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Advancements In Sarcoma- And Nerve-Specific Fluorescence Imaging For Surgical Guidance, Kendra A. Hebert 2024 Dartmouth College

Advancements In Sarcoma- And Nerve-Specific Fluorescence Imaging For Surgical Guidance, Kendra A. Hebert

Dartmouth College Master’s Theses

Fluorescence guided surgery (FGS) is an evolving field that aims to improve patient outcomes by using fluorophores to identify important tissues during surgery, such as tumors and nerves. In this thesis work, we explored different methods of identifying nerve and tumor tissues for FGS and a novel fluorescence-based method to determine the depths of these structures.

Researchers have explored using fluorescence guided surgery for surgical resection of cancerous tissues, including recent work by our group focusing on identifying soft tissue sarcomas with ABY-029, an epidermal growth factor receptor targeting probe. However, our preclinical and clinical work shows no single reporter …


Identification And Characterization Of Two Novel Kcnh2 Mutations Contributing To Long Qt Syndrome, Anthony Owusu-Mensah, Jacqueline Treat, Joyce Bernardi, Ryan Pfeiffer, Robert Goodrow, Bright Tsevi, Victoria Lam, Michel Audette, Jonathan M. Cordeiro, Makarand Deo 2024 Old Dominion University

Identification And Characterization Of Two Novel Kcnh2 Mutations Contributing To Long Qt Syndrome, Anthony Owusu-Mensah, Jacqueline Treat, Joyce Bernardi, Ryan Pfeiffer, Robert Goodrow, Bright Tsevi, Victoria Lam, Michel Audette, Jonathan M. Cordeiro, Makarand Deo

Electrical & Computer Engineering Faculty Publications

We identified two different inherited mutations in KCNH2 gene, or human ether-a-go-go related gene (hERG), which are linked to Long QT Syndrome. The first mutation was in a 1-day-old infant, whereas the second was in a 14-year-old girl. The two KCNH2 mutations were transiently transfected into either human embryonic kidney (HEK) cells or human induced pluripotent stem-cell derived cardiomyocytes. We performed associated multiscale computer simulations to elucidate the arrhythmogenic potentials of the KCNH2 mutations. Genetic screening of the first and second index patients revealed a heterozygous missense mutation in KCNH2, resulting in an amino acid change (P632L) in the …


Estimation Of Differential Pathlength Factor From Nirs Measurement In Skeletal Muscle, B. Koirala, A. Concas, A. Cincotti, Yi Sun, A. Hernández, M. L. Goodwin, L. B. Gladden, N. Lai 2024 Old Dominion University

Estimation Of Differential Pathlength Factor From Nirs Measurement In Skeletal Muscle, B. Koirala, A. Concas, A. Cincotti, Yi Sun, A. Hernández, M. L. Goodwin, L. B. Gladden, N. Lai

Electrical & Computer Engineering Faculty Publications

The utilization of continuous wave (CW) near-infrared spectroscopy (NIRS) device to measure non-invasively muscle oxygenation in healthy and disease states is limited by the uncertainties related to the differential path length factor (DPF). DPF value is required to quantify oxygenated and deoxygenated heme groups' concentration changes from measurement of optical densities by NIRS. An integrated approach that combines animal and computational models of oxygen transport and utilization was used to estimate the DPF value in situ. The canine model of muscle oxidative metabolism allowed measurement of both venous oxygen content and tissue oxygenation by CW NIRS under different oxygen delivery …


Wavelet-Based Harmonization Of Local And Global Model Shifts In Federated Learning For Histopathological Images, W. Farzana, A. Temtam, K. M. Iftekharuddin 2024 Old Dominion University

Wavelet-Based Harmonization Of Local And Global Model Shifts In Federated Learning For Histopathological Images, W. Farzana, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Federated Learning (FL) is a promising machine learning approach for development of data-driven global model using collaborative local models across multiple local institutions. However, the heterogeneity of medical imaging data is one of the challenges within FL. This heterogeneity is caused by the variation in imaging scanner protocols across institutions, which may result in weight shift among local models leading to deterioration in predictive accuracy of global model. The prevailing approaches involve applying different FL averaging techniques to enhance the performance of the global model, ignoring the distinct imaging features of the local domain. In this work, we address both …


Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi 2024 Marquette University

Investigation Of The Effect Of Preparation Parameters On The Structural And Mechanical Properties Of Gelatin/Elastin/Sodium Hyaluronate Scaffolds Fabricated By The Combined Foaming And Freeze-Drying Techniques, Mansour Qamash, S. Misagh Imani, Meisam Omidi, Ciara Glancy, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

This paper aimed to evaluate the effects of different preparation parameters, including agitation speed, agitation time, and chilling temperature, on the structural and mechanical properties of a novel gelatin/elastin/sodium hyaluronate tissue engineering scaffold, recently developed by our research group. Fabricated using a combination of foaming and freeze-drying techniques, the scaffolds were assessed to understand how these parameters influence their morphology, internal microstructure, porosity, mechanical properties, and degradation behavior. The fabrication process used in this study involved preparing a homogeneous aqueous solution containing 8% gelatin, 2% elastin, and 0.5% sodium hyaluronate (w/v), which was then subjected to mechanical agitation at speeds …


Modernizing And Harmonizing Regulatory Data Requirements For Genetically Modified Crops-Perspectives From A Workshop, Nicholas P Storer, Abigail R Simmons, Jordan Sottosanto, Jennifer A Anderson, Ming Hua Huang, Debbie Mahadeo, Carey A Mathesius, Mitscheli Sanches da Rocha, Shuang Song, Ewa Urbanczyk-Wochniak 2024 The Texas Medical Center Library

Modernizing And Harmonizing Regulatory Data Requirements For Genetically Modified Crops-Perspectives From A Workshop, Nicholas P Storer, Abigail R Simmons, Jordan Sottosanto, Jennifer A Anderson, Ming Hua Huang, Debbie Mahadeo, Carey A Mathesius, Mitscheli Sanches Da Rocha, Shuang Song, Ewa Urbanczyk-Wochniak

Faculty, Staff and Student Publications

Genetically modified (GM) crops that have been engineered to express transgenes have been in commercial use since 1995 and are annually grown on 200 million hectares globally. These crops have provided documented benefits to food security, rural economies, and the environment, with no substantiated case of food, feed, or environmental harm attributable to cultivation or consumption. Despite this extensive history of advantages and safety, the level of regulatory scrutiny has continually increased, placing undue burdens on regulators, developers, and society, while reinforcing consumer distrust of the technology. CropLife International held a workshop at the 16th International Society of Biosafety Research …


Polarizable Amoeba Force Field Predicts Thin And Dense Hydration Layer Around Monosaccharides, Luke A. Newman, Mackenzie G. Patton, Breyanna A. Rodriguez, Ethan W. Summer, Valerie Vaissier Welbourn 2024 Virginia Tech

Polarizable Amoeba Force Field Predicts Thin And Dense Hydration Layer Around Monosaccharides, Luke A. Newman, Mackenzie G. Patton, Breyanna A. Rodriguez, Ethan W. Summer, Valerie Vaissier Welbourn

Chemistry & Biochemistry Faculty Publications

Polarizable force fields crucially enhance the modeling of macromolecules in polar media. Here, we present new parameters to model six common monosaccharides with the polarizable AMOEBA force field. These parameters yield a thinner, but denser, hydration layer than that previously reported. This denser hydration layer results in eliminating non-physical aggregation of glucose in water-an issue that has plagued molecular dynamics simulations of carbohydrates for decades.


De-Risking Pretreatment Of Microalgae To Produce Fuels And Chemical Co-Products, Jacob S. Kruger, Skylar Schutter, Eric P. Knoshaug, Bonnie Panczak, Hannah Alt, Alicia Sowell, Stafanie Van Wychen, Matthew Fowler, Kyoko Hirayama, Anuj Thakkar, Sandeep Kumar 2024 National Renewable Energy Laboratory

De-Risking Pretreatment Of Microalgae To Produce Fuels And Chemical Co-Products, Jacob S. Kruger, Skylar Schutter, Eric P. Knoshaug, Bonnie Panczak, Hannah Alt, Alicia Sowell, Stafanie Van Wychen, Matthew Fowler, Kyoko Hirayama, Anuj Thakkar, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

Conversion of microalgae to renewable fuels and chemical co-products by pretreating and fractionation holds promise as an algal biorefinery concept, but a better understanding of the pretreatment performance as a function of algae strain and composition is necessary to de-risk algae conversion operations. Similarly, there are few examples of algae pretreatment at scales larger than the bench scale. This work aims to de-risk algal biorefinery operations by evaluating the pretreatment performance across nine different microalgae samples and five different pretreatment methods at small (5 mL) scale and further de-risk the operation by scaling pretreatment for one species to the 80 …


Salmonella Detection In Food Using A Hek-Htlr5 Reported Cell-Based Sensor, Esma Eser, Victoria A. Felton, Rishi Drolia, Arun K. Bhunia 2024 Purdue University

Salmonella Detection In Food Using A Hek-Htlr5 Reported Cell-Based Sensor, Esma Eser, Victoria A. Felton, Rishi Drolia, Arun K. Bhunia

Biological Sciences Faculty Publications

The development of a rapid, sensitive, specific method for detecting foodborne pathogens is paramount for supplying safe food to enhance public health safety. Despite the significant improvement in pathogen detection methods, key issues are still associated with rapid methods, such as distinguishing living cells from dead, the pathogenic potential or health risk of the analyte at the time of consumption, the detection limit, and the sample-to-result. Mammalian cell-based assays analyze pathogens’ interaction with host cells and are responsive only to live pathogens or active toxins. In this study, a human embryonic kidney (HEK293) cell line expressing Toll-Like Receptor 5 (TLR-5) …


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 2024 Old Dominion University

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 …


Domain Adaptive Federated Learning For Multi-Institution Molecular Mutation Prediction And Bias Identification, W. Farzana, M. A. Witherow, I. Longoria, M. S. Sadique, A. Temtam, K. M. Iftekharuddin 2024 Old Dominion University

Domain Adaptive Federated Learning For Multi-Institution Molecular Mutation Prediction And Bias Identification, W. Farzana, M. A. Witherow, I. Longoria, M. S. Sadique, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Deep learning models have shown potential in medical image analysis tasks. However, training a generalized deep learning model requires huge amounts of patient data that is usually gathered from multiple institutions which may raise privacy concerns. Federated learning (FL) provides an alternative to sharing data across institutions. Nonetheless, FL is susceptible to a few challenges including inversion attacks on model weights, heterogenous data distributions, and bias. This study addresses heterogeneity and bias issues for multi-institution patient data by proposing domain adaptive FL modeling using several radiomics (volume, fractal, texture) features for O6-methylguanine-DNA methyltransferase (MGMT) classification across multiple institutions. The proposed …


Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman 2024 CSE Leading University

Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman

Electrical & Computer Engineering Faculty Publications

Chronic Kidney Diesease (CKD) is a significant health issue, ranking as the fourth leading cause of mortality worldwide. The traditional diagnosis and treatment process, reliant on medical experts, is time-consuming. Therefore, thereis an urgent need for more efficient diagnostic methods to improve patient outcomes and reduce mortality rates. In this study, we employ Machine Learning (ML) and Deep Learning (DL) techniques to predict CKD based on important features. Feature analysis was performed using a correlation matrix and the LASSO algo-rithm to identify the most relevant features for model training. We evaluated several ML and DL classifiers, including Logistic Regression (LR), …


Receptor-Targeted Next-Generation Probiotics Ameliorate Mammalian Colitis, Nicholas L. F. Gallina, Vignesh Nathan, Akshay Krishnakumar, Dongqi Liu, Rishi Drolia, Nicole Irrizary Tardi, Yang Fu, Manalee Samadar, Shivendra Tenguria, Alvin Cai, Ruth Eunice Centeno-Martinez, Timothy A. Johnson, Abigail Cox, Lavanya Reddivari, Bruce Applegate, Xingjian Bai, Luping Xu, Deepti Tanjore, Ramesh Vemulapalli, Rahim Rahimi, Arun K. Bhunia 2024 Purdue University

Receptor-Targeted Next-Generation Probiotics Ameliorate Mammalian Colitis, Nicholas L. F. Gallina, Vignesh Nathan, Akshay Krishnakumar, Dongqi Liu, Rishi Drolia, Nicole Irrizary Tardi, Yang Fu, Manalee Samadar, Shivendra Tenguria, Alvin Cai, Ruth Eunice Centeno-Martinez, Timothy A. Johnson, Abigail Cox, Lavanya Reddivari, Bruce Applegate, Xingjian Bai, Luping Xu, Deepti Tanjore, Ramesh Vemulapalli, Rahim Rahimi, Arun K. Bhunia

Biological Sciences Faculty Publications

Introduction: a loss of intestinal barrier function, inflammation, and an elevated expression of epithelial heat shock protein 60 (Hsp60) are features of an inflamed bowel. Probiotics have been used to alleviate colitis-induced pathologies, but offer poor adhesion and adaptation to the diseased gut. We hypothesize that enhancing probiotic adhesion in the inflamed bowel may ameliorate such pathologies. Listeria adhesion protein (LAP; 94-kDa acetaldehyde alcohol dehydrogenase) aids Listeria attachment to the epithelial cells by interacting with the mammalian receptor Hsp60. Bioengineered Lactobacillus casei probiotics (BLPs) expressing LAP showed strong interaction with epithelial Hsp60, a high immunomodulatory response, and sustained epithelial barrier …


Borophene And Graphene For Non-Enzymatic Biosensor- Ab-Initio Study, Omar A. Ismail 2023 American University in Cairo

Borophene And Graphene For Non-Enzymatic Biosensor- Ab-Initio Study, Omar A. Ismail

Theses and Dissertations

Non-enzymatic glucose sensing holds promise to overcome limitations associated with glucose oxidase, such as oxygen dependence and short shelf life. This study explores the potential sensing capabilities of borophene and graphene through direct interaction with various compounds, including β-glucose, uric acid, ascorbic acid, fructose, and acetaminophen. Using Density Functional Theory (DFT), we calculated binding energies and the respective Density of States (DOS) for these adsorbates on both graphene and borophene surfaces. Preliminary results suggest that borophene might exhibit nearly twice the affinity for β-glucose compared to graphene. Moreover, the calculated Density of States reveals distinct distortions in the electronic states …


The Interaction Of The Cotton Piece With The Piles Of The Scrabble Cotton Drum, Fazliddin Egamberdiev, Ilkhom Abbazov, Oybek Kholmuratov, Rashid Kaldybaev 2023 Jizzakh Polytechnic Institute, Jizzakh city, Republic of Uzbekistan

The Interaction Of The Cotton Piece With The Piles Of The Scrabble Cotton Drum, Fazliddin Egamberdiev, Ilkhom Abbazov, Oybek Kholmuratov, Rashid Kaldybaev

Technical science and innovation

This article presents the results of an analytical study of the process of loosening and cleaning raw cotton from small debris by pileging working bodies of purifiers, on the basis of which directions for further research were chosen to optimize the parameters of the developed pile drum with spherical piles and rubber strips. Cotton entering production contains impurities. The processes of loosening and cleaning the fiber shreds are key in the initial stages of ginning, as they prepare the raw cotton for ginning and directly affect the reliability, productivity of these processes and the quality of the resulting fiber. Weed …


Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, FRANCESCO GREGORETTI 2023 Turin Polytechnic University, Tashkent city, Republic of Uzbekistan;

Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, Francesco Gregoretti

Technical science and innovation

Modern methods for solving problems of planning the execution of batches of tasks in multi-stage systems are characterized by the presence of restrictions on their dimensionality, the impossibility of guaranteed obtaining better results in comparison with fixed packages for different values of the input parameters of the problem. In the article, the author solved the problem of optimizing the composition of job packages running in multi-stage systems using the branch and bound method. Research has been carried out on various ways to form package execution orders tasks in multi-stage systems (heuristic rules for ordering packages tasks in the sequence of …


An Experimental Investigation Of The New Vibration Viscometer, Jamshidbek Ulugbek ugli Shamuratov 2023 Tashkent State Technical University, Tashkent city, Republic of Uzbekistan

An Experimental Investigation Of The New Vibration Viscometer, Jamshidbek Ulugbek Ugli Shamuratov

Technical science and innovation

The characteristics of the new oscillating-plate viscometer have been investigated experimentally. The results obtained are as follows: the resonant frequency of plate oscillation decreases with increasing viscosity; the apparatus constant 𝐾 determined experimentally includes the end and slip effects; the dimensions of the plate should be determined by referring to empirical relations between 𝜌𝜇 and Λ(≡{(𝐸𝑎𝐸)−1}𝑛) for various dimensions of the plate; where 𝜌 is the density, 𝜇 is the viscosity; 𝐸𝑎 the resonant amplitude of plate in the air; E the amplitude of plate in a liquid, and 𝑛 a constant. If the distance between the plate and the …


Indicators Affecting Passenger Service Processes And Their Scientific Interpretation, Maxliyoxon Madaminova Maxamatjon qizi, Saidazim Amanullayevich Ganihodjayev 2023 Tashkent State Transport University, Tashkent city, Republic of Uzbekistan)

Indicators Affecting Passenger Service Processes And Their Scientific Interpretation, Maxliyoxon Madaminova Maxamatjon Qizi, Saidazim Amanullayevich Ganihodjayev

Technical science and innovation

Many traffic flow parameters affect the performance of the road network at high voltage. These are low vehicle speeds, high vehicle distances relative to road capacity, and density per unit time (lane occupancy). In turn, a number of factors affect the decrease in traffic speed: the presence of slow-moving vehicles in the stream; pedestrians crossing the road irregularly; increase in traffic flow, etc. The issues of public transportation depend on many factors, each of which requires a separate approach and a complex solution. In large cities around the world, the quality indicators of public transport services, including the issues of …


Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot qizi PhD 2023 Tashkent State Technical University, Tashkent city, Republic of Uzbekistan

Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot Qizi Phd

Technical science and innovation

Currently, much attention is paid to the issue of energy efficiency of gas processing enterprises. The continuous growth of world prices for energy resources requires constant improvement of the management system, providing the most optimal conditions for the flow of technological processes. A conceptual model of the heat-mass transfer process occurring in the absorber as an object of research has been developed, which characterizes the relationship of the variables involved in the drying process of natural gas, control, measurable and immeasurable, as well as controlled parameters have been selected, which are used to develop and study a mathematical model of …


Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia 2023 Brigham Young University

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 …


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