Digital Commons Network^™

Evaluation Of The Effectiveness Of Uv-C Dose For Photoinactivation Of Sars-Cov-2 In Contaminated N95 Respirator, Surgical And Cotton Fabric Masks, Patrícia Metolina, Lilian Gomes De Oliveira, Bruno Ramos, Yan De Souza Angelo, Paola Minoprio, Antonio Carlos Silva Costa Teixeira

Faculty, Staff and Student Publications

As part of efforts to combat the Covid-19 pandemic and decrease the high transmissibility of the new coronavirus, SARS-CoV-2, effective inactivation strategies, such as UV-C decontamination technologies, can be reliably disseminated and well-studied. The present study investigated the susceptibility of a high viral load of SARS-CoV-2 in filtering facepiece respirators (FFR) N95, surgical mask, cotton fabric mask and N95 straps under three different doses of UV-C, applying both real-time PCR (qPCR) and plaque formation assays to quantify viral load reduction and virus infectivity, respectively. The results show that more than 95% of the amount of SARS-CoV-2 RNA could be reduced …

Hip Osteoarthritis: A Novel Network Analysis Of Subchondral Trabecular Bone Structures, Mohsen Dorraki, Dzenita Muratovic, Anahita Fouladzadeh, Johan W Verjans, Andrew Allison, David M Findlay, Derek Abbott

Faculty, Staff and Student Publications

Hip osteoarthritis (HOA) is a degenerative joint disease that leads to the progressive destruction of subchondral bone and cartilage at the hip joint. Development of effective treatments for HOA remains an open problem, primarily due to the lack of knowledge of its pathogenesis and a typically late-stage diagnosis. We describe a novel network analysis methodology for microcomputed tomography (micro-CT) images of human trabecular bone. We explored differences between the trabecular bone microstructure of femoral heads with and without HOA. Large-scale automated extraction of the network formed by trabecular bone revealed significant network properties not previously reported for bone. Profound differences …

A Semi-Mechanistic Dose-Finding Design In Oncology Using Pharmacokinetic/Pharmacodynamic Modeling, Xiao Su, Yisheng Li, Peter Müller, Chia-Wei Hsu, Haitao Pan, Kim-Anh Do

Faculty, Staff and Student Publications

While a number of phase I dose-finding designs in oncology exist, the commonly used ones are either algorithmic or empirical model-based. We propose a new framework for modeling the dose-response relationship, by systematically incorporating the pharmacokinetic (PK) data collected in the trial and the hypothesized mechanisms of the drug effects, via dynamic PK/PD modeling, as well as modeling of the relationship between a latent cumulative pharmacologic effect and a binary toxicity outcome. This modeling framework naturally incorporates the information on the impact of dose, schedule and method of administration (e.g., drug formulation and route of administration) on toxicity. The resulting …

Estimation Of Tumor Cell Total Mrna Expression In 15 Cancer Types Predicts Disease Progression, Shaolong Cao, Jennifer R Wang, Shuangxi Ji, Peng Yang, Yaoyi Dai, Shuai Guo, Matthew D Montierth, John Paul Shen, Xiao Zhao, Jingxiao Chen, Jaewon James Lee, Paola A Guerrero, Nicholas Spetsieris, Nikolai Engedal, Sinja Taavitsainen, Kaixian Yu, Julie Livingstone, Vinayak Bhandari, Shawna M Hubert, Najat C Daw, P Andrew Futreal, Eleni Efstathiou, Bora Lim, Andrea Viale, Jianjun Zhang, Matti Nykter, Bogdan A Czerniak, Powel H Brown, Charles Swanton, Pavlos Msaouel, Anirban Maitra, Scott Kopetz, Peter Campbell, Terence P Speed, Paul C Boutros, Hongtu Zhu, Alfonso Urbanucci, Jonas Demeulemeester, Peter Van Loo, Wenyi Wang

Faculty, Staff and Student Publications

Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene …

A Multinational Delphi Consensus To End The Covid-19 Public Health Threat, Jeffrey V Lazarus, Diana Romero, Christopher J Kopka, Salim Abdool Karim, Laith J Abu-Raddad, Gisele Almeida, Ricardo Baptista-Leite, Joshua A Barocas, Mauricio L Barreto, Yaneer Bar-Yam, Quique Bassat, Carolina Batista, Morgan Bazilian, Shu-Ti Chiou, Carlos Del Rio, Gregory J Dore, George F Gao, Lawrence O Gostin, Margaret Hellard, Jose L Jimenez, Gagandeep Kang, Nancy Lee, Mojca Matičič, Martin Mckee, Sabin Nsanzimana, Miquel Oliu-Barton, Bary Pradelski, Oksana Pyzik, Kenneth Rabin, Sunil Raina, Sabina Faiz Rashid, Magdalena Rathe, Rocio Saenz, Sudhvir Singh, Malene Trock-Hempler, Sonia Villapol, Peiling Yap, Agnes Binagwaho, Adeeba Kamarulzaman, Ayman El-Mohandes

Faculty, Staff and Students Publications

Despite notable scientific and medical advances, broader political, socioeconomic and behavioural factors continue to undercut the response to the COVID-19 pandemic1,2. Here we convened, as part of this Delphi study, a diverse, multidisciplinary panel of 386 academic, health, non-governmental organization, government and other experts in COVID-19 response from 112 countries and territories to recommend specific actions to end this persistent global threat to public health. The panel developed a set of 41 consensus statements and 57 recommendations to governments, health systems, industry and other key stakeholders across six domains: communication; health systems; vaccination; prevention; treatment and …

The Tumor Invasion Paradox In Cancer Stem Cell-Driven Solid Tumors, Alexandra Shyntar, Ashna Patel, Meghan Rhodes, Heiko Enderling, Thomas Hillen

Faculty, Staff and Student Publications

Cancer stem cells (CSCs) are key in understanding tumor growth and tumor progression. A counterintuitive effect of CSCs is the so-called tumor growth paradox: the effect where a tumor with a higher death rate may grow larger than a tumor with a lower death rate. Here we extend the modeling of the tumor growth paradox by including spatial structure and considering cancer invasion. Using agent-based modeling and a corresponding partial differential equation model, we demonstrate and prove mathematically a tumor invasion paradox: a larger cell death rate can lead to a faster invasion speed. We test this result on a …

The Impact Of Covid-19 On Opioid-Related Overdose Deaths In Texas, Karima Lalani, Christine Bakos-Block, Marylou Cardenas-Turanzas, Sarah Cohen, Bhanumathi Gopal, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

Prior to the COVID-19 pandemic, the United States was facing an epidemic of opioid overdose deaths, clouding accurate inferences about the impact of the pandemic at the population level. We sought to determine the existence of increases in the trends of opioid-related overdose (ORO) deaths in the Greater Houston metropolitan area from January 2015 through December 2021, and to describe the social vulnerability present in the geographic location of these deaths. We merged records from the county medical examiner's office with social vulnerability indexes (SVIs) for the region and present geospatial locations of the aggregated ORO deaths. Time series analyses …

Genetic Conditions Of Short Stature: A Review Of Three Classic Examples, Merlin G Butler, Bradley S Miller, Alicia Romano, Judith L. Ross, M Jennifer Abuzzahab, Philippe Backeljauw, Vaneeta Bamba, Amrit Bhangoo, Nelly Mauras, Mitchell Geffner

Department of Pediatrics Faculty Papers

Noonan, Turner, and Prader-Willi syndromes are classical genetic disorders that are marked by short stature. Each disorder has been recognized for several decades and is backed by extensive published literature describing its features, genetic origins, and optimal treatment strategies. These disorders are accompanied by a multitude of comorbidities, including cardiovascular issues, endocrinopathies, and infertility. Diagnostic delays, syndrome-associated comorbidities, and inefficient communication among the members of a patient's health care team can affect a patient's well-being from birth through adulthood. Insufficient information is available to help patients and their multidisciplinary team of providers transition from pediatric to adult health care systems. …

Scgwas: Landscape Of Trait-Cell Type Associations By Integrating Single-Cell Transcriptomics-Wide And Genome-Wide Association Studies, Peilin Jia, Ruifeng Hu, Fangfang Yan, Yulin Dai, Zhongming Zhao

Faculty, Staff and Student Publications

BACKGROUND: The rapid accumulation of single-cell RNA sequencing (scRNA-seq) data presents unique opportunities to decode the genetically mediated cell-type specificity in complex diseases. Here, we develop a new method, scGWAS, which effectively leverages scRNA-seq data to achieve two goals: (1) to infer the cell types in which the disease-associated genes manifest and (2) to construct cellular modules which imply disease-specific activation of different processes.

RESULTS: scGWAS only utilizes the average gene expression for each cell type followed by virtual search processes to construct the null distributions of module scores, making it scalable to large scRNA-seq datasets. We demonstrated scGWAS in …

Federated Learning Algorithms For Generalized Mixed-Effects Model (Glmm) On Horizontally Partitioned Data From Distributed Sources, Wentao Li, Jiayi Tong, Md Monowar Anjum, Noman Mohammed, Yong Chen, Xiaoqian Jiang

Faculty, Staff and Student Publications

OBJECTIVES: This paper developed federated solutions based on two approximation algorithms to achieve federated generalized linear mixed effect models (GLMM). The paper also proposed a solution for numerical errors and singularity issues. And showed the two proposed methods can perform well in revealing the significance of parameter in distributed datasets, comparing to a centralized GLMM algorithm from R package ('lme4') as the baseline model.

METHODS: The log-likelihood function of GLMM is approximated by two numerical methods (Laplace approximation and Gaussian Hermite approximation, abbreviated as LA and GH), which supports federated decomposition of GLMM to bring computation to data. To solve …

Towards A Common Lexicon For Equity, Diversity, And Inclusion Work In Academic Medicine, José E Rodríguez, Edgar Figueroa, Kendall M Campbell, Judy C Washington, Octavia Amaechi, Tanya Anim, Kari-Claudia Allen, Krys Foster, Maia Hightower, Yury Parra, Maria H Wusu, William A Smith, Mary Ann Villarreal, Linda H Pololi

Department of Family & Community Medicine Faculty Papers

Differential rewarding of work and experience has been a longtime feature of academic medicine, resulting in a series of academic disparities. These disparities have been collectively called a cultural or minority "tax," and, when considered beyond academic medicine, exist across all departments, colleges, and schools of institutions of higher learning-from health sciences to disciplines located on university campuses outside of medicine and health. A shared language can provide opportunities for those who champion this work to pool resources for larger impacts across the institution. This article aims to catalog the terms used across academic medicine disciplines to establish a common …

Classification Of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics, Katelyn F Handley, Travis T Sims, Nicholas W Bateman, Deanna Glassman, Katherine I Foster, Sanghoon Lee, Jun Yao, Hui Yao, Bryan M Fellman, Jinsong Liu, Zhen Lu, Kelly A Conrads, Brian L Hood, Waleed Barakat, Li Zhao, Jianhua Zhang, Shannon N Westin, Joseph Celestino, Kelly M Rangel, Sunil Badal, Igor Pereira, Prahlad T Ram, George L Maxwell, Livia S Eberlin, P Andrew Futreal, Robert C Bast, Nicole D Fleming, Thomas P Conrads, Anil K Sood

Faculty, Staff and Student Publications

IMPORTANCE: Despite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics.

OBJECTIVE: To develop and characterize a gross morphologic classification system for HGSOC.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of …

Cancer Incidence And Stage At Diagnosis Among People With Psychotic Disorders: Systematic Review And Meta-Analysis., Jared C Wootten, Joshua C Wiener, Phillip S Blanchette, Kelly K. Anderson

Epidemiology and Biostatistics Publications

Research regarding the incidence of cancer among people with psychotic disorders relative to the general population is equivocal, although the evidence suggests that they have more advanced stage cancer at diagnosis. We conducted a systematic review and meta-analysis to examine the incidence and stage at diagnosis of cancer among people with, relative to those without, psychotic disorders. We searched the MEDLINE, EMBASE, PsycINFO, and CINAHL databases. Articles were included if they reported the incidence and/or stage at diagnosis of cancer in people with psychotic disorders. Random effects meta-analyses were used to determine risk of cancer and odds of advanced stage …

Development Of The Invasive Candidiasis Discharge [I Can Discharge] Model: A Mixed Methods Analysis, Jinhee Jo, Truc T Tran, Nicholas D Beyda, Debora Simmons, Joshua A Hendrickson, Masaad Saeed Almutairi, Faris S Alnezary, Anne J Gonzales-Luna, Edward J Septimus, Kevin W Garey

Faculty, Staff and Student Publications

Patients with invasive candidiasis (IC) have complex medical and infectious disease problems that often require continued care after discharge. This study aimed to assess echinocandin use at hospital discharge and develop a transition of care (TOC) model to facilitate discharge for patients with IC. This was a mixed method study design that used epidemiologic assessment to better understand echinocandin use at hospital discharge TOC. Using grounded theory methodology focused on patients given echinocandins during their last day of hospitalization, a TOC model for patients with IC, the invasive candidiasis [I Can] discharge model was developed to better understand discharge barriers. …

Aging After Stroke: How To Define Post-Stroke Sarcopenia And What Are Its Risk Factors?, Sheng Li, Javier Gonzalez-Buonomo, Jaskiran Ghuman, Xinran Huang, Aila Malik, Nuray Yozbatiran, Elaine Magat, Gerard E Francisco, Hulin Wu, Walter R Frontera

Faculty, Staff and Student Publications

BACKGROUND: Sarcopenia, generally described as "aging-related loss of skeletal muscle mass and function", can occur secondary to a systemic disease.

AIM: This project aimed to study the prevalence of sarcopenia in chronic ambulatory stroke survivors and its associated risk factors using the two most recent diagnostic criteria.

DESIGN: A cross-sectional observational study.

SETTING: A scientific laboratory.

POPULATION: Chronic stroke.

METHODS: Twenty-eight ambulatory chronic stroke survivors (12 females; mean age=57.8±11.8 years; time after stroke=76±45 months), hand-grip strength, gait speed, and appendicular skeletal muscle mass (ASM) were measured to define sarcopenia. Risk factors, including motor impairment and spasticity, were identified using regression …

Svat: Secure Outsourcing Of Variant Annotation And Genotype Aggregation, Miran Kim, Su Wang, Xiaoqian Jiang, Arif Harmanci

Faculty, Staff and Student Publications

BACKGROUND: Sequencing of thousands of samples provides genetic variants with allele frequencies spanning a very large spectrum and gives invaluable insight into genetic determinants of diseases. Protecting the genetic privacy of participants is challenging as only a few rare variants can easily re-identify an individual among millions. In certain cases, there are policy barriers against sharing genetic data from indigenous populations and stigmatizing conditions.

RESULTS: We present SVAT, a method for secure outsourcing of variant annotation and aggregation, which are two basic steps in variant interpretation and detection of causal variants. SVAT uses homomorphic encryption to encrypt the data at …

Automated Extraction Of Anatomical Measurements From Temporal Bone Ct Imaging, Andy S Ding, Alexander Lu, Zhaoshuo Li, Deepa Galaiya, Masaru Ishii, Jeffrey H Siewerdsen, Russell H Taylor, Francis X Creighton

Faculty, Staff and Student Publications

OBJECTIVE: Proposed methods of minimally invasive and robot-assisted procedures within the temporal bone require measurements of surgically relevant distances and angles, which often require time-consuming manual segmentation of preoperative imaging. This study aims to describe an automatic segmentation and measurement extraction pipeline of temporal bone cone-beam computed tomography (CT) scans.

STUDY DESIGN: Descriptive study of temporal bone measurements.

SETTING: Academic institution.

METHODS: A propagation template composed of 16 temporal bone CT scans was formed with relevant anatomical structures and landmarks manually segmented. Next, 52 temporal bone CT scans were autonomously segmented using deformable registration techniques from the Advanced Normalization Tools …

First-In-Human Study Of An Ox40 (Ivuxolimab) And 4-1bb (Utomilumab) Agonistic Antibody Combination In Patients With Advanced Solid Tumors, Omid Hamid, Alberto A Chiappori, John A Thompson, Toshihiko Doi, Siwen Hu-Lieskovan, Ferry A L M Eskens, Willeke Ros, Adi Diab, Jean-Philippe Spano, Naiyer A Rizvi, Jeffrey S Wasser, Eric Angevin, Patrick A Ott, Alison Forgie, Wenjing Yang, Cen Guo, Jeffrey Chou, Anthony B El-Khoueiry

Faculty, Staff and Student Publications

Background: Ivuxolimab (PF-04518600) and utomilumab (PF-05082566) are humanized agonistic IgG2 monoclonal antibodies against OX40 and 4-1BB, respectively. This first-in-human, multicenter, open-label, phase I, dose-escalation/dose-expansion study explored safety, tolerability, pharmacokinetics, pharmacodynamics, and antitumor activity of ivuxolimab+utomilumab in patients with advanced solid tumors.

Methods: Dose-escalation: patients with advanced bladder, gastric, or cervical cancer, melanoma, head and neck squamous cell carcinoma, or non-small cell lung cancer (NSCLC) who were unresponsive to available therapies, had no standard therapy available or declined standard therapy were enrolled into five dose cohorts: ivuxolimab (0.1-3 mg/kg every 2 weeks (Q2W)) intravenously plus utomilumab (20 or 100 mg every …

Netbce: An Interpretable Deep Neural Network For Accurate Prediction Of Linear B-Cell Epitopes, Haodong Xu, Zhongming Zhao

Faculty, Staff and Student Publications

Identification of B-cell epitopes (BCEs) plays an essential role in the development of peptide vaccines and immuno-diagnostic reagents, as well as antibody design and production. In this work, we generated a large benchmark dataset comprising 124,879 experimentally supported linear epitope-containing regions in 3567 protein clusters from over 1.3 million B cell assays. Analysis of this curated dataset showed large pathogen diversity covering 176 different families. The accuracy in linear BCE prediction was found to strongly vary with different features, while all sequence-derived and structural features were informative. To search more efficient and interpretive feature representations, a ten-layer deep learning framework …

Artificial Intelligence For Radiation Oncology Applications Using Public Datasets, Kareem A Wahid, Enrico Glerean, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski, Mohamed A Naser, Renjie He, Abdallah S R Mohamed, Clifton D Fuller

Faculty, Staff and Student Publications

Artificial intelligence (AI) has exceptional potential to positively impact the field of radiation oncology. However, large curated datasets - often involving imaging data and corresponding annotations - are required to develop radiation oncology AI models. Importantly, the recent establishment of Findable, Accessible, Interoperable, Reusable (FAIR) principles for scientific data management have enabled an increasing number of radiation oncology related datasets to be disseminated through data repositories, thereby acting as a rich source of data for AI model building. This manuscript reviews the current and future state of radiation oncology data dissemination, with a particular emphasis on published imaging datasets, AI …

Aapm Report 373: The Content, Structure, And Value Of The Professional Doctorate In Medical Physics (Dmp), Jay W Burmeister, Charles W Coffey, John D Hazle, Neil Kirby, Yu Kuang, Michael A Lamba, Brian Loughery, Niko Papanikolaou

Faculty, Staff and Student Publications

The Professional Doctorate in Medical Physics (DMP) was originally conceived as a solution to the shortage of medical physics residency training positions. While this shortage has now been largely satisfied through conventional residency training positions, the DMP has expanded to multiple institutions and grown into an educational pathway that provides specialized clinical training and extends well beyond the creation of additional training spots. As such, it is important to reevaluate the purpose and the value of the DMP. Additionally, it is important to outline the defining characteristics of the DMP to assure that all existing and future programs provide this …

Cardio-Onco-Metabolism – Metabolic Vulnerabilities In Cancer And The Heart, Anja Karlstaedt, Heinrich Taegtmeyer

Faculty, Staff and Student Publications

Cancer and cardiovascular diseases (CVDs) are the leading cause of death worldwide. Metabolic remodeling is a hallmark of both cancer and the failing heart. Tumors reprogram metabolism to optimize nutrient utilization and meet increased demands for energy provision, biosynthetic pathways, and proliferation. Shared risk factors for cancer and CVDs suggest intersecting mechanisms for disease pathogenesis and progression. In this review, we aim to highlight the role of metabolic remodeling in cancer and its potential to impair cardiac function. Understanding these mechanisms will help us develop biomarkers, better therapies, and identify patients at risk of developing heart disease after surviving cancer.

Identifying Candidate Genes And Drug Targets For Alzheimer’S Disease By An Integrative Network Approach Using Genetic And Brain Region-Specific Proteomic Data, Andi Liu, Astrid M Manuel, Yulin Dai, Brisa S Fernandes, Nitesh Enduru, Peilin Jia, Zhongming Zhao

Faculty, Staff and Student Publications

Genome-wide association studies (GWAS) have identified more than 75 genetic variants associated with Alzheimer's disease (ad). However, how these variants function and impact protein expression in brain regions remain elusive. Large-scale proteomic datasets of ad postmortem brain tissues have become available recently. In this study, we used these datasets to investigate brain region-specific molecular pathways underlying ad pathogenesis and explore their potential drug targets. We applied our new network-based tool, Edge-Weighted Dense Module Search of GWAS (EW_dmGWAS), to integrate ad GWAS statistics of 472 868 individuals with proteomic profiles from two brain regions from two large-scale ad cohorts [parahippocampal gyrus …

Video-Urodynamics Efficacy Of Sacral Neuromodulation For Neurogenic Bladder Guided By Three-Dimensional Imaging Ct And C-Arm Fluoroscopy: A Single-Center Prospective Study, Shuaishuai Shan, Wen Zhu, Guoxian Zhang, Qinyong Zhang, Yingyu Che, Jianguo Wen, Qingwei Wang

Faculty, Staff and Student Publications

To assess the efficacy of sacral neuromodulation (SNM) for neurogenic bladder (NB), guided by intraoperative three-dimensional imaging of sacral computed tomography (CT) and mobile C-arm fluoroscopy through video-urodynamics examination. We enrolled 52 patients with NB who underwent conservative treatment with poor results between September 2019 and June 2021 and prospectively underwent SNM guided by intraoperative three-dimensional imaging of sacral CT and mobile C-arm fluoroscopy. Video-urodynamics examination, voiding diary, quality of life questionnaire, overactive bladder symptom scale (OABSS) scoring, and bowel dysfunction exam were completed and recorded at baseline, at SNM testing, and at 6-month follow-up phases. Finally, we calculated the …

Molecular Pathways Enhance Drug Response Prediction Using Transfer Learning From Cell Lines To Tumors And Patient-Derived Xenografts, Yi-Ching Tang, Reid T Powell, Assaf Gottlieb

Faculty, Staff and Student Publications

Computational models have been successful in predicting drug sensitivity in cancer cell line data, creating an opportunity to guide precision medicine. However, translating these models to tumors remains challenging. We propose a new transfer learning workflow that transfers drug sensitivity predicting models from large-scale cancer cell lines to both tumors and patient derived xenografts based on molecular pathways derived from genomic features. We further compute feature importance to identify pathways most important to drug response prediction. We obtained good performance on tumors (AUROC = 0.77) and patient derived xenografts from triple negative breast cancers (RMSE = 0.11). Using feature importance, …

Regional Variation In Brain Tissue Texture In Patients With Tonic-Clonic Seizures, Jennifer A Ogren, Luke A Allen, Bhaswati Roy, Beate Diehl, John M Stern, Dawn S Eliashiv, Samden D Lhatoo, Ronald M Harper, Rajesh Kumar

Faculty, Staff and Student Publications

Patients with epilepsy, who later succumb to sudden unexpected death, show altered brain tissue volumes in selected regions. It is unclear whether the alterations in brain tissue volume represent changes in neurons or glial properties, since volumetric procedures have limited sensitivity to assess the source of volume changes (e.g., neuronal loss or glial cell swelling). We assessed a measure, entropy, which can determine tissue homogeneity by evaluating tissue randomness, and thus, shows tissue integrity; the measure is easily calculated from T1-weighted images. T1-weighted images were collected with a 3.0-Tesla MRI from 53 patients with tonic-clonic (TC) …

Effect Of The Tokyo 2020 Summer Olympic Games On Covid-19 Incidence In Japan: A Synthetic Control Approach, Daisuke Yoneoka, Akifumi Eguchi, Kentato Fukumoto, Takayuki Kawashima, Yuta Tanoue, Takahiro Tabuchi, Hiroaki Miyata, Cyrus Ghaznavi, Kenji Shibuya, Shuhei Nomura

2020-Current year OA Pubs

BACKGROUND: The Tokyo 2020 Summer Olympic Games (23 July-8 August 2021) were held in the middle of Japan's fifth wave of COVID-19, when the number of cases was on the rise, and coincided with the fourth state of emergency implemented by the host city, Tokyo.

AIM: This study aimed to assess whether the hosting of the Games was associated with a change in the number of COVID-19 cases in Japan using a synthetic control method.

METHODS: A weighted average of control countries with a variety of predictors was used to estimate the counterfactual trajectory of daily COVID-19 cases per 1 …

Mri-Based Digital Models Forecast Patient-Specific Treatment Responses To Neoadjuvant Chemotherapy In Triple-Negative Breast Cancer, Chengyue Wu, Angela M Jarrett, Zijian Zhou, Nabil Elshafeey, Beatriz E Adrada, Rosalind P Candelaria, Rania M M Mohamed, Medine Boge, Lei Huo, Jason B White, Debu Tripathy, Vicente Valero, Jennifer K Litton, Clinton Yam, Jong Bum Son, Jingfei Ma, Gaiane M Rauch, Thomas E Yankeelov

Faculty, Staff and Student Publications

Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to improve targeting and evaluation of responses to therapy in this disease are needed. Here, we integrate quantitative MRI data with biologically based mathematical modeling to accurately predict the response of TNBC to neoadjuvant systemic therapy (NAST) on an individual basis. Specifically, 56 patients with TNBC enrolled in the ARTEMIS trial (NCT02276443) underwent standard-of-care doxorubicin/cyclophosphamide (A/C) and then paclitaxel for NAST, where dynamic contrast-enhanced MRI and diffusion-weighted MRI were acquired before treatment and after two and four cycles of A/C. A biologically based model was established to …

Bet Inhibition Induces Vulnerability To Mcl1 Targeting Through Upregulation Of Fatty Acid Synthesis Pathway In Breast Cancer, Gonghong Yan, Augustin Luna, Heping Wang, Behnaz Bozorgui, Xubin Li, Maga Sanchez, Zeynep Dereli, Nermin Kahraman, Goknur Kara, Xiaohua Chen, Caishang Zheng, Daniel Mcgrail, Nidhi Sahni, Yiling Lu, Ozgun Babur, Murat Cokol, Bora Lim, Bulent Ozpolat, Chris Sander, Gordon B Mills, Anil Korkut

Faculty, Staff and Student Publications

Therapeutic options for treatment of basal-like breast cancers remain limited. Here, we demonstrate that bromodomain and extra-terminal (BET) inhibition induces an adaptive response leading to MCL1 protein-driven evasion of apoptosis in breast cancer cells. Consequently, co-targeting MCL1 and BET is highly synergistic in breast cancer models. The mechanism of adaptive response to BET inhibition involves the upregulation of lipid synthesis enzymes including the rate-limiting stearoyl-coenzyme A (CoA) desaturase. Changes in lipid synthesis pathway are associated with increases in cell motility and membrane fluidity as well as re-localization and activation of HER2/EGFR. In turn, the HER2/EGFR signaling results in the accumulation …

Feasibility And Sensitivity Study Of Radiomic Features In Photoacoustic Imaging Of Patient-Derived Xenografts, Lorena Escudero Sanchez, Emma Brown, Leonardo Rundo, Stephan Ursprung, Evis Sala, Sarah E Bohndiek, Ignacio Xavier Partarrieu

2020-Current year OA Pubs

Photoacoustic imaging is an increasingly popular method of exploring the tumour microenvironment, which can provide insight into tumour oxygenation status and potentially treatment response assessment. Currently, the measurements most commonly performed on such images are the mean and median of the pixel values of the tumour volumes of interest. We investigated expanding the set of measurements that can be extracted from these images by adding radiomic features. In particular, we found that Skewness was sensitive to differences between basal and luminal patient derived xenograft cancer models with an [Formula: see text] of 0.86, and that it was robust to variations …