Digital Commons Network^™

Combining Biology-Based And Mri Data-Driven Modeling To Predict Response To Neoadjuvant Chemotherapy In Patients With Triple-Negative Breast Cancer, Casey E Stowers, Chengyue Wu, Zhan Xu, Sidharth Kumar, Clinton Yam, Jong Bum Son, Jingfei Ma, Jonathan I Tamir, Gaiane M Rauch, Thomas E Yankeelov

Faculty, Staff and Student Publications

Purpose

To combine deep learning and biology-based modeling to predict the response of locally advanced, triple-negative breast cancer before initiating neoadjuvant chemotherapy (NAC).

Materials and Methods

In this retrospective study, a biology-based mathematical model of tumor response to NAC was constructed and calibrated on a patient-specific basis using imaging data from patients enrolled in the MD Anderson A Robust TNBC Evaluation FraMework to Improve Survival trial (ARTEMIS; ClinicalTrials.gov registration no. NCT02276443) between April 2018 and May 2021. To relate the calibrated parameters in the biology-based model and pretreatment MRI data, a convolutional neural network (CNN) was employed. The CNN …

Chronic Circadian Misalignment Accelerates Sarcopenia Progression In Mice, Takashi Seya, Nobuya Koike, Naoki Okubo, Yasuhiro Umemura, Yoshiki Tsuchiya, Kazuya Yabumoto, Yasuhiro Endo, Kanako Iinuma, Akiyo Kakibuchi, Akira Sugimoto, Kenji Takahashi, Seung-Hee Yoo, Zheng Chen, Kazuhiro Yagita

Faculty, Staff and Student Publications

Introduction: In today's 24/7 society, circadian misalignment caused by environmental and lifestyle factors is associated with various adverse health consequences. Understanding tissue-specific pathology is required to counter this growing public health challenge. A potential association of environmental circadian misalignment with sarcopenia, or accelerated loss of skeletal muscle strength and mass, is poorly documented.

Methods: 14-week-old wild-type C57BL/6J male mice were exposed to a chronic jet lag (CJL) paradigm consisting of an 8-h phase advance every 4 days (the ADV group) or a fixed light-dark cycle (the LD group) for 64 weeks. Grip strength was measured during the experiment, and hindlimb …

Accumulated Seizure Burden Predicts Neurodevelopmental Outcome At 36 Months Of Age In Patients With Tuberous Sclerosis Complex, S Katie Z Ihnen, Samuel Alperin, Jamie K Capal, Alexander L Cohen, Jurriaan M Peters, E Martina Bebin, Hope A Northrup, Mustafa Sahin, Darcy A Krueger

Faculty, Staff and Student Publications

Objective: Epilepsy and intellectual disability are common in tuberous sclerosis complex (TSC). Although early life seizures and intellectual disability are known to be correlated in TSC, the differential effects of age at seizure onset and accumulated seizure burden on development remain unclear.

Methods: Daily seizure diaries, serial neurodevelopmental testing, and brain magnetic resonance imaging were analyzed for 129 TSC patients followed from 0 to 36 months. We used machine learning to identify subgroups of patients based on neurodevelopmental test scores at 36 months of age and assessed the stability of those subgroups at 12 months. We tested the ability of …

Practical Application Of Multivendor Mri-Based R2* Mapping For Liver Iron Quantification At 15 T And 30 T, Gregory Simchick, Ruiyang Zhao, Qing Yuan, Mounes Aliyari Ghasabeh, Stefan Ruschke, Dimitrios C Karampinos, David T Harris, Raphael Do Vale Souza, Ryan J Mattison, Michael R Jeng, Ivan Pedrosa, Ihab R Kamel, Shreyas Vasanawala, Takeshi Yokoo, Scott B Reeder, Diego Hernando

Faculty, Staff and Student Publications

Background: Recent multicenter, multivendor MRI-based R2* vs. liver iron concentration (LIC) calibrations (i.e., MCMV calibrations) may facilitate broad clinical dissemination of R2*-based LIC quantification. However, these calibrations are based on a centralized offline R2* reconstruction, and their applicability with vendor-provided R2* maps is unclear.

Purpose: To determine R2* ranges of agreement between the centralized and three MRI vendors' R2* reconstructions.

Study type: Prospective.

Subjects: Two hundred and seven subjects (mean age 37.6 ± 19.6 years; 117 male) with known or suspected iron overload from four academic medical centers.

Field strength/sequence: Standardized multiecho spoiled gradient echo sequence at 1.5 T and …

Development Of Microcystoid Macular Degeneration In The Retina Of Nonhuman Primates: Time-Course And Associated Pathologies, Thomas C M Lavery, Carol A Rasmussen, Alexander W Katz, Charlene B Y Kim, James N Ver Hoeve, Paul E Miller, Peter J Sonnentag, Brian J Christian, Christopher J Murphy, David R Piwnica-Worms, Seth T Gammon, Xudong Qiu, Paul L Kaufman, T Michael Nork

Faculty, Staff and Student Publications

Purpose: Microcystoid macular degeneration (MMD) is a condition where cystoid vacuoles develop within the inner nuclear layer of the retina in humans in a variety of disorders. Here we report the occurrence of MMD in non-human primates (NHPs) with various retinal ganglion cell (RGC) pathologies and evaluate the hypothesis that MMD does not precede RGC loss but follows it.

Methods: Morphological studies were performed of the retinas of NHPs, specifically both rhesus (Macaca mulatta) and cynomolgus macaques (Macaca fascicularis), in which MMD was identified after induction of experimental glaucoma (EG), hemiretinal endodiathermy axotomy (HEA), and spontaneous …

Explainable Diagnosis Prediction Through Neuro-Symbolic Integration, Qiuhao Lu, Rui Li, Elham Sagheb, Andrew Wen, Jinlian Wang, Liwei Wang, Jungwei W Fan, Hongfang Liu

Faculty, Staff and Student Publications

Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of medical conditions can significantly impact patient outcomes. Traditional machine learning and deep learning models have achieved notable success in this domain but often lack interpretability which is a crucial requirement in clinical settings. In this study, we explore the use of neuro-symbolic methods, specifically Logical Neural Networks (LNNs), to develop explainable models for diagnosis prediction. Essentially, we design and implement LNN-based models that integrate domain-specific knowledge through logical rules with learnable weights and thresholds. Our models, particularly Mmulti-pathway and Mcomprehensive, demonstrate superior performance over traditional models …

Rank Aggregation Methods And Tools In Genomic Data Analysis, Wenping Zou, Savannah Mwesigwa, Sayed-Rzgar Hosseini, Zhongming Zhao

Faculty, Staff and Student Publications

Rank aggregation (RA) is the process of consolidating disparate rankings into a single unified ranking. It holds immense potential in the field of genomics. RA has applications in diverse research areas, such as gene expression analysis, meta-analysis, gene prioritization, and biomarker discovery. However, there are many challenges in the application of the RA approach to biological data, such as dealing with heterogeneous data sources, rankings of mixed quality, and evaluating the consolidated rankings. In this review, we present an overview of the existing RA methods with an emphasis on those that have been tailored to the complexities of genomics research. …

Temporal Ensemble Logic For Integrative Representation Of The Entirety Of Clinical Trials, Xiaojin Li, Yan Huang, Rashmie Abeysinghe, Zenan Sun, Hongyu Chen, Pengze Li, Xing He, Shiqiang Tao, Cui Tao, Jiang Bian, Licong Cui, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Clinical trials are typically specified with protocols that define eligibility criteria, treatment regimens, follow-up schedules, and outcome assessments. Temporality is a hallmark of all clinical trials, reflected within and across trial components, with complex dependencies unfolding across multiple time points. Despite their importance, clinical trial protocols are described in free-text format, limiting their semantic precision and the ability to support automated reasoning, leverage data across studies and sites, or simulate trial execution under varying assumptions using Real-World Data. This paper introduces a formalized representation of clinical trials using Temporal Ensemble Logic (TEL). TEL incorporates metricized modal operators, such as “always …

Nrg Oncology White Paper On The Relative Biological Effectiveness In Proton Therapy, Harald Paganetti, Charles B Simone, Walter R Bosch, Daphne Haas-Kogan, David G Kirsch, Heng Li, Xiaoying Liang, Wei Liu, Anita Mahajan, Michael D Story, Paige A Taylor, Henning Willers, Ying Xiao, Jeffrey C Buchsbaum

Faculty, Staff and Student Publications

This position paper, led by the NRG Oncology Particle Therapy Work Group, focuses on the concept of relative biologic effect (RBE) in clinical proton therapy (PT), with the goal of providing recommendations for the next-generation clinical trials with PT on the best practice of investigating and using RBE, which could deviate from the current standard proton RBE value of 1.1 relative to photons. In part 1, current clinical utilization and practice are reviewed, giving the context and history of RBE. Evidence for variation in RBE is presented along with the concept of linear energy transfer (LET). The intertwined nature of …

Individualized Frequency And Montage Tacs To Engage Theta-Gamma Coupling And Enhance Working Memory In Mild Cognitive Impairment, Mina Mirjalili, Iryna S Palamarchuk, Heather Brooks, Reza Zomorrodi, Ashley Melichercik, Wei Wang, Sean M Nestor, Daniel M Blumberger, Abhishek Datta, Christopher Bowie, Bernadette Mdawar, Kullervo Hynynen, Sanjeev Kumar, Tarek K Rajji

Faculty, Staff and Student Publications

Mild Cognitive Impairment (MCI) is a clinical prodromal stage of Alzheimer's disease. Enhancing executive functions in patients with MCI could optimize cognitive compensatory mechanisms and slow cognitive decline. The prefrontal cortex (PFC) and its connections to the hippocampus support executive functions, including working memory. Transcranial alternating current stimulation (tACS) can modulate these connections by engaging theta-gamma coupling (TGC) and may thereby strengthen working memory. This study, "tACS to engage theta-gamma coupling and enhance working memory in MCI" (tACS-MCI), will assess the feasibility and cognitive effects of EEG and MRI-guided individualized tACS. The stimulation will target the prefrontal and temporal cortices …

Characterization Of Additive Gene-Environment Interactions For Colorectal Cancer Risk, Claire E Thomas, Yi Lin, Michelle Kim, Eric S Kawaguchi, Conghui Qu, Caroline Y Um, Brigid M Lynch, Bethany Van Guelpen, Kostas Tsilidis, Robert Carreras-Torres, Franzel J B Van Duijnhoven, Lori C Sakoda, Peter T Campbell, Yu Tian, Jenny Chang-Claude, Stéphane Bézieau, Arif Budiarto, Julie R Palmer, Polly A Newcomb, Graham Casey, Loic Le Marchandz, Marios Giannakis, Christopher I Li, Andrea Gsur, Christina Newton, Mireia Obón-Santacana, Victor Moreno, Pavel Vodicka, Hermann Brenner, Michael Hoffmeister, Andrew J Pellatt, Robert E Schoen, Niki Dimou, Neil Murphy, Marc J Gunter, Sergi Castellví-Bel, Jane C Figueiredo, Andrew T Chan, Mingyang Song, Li Li, D Timothy Bishop, Stephen B Gruber, James W Baurley, Stephanie A Bien, David V Conti, Jeroen R Huyghe, Anshul Kundaje, Yu-Ru Su, Jun Wang, Temitope O Keku, Michael O Woods, Sonja I Berndt, Stephen J Chanock, Catherine M Tangen, Alicja Wolk, Andrea Burnett-Hartman, Anna H Wu, Emily White, Matthew A Devall, Virginia Díez-Obrero, David A Drew, Edward Giovannucci, Akihisa Hidaka, Andre E Kim, Juan Pablo Lewinger, John Morrison, Jennifer Ose, Nikos Papadimitriou, Bens Pardamean, Anita R Peoples, Edward A Ruiz-Narvaez, Anna Shcherbina, Mariana C Stern, Xuechen Chen, Duncan C Thomas, Elizabeth A Platz, W James Gauderman, Ulrike Peters, Li Hsu

Faculty, Staff and Student Publications

Background: Colorectal cancer (CRC) is a common, fatal cancer. Identifying subgroups who may benefit more from intervention is of critical public health importance. Previous studies have assessed multiplicative interaction between genetic risk scores and environmental factors, but few have assessed additive interaction, the relevant public health measure.

Methods: Using resources from CRC consortia, including 45,247 CRC cases and 52,671 controls, we assessed multiplicative and additive interaction (relative excess risk due to interaction, RERI) using logistic regression between 13 harmonized environmental factors and genetic risk score, including 141 variants associated with CRC risk.

Results: There was no evidence of multiplicative interaction …

Optimization Of Proximity Labeling In Endothelial Cells: Overcoming Endogenous Biotin Interference And Cost Barriers, Ying Jiang, Kuizhi Qu, Mengjun Dai, Yan-Ning Rui, Zhen Xu

Faculty, Staff and Student Publications

Proximity labeling has become a powerful technique for mapping protein-protein interactions under physiologically relevant conditions, with TurboID offering high enzymatic activity and rapid labeling. However, its application in endothelial systems has been limited, partly due to the presence of endogenous biotin in specialized media, which reduces labeling specificity. Here, we optimized TurboID-mediated proximity labeling in brain microvascular endothelial cells by addressing two key challenges: endogenous biotin interference and cost-effective depletion. We discovered that endothelial cell medium contains substantial biotin levels, which saturate TurboID labeling and obscure the effects of exogenous biotin. Using High Capacity NeutrAvidin

Correction: Topss: Tolerability Of Transcranial Direct Current Stimulation In Pediatric Stroke Survivors, Stuart Fraser, Anna Clearman, Melika Abrahams, Bernadette Gillick, Tia Lal, Sean Savitz, Nuray Yozbatiran

Faculty, Staff and Student Publications

[This corrects the article DOI: 10.3389/fnhum.2025.1629499.].

Mechanisms Of How Sarcopenia Affects Functional Outcomes In Acute Ischaemic Stroke, Dong-Seok Gwak, Jinyong Chung, Dawid Schellingerhout, Hyerin Oh, Sang-Wuk Jeong, Ji Sung Lee, Dong-Eog Kim

Faculty, Staff and Student Publications

Sarcopenia, a common geriatric condition characterized by the loss of skeletal muscle mass and function, can negatively affect functional outcomes in acute ischaemic stroke; however, the underlying mechanisms remain unclear. We hypothesized that sarcopenia affects post-stroke outcomes, mediated through its impact on dysphagia, early neurological deterioration, or post-stroke recovery, particularly in patients with motor deficits. To explore this hypothesis, we included 600 consecutive elderly (≥65 years) patients with acute (< 1 week) ischaemic stroke and assessed: (i) the relationships sarcopenia has with dysphagia, early neurological deterioration and various phases of recovery after stroke (in-hospital, post-discharge [up to 3 months], and chronic [3 months to 1 year]) and (ii) whether either presenting symptoms or lesion locations modify the impact of sarcopenia on stroke outcomes. Temporal muscle thickness, a marker of sarcopenia, was measured by brain magnetic resonance imaging and dichotomized into low versus high temporal muscle thickness at the 25th percentile cut-off point. Logistic regression analysis, mediation analysis and statistical brain mapping were conducted. Mean age was 75.3 ± 6.1 years and 303 (50.5%) were male. Low temporal muscle thickness (< 5.1 mm) was independently associated with dysphagia (adjusted odds ratio 1.89 [95% confidence interval 1.06–3.37], P = 0.03), early neurological deterioration (adjusted odds ratio 2.75 [95% confidence interval 1.61–4.71], P < 0.001) and post-discharge recovery (adjusted odds ratio 0.56 [95% confidence interval 0.34–0.94], P = 0.03) but not with in-hospital or chronic recovery. In addition, dysphagia, early neurological …

Recovery Of Verbal Working Memory Depends On Left Hemisphere White Matter Tracts, Randi C Martin, Junhua Ding, Ali I Alwani, Steve H Fung, Tatiana T Schnur

Faculty, Staff and Student Publications

Researchers propose that the recovery of language function following stroke depends on the recruitment of perilesional regions in the left hemisphere and/or homologous regions in the right hemisphere. Many investigations of recovery focus on changes in gray matter regions, whereas relatively few examine white matter tracts and none address the role of these tracts in the recovery of verbal working memory. The present study addressed these gaps, examining the role of left versus right hemisphere tracts in the longitudinal recovery of phonological and semantic working memory. For 24 individuals with left hemisphere stroke, we assessed working memory performance within 1 …

Ai/Ml-Empowered Approaches For Predicting T Cell-Mediated Immunity And Beyond, Cheng-Chi Chao, Yulun Chiu, Lucas Yeung, Cassian Yee, Chongming Jiang, Xiling Shen

Faculty, Staff and Student Publications

T cells play a dual role in various physiopathological states, capable of eliminating tumors and infected cells, while also playing a pathogenic role when activated by autoantigens, causing self-tissue damage. The regulation of T cell-peptide/major histocompatibility complex (TCR-pMHC) recognition is crucial for maintaining disease balance and treating cancer, infections, and autoimmune diseases. Despite efforts, predictive models of TCR-pMHC specificity are still in the early stages. Inspired by advances in protein structure prediction via deep neural networks, we evaluated AlphaFold 3 (AF3)-based AI computation as a method to predict TCR epitope specificity. We demonstrate that AlphaFold can model TCR-pMHC interactions, distinguishing …

Innovative Approaches In Precision Radiation Oncology: Advanced Imaging Technologies And Challenges Which Shape The Future Of Radiation Therapy, Yue Yan, Daniel A Alexander, Bryan P Bednarz, Lawrence F Bronk, Huixiao Chen, David J Gladstone, Bin Han, Christopher M Iannuzzi, Yuting Li, Ngoc Nguyen, Natasha Mulenga, Natalie N Viscariello, Yuenan Wang, Joseph Weygand, Yana Zlateva, Fada Guan

Faculty, Staff and Student Publications

Radiation oncology is undergoing a transformative shift toward precision medicine through unprecedented advances in imaging technologies that enable increasingly personalized and adaptive cancer treatment. This comprehensive review synthesizes the underlying physical principles, current clinical applications, technical challenges, and quality assurance requirements across the complete spectrum of emerging imaging-guided radiation therapy approaches. We examine magnetic resonance-guided radiotherapy systems that enable daily soft-tissue visualization and online plan adaptation, positron emission tomography-guided platforms that allow real-time tracking of metabolically active tumor regions, advanced cone beam computed tomography systems supporting rapid adaptive workflows through artificial intelligence-enhanced image generation, and novel applications including Cherenkov radiation …

Correction: Innovative Approaches In Precision Radiation Oncology: Advanced Imaging Technologies And Challenges Which Shape The Future Of Radiation Therapy, Yue Yan, Daniel A Alexander, Bryan P Bednarz, Lawrence F Bronk, Huixiao Chen, David J Gladstone, Bin Han, Christopher M Iannuzzi, Yuting Li, Ngoc Nguyen, Natasha Mulenga, Natalie N Viscariello, Yuenan Wang, Joseph Weygand, Yana Zlateva, Fada Guan

Faculty, Staff and Student Publications

No abstract provided.

Refining Breast Cancer Genetic Risk And Biology Through Multi-Ancestry Fine-Mapping Analyses Of 192 Risk Regions, Guochong Jia, Zhishan Chen, Jie Ping, Qiuyin Cai, Ran Tao, Chao Li, Joshua A Bauer, Yuhan Xie, Stefan Ambs, Mollie E Barnard, Yu Chen, Ji-Yeob Choi, Yu-Tang Gao, Montserrat Garcia-Closas, Jian Gu, Jennifer J Hu, Motoki Iwasaki, Esther M John, Sun-Seog Kweon, Christopher I Li, Koichi Matsuda, Keitaro Matsuo, Katherine L Nathanson, Barbara Nemesure, Olufunmilayo I Olopade, Tuya Pal, Sue K Park, Boyoung Park, Michael F Press, Maureen Sanderson, Dale P Sandler, Chen-Yang Shen, Melissa A Troester, Song Yao, Ying Zheng, Thomas Ahearn, Abenaa M Brewster, Adeyinka Falusi, Anselm J M Hennis, Hidemi Ito, Michiaki Kubo, Eun-Sook Lee, Timothy Makumbi, Paul Ndom, Dong-Young Noh, Katie M O'Brien, Oladosu Ojengbede, Andrew F Olshan, Min-Ho Park, Sonya Reid, Taiki Yamaji, Gary Zirpoli, Ebonee N Butler, Maosheng Huang, Siew-Kee Low, John Obafunwa, Clarice R Weinberg, Haoyu Zhang, Hongyu Zhao, Michelle L Cote, Christine B Ambrosone, Dezheng Huo, Bingshan Li, Daehee Kang, Julie R Palmer, Xiao-Ou Shu, Christopher A Haiman, Xingyi Guo, Jirong Long, Wei Zheng

Faculty, Staff and Student Publications

Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant. Analyses integrating functional genomics data identified 195 putative susceptibility genes, enriched in PI3K/AKT, TNF/NF-κB, p53 …

Exploring The Role Of Reward Functioning In The Overlap Of Post-Traumatic Stress And Cocaine Use Disorder, Kate Hull, Hanaan Bing-Canar, Krista Miloslavich, Christopher Holden, Aneet Ahluwalia, Scott D Lane, Joy M Schmitz, Margaret C Wardle

Faculty, Staff and Student Publications

Background: Posttraumatic stress disorder (PTSD) symptoms are common in people with cocaine use disorder (CUD), and even sub-threshold PSTD symptoms result in worse treatment outcomes. Difficulties with reward functioning may drive this comorbidity. Impairments in reward functioning are prominent in both PTSD and CUD and contribute to development of substance use problems after trauma. There are three distinct reward processes that may be involved in the PTSD/CUD overlap: consummatory reward (ability to experience pleasure), motivational reward (willingness to exert effort for rewards), and reward learning (adapting behavior based on reward history). Here we test whether impairments in these reward functions …

A Biomechanical Study Of Neck Strength And Impact Dynamics On Head And Neck Injury Parameters, Rahid Zaman, Mohammad Ibrahim Hossain, Ahmed Zubayer Raiyan, Shuvo Chowdhury, Aaron Jackson, Arthur Thomas Koster, Ashfaq Adnan

Faculty, Staff and Student Publications

Introduction: Head and neck injuries, including traumatic brain injuries (TBI), are a leading cause of disability and death worldwide. It affects millions of people worldwide, from automobiles to sports to military personnel. This study investigates the influence of impact locations, severities, and neck strength on head and neck injury parameters using a musculoskeletal head-neck model in OpenSim software.

Methods: We hypothesize that eccentric impacts, particularly those on the anterolateral side, increase GAMBIT and Neck Injury Criteria (NIC) due to elevated rotational accelerations, and that higher neck strength mitigates GAMBIT and NIC under these impacts. To test our hypotheses, we investigated …

A Network-Based Discovery Of Prognostic Markers In Recurrent Idh Wild-Type Gliomas, Yang Liu, Jason Huse, Kasthuri Kannan

Faculty, Staff and Student Publications

Background: Isocitrate dehydrogenase wild-type (IDH wild-type) gliomas represents the most aggressive subtype of diffuse gliomas, characterized by therapeutic resistance and dismal prognosis. Despite advances in molecular classification, reliable prognostic biomarkers for these tumors remain limited, particularly for recurrent disease. This study aims to identify gene expression signatures associated with survival outcomes in recurrent IDH wild-type gliomas, with the goal of improving patient stratification and potential therapeutic targeting.

Methods: We analyzed gene expression data from 180 recurrent IDH wild-type glioma samples from the Glioma Longitudinal AnalySiS (GLASS) Consortium. Using multiple computational approaches including a novel network-based method (netSurvival) and various survival …

Exposure Therapy Consortium: Outcomes Of The Proof-Of-Principle Study, Jasper A J Smits, Jonathan S Abramowitz, Rebecca A Anderson, Joanna J Arch, Daniel Badeja, Snir Barzilay, Amanda N Belanger, Thomas Borchert, Emma Bryant, Alane S Burger, Laura J Dixon, Christina D Dutcher, Hayley E Fitzgerald, Bronwyn M Graham, Anke Haberkamp, Stefan G Hofmann, Jürgen Hoyer, Jonathan D Huppert, David Johnson, Baraa Q Kabha, Alex Kirk, Jürgen Margraf, Peter M Mcevoy, Bryan Mcspadden, Jill Newby, Michael W Otto, Santiago Papini, E Marie Parsons, Andre Pittig, Roxana Pittig, Winfried Rief, Svenja Schaumburg, Kiara R Timpano, Lena Waltemate, Andre Wannemüller, Cornelia Weise, Exposure Therapy Consortium

Faculty, Staff and Student Publications

Background: This paper reports on the outcomes of a proof-of-principle study for the Exposure Therapy Consortium, a global network of researchers and clinicians who work to improve the effectiveness and uptake of exposure therapy. The study aimed to test the feasibility of the consortium's big-team science approach and test the hypothesis that adding post-exposure processing focused on enhancing threat reappraisal would enhance the efficacy of a one-session large-group interoceptive exposure therapy protocol for reducing anxiety sensitivity.

Methods: The study involved a multi-site cluster-randomized controlled trial comparing exposure with post-processing (ENHANCED), exposure without post-processing (STANDARD), and a stress management intervention (CONTROL) …

Analyzing Pain Patterns In Stroke Survivors In Outpatient Clinics: A Retrospective, Cross-Sectional, Observational Study, Deniz Dishman, Catherine Gonzalez, Tia S Thomas, Hari Kishan Indupuru, Seokhun Kim, Charles Green, Anjail Sharrief, Sean I Savitz

Faculty, Staff and Student Publications

Background: Pain is one of the most common sequelae after a stroke. Yet it is under-recognized, under-treated, and under-investigated, with no standard care guidelines for management during post-stroke recovery.

Purpose: The primary objective of this study was to capture the prevalence of pain and different pain types in stroke survivors.

Patients and methods: The study included stroke survivors who completed a pre-visit telehealth review of systems instrument between March 1, 2020, and February 28, 2022. 442 out-patient subjects were identified and matched to their respective electronic health record from the incident stroke. Subjects were divided into pain and no-pain groups …

Long-Term Follow-Up Of A Phase 2 Study Of All-Trans Retinoic Acid, Arsenic Trioxide, And Gemtuzumab Ozogamicin In Acute Promyelocytic Leukemia, Wei-Ying Jen, Jennifer Marvin-Peek, Hagop M Kantarjian, Yesid Alvarado, Gautam Borthakur, Elias Jabbour, William Wierda, Tapan M Kadia, Naval G Daver, Courtney D Dinardo, Nicholas J Short, Nitin Jain, Alessandra Ferrajoli, Steven Kornblau, Musa Yilmaz, Maro Ohanian, David Mccue, Jan Burger, Danielle Hammond, Keyur Patel, Ghayas C Issa, Naveen Pemmaraju, Koji Sasaki, Abhishek Maiti, Hussein A Abbas, Kelly Chien, Koichi Takahashi, Fadi Haddad, Prithviraj Bose, Lucia Masarova, Guillermo Montalban-Bravo, Mahesh Swaminathan, Mark Brandt, Sherry Pierce, Guillermo Garcia-Manero, Farhad Ravandi

Faculty, Staff and Student Publications

Background: All-trans retinoic acid (ATRA) and arsenic trioxide (ATO) combinations have produced excellent outcomes in patients with standard-risk acute promyelocytic leukemia (APL). Herein, the authors update their long-term results with the regimen of ATO-ATRA and gemtuzumab ozogamicin (GO) in standard-risk and high-risk APL.

Methods: This was a phase 2 trial of patients with newly diagnosed APL. Induction comprised ATRA 45 mg/m2 and ATO 0.15 mg/kg daily. GO 6-9 mg/m2 was added for high-risk patients and for standard-risk patients who developed leukocytosis >10 × 109/L. Consolidation consisted of four courses of ATO-ATRA, with GO for patients who had PML::RARA persistence.

Results: …

The Tripod-Llm Reporting Guideline For Studies Using Large Language Models, Jack Gallifant, Majid Afshar, Saleem Ameen, Yindalon Aphinyanaphongs, Shan Chen, Giovanni Cacciamani, Dina Demner-Fushman, Dmitriy Dligach, Roxana Daneshjou, Chrystinne Fernandes, Lasse Hyldig Hansen, Adam Landman, Lisa Lehmann, Liam G Mccoy, Timothy Miller, Amy Moreno, Nikolaj Munch, David Restrepo, Guergana Savova, Renato Umeton, Judy Wawira Gichoya, Gary S Collins, Karel G M Moons, Leo A Celi, Danielle S Bitterman

Faculty, Staff and Student Publications

Large language models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present transparent reporting of a multivariable model for individual prognosis or diagnosis (TRIPOD)-LLM, an extension of the TRIPOD + artificial intelligence statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion. The guidelines introduce a modular format accommodating various LLM research designs and tasks, with 14 main items and 32 subitems applicable across all categories. Developed through an expedited Delphi process and expert consensus, TRIPOD-LLM emphasizes …

Prevalence Of Carotid Ultrasound Screening In Survivors Of Childhood Cancer: A Report From The Childhood Cancer Survivor Study, Yolanda Bryce, Jillian A Whitton, Kayla L Stratton, Wendy M Leisenring, Eric J Chow, Gregory Armstrong, Brent Weil, Bryan Dieffenbach, Rebecca M Howell, Kevin C Oeffinger, Paul C Nathan, Emily S Tonorezos

Faculty, Staff and Student Publications

Introduction: Many childhood cancer survivors are at risk for cardiovascular disease and stroke. The North American Children's Oncology Group long-term follow-up guidelines recommend carotid ultrasound in cancer survivors 10 years after neck radiation therapy (RT) ≥40 Gy. The use of carotid ultrasound in this population has not been described.

Methods: Survivors of childhood cancer diagnosed 1970-1999 (N = 8693) and siblings (N = 1989) enrolled in the Childhood Cancer Survivor Study were asked if they had ever had a carotid ultrasound. Prevalence of carotid ultrasound was evaluated. Prevalence ratios (PR) and 95% confidence intervals (CIs) were evaluated in multivariate Poisson …

Acute Myeloid Leukemia Management And Research In 2025, Hagop M Kantarjian, Courtney D Dinardo, Tapan M Kadia, Naval G Daver, Jessica K Altman, Eytan M Stein, Elias Jabbour, Charles A Schiffer, Amy Lang, Farhad Ravandi

Faculty, Staff and Student Publications

The first 5 decades of research in acute myeloid leukemia (AML) were dominated by the cytarabine plus anthracyclines backbone, with advances in strategies including allogeneic hematopoietic stem cell transplantation, high-dose cytarabine, supportive care measures, and targeted therapies for the subset of patients with acute promyelocytic leukemia. Since 2017, a turning point in AML research, 12 agents have received regulatory approval for AML in the United States: venetoclax (BCL2 inhibitor); gemtuzumab ozogamicin (CD33 antibody-drug conjugate); midostaurin, gilteritinib, and quizartinib (fms-like tyrosine kinase 3 inhibitors); ivosidenib, olutasidenib, and enasidenib (isocitrate dehydrogenase 1 and 2 inhibitors); oral azacitidine (a partially absorbable formulation); CPX351 …

Machine Learning Predicting Acute Pain And Opioid Dose In Radiation Treated Oropharyngeal Cancer Patients, Vivian Salama, Laia Humbert-Vidan, Brandon Godinich, Kareem A Wahid, Dina M Elhabashy, Mohamed A Naser, Renjie He, Abdallah S R Mohamed, Ariana J Sahli, Katherine A Hutcheson, Gary Brandon Gunn, David I Rosenthal, Clifton D Fuller, Amy C Moreno

Faculty, Staff and Student Publications

Introduction: Acute pain is common among oral cavity/oropharyngeal cancer (OCC/OPC) patients undergoing radiation therapy (RT). This study aimed to predict acute pain severity and opioid doses during RT using machine learning (ML), facilitating risk-stratification models for clinical trials.

Methods: A retrospective study examined 900 OCC/OPC patients treated with RT during 2017-2023. Pain intensity was assessed using NRS (0-none, 10-worst) and total opioid doses were calculated using morphine equivalent daily dose (MEDD) conversion factors. Analgesics efficacy was assessed using combined pain intensity and total MEDD. ML predictive models were developed and validated, including Logistic Regression (LR), Support Vector Machine (SVM), Random …

Psychometric Properties And Meaningful Change Thresholds For The Qol-E Instrument In Patients With Myelodysplastic Neoplasms, Esther Natalie Oliva, Shien Guo, Jennifer Lord-Bessen, Aylin Yucel, Roberto Latagliata, Massimo Breccia, Giuseppe A Palumbo, Grazia Sanpaolo, Marta Riva, Valeria Santini, Uwe Platzbecker, Guillermo Garcia-Manero, Pierre Fenaux, Christopher G Pelligra

Faculty, Staff and Student Publications

peripheral blood cytopenias, and an increased risk of progression to acute myeloid leukemia. One of the main treatment goals is improving quality of life (QoL), particularly for patients with lower-risk MDS (LR-MDS) who may live longer with compromised QoL. The QOL-E© is a patient-reported outcome (PRO) measure specifically developed to address the lack of a health-related QoL questionnaire for patients with MDS. The objective of this study was to evaluate the psychometric performance of the QOL-E in patients with LR-MDS.

Methods: Data from four clinical trials in MDS (MEDALIST, DARB-MDS, EQoL-MDS, and RevMDS trials) were used to assess construct validity, …