Biomedical Informatics Commons^™

A Scoping Review Of Patient Safety Checklists In Pediatrics, Kawtar Zouaidi, Tate W Miner, Muhammad F Walji, Kristin N Ray, Elsbeth Kalenderian, Donald B Rindal, Katie J Suda

Faculty, Staff and Student Publications

Objective: To examine the utilization and effectiveness of safety checklists in pediatric clinical care.

Methods: A comprehensive literature search was conducted using Medline to identify studies related to the development and/or implementation of patient safety checklists in pediatrics. All study designs were included for citations published through September 2023.

Results: Following abstract and full-text screening, 74 studies remained for data extraction and analysis. Pediatric surgery emerged as the main setting for checklists use (n = 35), followed by Intensive Care Units (n = 21), and Emergency Departments (n = 9). Of the 74 reviewed papers, 37 (50%) designed and developed …

Defining Spine Cancer Pain Syndromes: A Systematic Review And Proposed Terminology, Markian Pahuta, Ilya Laufer, Sheng-Fu Larry Lo, Stefano Boriani, Charles Fisher, Nicolas Dea, Michael H Weber, Dean Chou, Arjun Sahgal, Laurence Rhines, Jeremy Reynolds, Aron Lazary, Alessandro Gasbarrinni, Jorrit-Jan Verlaan, Ziya Gokaslan, Chetan Bettegowda, Mohamed Sarraj, Ori Barzilai, Ao Spine Knowledge Forum Tumor

Faculty, Staff and Student Publications

STUDY DESIGN: Systematic Review.

OBJECTIVES: Formalized terminology for pain experienced by spine cancer patients is lacking. The common descriptors of spine cancer pain as mechanical or non-mechanical is not exhaustive. Misdiagnosed spinal pain may lead to ineffective treatment recommendations for cancer patients.

METHODS: We conducted a systematic review of pain terminology that may be relevant to spinal oncology patients. We provide a comprehensive and unbiased summary of the existing evidence, not limited to the spine surgery literature, and subsequently consolidate these data into a practical, clinically relevant nomenclature for spine oncologists.

RESULTS: Our literature search identified 3515 unique citations. Through …

The Influence Of The Microbiome On Radiotherapy And Dna Damage Responses, Aadil Sheikh, Michael A Curran

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Colorectal cancer (CRC) is one of the most prevalent cancers in terms of diagnosis and mortality. Radiotherapy (RT) remains a mainstay of CRC therapy. As RT relies on DNA damage to promote tumor cell death, the activity of cellular DNA damage repair pathways can modulate cancer sensitivity to therapy. The gut microbiome has been shown to influence intestinal health and is independently associated with CRC development, treatment responses and outcomes. The microbiome can also modulate responses to CRC RT through various mechanisms such as community structure, toxins and metabolites. In this review we explore the use of RT in the …

Patient-Reported Outcomes During Pelvic Radiation Therapy: A Secondary Analysis On Sexual Function From Nrg-Rtog 1203, Kelsey L Corrigan, Rebecca Paulus, Ann H Klopp, Lari B Wenzel, Anamaria R Yeung, J Spencer Thompson, Desiree E Doncals, Vijayananda Kundapur, Nancy H Wiggers, Dasarahally S Mohan, Sharad A Ghamande, Shannon N Westin, Kara L Schnarr, Michael L Haas, David K Gaffney, Steven E Waggoner, Pamela J Vanderwall, Noha T Jastaniyah, Stephanie L Pugh, Lisa A Kachnic

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Purpose: NRG-RTOG 1203 reported that intensity-modulated radiation therapy (IMRT) reduced patient-reported GI toxicities in patients with cervical/endometrial cancer receiving postoperative RT, compared with 3-dimensional conformal radiation therapy (3DRT). We conducted a secondary analysis of patient-reported sexual function (PR-SF) among treatment groups to identify factors associated with sexual dysfunction.

Methods and materials: Patients on NRG-RTOG 1203 were randomly assigned to 3DRT versus IMRT and completed Patient-Reported Outcomes (PRO)-Common Terminology Criteria for Adverse Events (CTCAE) and FACT-Cx surveys at baseline, week 5 of RT, and at 4-6 weeks, 1 year, and 3 years after RT. Patient responses to FACT-Cx sexual function questions …

Reproducibility And Repeatability Of 18f-(2s, 4r)-4-Fluoroglutamine Pet Imaging In Preclinical Oncology Models, Gregory D Ayers, Allison S Cohen, Seong-Woo Bae, Xiaoxia Wen, Alyssa Pollard, Shilpa Sharma, Trey Claus, Adria Payne, Ling Geng, Ping Zhao, Mohammed Noor Tantawy, Seth T Gammon, H Charles Manning

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Introduction: Measurement of repeatability and reproducibility (R&R) is necessary to realize the full potential of positron emission tomography (PET). Several studies have evaluated the reproducibility of PET using 18F-FDG, the most common PET tracer used in oncology, but similar studies using other PET tracers are scarce. Even fewer assess agreement and R&R with statistical methods designed explicitly for the task. 18F-(2S, 4R)-4-fluoro-glutamine (18F-Gln) is a PET tracer designed for imaging glutamine uptake and metabolism. This study illustrates high reproducibility and repeatability with 18F-Gln for in vivo research.

Methods: Twenty mice bearing colorectal cancer cell line xenografts were injected with ~9 …

Patterns Of Loco-Regional Progression And Patient Outcomes After Definitive-Dose Radiation Therapy For Anaplastic Thyroid Cancer, Julianna K Bronk, Alexander Augustyn, Abdallah S R Mohamed, C David Fuller, Adam S Garden, Amy C Moreno, Anna Lee, William H Morrison, Jack Phan, Jay P Reddy, David I Rosenthal, Michael T Spiotto, Steven J Frank, Ramona Dadu, Naifa Busaidy, Mark Zafereo, Jennifer R Wang, Anastasios Maniakas, Renata Ferrarotto, Priyanka C Iyer, Maria E Cabanillas, G Brandon Gunn

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Background: The aim of this study is to characterize the patterns of loco-regional progression (LRP) and outcomes after definitive-dose intensity modulated radiation therapy (IMRT) for anaplastic thyroid cancer (ATC) with macroscopic neck disease at the time of IMRT.

Methods: Disease/treatment characteristics and outcomes for patients with unresected or incompletely resected ATC who received IMRT (≥45 Gy) were retrospectively reviewed. For those with LRP after IMRT, progressive/recurrent gross tumor volumes (rGTV) were contoured on diagnostic CTs and co-registered with initial planning CTs using deformable image registration. rGTVs were classified based on established spatial/dosimetric criteria.

Results: Forty patients treated between 2010-2020 formed …

Selective Inhibition Of Canonical Stat3 Signaling Suppresses K-Ras Mutant Lung Tumorigenesis And Reinvigorates Anti-Tumor Immunity, Michael J Clowers, Zahraa Rahal, Sung-Nam Cho, Avantika Krishna, Bo Yuan, Leticia G Hamana Zorrilla, T Kris Eckols, Moses M Kasembeli, Samuel Liu, Stephen Peng, Marco Ramos-Castaneda, Annamarie L Thompson, Carlos Ignacio Rodriguez Reyna, Katherine E Larsen, Maria T Grimaldo, Shanshan Deng, Nastaran Karimi, Cody Chou, Walter V Velasco, Melody Zarghooni, Sayan Alekseev, Luisa M Solis Soto, Edwin J Ostrin, Humam Kadara, Suhendan Ekmekcioglu, David J Tweardy, Seyed Javad Moghaddam

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Introduction: K-ras mutant lung adenocarcinoma (KM-LUAD) is a difficult-to-treat cancer subtype in which chronic inflammation pervades the tumor immune microenvironment (TIME). Pro-inflammatory pathways dampen the response to treatments, including immune checkpoint inhibitors, necessitating therapies that target this inflammatory signaling network in the TIME. One of the lynchpins of chronic inflammation in KM-LUAD is signal transducer and activator of transcription 3 (STAT3).

Methods: Here, we tested the anti-tumor and early immunotherapeutic efficacy of TTI-101, a selective small-molecule inhibitor of canonical STAT3 signaling, in a K-rasG12D mutant lung cancer mouse model (CC-LR).

Results: Treatment of CC-LR mice with TTI-101 resulted in reduced …

Dedifferentiated Liposarcomas Treated With Immune Checkpoint Blockade: The Md Anderson Experience, Madeline B Torres, Cheuk Hong Leung, Marianne Zoghbi, Rossana Lazcano, Davis Ingram, Khalida Wani, Emily Z Keung, M Alejandra Zarzour, Christopher P Scally, Kelly K Hunt, Anthony Conley, Andrew J Bishop, B Ashleigh Guadagnolo, Ahsan Farooqi, Devarati Mitra, Alison K Yoder, Michael S Nakazawa, Dejka Araujo, Andrew Livingston, Ravin Ratan, Shreyaskumar Patel, Vinod Ravi, Alexander J Lazar, Christina L Roland, Neeta Somaiah, Elise F Nassif Haddad

Faculty, Staff and Student Publications

Background: Dedifferentiated liposarcoma (DDLPS) is one of the most common types of soft tissue sarcoma (STS) characterized by liposarcomatous differentiation and a predilection for the retroperitoneum. Despite the growing number of histology-specific immune checkpoint blockade (ICB) trials in STS, it is still difficult to identify the radiographic objective response rate (ORR) for DDLPS in the real world setting. This study aimed to evaluate the ORR and survival of patients with DDLPS treated with ICB at a single center.

Methods: We conducted a retrospective study of 31 patients with pathologically confirmed DDLPS treated with ICB at MD Anderson Cancer Center between …

A Plain Language Summary Of The Final Analysis Of The Griffin Study Of Daratumumab Plus Lenalidomide, Bortezomib, And Dexamethasone For People With Newly Diagnosed Multiple Myeloma, Peter M Voorhees, Douglas W Sborov, Jacob Laubach, Jonathan L Kaufman, Brandi Reeves, Cesar Rodriguez, Rebecca Silbermann, Luciano J Costa, Larry D Anderson, Nitya Nathwani, Nina Shah, Naresh Bumma, Yvonne A Efebera, Sarah A Holstein, Caitlin Costello, Andrzej Jakubowiak, Tanya M Wildes, Robert Z Orlowski, Kenneth H Shain, Andrew J Cowan, Shira Dinner, Katharine S Gries, Huiling Pei, Annelore Cortoos, Sharmila Patel, Thomas S Lin, Saad Z Usmani, Paul G Richardson

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No abstract provided.

Grape-Pi: Graph-Based Neural Networks For Enhanced Protein Identification In Proteomics Pipelines, Chunhui Gu, Seyyed Mahmood Ghasemi, Yining Cai, Johannes F Fahrmann, James P Long, Hiroyuki Katayama, Chong Wu, Jody Vykoukal, Jennifer B Dennison, Samir Hanash, Kim-Anh Do, Ehsan Irajizad

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Motivation: Protein identification via mass spectrometry (MS) is the primary method for untargeted protein detection. However, the identification process is challenging due to data complexity and the need to control false discovery rates (FDR) of protein identification. To address these challenges, we developed a graph neural network (GNN)-based model, Graph Neural Network using Protein-Protein Interaction for Enhancing Protein Identification (Grape-Pi), which is applicable to all proteomics pipelines. This model leverages protein-protein interaction (PPI) data and employs two types of message-passing layers to integrate evidence from both the target protein and its interactors, thereby improving identification accuracy.

Results: Grape-Pi achieved significant …

A Critical Assessment Of Artificial Intelligence In Magnetic Resonance Imaging Of Cancer, Chengyue Wu, Meryem Abbad Andaloussi, David A Hormuth, Ernesto A B F Lima, Guillermo Lorenzo, Casey E Stowers, Sriram Ravula, Brett Levac, Alexandros G Dimakis, Jonathan I Tamir, Kristy K Brock, Caroline Chung, Thomas E Yankeelov

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Given the enormous output and pace of development of artificial intelligence (AI) methods in medical imaging, it can be challenging to identify the true success stories to determine the state-of-the-art of the field. This report seeks to provide the magnetic resonance imaging (MRI) community with an initial guide into the major areas in which the methods of AI are contributing to MRI in oncology. After a general introduction to artificial intelligence, we proceed to discuss the successes and current limitations of AI in MRI when used for image acquisition, reconstruction, registration, and segmentation, as well as its utility for assisting …

Inhibition Of Nitric Oxide Synthase Transforms Carotid Occlusion-Mediated Benign Oligemia Into De Novo Large Cerebral Infarction, Ha Kim, Jinyong Chung, Jeong Wook Kang, Dawid Schellingerhout, Soo Ji Lee, Hee Jeong Jang, Inyeong Park, Taesu Kim, Dong-Seok Gwak, Ji Sung Lee, Sung-Ha Hong, Kang-Hoon Je, Hee-Joon Bae, Joohon Sung, Eng H Lo, James Faber, Cenk Ayata, Dong-Eog Kim

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No abstract provided.

Upregulation Of Delta Opioid Receptor By Meningeal Interleukin-10 Prevents Relapsing Pain, Kufreobong E Inyang, Jaewon Sim, Kimberly B Clark, Matan Geron, Karli Monahan, Christine Evans, Patrick O'Connell, Sophie Laumet, Bo Peng, Jiacheng Ma, Cobi J Heijnen, Robert Dantzer, Grégory Scherrer, Annemieke Kavelaars, Matthew Bernard, Yasser A Aldhamen, Joseph K Folger, Alexis Bavencoffe, Geoffroy Laumet

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Chronic pain often includes periods of transient amelioration and even remission that alternate with severe relapsing pain. While most research on chronic pain has focused on pain development and maintenance, there is a critical unmet need to better understand the mechanisms that underlie pain remission and relapse. We found that interleukin (IL)-10, a pain resolving cytokine, is produced by resident macrophages in the spinal meninges during remission from pain and signaled to IL-10 receptor-expressing sensory neurons. Using unbiased RNA-sequencing, we identified that IL-10 upregulated expression and antinociceptive activity of δ-opioid receptor (δOR) in the dorsal root ganglion. Genetic or pharmacological …

Privacy-Preserving Collaborative Population Stratification With Dynamic Algorithm And Hyperparameter Selection, Maryam Ghasemian, Lynette Hammond Gerido, Erman Ayday

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We present a privacy-preserving selection layer for collaborative population stratification under 𝜖-local differential privacy (LDP). Rather than fixing a single pipeline (e.g., PCA+K-Means with preset 𝐾), our framework lets parties choose among three DP pipelines: PCA→Noise, Noise→PCA, and Noise-Only, according to their resources, and has an honest-but-curious server aggregate only DP shares to automatically select the clustering algorithm (K-Means, GMM, or Hierarchical) and 𝐾 that maximize internal metrics (Silhouette, Calinski–Harabasz, Davies–Bouldin). Because selection operates on DP data, it adds no further privacy loss. On openSNP (942 samples, 28,396 SNPs), the PCA-augmented pipelines yield higher utility …

On The Empirical Power Of Goodness-Of-Fit Tests In Watermark Detection, Weiqing He, Xiang Li, Tianqi Shang, Li Shen, Weijie Su, Qi Long

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Large language models (LLMs) raise concerns about content authenticity and integrity because they can generate human-like text at scale. Text watermarks, which embed detectable statistical signals into generated text, offer a provable way to verify content origin. Many detection methods rely on pivotal statistics that are i.i.d. under human-written text, making goodness-of-fit (GoF) tests a natural tool for watermark detection. However, GoF tests remain largely underexplored in this setting. In this paper, we systematically evaluate eight GoF tests across three popular watermarking schemes, using three open-source LLMs, two datasets, various generation temperatures, and multiple post-editing methods. We find that general …

Privacy-Preserving Verification Of Ml Preprocessing Via Model Behavior Indicators, Wenbiao Li, Anisa Halimi, Jaideep Vaidya, Xiaoqian Jiang, Erman Ayday

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We present a privacy-preserving framework to verify whether a declared data preprocessing pipeline was correctly applied before training a machine learning model on sensitive data. The verifier has only black-box query access to the model and combines three behavior indicators: shift in prediction accuracy, Kullback-Leibler (KL) divergence between output distributions, and explanation vectors from Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). The method requires neither the original training records nor ground-truth labels. It supports two tasks: (i) a binary decision on correctness and (ii) a multi-class diagnosis identifying which step is missing. Experiments on three tabular datasets …

Safeguarding Privacy In Genome Research: A Comprehensive Framework For Authors, Maryam Ghasemian, Lynette Hammond Gerido, Erman Ayday

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As genomic research continues to advance, sharing of genomic data and research outcomes has become increasingly important for fostering collaboration and accelerating scientific discovery. However, such data sharing must be balanced with the need to protect the privacy of individuals whose genetic information is being utilized. This paper presents a bidirectional framework for evaluating privacy risks associated with data shared (both in terms of summary statistics and research datasets) in genomic research papers, particularly focusing on re-identification risks such as membership inference attacks (MIA). The framework consists of a structured workflow that begins with a questionnaire designed to capture researchers' …

Not Fully Synthetic: Llm-Based Hybrid Approaches Towards Privacy-Preserving Clinical Note Sharing, Atiquer Rahman Sarkar, Yao-Shun Chuang, Xiaoqian Jiang, Noman Mohammed

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The publication and sharing of clinical notes are crucial for healthcare research and innovation. However, privacy regulations such as HIPAA and GDPR pose significant challenges. While de-identification techniques aim to remove protected health information, they often fall short of achieving complete privacy protection. Similarly, the current state of synthetic clinical note generation can lack nuance and content coverage. To address these limitations, we propose an approach that combines de-identification, filtration, and synthetic clinical note generation. Variations of this approach currently retain 36%-61% of the original note's content and fill the remaining gaps using an LLM, ensuring high information coverage. We …

Enhancing Cross-Domain Generalizability In Social Determinants Of Health Extraction With Prompt-Tuning Large Language Models, Cheng Peng, Zehao Yu, Kaleb E Smith, Wei-Hsuan Lo-Ciganic, Jiang Bian, Yonghui Wu

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The progress in natural language processing (NLP) using large language models (LLMs) has greatly improved patient information extraction from clinical narratives. However, most methods based on the fine-tuning strategy have limited transfer learning ability for cross-domain applications. This study proposed a novel approach that employs a soft prompt-based learning architecture, which introduces trainable prompts to guide LLMs toward desired outputs. We examined two types of LLM architectures, including encoder-only GatorTron and decoder-only GatorTronGPT, and evaluated their performance for the extraction of social determinants of health (SDoH) using a cross-institution dataset from the 2022 n2c2 challenge and a cross-disease dataset from …

Enhancing Medical Coding Efficiency Through Domain-Specific Fine-Tuned Large Language Models, Zhen Hou, Hao Liu, Jiang Bian, Xing He, Yan Zhuang

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Medical coding is essential for healthcare operations yet remains predominantly manual, error-prone (up to 20%), and costly (up to $18.2 billion annually). Although large language models (LLMs) have shown promise in natural language processing, their application to medical coding has produced limited accuracy. In this study, we evaluated whether fine-tuning LLMs with specialized ICD-10 knowledge can automate code generation across clinical documentation. We adopted a two-phase approach: initial fine-tuning using 74,260 ICD-10 code-description pairs, followed by enhanced training to address linguistic and lexical variations. Evaluations using a proprietary model (GPT-4o mini) on a cloud platform and an open-source model (Llama) …

Using Digitally Delivered Measurement-Based Care In Substance Use Disorder Treatment: Qualitative Analysis Of Patients’ Perspectives, Tessa Frohe, Eliza B Cohn, Madeline C Frost, Tascha R Johnson, Kevin A Hallgren

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Background: Measurement-based care (MBC) is a clinical practice where patients complete standardized outcome measures throughout treatment to monitor clinical progress and inform clinical decision-making. However, MBC is rarely adopted in routine substance use disorder (SUD) treatment. We developed a digital MBC system and pilot tested it in an outpatient adult community SUD treatment setting.

Objectives:The current study aims to characterize qualitative feedback from the pilot participants about their experiences using the MBC system in SUD treatment, focusing on perceived benefits, drawbacks, and suggestions for improvement.

Methods: Participants (N=30; n=11 female 37%) completed weekly MBC questionnaires via smartphone for 6 …

Medication Prescribing Checklists And Their Impact On Patient Safety: A Scoping Review, Yilei Liu, Tate W Miner, Kawtar Zouaidi, Anika N Roy, Muhammad F Walji, Kristin N Ray, Donald B Rindal, Elsbeth Kalenderian, Katie J Suda

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Background: Medication prescribing checklists and the impact on patient safety remain unexplored.

Objectives: This scoping review aimed to identify key elements of these checklists and evaluate their impact on patient safety outcomes.

Methods: We searched PubMed and Embase for studies reporting checklists in medication prescribing practices and the impact on patient safety outcomes as of October 23, 2024. We applied Fisher's exact test to evaluate the association between checklist effectiveness (based on patient safety outcomes) with study design (randomized controlled trials [RCTs] vs non-RCTs) and intervention type (bundled intervention vs checklist-only intervention).

Results: After full-text review, 53 articles met inclusion …

Daily Movement Activities Are Associated With Within-Person Instability Of Cognitive Function In Older Adults: Evidence From An Ambulatory Assessment Study, Chih-Hsiang Yang, Donald Hedeker, Jongwon Lee, Halle Prine, Donna Coffman, Jingkai Wei, Jonathan George Hakun

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Background and objectives: Physical inactivity and excessive sedentary time (ST) are associated with poor cognitive health in older adults. However, current literature largely relies on cross-sectional designs or in-lab cognitive assessments, which do not adequately reflect cognitive function in naturalistic settings. Further, existing studies have largely overlooked the variability or the instability in daily cognitive function, which represents a critical marker of cognitive decline. This ambulatory assessment study examined the temporal associations of daily movement behaviors with the mean levels and the variability of cognition among older adults at risk of dementia.

Research design and methods: 96 older adults from …

Association Of Cardiovascular Disease With Dementia: A Longitudinal Analysis Using National Alzheimer’S Coordinating Center Data, Diana Summanwar, Hyena Kim, Jingkai Wei, Malaz Boustani, Alvaro Alonso, Ambar Kulshreshtha

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We analyzed how cardiovascular disease subtypes influence the prevalence and incidence of dementia among 30,582 individuals aged 50 and older in the National Alzheimer's Coordinating Center cohort. We calculated prevalence ratios (aPR) and hazard ratios (aHR), using models adjusted for age, sex, race, years of education, hypertension, diabetes, and dyslipidemia. Stroke (aPR: 1.26; 95% CI: 1.20-1.32) and history of arrhythmias (aPR: 1.17; 95% CI: 1.09-1.24) were associated with higher dementia prevalence. In survival analysis, stroke was associated with a 55% increased risk of incident dementia (aHR: 1.55; 95% CI: 1.36-1.77).

Neutrophils Unveiled In Chronic Lymphocytic Leukemia, Sheighlah Mcmanus, Priyanka Khare, Maria Teresa S Bertilaccio

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This review explores neutrophils' roles in chronic lymphocytic leukemia (CLL), highlighting their functions within the immune system. While neutrophils are known for fighting infections, their altered behavior in CLL significantly impacts disease progression. This review notes the reduced phagocytic abilities of neutrophils and the increased formation of neutrophil extracellular traps (NETs) in patients with CLL. It also examines the effects of CLL treatments, including chemotherapy, immunotherapy and targeted therapies, on neutrophils' count and function, stressing the need for improved strategies to manage therapy-induced immune dysfunction. This review also provides detailed information about the interactions between neutrophils and other immune elements …

Microbial Imprints On Colorectal Cancer: The Epigenetic Silencing Of Phlpp1 As A Prognostic Nexus, Xiangsheng Huang, Faraz Bishehsari

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No abstract provided.

Editorial: Protein Regulation By Lipids, Mikhail V Bogdanov, Elena G Govorunova

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No abstract provided.

Protecting Organs-At-Risk In Cancer Therapies Through Temporary Organ Displacement: A Comprehensive Review, Rance B Tino, Michael Li, Amirreza Heshmat, Ayush Suresh, Anasimone Guillaume, Kristy K Brock, Bruno C Odisio, Eugene J Koay

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Radiation therapy (RT) and locoregional ablation are cornerstones of modern oncology, yet their therapeutic potential is frequently limited by the challenge of sparing healthy organs-at-risk (OARs) from treatment-related complications. Temporary organ displacement (TOD) techniques directly address this issue by creating a physical separation using 'spacers' during treatment, thereby minimizing collateral damage while enhancing therapeutic precision. The clinical benefits, including improved tumor control, reduced morbidity, and enhanced survival, are documented across malignancies of the head and neck, thorax, abdomen, and pelvis. To create a unified framework for this evolving field, this comprehensive review provides a systematic classification of TOD techniques based …

Digital Twins In Healthcare: A Comprehensive Review And Future Directions, Hamid Khoshfekr Rudsari, Becky Tseng, Hongxu Zhu, Lulu Song, Chunhui Gu, Abhishikta Roy, Ehsan Irajizad, Joseph Butner, James Long, Kim-Anh Do

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Digital Twin (DT) technology has emerged as a transformative force in healthcare, offering unprecedented opportunities for personalized medicine, treatment optimization, and disease prevention. This comprehensive review examines the current state of DTs in healthcare, analyzing their implementation across different physiological levels-from cellular to whole-body systems. We systematically review the latest developments, methodologies, and applications while identifying challenges and opportunities. Our analysis encompasses technical frameworks for cardiovascular, neurological, respiratory, metabolic, hepatic, oncological, and cellular DTs, highlighting significant achievements such as population-scale cardiac modeling (3,461 patient cohort), reduced atrial fibrillation recurrence rates through patient-specific cardiac models, improved brain tumor radiotherapy planning, advanced …

Role Of Mir-204 In Controlling Metabolic Functions Of The Subretinal Microglia, Yan Chen, Sarah E Bounds, Neloy Kundu, James Regun Karmoker, Yin Liu, Dongin Kim, Jiyang Cai

Faculty, Staff and Student Publications

Rationale: MicroRNA-204 (miR-204) is one of the most abundant miRNA species in the retinal pigment epithelium (RPE) and RPE-derived extracellular vesicles (EVs). Knockout (KO) of miR-204 leads to dysfunction and degeneration of both the RPE and the retina. In addition to previously reported retinal pathologies, we observed the accumulation of lipid-laden subretinal microglia in miR-204 KO mice. This study aimed to identify potential molecular targets of miR-204 involved in microglia lipid processing and to determine whether RPE-derived EVs can improve the function of miR-204-deficient retinal microglia.

Methods: Lipid accumulation in microglia was detected by staining with LipidTox, a fluorescent dye …