Medicine and Health Sciences Commons^™

The Role Of Floodplain Complexity In Wood Turtle Habitat Use, Laura S. Deming

Antioch University Dissertations & Theses

Wood turtles occupy cold, low-gradient riverine habitat throughout the northeastern United State and southeastern Canada. Stream alterations, such as dams, channel straightening, and floodplain development have diminished the natural hydrologic and sedimentation regimes that result in complex channel and floodplain geomorphology. Studies throughout the species’ range have quantified many aspects of their habitat, but none have quantified components of geomorphology of wood turtle sites. The goal of this study was to explore the role of stream channel and floodplain geomorphology in wood turtle habitat use, with specific objectives to (1) quantify components of stream channel and floodplain geomorphic complexity, (2) …

S-Methyl Cysteine Sulfoxide And Its Potential Role In Human Health: A Scoping Review, Caroline R. Hill, Alex Haoci Liu, Lyn Mccahon, Liezhou Zhong, Armaghan Shafaei, Lois Balmer, Joshua R. Lewis, Jonathan M. Hodgson, Lauren C. Blekkenhorst

Research outputs 2022 to 2026

Higher intakes of cruciferous and allium vegetables are associated with a lower risk of cardiometabolic-related outcomes in observational studies. Whilst acknowledging the many healthy compounds within these vegetables, animal studies indicate that some of these beneficial effects may be partially mediated by S-methyl cysteine sulfoxide (SMCSO), a sulfur-rich, non-protein, amino acid found almost exclusively within cruciferous and alliums. This scoping review explores evidence for SMCSO, its potential roles in human health and possible mechanistic action. After systematically searching several databases (EMBASE, MEDLINE, SCOPUS, CINAHL Plus Full Text, Agricultural Science), we identified 21 original research articles meeting our inclusion criteria. These …

Towards Developing Glut2 Specific Probes For Biochemical And Biomedical Applications, Abdelrahman Ismail

Dissertations, Master's Theses and Master's Reports

Facilitated Glucose transporters (GLUTs) are membrane proteins responsible for the uptake of simple sugars and other structurally similar metabolites in all mammalian cells. One of the hallmarks of cancer is dysfunctional sugar metabolism, known as the Warburg effect, and one of the manifestations of that effect is abnormal GLUT expression. There are 14 known GLUT proteins with different expression patterns in different tissues, and tumors tend to express certain GLUTs that are not present in surrounding healthy tissue. Therefore, selective targeting of GLUTs presents a potentially powerful tool for diagnostics and treatment of cancer and other diseases. This has been …

Structural Optimization And Stability Enhancement Of Uba(2) And Ntl9 Using The Computational Tool: Emcast, Bahar Ghazi Esfahani

Graduate Student Theses, Dissertations, & Professional Papers

This study enhances protein stability prediction by refining EmCAST (Empirical C-Alpha Stability Tool), a computational tool used to identify stabilizing mutations in protein domains. We applied EmCAST to two model proteins: the α-helical ubiquitin-associated domain 2 (UBA(2)) and the α/β N-terminal domain of ribosomal protein L9 (NTL9). Protein stability is critical for proper function, and mutations can lead to misfolding and disease. To validate EmCAST’s predictions, guanidine hydrochloride-induced denaturation was monitored using circular dichroism (CD) spectroscopy for both wild-type and mutant variants. Results guided refinements to EmCAST’s algorithm, incorporating new experimental datasets to improve accuracy. Additionally, we examined the assumption …

Learning Paradigms For Rhythm Detection And Generation Using Mathematical Models, Biophysical And Artificial Neural Networks, Prianka Bose

Dissertations

Humans possess an inherent ability to recognize evenly-spaced rhythms, known as isochronous rhythms, owing to the brain's predisposition to entrain to external auditory stimuli with regular temporal intervals. The central focus of this research is to understand how the brain learns and retains rhythmic time intervals in the context of music. This dissertation studies rhythm detection and generation through mathematical models, biophysical networks, and artificial neural networks, addressing both isochronous and non-isochronous patterns.

A primary focus of the thesis is on isochronous rhythms. In particular, given a perturbation to an isochronous rhythm such as a tempo change or phase shift …

Machine Learning Methods For Pattern Recognition Analysis Of Genomic And Molecular Data, Kuang Du

Dissertations

While immune therapies achieve remarkable success in treating various cancers, only a subset of patients achieves a durable clinical response, and many exhibit innate or acquired resistance. Precision medicine aims to tailor treatments to individual patients based on specific biological markers, ensuring that each patient receives the therapy most likely to be effective. Predictive biomarkers and gene signatures offer potential for more personalized treatment strategies by identifying patients likely to benefit. Recent studies suggest that gene signatures, comprising sets of genes, hold predictive value for certain clinical variables. Typically derived from biological expert knowledge, these signatures demonstrate substantial predictive potential, …

Multi-Sensor Data Fusion And Gis-Drastic Integration For Groundwater Vulnerability Assessment With Rainfall Consideration, Wu Jiazhe, Dai Xinrui, Su Yangcheng, Zheng Xiangtian, Bushra Ghaffar, Rabiya Nasir, Ahsan Jamil, Zeeshan Zafar, Mohammad Suhail Meer, M. Abdullah-Al-Wadud, Rahila Naseer, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

In many areas of the world, particularly in arid and semi-arid regions, groundwater is the primary source of fresh water, and it supplies around one-third of the world's fresh water. Agriculture is the primary economic sector on the coast in the southern district (Nowshera). More food productivity is required due to the expanding population and diminishing agricultural lands, which increases the use of chemical pesticides and fertilizers in farming. The current study was conducted in northwestern parts of Pakistan to evaluate the impacts of the frequent use of pesticides and fertilizers in agricultural fields. Nine hydrogeological parameters were considered, and …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Single-Step Synthesis Of Activated Carbon From Arabica Spent Coffee Ground Using K2co3 As Activator Agent, Ghina Ivana Mieldan, Yuliusman Yuliusman

Journal of Materials Exploration and Findings

Activated carbon is a nanomaterial that is often used as an effective adsorbent. Activated carbon raw materials can use biomass, such as coffee grounds, which can be found along with the growth of public interest in coffee drinks. Chemical activators are used for activation to increase biomass carbon's adsorption capacity. Using K₂CO₃ activator to increase the specific surface area of activated carbon is more harmless than KOH. The use of spent coffee grounds as carbon source and food additive K₂CO₃ as an activator can make food-grade activated carbon that can be used for food. …

Effect Of Alkyd And Polyester Resin Compositions On Corrosion Resistance, Blistering, And Adhesion In Utilization Of Oily Sludge As Anti-Rust Coating Material, Gerets Land Kakalang, Yohanes David Kristianto, Johny Wahyuadi Mudaryoto

Journal of Materials Exploration and Findings

Oil sludge is a waste derived from upstream and downstream activities of the oil and gas industry which is estimated at 10,000 tonnes generated from all PERTAMINA downstream activities spread across various fields, processing units and depots throughout Indonesia. Oil sludge has the same characteristics as asphalt, where asphalt in previous studies can be used as an anti-rust coating, so that the handling of oily sludge can be topped up by reusing and having its own added value. The purpose of this research is to utilise waste oily sludge as an alternative anti-rust coating material and compare alkyd resin and …

Surgical Delay-Associated Mortality Risk Varies By Subtype In Loco-Regional Breast Cancer Patients In Seer-Medicare, Macall Leslie Salewon, Rashmi Pathak, William Dooley, Ronald Squires, Hallgeir Rui, Inna Chervoneva, Takemi Tanaka

Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers

Substantial evidence supports that delay of surgery after breast cancer diagnosis is associated with increased mortality risk, leading to the introduction of a new Commission on Cancer quality measure for receipt of surgery within 60 days of diagnosis for non-neoadjuvant patients. Breast cancer subtype is a critical prognostic factor and determines treatment options; however, it remains unknown whether surgical delay-associated breast cancer-specific mortality (BCSM) risk differs by subtype. This retrospective cohort study aimed to assess whether the impact of delayed surgery on survival varies by subtype (hormone [HR] + /HER2 -, HR -/HER2 -, and HER2 +) in patients with …

Immune Checkpoint Inhibitor-Associated Cutaneous Adverse Events: Mechanisms Of Occurrence, Abdulaziz M. Eshaq, Thomas W. Flanagan, Abdulqader A. Ba Abbad, Zain Alabden A. Makarem, Mohammed S. Bokir, Ahmed K. Alasheq, Sara A. Al Asheikh, Abdullah M. Almashhor, Faroq Binyamani, Waleed A. Al-Amoudi, Abdulaziz S. Bawzir, Youssef Haikel, Mossad Megahed, Mohamed Hassan

School of Medicine Faculty Publications

Immunotherapy, particularly that based on blocking checkpoint proteins in many tumors, including melanoma, Merkel cell carcinoma, non-small cell lung cancer (NSCLC), triple-negative breast (TNB cancer), renal cancer, and gastrointestinal and endometrial neoplasms, is a therapeutic alternative to chemotherapy. Immune checkpoint inhibitor (ICI)-based therapies have the potential to target different pathways leading to the destruction of cancer cells. Although ICIs are an effective treatment strategy for patients with highly immune-infiltrated cancers, the development of different adverse effects including cutaneous adverse effects during and after the treatment with ICIs is common. ICI-associated cutaneous adverse effects include mostly inflammatory and bullous dermatoses, as …

Artificial Intelligence In Fetal And Pediatric Echocardiography, Alan Wang, Tam T Doan, Charitha Reddy, Pei-Ni Jone

Faculty, Staff and Students Publications

Echocardiography is the main modality in diagnosing acquired and congenital heart disease (CHD) in fetal and pediatric patients. However, operator variability, complex image interpretation, and lack of experienced sonographers and cardiologists in certain regions are the main limitations existing in fetal and pediatric echocardiography. Advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offer significant potential to overcome these challenges by automating image acquisition, image segmentation, CHD detection, and measurements. Despite these promising advancements, challenges such as small number of datasets, algorithm transparency, physician comfort with AI, and accessibility must be addressed to fully integrate AI …

An Ontology-Based Approach For Understanding Appendicectomy Processes And Associated Resources, Nadeesha Pathiraja Rathnayaka Hitige, Ting Song, Steven J Craig, Kimberley J Davis, Xubing Hao, Licong Cui, Ping Yu

Faculty, Staff and Student Publications

Background: Traditional methods for analysing surgical processes often fall short in capturing the intricate interconnectedness between clinical procedures, their execution sequences, and associated resources such as hospital infrastructure, staff, and protocols.

Aim: This study addresses this gap by developing an ontology for appendicectomy, a computational model that comprehensively represents appendicectomy processes and their resource dependencies to support informed decision making and optimise appendicectomy healthcare delivery.

Methods: The ontology was developed using the NeON methodology, drawing knowledge from existing ontologies, scholarly literature, and de-identified patient data from local hospitals.

Results: The resulting ontology comprises 108 classes, including 11 top-level classes and …

Increasing Youth Engagement In Community Heritage And Social Justice Through Implementation Of A Youth Participatory Empowerment Model, Jancarlos Wagner-Romero, Mary Gillis, Lindsay Clemens, Amanda J. Dworak Rowland, Curlinda Mitchell-Blacksheep, Melanie Canaday-Talley

Journal of Multicultural Affairs

Youth in traditionally marginalized communities are often the target of policies and practices without the opportunity to provide input. This article highlights effective strategies to empower youth to become active participants in their communities. Using a Youth Participatory Empowerment Model (YPEM), youth participants from six demographically distinct communities engaged in YPEM-supported activities and strategies to identify and address a need within their community. To gain insight into successful strategies, qualitative data from pre and post implementation focus group interviews and observational field notes informed the conclusions. The participant youth represent tribal, undocumented, rural, suburban, and urban youth from underserved populations. …

Measurement Of Breast Artery Calcification Using An Artificial Intelligence Detection Model And Its Association With Major Adverse Cardiovascular Events, Suzanne Rose, Josette Hartnett, Zachary Estep, Daniyal Ameen, Shweta Karki, Edward Schuster, Rebecca Newman, David Hsi

Department of Medicine Faculty Papers

Breast artery calcification (BAC) obtained from standard mammographic images is currently under evaluation to stratify risk of major adverse cardiovascular events in women. Measuring BAC using artificial intelligence (AI) technology, we aimed to determine the relationship between BAC and coronary artery calcification (CAC) severity with Major Adverse Cardiac Events (MACE). This retrospective study included women who underwent chest computed tomography (CT) within one year of mammography. T-test assessed the associations between MACE and variables of interest (BAC versus MACE, CAC versus MACE). Risk differences were calculated to capture the difference in observed risk and reference groups. Chi-square tests and/or Fisher's …

Editorial: Artificial Intelligence For Smart Health: Learning, Simulation, And Optimization, Bing Yao, Nathan Gaw, Hyo Kyung Lee

Faculty Publications

With rapid developments in medical sensing and imaging, we now live in an era of data explosion in which large amounts of data are readily available in clinical environments. The fast-growing biomedical and healthcare data provide unprecedented opportunities for data-driven scientific knowledge discovery and clinical decision support. Our Research Topic aims to catalyze synergies among biomedical informatics, machine learning, computer simulation, operations research, systems engineering, and other related fields with three specific goals: (1) develop cutting-edge data-driven models to accelerate scientific knowledge discovery in biomedicine using healthcare data collected from laboratory systems, imaging systems, and medical and sensing devices; (2) …

Ethical Aspects Of Utilising Artificial Intelligence In Clinical Settings, Jeffrey Byrnes, Michael Robinson

Philosophy Faculty Articles and Research

In response to recent proposals to utilize artificial intelligence (AI) to automate ethics consultations in healthcare, we raise two main problems for the prospect of having healthcare professionals rely on AI-driven programs to provide ethical guidance in clinical matters. The first cause for concern is that, because these programs would effectively function like black boxes, this approach seems to preclude the kind of transparency that would allow clinical staff to explain and justify treatment decisions to patients, fellow caregivers, and those tasked with providing oversight. The other main problem is that the kind of authority that would need to be …

Transparency And Authority Concerns With Using Ai To Make Ethical Recommendations In Clinical Settings, Jeffrey Byrnes, Michael Robinson

Philosophy Faculty Articles and Research

In response to recent proposals to utilize artificial intelligence (AI) to automate ethics consultations in healthcare, we raise two main problems for the prospect of having healthcare professionals rely on AI-driven programs to provide ethical guidance in clinical matters. The first cause for concern is that, because these programs would effectively function like black boxes, this approach seems to preclude the kind of transparency that would allow clinical staff to explain and justify treatment decisions to patients, fellow caregivers, and those tasked with providing oversight. The other main problem is that the kind of authority that would need to be …

Advancing Continuous Manufacturing: The Role Of Process Analytical Technology In Process Development, Samuel R. Henson

Electronic Theses and Dissertations

The pharmaceutical industry is actively pursuing technologies which improve manufacturing processes with the goal of producing high-quality pharmaceutical products for patients, manifesting in an industry-wide investment in continuous manufacturing (CM). Process analytical technology (PAT) has been recognized for its successful monitoring of critical quality attributes during routine production and is often cited alongside CM due to its ability to make timely, in-line measurements of intermediate materials. Various PAT tools are valuable in process development, particularly as continuous wet granulation processes are developed for use within pharmaceutical manufacturing. This work applied PAT and chemometric modeling during CM process development to enhance …

Efficient Development Of Density-Insensitive Near-Infrared Methods For In-Line Drug Content Monitoring In Continuous Powder Streams, Natasha L. Velez-Silva

Electronic Theses and Dissertations

A well-defined action plan to respond effectively to sudden changes in product demand is critical for preventing drug shortages within the pharmaceutical industry. An effective way to increase the output of a continuous manufacturing (CM) process is through flow rate adjustments. However, robust analytical methods must be in place to ensure consistent analytical performance across varying flow rates. Existing approaches for mitigating the physical effects of flow rate on Near-Infrared (NIR) measurements are often burdensome. Thus, efficient robust modeling strategies that reduce the current calibration burden and ensure model insensitivity to the physical variations in CM systems are needed. In …

Assembly Of Ppsu-Oligomers, Mariam Nesterov

Student Theses and Dissertations

The development of nanostructures for delivering multiple proteins to targeted antibodies has become a promising avenue in biotechnology, driven by advancements in synthetic polymers like poly(propylene sulfone), PPSU. However, the PPSU polymer faces a major limitation - its high insolubility. To address this challenge, this study investigates whether PPSU oligomers can enhance both the solubility and stability of lysozyme, a model protein that is cost-effective and widely accessible. Using dimer, trimer, tetramer, and hexamer configurations, we analyzed the interactions between PPSU oligomer and lysozyme under varying conditions. Our results show that the dimer and trimer are water soluble (no aggregate …

A Comprehensive Usability And Economic Analysis Of Heat-Related Wearable Technologies: Applications To Occupational Health, Ryan T. Cannady

Theses & Dissertations

The purpose of this research was to analyze the usability and economic considerations of real-time wearable technologies that are implemented in occupational settings to assess risk of heat stress and heat strain. The study population included current agriculture workers and Department of Energy (DOE), Environmental Management (EM) contractors. We employed a mixed-methods approach to comprehensively analyze the usability and economic considerations of heat-related technologies. Specifically, our approach assessed three distinct aspects the applications of these technologies in occupational settings to comprehensively address our research objective: (1) worker perceptions of heat-related wearable technologies, (2) field-based assessment of these heat-related wearable technologies, …

Influence Of Antibody–Drug Conjugate Cleavability, Drug-To-Antibody Ratio, And Free Payload Concentration On Systemic Toxicities: A Systematic Review And Meta-Analysis, Shou Ching Tang, Carrie Wynn, Tran Le, Martin Mccandless, Yunxi Zhang, Ritesh Patel, Nita Maihle, William Hillegass

School of Medicine Faculty Publications

While in theory antibody drug conjugates (ADCs) deliver high-dose chemotherapy directly to target cells, numerous side effects are observed in clinical practice. We sought to determine the effect of linker design (cleavable versus non-cleavable), drug-to-antibody ratio (DAR), and free payload concentration on systemic toxicity. Two systematic reviews were performed via PubMed search of clinical trials published between January 1998—July 2022. Eligible studies: (1) clinical trial for cancer therapy in adults, (2) ≥ 1 study arm included a single-agent ADC, (3) ADC used was commercially available/FDA-approved. Data was extracted and pooled using generalized linear mixed effects logistic models. 40 clinical trials …

Racial And Ethnic Differences In Outcomes Of Neonates Born At Less Than 30 Weeks' Gestation, 2018-2022, Nansi S. Boghossian, Marco Geraci, Erika M. Edwards, Jeffrey D. Horbar

Faculty Publications

Importance: Previous research has examined outcomes among very preterm newborns by the birthing parent's race and ethnicity, but knowledge about these trends during the COVID-19 pandemic is limited. Objective: To examine trends in outcomes among Black, Hispanic, and Asian preterm newborns compared with White preterm newborns. Design, Setting, and Participants: This cohort study (2018-2022) took place at 774 neonatal intensive care units in the Vermont Oxford Network. Participants were newborns born at 22 to 29 weeks' gestation. Exposure: Race and ethnicity. Main Outcomes and Measures: The primary outcomes were mortality and complications, including respiratory distress syndrome, necrotizing enterocolitis (NEC), early-onset …

Feasibility Of Large Language Models For Ceus Li-Rads Categorization Of Small Liver Nodules In Patients At Risk For Hepatocellular Carcinoma, Jiayan Huang, Rui Yang, Xiaotong Huang, Keyu Zeng, Yan Liu, Jun Luo, Andrej Lyshchik, Qiang Lu

Department of Radiology Faculty Papers

BACKGROUND: Large language models (LLMs) offer opportunities to enhance radiological applications, but their performance in handling complex tasks remains insufficiently investigated.

PURPOSE: To evaluate the performance of LLMs integrated with Contrast-enhanced Ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) in diagnosing small (≤20mm) hepatocellular carcinoma (sHCC) in high-risk patients.

MATERIALS AND METHODS: From November 2014 to December 2023, high-risk HCC patients with untreated small (≤20mm) focal liver lesions (sFLLs), were included in this retrospective study. ChatGPT-4.0, ChatGPT-4o, ChatGPT-4o mini, and Google Gemini were integrated with imaging features from structured CEUS LI-RADS reports to assess their diagnostic performance for sHCC. …

Artificial Intelligence-Based Methodologies For Early Diagnostic Precision And Personalized Therapeutic Strategies In Neuro-Ophthalmic And Neurodegenerative Pathologies, Rahul Kumar, Ethan Waisberg, Joshua Ong, Phani Paladugu, Dylan Amiri, Jeremy Saintyl, Jahnavi Yelamanchi, Robert Nahouraii, Ram Jagadeesan, Alireza Tavakkoli

SKMC Student Presentations and Publications

Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer's disease, Parkinson's disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques-Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging-in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and …

Mental Health Care Disparities Among Us Pregnant Individuals In 2020–2021: A Cross-Sectional Study, Julisa Tindall, Monique J. Brown Ph.D., Mph, Peiyin Hung

Faculty Publications

Purpose

To examine maternal characteristics associated with perceived unmet mental health needs and mental health care settings, focusing on residential rurality and race/ethnicity.

Methods

This cross-sectional study analyzed self-reported unmet mental health needs and mental health care settings among 1097 pregnant respondents in the 2020–2021 National Survey on Drug Use and Health, incorporating the complex sampling weights for national representativeness.

Findings

Non-Hispanic Black pregnant individuals and those living in nonmetro rural areas reported lower odds of unmet mental health needs compared to those in large metro areas and non-Hispanic White individuals. Pregnant individuals in nonmetro rural areas and non-Hispanic other …

Comparing Multivalent Cross-Linked Sodium Alginate/ Montmorillonite Beads Containing Curcumin Or Cayenne Pepper As Drug Carriers And Their Antimicrobial Resistance, Shionainn Traynor, Shubham Sharma

SURE Journal: Science Undergraduate Research Experience Journal

The aim of the following work was to investigate and compare curcumin and cayenne pepper in microbeads composed of sodium alginate (SA) crosslinked with montmorillonite (MMT) to act as drug carriers and their antimicrobial resistance. The microbeads were prepared through ion-exchange in multivalent solutions of CaCl₂, MgCl₂ and AlCl₃. The microbeads were characterized by Scanning Electron Microscopy (SEM), Energy Dispersive X-ray analysis (EDX) and the time required for intercalation of curcumin and cayenne pepper with MMT. Simulated intestinal fluid (pH 7.3) and gastric fluid (pH 1.2) at 37°C were used for comparison in swelling studies. …

Mathematical Modelling Of Disease Outbreak, Favour Christian, Matthew Molloy

SURE Journal: Science Undergraduate Research Experience Journal

Establishing a model framework for more research necessitates a thorough understanding of the causes, distribution, prevalence, and evolution of infectious illnesses. The main mathematical concept used in this modelling simulation is ordinary differential equations (ODEs). The purpose of this study was to investigate the significance of the many criteria linked to a zombie virus spread. The zombie framework provides an accessible and relatively simple representation of the nature of infectious disease spread, allowing for tractable assumptions and the development of more complex situations.

The models are designed around a zombie outbreak in which the zombie virus is spread through a …