are reminiscent of other cellular homeostatic systems, suggesting that a cytoskeletal homeostatic response exists. In this study, we propose a framework for understanding DLK mediated neuronal cytoskeletal homeostasis. We demonstrate that low dose nocodazole treatment activates DLK signaling. Activation of DLK signaling results in a DLK-dependent transcriptional signature, which we identify through RNA-seq. This signature includes genes likely …

Leveraging Murine Models Of The Neurofibromatosis Type 1 Cancer Predisposition Syndrome To Elucidate The Cellular Circuits That Drive Pediatric Low-Grade Glioma Formation And Progression, David H Gutmann

2020-Current year OA Pubs

Brain tumors are the leading cause of cancer-related death in children, where low-grade gliomas (LGGs) predominate. One common hereditary cause for LGGs involves neurofibromatosis-1 (NF1) gene mutation, as seen in individuals with the NF1 cancer predisposition syndrome. As such, children with NF1 are at increased risk of developing LGGs of the optic pathway, brainstem, cerebellum, and midline brain structures. Using genetically engineered mouse models, studies have revealed both cell-intrinsic (MEK signaling) and stromal dependencies that underlie their formation and growth. Importantly, these dependencies represent vulnerabilities against which targeted agents can be used for preclinical investigation prior to clinical translation.

Intermuscular Coherence As An Early Biomarker For Amyotrophic Lateral Sclerosis: The Protocol For A Prospective, Multicenter Study, Naoum P Issa, Serdar Aydin, Eric Polley, Nathan Carberry, Mark A. Garret, Sean Smith, Ali A. Habib, Nicholas W. Baumgartner, Betty Soliven, Kourosh Rezania

2020-Current year OA Pubs

OBJECTIVE: To describe the protocol of a prospective study to test the validity of intermuscular coherence (IMC) as a diagnostic tool and biomarker of upper motor neuron degeneration in amyotrophic lateral sclerosis (ALS).

METHODS: This is a multicenter, prospective study. IMC of muscle pairs in the upper and lower limbs is gathered in ∼650 subjects across three groups using surface electrodes and conventional electromyography (EMG) machines. The following subjects will be tested: 1) neurotypical controls; 2) patients with symptomatology suggestive for early ALS but not meeting probable or definite ALS by Awaji Criteria; 3) patients with a known ALS mimic. …

Advancements And Challenges In Additively Manufactured Functionally Graded Materials: A Comprehensive Review, Suhas Alkunte, Ismail Fidan, Vivekanand Naikwadi, Shamil Gudavasov, Mohammad Alshaikh Ali, Mushfig Mahmudov, Seymur Hasanov, Muralimohan Cheepu

Engineering Technology Faculty Publications

This paper thoroughly examines the advancements and challenges in the field of additively manufactured Functionally Graded Materials (FGMs). It delves into conceptual approaches for FGM design, various manufacturing techniques, and the materials employed in their fabrication using additive manufacturing (AM) technologies. This paper explores the applications of FGMs in diverse fields, including structural engineering, automotive, biomedical engineering, soft robotics, electronics, 4D printing, and metamaterials. Critical issues and challenges associated with FGMs are meticulously analyzed, addressing concerns related to production and performance. Moreover, this paper forecasts future trends in FGM development, highlighting potential impacts on diverse industries. The concluding section summarizes …

Energy Efficiency In Additive Manufacturing: Condensed Review, Ismail Fidan, Vivekanand Naikwadi, Suhas Alkunte, Roshan Mishra, Khalid Tantawi

Engineering Technology Faculty Publications

Today, it is significant that the use of additive manufacturing (AM) has growing in almost every aspect of the daily life. A high number of sectors are adapting and implementing this revolutionary production technology in their domain to increase production volumes, reduce the cost of production, fabricate light weight and complex parts in a short period of time, and respond to the manufacturing needs of customers. It is clear that the AM technologies consume energy to complete the production tasks of each part. Therefore, it is imperative to know the impact of energy efficiency in order to economically and properly …

Cep120 Is Essential For Kidney Stromal Progenitor Cell Growth And Differentiation, Ewa Langner, Tao Cheng, Eirini Kefaloyianni, Charles Gluck, Baolin Wang, Moe R Mahjoub

2020-Current year OA Pubs

Mutations in genes that disrupt centrosome structure or function can cause congenital kidney developmental defects and lead to fibrocystic pathologies. Yet, it is unclear how defective centrosome biogenesis impacts renal progenitor cell physiology. Here, we examined the consequences of impaired centrosome duplication on kidney stromal progenitor cell growth, differentiation, and fate. Conditional deletion of the ciliopathy gene Cep120, which is essential for centrosome duplication, in the stromal mesenchyme resulted in reduced abundance of interstitial lineages including pericytes, fibroblasts and mesangial cells. These phenotypes were caused by a combination of delayed mitosis, activation of the mitotic surveillance pathway leading to apoptosis, …

Non-Invasive Auricular Vagus Nerve Stimulation For Subarachnoid Hemorrhage (Navsah): Protocol For A Prospective, Triple-Blinded, Randomized Controlled Trial, Anna Huguenard, Gansheng Tan, Gabrielle Johnson, Markus Adamek, Andrew Coxon, Terrance Kummer, Joshua Osbun, Ananth Vellimana, David Limbrick, Gregory Zipfel, Peter Brunner, Eric Leuthardt

2020-Current year OA Pubs

BACKGROUND: Inflammation has been implicated in driving the morbidity associated with subarachnoid hemorrhage (SAH). Despite understanding the important role of inflammation in morbidity following SAH, there is no current effective way to modulate this deleterious response. There is a critical need for a novel approach to immunomodulation that can be safely, rapidly, and effectively deployed in SAH patients. Vagus nerve stimulation (VNS) provides a non-pharmacologic approach to immunomodulation, with prior studies demonstrating VNS can reduce systemic inflammatory markers, and VNS has had early success treating inflammatory conditions such as arthritis, sepsis, and inflammatory bowel diseases. The aim of the Non-invasive …

Promoting Understanding Of Three Dimensions Of Science Learning Plus Nature Of Science Using Phenomenon-Based Learning, Maryam Saberi, Noushin Nouri

Teaching and Learning Faculty Publications

The utilization of phenomenon-based learning (PhBL) for science instruction remains limited despite its alignment with the goals outlined in the Next Generation Science Standards (NGSS; NGSS Lead States, 2013) due to the lack of exemplary materials and inadequate training opportunities for teachers. The aim of this article is to illustrate the steps of the PhBL method by providing an exploratory learning experience as it was implemented in a preservice setting. In this study, we provide an innovative perspective by illuminating how this kind of instruction can be used as a context to explicitly discuss the three dimensions of learning (i.e., …

Predicting Medical Laboratory Science Certification Examination Success: The Role Of Affective Performance, Jed Doxtater, Charlie P. Cruz

Health Professions Education

Purpose: This study aimed at associating the Board of Certification (BOC) pass rates with the affective performances of Medical Laboratory Science (MLS) students.

Method: Retrospective data analysis on the BOC pass rates, advanced clinical practicum (ACP) routes, affective assessment, grade point average (GPA), highest academic degree (HAD) upon graduation, years to degree completion, and gender was conducted on thirty-three (33) MLS graduates between 2017 and 2022 from a higher education institution (HEI) in Wyoming.

Results: Based on the Chi-square (X2) test, BOC was associated with HAD and affective performance, but no significant statistical association was established between …

The Role Of Mek Inhibition In Pediatric Low-Grade Gliomas, Shehryar R Sheikh, Laura J Klesse, Ross Mangum, Ashley Bui, Benjamin I Siegel, Mohamed S Abdelbaki, Neha J Patel

2020-Current year OA Pubs

Pediatric low-grade gliomas (pLGGs) are the most common brain tumors in children. Many patients with unresectable tumors experience recurrence or long-term sequelae from standard chemotherapeutics. This mini-review explores the emerging role of MEK inhibitors in the management of pLGGs, highlighting their potential to transform current treatment paradigms. We review the molecular basis for therapeutic MEK inhibition in the context of pLGG, provide an evidence base for the use of the major MEK inhibitors currently available in the market for pLGG, and review the challenges in the use of MEKi inhibitors in this population.

Delayed Macrophage Targeting By Clodronate Liposomes Worsens The Progression Of Cytokine Storm Syndrome, Kunjan Khanna, Emily Eul, Hui Yan, Roberta Faccio

2020-Current year OA Pubs

Excessive macrophage activation and production of pro-inflammatory cytokines are hallmarks of the Cytokine Storm Syndrome (CSS), a lethal condition triggered by sepsis, autoimmune disorders, and cancer immunotherapies. While depletion of macrophages at disease onset protects from lethality in an infection-induced CSS murine model, patients are rarely diagnosed early, hence the need to characterize macrophage populations during CSS progression and assess the therapeutic implications of macrophage targeting after disease onset. In this study, we identified MHCII

Campylobacter Colonization And Undernutrition In Infants In Rural Eastern Ethiopia — A Longitudinal Community-Based Birth Cohort Study, Dehao Chen, Nurmohammad Shaik, Mark J Manary, Et Al.

2020-Current year OA Pubs

BACKGROUND:

METHODS: We followed a birth cohort of 106 infants in rural smallholder households in eastern Ethiopia up to 13 months of age. We measured anthropometry, surveyed sociodemographic determinants, and collected stool and urine samples. A short survey was conducted during monthly visits, infant stool samples were collected, and

RESULTS: The

CONCLUSION: This study found that most determinants associated with increased

Intrusive Traumatic Re-Experiencing Domain: Functional Connectivity Feature Classification By The Enigma Ptsd Consortium, Benjamin Suarez-Jimenez, Amit Lazarov, Sigal Zilcha-Mano, Xi Zhu, Yoojean Kim, Jacklynn M. Fitzgerald

Psychology Faculty Research and Publications

Background

Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity connectivity perspective.

Methods

Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium (n = 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data. We assessed the …

Exploring The Association Between Structural Racism And Mental Health: Geospatial And Machine Learning Analysis, Fahimeh Mohebbi, Amir Masoud Forati, Lucas Torres, Terri A. Deroon-Cassini, Jennifer Harris, Carissa W. Tomas, John R. Mantsch, Rina Ghose

Psychology Faculty Research and Publications

Background:

Structural racism produces mental health disparities. While studies have examined the impact of individual factors such as poverty and education, the collective contribution of these elements, as manifestations of structural racism, has been less explored. Milwaukee County, Wisconsin, with its racial and socioeconomic diversity, provides a unique context for this multifactorial investigation.

Objective:

This research aimed to delineate the association between structural racism and mental health disparities in Milwaukee County, using a combination of geospatial and deep learning techniques. We used secondary data sets where all data were aggregated and anonymized before being released by federal agencies.

Methods:

We …

Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong

Computer Science Faculty Publications

Neurological disabilities cause diverse health and mental challenges, impacting quality of life and imposing financial burdens on both the individuals diagnosed with these conditions and their caregivers. Abnormal brain activity, stemming from malfunctions in the human nervous system, characterizes neurological disorders. Therefore, the early identification of these abnormalities is crucial for devising suitable treatments and interventions aimed at promoting and sustaining quality of life. Electroencephalogram (EEG), a non-invasive method for monitoring brain activity, is frequently employed to detect abnormal brain activity in neurological and mental disorders. This study introduces an approach that extends the understanding and identification of neurological disabilities …

Identifying New Cancer Genes Based On The Integration Of Annotated Gene Sets Via Hypergraph Neural Networks, Chao Deng, Hong-Dong Li, Li-Shen Zhang, Yiwei Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

Results

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of …

Can Large Language Models Discern Evidence For Scientific Hypotheses? Case Studies In The Social Sciences, Sai Koneru, Jian Wu, Sarah Rajtmajer

Computer Science Faculty Publications

Hypothesis formulation and testing are central to empirical research. A strong hypothesis is a best guess based on existing evidence and informed by a comprehensive view of relevant literature. However, with exponential increase in the number of scientific articles published annually, manual aggregation and synthesis of evidence related to a given hypothesis is a challenge. Our work explores the ability of current large language models (LLMs) to discern evidence in support or refute of specific hypotheses based on the text of scientific abstracts. We share a novel dataset for the task of scientific hypothesis evidencing using community-driven annotations of studies …

Hite: A Fast And Accurate Dynamic Boundary Adjustment Approach For Full-Length Transposable Element Detection And Annotation, Kang Hu, Peng Ning, Minghua Xu, You Zou, Jianye Chang, Xin Gao, Yaohang Li, Jue Ruan, Bin Hu, Jianxin Wang

Computer Science Faculty Publications

Recent advancements in genome assembly have greatly improved the prospects for comprehensive annotation of Transposable Elements (TEs). However, existing methods for TE annotation using genome assemblies suffer from limited accuracy and robustness, requiring extensive manual editing. In addition, the currently available gold-standard TE databases are not comprehensive, even for extensively studied species, highlighting the critical need for an automated TE detection method to supplement existing repositories. In this study, we introduce HiTE, a fast and accurate dynamic boundary adjustment approach designed to detect full-length TEs. The experimental results demonstrate that HiTE outperforms RepeatModeler2, the state-of-the-art tool, across various species. Furthermore, …

Flexible Fitting Of Alphafold2-Predicted Models To Cryo-Em Density Maps Using Elastic Network Models: A Methodological Affirmation, Maytha Alshammari, Jing He, Willy Wriggers

Computer Science Faculty Publications

Motivation: This study investigates the flexible refinement of AlphaFold2 models against corresponding cryo-electron microscopy (cryo-EM) maps using normal modes derived from elastic network models (ENMs) as basis functions for displacement. AlphaFold2 generally predicts highly accurate structures, but 18 of the 137 models of isolated chains exhibit a TM-score below 0.80. We achieved a significant improvement in four of these deviating structures and used them to systematically optimize the parameters of the ENM motion model.

Results: We successfully refined four AlphaFold2 models with notable discrepancies: lipid-preserved respiratory supercomplex (TM-score increased from 0.52 to 0.69), flagellar L-ring protein (TM-score increased from 0.53 …

Sccad: Cluster Decomposition-Based Anomaly Detection For Rare Cell Identification In Single-Cell Expression Data, Yunpei Xu, Shaokai Wang, Qilong Feng, Jiazhi Xia, Yaohang Li, Hong-Dong Li, Jianxin Wang

Computer Science Faculty Publications

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate …

Remote Multi-Person Heart Rate Monitoring With Smart Speakers: Overcoming Separation Constraint, Ngoc Doan Thu Tran, Dong Ma, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Heart rate is a key vital sign that can be used to understand an individual’s health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present …

Lithography-Free Highly Sensitive Detection Of Glucose Based On Colloidal Spheres, Habibe Durmaz

Turkish Journal of Physics

Diabetes has emerged as a global health crisis, with a substantial increase in prevalence and associated healthcare costs. The urgency for early diagnosis to prevent complications has fueled research into advanced biosensing technologies. Plasmonic sensors, leveraging localized surface plasmon resonance (LSPR), have gained prominence for their sensitivity. This study explores a metamaterial-based sensor platform comprising nanospheres fabricated through colloidal lithography. A comprehensive numerical and experimental analysis of the designed metamaterial-based perfect absorber is presented, focusing on the spectral response at the resonance frequency of 525 nm. Finite-difference time-domain (FDTD) simulations reveal the field and charge distributions, enabling a systematic exploration …

Immunohistochemical Analysis Of Dentigerous Cysts And Odontogenic Keratocysts Associated With Impacted Third Molars—A Systematic Review, Luis Eduardo Almeida, David Lloyd, Daniel Boettcher, Olivia Kraft, Samuel Zammuto

School of Dentistry Faculty Research and Publications

Objective: This systematic review investigates the diagnostic, prognostic, and therapeutic implications of immunohistochemical markers in dentigerous cysts (DCs) and odontogenic keratocysts (OKCs) associated with impacted third molars.

Materials and Methods: A comprehensive search strategy was employed across major databases including MEDLINE/PubMed, EMBASE, and Web of Science, from the inception of the databases to March 2024. Keywords and Medical Subject Heading (MeSH) terms such as “dentigerous cysts”, “odontogenic keratocysts”, “immunohistochemistry”, “Ki-67”, and “p53” were used. The PRISMA 2020 guidelines were followed to ensure methodological rigor. Inclusion criteria encompassed studies on humans and animals providing definitive diagnoses or specific signs and symptoms …

Bayesian Rare Variant Analysis Identifies Novel Schizophrenia Putative Risk Genes, Shengtong Han

School of Dentistry Faculty Research and Publications

The genetics of schizophrenia is so complex that it involves both common variants and rare variants. Rare variant association studies of schizophrenia are challenging because statistical methods for rare variant analysis are under-powered due to the rarity of rare variants. The recent Schizophrenia Exome meta-analysis (SCHEMA) consortium, the largest consortium in this field to date, has successfully identified 10 schizophrenia risk genes from ultra-rare variants by burden test, while more risk genes remain to be discovered by more powerful rare variant association test methods. In this study, we use a recently developed Bayesian rare variant association method that is powerful …

Preservice Eal/D Teachers’ Relational Agency During Online Paired Practicum, Hongzhi Yang, Andrew Ross

Australian Journal of Teacher Education

There is scant research on preservice English as an additional language or dialect (EAL/D) teachers’ paired practicums in an online context. Underpinned by Cultural Historical Activity Theory, this paper explores how preservice EAL/D teachers exercise their relational agency during online paired practicums. Data were collected from five preservice EAL/D teachers’ weekly journals written during their paired practicums and interviews after they completed their paired practicums. Following the key components of relational agency, the thematic analysis highlights the dialectical relationship between preservice teachers’ relational agency and different types of collaboration, evidenced by the formation of mutual objects, tool mediation, and shared …

Genetic Risk For Alzheimer’S Disease Alters Perceived Executive Dysfunction In Cognitively Healthy Middle-Aged And Older Adults, Sarah A. Evans, Elizabeth R. Paitel, Riya Bhasin, Kristy A. Nielson

Psychology Faculty Research and Publications

Background:

Subjective cognitive complaints (SCC) may be an early indicator of future cognitive decline. However, findings comparing SCC and objective cognitive performance have varied, particularly in the memory domain. Even less well established is the relationship between subjective and objective complaints in non-amnestic domains, such as in executive functioning, despite evidence indicating very early changes in these domains. Moreover, particularly early changes in both amnestic and non-amnestic domains are apparent in those carrying the Apolipoprotein-E ɛ4 allele, a primary genetic risk for Alzheimer’s disease (AD).

Objective:

This study investigated the role of the ɛ4 allele in the consistency between subjective …

Pathophysiology Of Pain And Mechanisms Of Neuromodulation: A Narrative Review (A Neuron Project)., Marcin Karcz, Alaa Abd-Elsayed, Krishnan Chakravarthy, Mansoor M Aman, Natalie Strand, Mark N Malinowski, Usman Latif, David Dickerson, Tolga Suvar, Timothy Lubenow, Evan Peskin, Ryan D'Souza, Eric Cornidez, Andrew Dudas, Christopher Lam, Michael Farrell Ii, Geum Yeon Sim, Mohamad Sebai, Rosa Garcia, Lucas Bracero, Yussr Ibrahim, Syed Jafar Mahmood, Marco Lawandy, Daniel Jimenez, Leili Shahgholi, Kamil Sochacki, Mohamed Ehab Ramadan, Vinicius Tieppo Francio, Dawood Sayed, Timothy Deer

Neuroscience Articles

Pain serves as a vital innate defense mechanism that can significantly impact an individual's quality of life. Understanding the physiological effects of pain well plays an important role in developing novel pain treatments. Nociceptor neurons play a key role in pain and inflammation. Interactions between nociceptors and the immune system occur both at the site of injury and within the central nervous system. Modulating chemical mediators and nociceptor activity offers promising new approaches to pain management. Essentially, the sensory nervous system is essential for modulating the body's protective response, making it critical to understand these interactions to discover new pain …

The Complexities Of Disproportionality In A Large Urban School District: A Look Into District Interventions And Identification Processes, Linnie Tennile Tarrant

Dissertations of Practice

This study delves into the implementation of the multi-tiered system of supports (MTSS) and the special education identification process in a large urban school district in Illinois, with a specific focus on disproportionality in special education referrals. The district has been identified as disproportionate in categorizing African American students under the emotional disturbance (ED) category since 2014. Using a grounded theory approach, interviews were conducted with ten building-level administrators to investigate the consistency of MTSS implementation and the process of identifying students for special education services. Data was collected through in-depth interviews, and themes were analyzed using open, axial, and …

Using A Degree-Based Network Model To Understand And Control Traffic Jams In The Atlanta Metropolitan Area, Ian Salamone-Lent, Theresa Washington, Asma Azizi

The Kennesaw Journal of Undergraduate Research

Traffic congestion is an enduring problem for major metropolitan areas, such as Atlanta, GA. Our goal is to understand the nature of traffic congestion patterns in the highway system of Cobb County in Atlanta, GA. We created a road network representative of the Cobb County highway system and then superimposed a degree-based SIR model to simulate traffic congestion on that network. The model’s parameters, propagation and dissipation rates, were estimated using empirical traffic data, which are vehicles’ speed time series and speed limit of each road in the network. We then conducted a local sensitivity analysis of the model’s key …

From Mind To Matter: Patterns Of Innovation In The Archaeological Record And The Ecology Of Social Learning, Kathryn Demps, Nicole M. Herzog, Matt Clark

Anthropology Faculty Publications and Presentations

Archaeology and cultural evolution theory both predict that environmental variation and population size drive the likelihood of inventions (via individual learning) and their conversion to population-wide innovations (via social uptake). We use the case study of the adoption of the bow and arrow in the Great Basin to infer how patterns of cultural variation, invention, and innovation affect investment in new technologies over time and the conditions under which we could predict cultural innovation to occur. Using an agent-based simulation to investigate the conditions that manifest in the innovation of technology, we find the following: (1) increasing ecological variation results …