Life Sciences Commons^™

Accelerating Artificial Intelligence: How Federated Learning Can Protect Privacy, Facilitate Collaboration, And Improve Outcomes, Malhar Patel, Ittai Dayan, Elliot K Fishman, Mona Flores, Fiona J Gilbert, Michal Guindy, Eugene J Koay, Michael Rosenthal, Holger R Roth, Marius G Linguraru

Faculty, Staff and Student Publications

Cross-institution collaborations are constrained by data-sharing challenges. These challenges hamper innovation, particularly in artificial intelligence, where models require diverse data to ensure strong performance. Federated learning (FL) solves data-sharing challenges. In typical collaborations, data is sent to a central repository where models are trained. With FL, models are sent to participating sites, trained locally, and model weights aggregated to create a master model with improved performance. At the 2021 Radiology Society of North America's (RSNA) conference, a panel was conducted titled "Accelerating AI: How Federated Learning Can Protect Privacy, Facilitate Collaboration and Improve Outcomes." Two groups shared insights: researchers from …

Mechanisms Of Resistance To Egfr-Targeted Therapies In Colorectal Cancer: More Than Just Genetics, Christine Parseghian, Madhulika Eluri, Scott Kopetz, Kanwal Raghav

Faculty, Staff and Student Publications

The development of acquired resistance to anti-EGFR therapies remains poorly understood, with most research to date exploring, and trying to overcome, various genomic mechanisms of resistance. However, recent work supports a model of resistance whereby transcriptomic mechanisms of resistance predominate in the presence of active cytotoxic chemotherapy combined with anti-EGFR therapy in the first-line setting, with a greater predominance of acquired MAPK mutations after single-agent anti-EGFR therapy in the later-line setting. The proposed model has implications for prospective studies evaluating anti-EGFR rechallenge strategies guided by acquired MAPK mutations and highlights the need to address transcriptional mechanisms of resistance.

Radiotherapy Reimagined: Integrating Nanomedicines Into Radiotherapy Clinical Trials, Allison N Duross, Jack Phan, Alexander J Lazar, Joshua M Walker, Alexander R Guimaraes, Carole Baas, Sunil Krishnan, Charles R Thomas, Conroy Sun, Alexander F Bagley

Faculty, Staff and Student Publications

Radioenhancing nanoparticles (NPs) are being evaluated in ongoing clinical trials for various cancers including head and neck, lung, esophagus, pancreas, prostate, and soft tissue sarcoma. Supported by decades of preclinical investigation and recent randomized trial data establishing clinical activity, these agents are poised to influence future multimodality treatment paradigms involving radiotherapy. Although the physical interactions between NPs and ionizing radiation are well characterized, less is known about how these agents modify the tumor microenvironment, particularly regarding tumor immunogenicity. In this review, we describe the key multidisciplinary considerations related to radiation, surgery, immunology, and pathology for designing radioenhancing NP clinical trials. …

Nitrite Cycling In The Primary Nitrite Maxima Of The Eastern Tropical North Pacific, Nicole M. Travis, Colette L. Kelly, Margaret R. Mulholland, Karen L. Casciotti

OES Faculty Publications

The primary nitrite maximum (PNM) is a ubiquitous feature of the upper ocean, where nitrite accumulates in a sharp peak at the base of the euphotic zone. This feature is situated where many chemical and hydrographic properties have strong gradients and the activities of several microbial processes overlap. Near the PNM, four major microbial processes are active in nitrite cycling: ammonia oxidation, nitrite oxidation, nitrate reduction and nitrite uptake. The first two processes are mediated by the nitrifying archaeal/bacterial community, while the second two processes are primarily conducted by phytoplankton. The overlapping spatial habitats and substrate requirements for these microbes …

Biophysical Interactions Control The Progression Of Harmful Algal Blooms In Chesapeake Bay: A Novel Lagrangian Particle Tracking Model With Mixotrophic Growth And Vertical Migration, Jilian Xiong, Jian Shen, Qubin Qin, Michelle C. Tomlinson, Yinglong J. Zhang, Xun Cai, Fei Yi, Linlin Cui, Margaret R. Mulholland

OES Faculty Publications

Climate change and nutrient pollution contribute to the expanding global footprint of harmful algal blooms. To better predict their spatial distributions and disentangle biophysical controls, a novel Lagrangian particle tracking and biological (LPT-Bio) model was developed with a high-resolution numerical model and remote sensing. The LPT-Bio model integrates the advantages of Lagrangian and Eulerian approaches by explicitly simulating algal bloom dynamics, algal biomass change, and diel vertical migrations along predicted trajectories. The model successfully captured the intensity and extent of the 2020 Margalefidinium polykrikoides bloom in the lower Chesapeake Bay and resolved fine-scale structures of bloom patchiness, demonstrating a reliable …

The Effect Of A 5-Week Concurrent Training Program On Acft Scores, Ruck March Times, And Aerobic Capacity In Army Rotc Cadets, Cody Durbin

Dissertations and Theses @ UNI

Most Army ROTC programs conduct physical training (PT) only 3 days per week and no study has directly compared the effects of conducting PT 5 days per week on ACFT scores, ruck march performance, and aerobic capacity. Past research has indicated greater performance adaptations with a concurrent training program and some research has shown that current ROTC PT programs may not be optimal in physically preparing ROTC cadets. Purpose: To examine the effectiveness of a 5-day per week periodized tactical strength and conditioning program on ACFT scores, and aerobic capacity in Army ROTC cadets. Methods: Eight ROTC cadets from UNI …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

A Single-Cell Atlas Of Bovine Skeletal Muscle Reveals Mechanisms Regulating Intramuscular Adipogenesis And Fibrogenesis, Leshan Wang, Peidong Gao, Chaoyag Li, Qianglin Liu, Zeyang Yao, Yuxia Li, Xujia Zhang, Jiangwen Sun, Constantine Simintiras, Matthew Welborn, Kenneth Mcmillin, Stephanie Oprescu, Shihuan Kuang, Xing Fu

Computer Science Faculty Publications

Background: Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis.

Methods: Skeletal muscle single-cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell-cell communication analysis, were performed to elucidate …

Integrative Big Transcriptomics Data Analysis Implicates Crucial Role Of Muc13 In Pancreatic Cancer, Anupam Dhasmana, Swati Dhasmana, Shivangi Agarwal, Sheema Khan, Shafiul Haque, Meena Jaggi, Murali M. Yallapu, Subhash C. Chauhan

School of Medicine Publications

Big data analysis holds a considerable influence on several aspects of biomedical health science. It permits healthcare providers to gain insights from large and complex datasets, leading to improvements in the understanding, diagnosis, medication, and restraint of pathological conditions including cancer. The incidences of pancreatic cancer (PanCa) are sharply rising, and it will become the second leading cause of cancer related deaths by 2030. Various traditional biomarkers are currently in use but are not optimal in sensitivity and specificity. Herein, we determine the role of a new transmembrane glycoprotein, MUC13, as a potential biomarker of pancreatic ductal adenocarcinoma (PDAC) …

Inter-Session Repeatability Of Marker-Less Motion Capture Of Treadmill Running Gait, Matthew F. Moran, Isabella C. Rogler, Justin C. Wager

Exercise Science Faculty Publications

Twenty-one experienced runners completed three treadmill running sessions on different days. Each session consisted of three consecutive 2 min trials at self-selected speeds (RPE = 3, 5, and 7). An eight-camera marker-less motion capture system and instrumented pressure treadmill (TM) collected data over the final ~25 s at each speed. Lower extremity joint angles (ankle, knee, and hip) and segmental angles (pelvis and trunk) were computed for each trial with foot contact and toe off being kinematically determined. Spatiotemporal metrics (ground contact time, step length, and cadence) were measured via TM and compared to their kinematically derived counterparts. All spatiotemporal …

The Effects Of Accentuated Eccentric Loading On Barbell And Trap Bar Countermovement Jumps, Christopher B. Taber, Calin Butler, Victoria Dabek, Benjamin Kochan, Kyle Mccormick, Emily Petro, Timothy J. Suchomel, Justin Merrigan

Exercise Science Faculty Publications

This study examined effects of accentuated eccentric loading (AEL) on barbell and trap bar loaded countermovement jumps (LCMJ). Twenty-one subjects (16 male, 5 female; Age: 23.5 ± 1.8 years; Body mass: 81.4 ± 10.6 kg; Height: 176.9 ± 7.2 cm; Training age: 7.1 ± 2.6 years) participated in this study. Upon establishing one repetition maximum and baseline jumping conditions, three experimental loading sessions were completed in random order. Barbell and trap bar LCMJ were performed with a spectrum of fixed loads from 20-50 kg during control conditions and with additional AEL loads of 10, 20, or 30 kg for experimental …

Validity And Reliability Of A Computer Vision System To Determine Bar Displacement And Velocity, Christopher Taber, Emma Patterson, Jui Shah, Padraig Francis, Justin C. Wager

Exercise Science Faculty Publications

This study examined the validity and reliability of a video-based smartphone application (VBA) to measure displacement and velocity in the barbell bench press, back squat, and deadlift. Nine resistance-trained subjects (three females; six males; age: 24.2±4.2 years; height 175.8±8.1 cm; body mass 87.2±18.2kg) completed two test-retest sessions for the barbell bench press, back squat, and deadlift one week apart. Eight repetitions were completed for the bench press, back squat, and deadlift with a load of 40kg and completed at fast and slow velocities. Bar displacement and average velocity were measured simultaneously using 3-D motion capture (MC) and a VBA. The …

Scale-Free Behavioral Dynamics Directly Linked With Scale-Free Cortical Dynamics, Sabrina A. Jones, Jacob H. Barfield, V. Kindler Norman, Woodrow L. Shew

Physics Faculty Publications and Presentations

Naturally occurring body movements and collective neural activity both exhibit complex dynamics, often with scale-free, fractal spatiotemporal structure. Scale-free dynamics of both brain and behavior are important because each is associated with functional benefits to the organism. Despite their similarities, scale-free brain activity and scale-free behavior have been studied separately, without a unified explanation. Here, we show that scale-free dynamics of mouse behavior and neurons in the visual cortex are strongly related. Surprisingly, the scale-free neural activity is limited to specific subsets of neurons, and these scale-free subsets exhibit stochastic winner-take-all competition with other neural subsets. This observation is inconsistent …