Biomedical Informatics Commons^™

Translating Mentoring Interventions Research Into Practice: Evaluation Of An Evidence-Based Workshop For Research Mentors On Developing Trainees’ Scientific Communication Skills, Erin K Dahlstrom, Christine Bell, Shine Chang, Hwa Young Lee, Cheryl B Anderson, Annie Pham, Christine Maidl Pribbenow, Carrie A Cameron

Faculty, Staff and Student Publications

A key part of keeping doctoral and postdoctoral trainees in STEM research careers is mentoring. Our previous research indicates that mentoring trainees in scientific communication (SC) skill development increases research career intention through two social-cognitive constructs, self-efficacy in and outcome expectations for acquiring SC skills, as well as science identity. While many mentor training interventions exist, no programs focus on developing SC skills specifically. The "Scientific Communication Advances Research Excellence" (SCOARE) program trains mentors to address trainee scientific communication (SC) skill development as an innovative approach to increase trainee research career persistence. The SCOARE training is a half-day workshop for …

A Narrative Review On Invasive Brain Stimulation For Treatment-Resistant Depression, Manoj P Dandekar, Alexandre P Diaz, Ziaur Rahman, Ritele H Silva, Ziad Nahas, Scott Aaronson, Sudhakar Selvaraj, Albert J Fenoy, Marsal Sanches, Jair C Soares, Patricio Riva-Posse, Joao Quevedo

Faculty, Staff and Student Publications

While most patients with depression respond to pharmacotherapy and psychotherapy, about one-third will present treatment resistance to these interventions. For patients with treatment-resistant depression (TRD), invasive neurostimulation therapies such as vagus nerve stimulation, deep brain stimulation, and epidural cortical stimulation may be considered. We performed a narrative review of the published literature to identify papers discussing clinical studies with invasive neurostimulation therapies for TRD. After a database search and title and abstract screening, relevant English-language articles were analyzed. Vagus nerve stimulation, approved by the U.S. Food and Drug Administration as a TRD treatment, may take several months to show therapeutic …

Serum Gamma Glutamyltransferase (Ggt) In Coronary Artery Disease: Exploring The Asian Indian Connection, Kunal K Singh, Aditya Kapoor, Roopali Khanna, Ankit Sahu, Vishwas Kapoor, Sudeep Kumar, Naveen Garg, Satyendra Tewari, Pravin Goel

Faculty, Staff and Student Publications

BACKGROUND: There is a need to identify novel markers for CAD, independent of traditional CV risk factors. One of these is gamma-glutamyl transferase (GGT), a marker of increased oxidative stress. Given the high prevalence of CAD in Asian Indians, the link of GGT and CAD in them needs to be studied.

AIM: To assess GGT in patients with angiographically documented CAD.

METHODS AND RESULTS: Two hundred patients aged 58.1 ± 9.95 years, 73% males, hypertension 56%, diabetes 40% were included. Mean GGT was 63.6 ± 44.33 (10–269 U/L). The levels of GGT progressively increased in those with single/double or triple-vessel …

Defective Dna Polymerase Beta Invoke A Cytosolic Dna Mediated Inflammatory Response, Shengyuan Zhao, Julia A Goewey Ruiz, Manu Sebastian, Dawit Kidane

Faculty, Staff and Student Publications

Base excision repair (BER) has evolved to maintain the genomic integrity of DNA following endogenous and exogenous agent induced DNA base damage. In contrast, aberrant BER induces genomic instability, promotes malignant transformation and can even trigger cancer development. Previously, we have shown that deoxyribo-5'-phosphate (dRP) lyase deficient DNA polymerase beta (POLB) causes replication associated genomic instability and sensitivity to both endogenous and exogenous DNA damaging agents. Specifically, it has been established that this loss of dRP lyase function promotes inflammation associated gastric cancer. However, the way that aberrant POLB impacts the immune signaling and inflammatory responses is still unknown. Here …

Evaluating A Pilot Culturally Sensitive Psychosocial Intervention On Posttraumatic Growth For Chinese American Breast Cancer Survivors, Qiao Chu, Moni Tang, Lingjun Chen, Lucy Young, Alice Loh, Carol Wang, Qian Lu

Faculty, Staff and Student Publications

This study investigated the potential benefit of a pilot culturally sensitive group support intervention, named Joy Luck Academy (JLA), in fostering posttraumatic growth among Chinese American breast cancer survivors. Eighty-six Chinese American breast cancer survivors participated in an eight-week single-arm pre-/post-test trial of an intervention program, which included educational lectures and peer mentor support. The JLA participants were compared with an independent sample of 109 Chinese American breast cancer survivors who went through routine care. Both groups completed baseline and eight-week follow-up assessments of the five facets of posttraumatic growth (meaningful interpersonal relationships, finding new possibilities in life, personal strength, …

Quaking But Not Parkin Is The Major Tumor Suppressor In 6q Deleted Region In Glioblastoma, Fatma Betul Aksoy Yasar, Takashi Shingu, Daniel B Zamler, Mohammad Fayyad Zaman, Derek Lin Chien, Qiang Zhang, Jiangong Ren, Jian Hu

Faculty, Staff and Student Publications

Glioblastoma (GBM) is a high-grade, aggressive brain tumor with dismal median survival time of 15 months. Chromosome 6q (Ch6q) is a hotspot of genomic alterations, which is commonly deleted or hyper-methylated in GBM. Two neighboring genes in this region, QKI and PRKN have been appointed as tumor suppressors in GBM. While a genetically modified mouse model (GEMM) of GBM has been successfully generated with Qk deletion in the central nervous system (CNS), in vivo genetic evidence supporting the tumor suppressor function of Prkn has not been established. In the present study, we generated a mouse model with Prkn-null allele …

Update On Mri In Evaluation And Treatment Of Endometrial Cancer, Ekta Maheshwari, Stephanie Nougaret, Erica B Stein, Gaiane M Rauch, Ken-Pin Hwang, R Jason Stafford, Ann H Klopp, Pamela T Soliman, Katherine E Maturen, Andrea G Rockall, Susanna I Lee, Elizabeth A Sadowski, Aradhana M Venkatesan

Faculty, Staff and Student Publications

Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, …

Socioeconomic, Clinical, And Molecular Features Of Breast Cancer Influence Overall Survival Of Latin American Women, Liz Maria De Almeida, Sandra Cortés, Marta Vilensky, Olivia Valenzuela, Laura Cortes-Sanabria, Mirian De Souza, Rafael Alonso Barbeito, Eliana Abdelhay, Nora Artagaveytia, Adrian Daneri-Navarro, Andrea S Llera, Bettina Müller, Osvaldo L Podhajcer, Carlos Velazquez, Elsa Alcoba, Isabel Alonso, Alicia I Bravo, Natalia Camejo, Dirce Maria Carraro, Mónica Castro, Sandra Cataldi, Alfonso Cayota, Mauricio Cerda, Alicia Colombo, Susanne Crocamo, Alicia Del Toro-Arreola, Raul Delgadillo-Cristerna, Lucia Delgado, Marisa Dreyer Breitenbach, Elmer Fernández, Jorge Fernández, Wanda Fernández, Ramon A Franco-Topete, Fancy Gaete, Jorge Gómez, Leivy P Gonzalez-Ramirez, Marisol Guerrero, Susan A Gutierrez-Rubio, Beatriz Jalfin, Alejandra Lopez-Vazquez, Dora Loria, Silvia Míguez, Andres De J Moran-Mendoza, Gilberto Morgan-Villela, Carina Mussetti, Maria Aparecida Nagai, Antonio Oceguera-Villanueva, Rui M Reis, Javier Retamales, Robinson Rodriguez, Cristina Rosales, Efrain Salas-Gonzalez, Laura Segovia, Juan M Sendoya, Aida A Silva-Garcia, Stella Viña, Livia Zagame, Beth Jones, Moysés Szklo, United States-Latin American Cancer Research Network (Us-Lacrn)

Faculty, Staff and Students Publications

Molecular profile of breast cancer in Latin-American women was studied in five countries: Argentina, Brazil, Chile, Mexico, and Uruguay. Data about socioeconomic characteristics, risk factors, prognostic factors, and molecular subtypes were described, and the 60-month overall cumulative survival probabilities (OS) were estimated. From 2011 to 2013, 1,300 eligible Latin-American women 18 years or older, with a diagnosis of breast cancer in clinical stage II or III, and performance status ≦̸1 were invited to participate in a prospective cohort study. Face-to-face interviews were conducted, and clinical and outcome data, including death, were extracted from medical records. Unadjusted associations were evaluated by …

The Transcriptomic Portrait Of Locally Advanced Breast Cancer And Its Prognostic Value In A Multi-Country Cohort Of Latin American Patients, Andrea Sabina Llera, Eliana Saul Furquim Werneck Abdelhay, Nora Artagaveytia, Adrián Daneri-Navarro, Bettina Müller, Carlos Velazquez, Elsa B Alcoba, Isabel Alonso, Daniela B Alves Da Quinta, Renata Binato, Alicia Inés Bravo, Natalia Camejo, Dirce Maria Carraro, Mónica Castro, Juan M Castro-Cervantes, Sandra Cataldi, Alfonso Cayota, Mauricio Cerda, Alicia Colombo, Susanne Crocamo, Alicia Del Toro-Arreola, Raúl Delgadillo-Cisterna, Lucía Delgado, Marisa Dreyer-Breitenbach, Laura Fejerman, Elmer A Fernández, Jorge Fernández, Wanda Fernández, Ramón A Franco-Topete, Carolina Gabay, Fancy Gaete, Adriana Garibay-Escobar, Jorge Gómez, Gonzalo Greif, Thomas G Gross, Marisol Guerrero, Marianne K Henderson, Miguel E Lopez-Muñoz, Alejandra Lopez-Vazquez, Silvina Maldonado, Andrés J Morán-Mendoza, Maria Aparecida Nagai, Antonio Oceguera-Villanueva, Miguel A Ortiz-Martínez, Jael Quintero, Antonio Quintero-Ramos, Rui M Reis, Javier Retamales, Ernesto Rivera-Claisse, Darío Rocha, Robinson Rodríguez, Cristina Rosales, Efrain Salas-González, Verónica Sanchotena, Laura Segovia, Juan Martín Sendoya, Aida A Silva-García, Alejandra Trinchero, Olivia Valenzuela, Vidya Vedham, Livia Zagame, United States-Latin American Cancer Research Network (Us-Lacrn);, Osvaldo L Podhajcer

Faculty, Staff and Students Publications

PURPOSES: Most molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches.

PATIENTS AND METHODS: We collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival …

Comparison Of Reverse Torque Values Of Abutment Screws With The Application Of Oil-Based And Water-Based Antibacterial Agents, Amin Nourizadeh, Elnaz Shafiee, Azin Khorramdel, Seyed Amin Mousavi, Mehran Rahbar

Faculty, Staff and Students Publications

BACKGROUND: Using antibacterial agents to remove the foul odor of the implant cavity and prevent peri-implantitis can affect the detorque values and lead to the loosening of the abutment screw. This study investigated the effects of tetracycline and chlorhexidine gel on detorque values.

METHODS: This in vitro study was carried out on three groups of five implants. Group G1 was the control group, and no material was applied to the implant cavity. In group G2, the implant cavity was first filled with artificial saliva and then with chlorhexidine gel. In group G3, the implant cavity was first filled with artificial …

Lessons Learned From An Enterprise-Wide Clinical Datathon, Andrew J Zimolzak, Jessica A Davila, Vamshi Punugoti, Ashok Balasubramanyam, Paul E Klotman, Laura A Petersen, Ryan H Rochat, Gloria Liao, Rory R Laubscher, Lee Leiber, Christopher I Amos

Faculty, Staff and Students Publications

In 2020, Baylor College of Medicine held a datathon to inform potential users of a new data warehouse, allow users to address clinical questions, identify warehouse capabilities and limitations, foster collaborations, and engage trainees. Senior faculty selected proposals based on feasibility and impact. Selectees worked with Information Technology for 2 months and presented findings. A survey of participants showed diverse levels of experience, high perceived value of the datathon, high rates of collaboration, and significant increases in knowledge. A datathon can promote familiarity with a new data warehouse, guide data warehouse improvement, and promote collaboration.

Esophageal Perforation Successfully Treated With Evt, Kavea Panneerselvam, Ronald Samuel, Robert J Sealock

Faculty, Staff and Students Publications

Esophageal perforation is rare and carries high morbidity and mortality. A high degree of suspicion is needed for timely diagnosis and treatment. A 54-year-old man presented with fever and confusion. Imaging revealed air in the hepatic inferior vena cava and concern for a fistula between the distal esophagus and the inferior vena cava. An upper endoscopic evaluation revealed a dental floss pick penetrating the distal esophagus. The foreign body was removed, and endoluminal vacuum therapy was used to close the perforation. Endoluminal vacuum therapy is an emerging therapy to treat full-thickness gastrointestinal injuries.

Modeling Recurrence In Idiopathic Subglottic Stenosis With Mobile Peak Expiratory Flow, Kyle Kimura, Liping Du, Lynn D Berry, Li-Ching Huang, Sheau-Chiann Chen, David O Francis, Alexander Gelbard

Faculty, Staff and Student Publications

OBJECTIVES/HYPOTHESIS: We sought to establish normative peak expiratory flow (PEF) data for patients with idiopathic subglottic stenosis (iSGS), evaluate whether immediate changes in PEF after a procedure predict long-term treatment response, and test if a decline in longitudinal PEF is associated with disease recurrence.

STUDY DESIGN: International, prospective, 3-year multicenter cohort study of 810 patients with untreated, newly diagnosed, or previously treated iSGS.

METHODS: iSGS patients consented and enrolled in the North American Airway Collaborative (NoAAC) iSGS

RESULTS: Within the NoAAC iSGS1000 cohort, 810 patients participated in a 3-year, prospective study comparing surgical treatment efficacy and 385 had appropriate PEF …

Associations Of High-Sensitivity Troponin And Natriuretic Peptide Levels With Outcomes After Intensive Blood Pressure Lowering: Findings From The Sprint Randomized Clinical Trial, Jarett D Berry, Vijay Nambi, Walter T Ambrosius, Haiying Chen, Anthony A Killeen, Addison Taylor, Robert D Toto, Elsayed Z Soliman, John W Mcevoy, Ambarish Pandey, Parag H Joshi, Stefan Blankenberg, Dalane W Kitzman, Christie M Ballantyne, James A De Lemos

Faculty, Staff and Students Publications

IMPORTANCE: Elevated high-sensitivity cardiac troponin T (hscTnT) and N-terminal pro-B-type natriuretic peptide (NTproBNP) levels are associated with risk of heart failure (HF) and mortality among individuals in the general population. However, it is unknown if this risk is modifiable.

OBJECTIVE: To test the hypothesis that elevated hscTnT and NTproBNP levels would identify individuals with the greatest risk for mortality and HF and the largest benefit associated with intensive systolic blood pressure (SBP) lowering.

DESIGN, SETTING, AND PARTICIPANTS: This is a nonprespecified post hoc analysis of the multicenter, prospective, randomized clinical Systolic Blood Pressure Intervention Trial (SPRINT), conducted from October 20, …

Nrf1 Association With Auts2-Polycomb Mediates Specific Gene Activation In The Brain, Sanxiong Liu, Kimberly A Aldinger, Chi Vicky Cheng, Takae Kiyama, Mitali Dave, Hanna K Mcnamara, Wukui Zhao, James M Stafford, Nicolas Descostes, Pedro Lee, Stefano G Caraffi, Ivan Ivanovski, Edoardo Errichiello, Christiane Zweier, Orsetta Zuffardi, Michael Schneider, Antigone S Papavasiliou, M Scott Perry, Jennifer Humberson, Megan T Cho, Astrid Weber, Andrew Swale, Tudor C Badea, Chai-An Mao, Livia Garavelli, William B Dobyns, Danny Reinberg

Faculty, Staff and Student Publications

The heterogeneous family of complexes comprising Polycomb repressive complex 1 (PRC1) is instrumental for establishing facultative heterochromatin that is repressive to transcription. However, two PRC1 species, ncPRC1.3 and ncPRC1.5, are known to comprise novel components, AUTS2, P300, and CK2, that convert this repressive function to that of transcription activation. Here, we report that individuals harboring mutations in the HX repeat domain of AUTS2 exhibit defects in AUTS2 and P300 interaction as well as a developmental disorder reflective of Rubinstein-Taybi syndrome, which is mainly associated with a heterozygous pathogenic variant in CREBBP/EP300. Moreover, the absence of AUTS2 or mutation in its …

Artificial Intelligence Algorithms For Medical Imaging And Healthcare, Jonathan William Stubblefield

Student Theses and Dissertations

In this dissertation, we studied several applications of artificial intelligence applications to healthcare. In the first chapter, we examined a machine learning algorithm for classifying patients presenting to the emergency department with acute respiratory distress syndrome (ARDS). Patients presenting with this life-threatening condition require a quick and accurate assessment of whether the condition is infectious or cardiac in etiology as the treatments for these etiologies of ARDS differ significantly. We used a transfer learning approach to develop our model. The model used a combination of clinical data and a chest x-ray as its input and achieved an accuracy 0.675 on …

Enhance Representation Learning Of Clinical Narrative With Neural Networks For Clinical Predictive Modeling, Yuqi Si

Dissertations and Theses (Open Access)

Medicine is undergoing a technological revolution. Understanding human health from clinical data has major challenges from technical and practical perspectives, thus prompting methods that understand large, complex, and noisy data. These methods are particularly necessary for natural language data from clinical narratives/notes, which contain some of the richest information on a patient. Meanwhile, deep neural networks have achieved superior performance in a wide variety of natural language processing (NLP) tasks because of their capacity to encode meaningful but abstract representations and learn the entire task end-to-end. In this thesis, I investigate representation learning of clinical narratives with deep neural networks …

Secondary Use Of Structured Electronic Health Records Data: From Observational Studies To Deep Learning-Based Predictive Modeling, Laila Bekhet

Dissertations and Theses (Open Access)

With the wide adoption of electronic health records (EHRs), researchers, as well as large healthcare organizations, governmental institutions, insurance, and pharmaceutical companies have been interested in leveraging this rich clinical data source to extract clinical evidence and develop predictive algorithms. Large vendors have been able to compile structured EHR data from sites all over the United States, de-identify these data, and make them available to data science researchers in a more usable format. For this dissertation, we leveraged one of the earliest and largest secondary EHR data sources and conducted three studies of increasing scope. In the first study, which …

Perspectives From The Society For Pediatric Research: Advice On Sustaining Science And Mentoring During Covid-19, Catherine S Forster, Suong T Nguyen, Weston T Powell, Daniel J Moore, Jacqueline Ho, Melvin B Heyman, Tara L Wenger, Fernando Gonzalez, Margaret Hostetter, Andrew Nowalk, Caroline E Rassbach, Debra Boyer, Pnina Weiss, Rebecca L Blankenburg, Jordan S Orange, Kate G Ackerman, Audrea M Burns, National Pediatric Physician-Scientist Collaborative Workgroup

Faculty, Staff and Students Publications

The COVID-19 pandemic will leave an indelible mark on the careers of current medical trainees. Given the disruptions to medical education, economic impact on institutions, and the uncertainties around future job prospects, trainees are facing unprecedented challenges. This situation is especially concerning for futures of pediatric physician-scientist trainees, where concerns regarding maintaining the pipeline were well documented prior to the emergence of COVID-19. In this Perspectives article, we leverage the unique expertise of our workgroup to address concerns of physician-scientist trainees and to provide suggestions on how to navigate career trajectories in the post-COVID-19 era. We identified and addressed four …

Invariant Natural Killer T-Cell Subsets Have Diverse Graft-Versus-Host-Disease-Preventing And Antitumor Effects, Kristina Maas-Bauer, Juliane K Lohmeyer, Toshihito Hirai, Teresa Lopes Ramos, Furqan M Fazal, Ulrike M Litzenburger, Kathryn E Yost, Jessica V Ribado, Neeraja Kambham, Arielle S Wenokur, Po-Yu Lin, Maite Alvarez, Melissa Mavers, Jeanette Baker, Ami S Bhatt, Howard Y Chang, Federico Simonetta, Robert S Negrin

Faculty, Staff and Students Publications

Invariant natural killer T (iNKT) cells are a T-cell subset with potent immunomodulatory properties. Experimental evidence in mice and observational studies in humans indicate that iNKT cells have antitumor potential as well as the ability to suppress acute and chronic graft-versus-host-disease (GVHD). Murine iNKT cells differentiate during thymic development into iNKT1, iNKT2, and iNKT17 sublineages, which differ transcriptomically and epigenomically and have subset-specific developmental requirements. Whether distinct iNKT sublineages also differ in their antitumor effect and their ability to suppress GVHD is currently unknown. In this work, we generated highly purified murine iNKT sublineages, characterized their transcriptomic and epigenomic landscape, …

Comprehensive Characterization Of Covid-19 Patients With Repeatedly Positive Sars-Cov-2 Tests Using A Large Us Electronic Health Record Database, Xiao Dong, Yujia Zhou, Xiao-Ou Shu, Elmer V Bernstam, Rebecca Stern, David M Aronoff, Hua Xu, Loren Lipworth

Faculty, Staff and Student Publications

In the absence of genome sequencing, two positive molecular tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) separated by negative tests, prolonged time, and symptom resolution remain the best surrogate measure of possible reinfection. Using a large electronic health record database, we characterized clinical and testing data for 23 patients with repeatedly positive SARS-CoV-2 PCR test results ≥60 days apart, separated by ≥2 consecutive negative test results. The prevalence of chronic medical conditions, symptoms, and severe outcomes related to coronavirus disease 19 (COVID-19) illness were ascertained. The median age of patients was 64.5 years, 40% were Black, and 39% …

A Comparison Of Machine Learning Classifiers For Pediatric Epilepsy Using Resting-State Functional Mri Latency Data, Ryan D Nguyen, Matthew D Smyth, Liang Zhu, Ludovic P Pao, Shannon K Swisher, Emmett H Kennady, Anish Mitra, Rajan P Patel, Jeremy E Lankford, Gretchen Von Allmen, Michael W Watkins, Michael E Funke, Manish N Shah

Faculty, Staff and Student Publications

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from …

First-In-Human Segmental Esophageal Reconstruction Using A Bioengineered Mesenchymal Stromal Cell-Seeded Implant, Johnathon M Aho, Saverio La Francesca, Scott D Olson, Fabio Triolo, Jeff Bouchard, Laura Mondano, Sumati Sundaram, Christina Roffidal, Charles S Cox, Louis M Wong Kee Song, Sameh M Said, William Fodor, Dennis A Wigle

Faculty, Staff and Student Publications

INTRODUCTION: Resection and reconstruction of the esophagus remains fraught with morbidity and mortality. Recently, data from a porcine reconstruction model revealed that segmental esophageal reconstruction using an autologous mesenchymal stromal cell-seeded polyurethane graft (Cellspan esophageal implant [CEI]) can facilitate esophageal regrowth and regeneration. To this end, a patient requiring a full circumferential esophageal segmental reconstruction after a complex multiorgan tumor resection was approved for an investigational treatment under the Food and Drug Administration Expanded Access Use (Investigational New Drug 17402).

METHODS: Autologous adipose-derived mesenchymal stromal cells (Ad-MSCs) were isolated from the Emergency Investigational New Drug patient approximately 4 weeks before …

Standardizing New Diagnostic Tests To Facilitate Rapid Responses To The Covid-19 Pandemic, Xiao Dong

Dissertations and Theses (Open Access)

In order to enhance the data interoperability, an expeditious and accurate standardization solution is highly desirable for naming rapidly emerging novel lab tests, and thus diminishes confusion in early responses to pandemic outbreaks. This is a preliminary study to explore the roles and implementation of medical informatics technology, especially natural language processing and ontology methods, in standardizing information about emerging lab tests during a pandemic, thereby facilitating rapid responses to the pandemic. The ultimate goal of this study is to develop an informatics framework for rapid standardization of lab testing names during a pandemic to better prepare for future public …

Deep Learning-Based Mixed-Dimensional Gaussian Mixture Model For Characterizing Variability In Cryo-Em, Muyuan Chen, Steven J Ludtke

Faculty, Staff and Students Publications

Structural flexibility and/or dynamic interactions with other molecules is a critical aspect of protein function. Cryogenic electron microscopy (cryo-EM) provides direct visualization of individual macromolecules sampling different conformational and compositional states. While numerous methods are available for computational classification of discrete states, characterization of continuous conformational changes or large numbers of discrete state without human supervision remains challenging. Here we present e2gmm, a machine learning algorithm to determine a conformational landscape for proteins or complexes using a three-dimensional Gaussian mixture model mapped onto two-dimensional particle images in known orientations. Using a deep neural network architecture, e2gmm can automatically resolve the …

Left Ventricular Recovery With Explantation Of Continuous-Flow Left Ventricular Assist Device After 5 Years Of Support, Andre Critsinelis, Chitaru Kurihara, Masashi Kawabori, Tadahisa Sugiura, Andrew B Civitello, Jeffrey A Morgan

Faculty, Staff and Students Publications

Mechanical circulatory support may result in sufficient myocardial recovery to allow for explantation of the left ventricular assist device (LVAD). The duration of support associated with left ventricular recovery has generally been 6-12 months. In this report, we present a patient in whom the left ventricle recovered after 5 years of support with a LVAD. Our report demonstrates that long-term monitoring for left ventricular recovery is prudent and may allow for late device explantation.

The Synergy Of Bet Inhibitors With Aurora A Kinase Inhibitors In Mycn-Amplified Neuroblastoma Is Heightened With Functional Tp53, Joanna S Yi, Oscar Sias-Garcia, Nicole Nasholm, Xiaoyu Hu, Amanda Balboni Iniguez, Matthew D Hall, Mindy Davis, Rajarshi Guha, Myrthala Moreno-Smith, Eveline Barbieri, Kevin Duong, Jessica Koach, Jun Qi, James E Bradner, Kimberly Stegmaier, William A Weiss, W Clay Gustafson

Faculty, Staff and Students Publications

Amplification of MYCN is a poor prognostic feature in neuroblastoma (NBL) indicating aggressive disease. We and others have shown BET bromodomain inhibitors (BETi) target MYCN indirectly by downregulating its transcription. Here we sought to identify agents that synergize with BETi and to identify biomarkers of resistance. We previously performed a viability screen of ∼1,900 oncology-focused compounds combined with BET bromodomain inhibitors against MYCN-amplified NBL cell lines. Reanalysis of our screening results prominently identified inhibitors of aurora kinase A (AURKAi) to be highly synergistic with BETi. We confirmed the anti-proliferative effects of several BETi+AURKAi combinations in MYCN-amplified NBL cell lines. Compared …

Digital Technology Needs In Maternal Mental Health: A Qualitative Inquiry, Alexandra Zingg, Laura Carter, Deevakar Rogith, Amy Franklin, Sudhakar Selvaraj, Jerrie Refuerzo, Sahiti Myneni

Faculty, Staff and Student Publications

Digital technologies offer many opportunities to improve mental healthcare management for women seeking pre- and-postnatal care. They provide a discrete, practical medium that is well-suited for the sensitive nature of mental health. Women who are more prone to experiencing peripartum depression (PPD), such as those of low-socioeconomic background or in high-risk pregnancies, can benefit the most from such technologies. However, current digital interventions directed towards this population provide suboptimal support, and their responsiveness to end user needs is quite limited. Our objective is to understand the digital terrain of information needs for low-socioeconomic status women with high-risk pregnancies, specifically within …

Deep Learning Predicts Chromosomal Instability From Histopathology Images, Zhuoran Xu, Akanksha Verma, Uska Naveed, Samuel F. Bakhoum, Pegah Khosravi, Olivier Elemento

Publications and Research

Chromosomal instability (CIN) is a hallmark of human cancer yet not readily testable for patients with cancer in routine clinical setting. In this study, we sought to explore whether CIN status can be predicted using ubiquitously available hematoxylin and eosin histology through a deep learning-based model. When applied to a cohort of 1,010 patients with breast cancer (Training set: n = 858, Test set: n = 152) from The Cancer Genome Atlas where 485 patients have high CIN status, our model accurately classified CIN status, achieving an area under the curve of 0.822 with 81.2% sensitivity and 68.7% specificity in …

Med-Bert: Pretrained Contextualized Embeddings On Large-Scale Structured Electronic Health Records For Disease Prediction, Laila Rasmy, Yang Xiang, Ziqian Xie, Cui Tao, Degui Zhi

Faculty, Staff and Student Publications

Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver impressive performance in many clinical tasks. Large training cohorts, however, are often required by these models to achieve high accuracy, hindering the adoption of DL-based models in scenarios with limited training data. Recently, bidirectional encoder representations from transformers (BERT) and related models have achieved tremendous successes in the natural language processing domain. The pretraining of BERT on a very large training corpus generates contextualized embeddings that can boost the performance of models trained on smaller datasets. Inspired by BERT, we propose Med-BERT, which adapts the BERT framework originally developed …