Medicine and Health Sciences Commons^™

Microenvironmental Ammonia Enhances T Cell Exhaustion In Colorectal Cancer, Hannah N Bell, Amanda K Huber, Rashi Singhal, Navyateja Korimerla, Ryan J Rebernick, Roshan Kumar, Marwa O El-Derany, Peter Sajjakulnukit, Nupur K Das, Samuel A Kerk, Sumeet Solanki, Jadyn G James, Donghwan Kim, Li Zhang, Brandon Chen, Rohit Mehra, Timothy L Frankel, Balázs Győrffy, Eric R Fearon, Marina Pasca Di Magliano, Frank J Gonzalez, Ruma Banerjee, Daniel R Wahl, Costas A Lyssiotis, Michael Green, Yatrik M Shah

Faculty, Staff and Student Publications

Effective therapies are lacking for patients with advanced colorectal cancer (CRC). The CRC tumor microenvironment has elevated metabolic waste products due to altered metabolism and proximity to the microbiota. The role of metabolite waste in tumor development, progression, and treatment resistance is unclear. We generated an autochthonous metastatic mouse model of CRC and used unbiased multi-omic analyses to reveal a robust accumulation of tumoral ammonia. The high ammonia levels induce T cell metabolic reprogramming, increase exhaustion, and decrease proliferation. CRC patients have increased serum ammonia, and the ammonia-related gene signature correlates with altered T cell response, adverse patient outcomes, and …

Taxonomic Classification Of Viral And Bacterial Dna Following 2021 Avian Mass Mortality Event, Tessa Baillargeon

Honors Theses and Capstones

From May through July 2021, an unusual mortality event occurred along the eastern coast and Midwest of the United States. Thousands of birds, mostly from the order Passeriformes, were part of the die-off including blue jays (Cyanocitta cristata), common grackles (Quiscalus quiscula), European starlings (Sturnus vulgaris), American robins (Turdus migratorius). Clinical signs included crusted eyes, swollen conjunctiva, otitis, seizures, and ataxia.

The New Hampshire Veterinary Diagnostic Laboratory (NHVDL) received over 100 affected birds from various collaborators throughout the United States including Washington DC, NJ, CT, MD, and OH. Given the timing and geologic …

Identification Of Novel Biosynthetic Gene Clusters Encoding For Polyketide/Nrps-Producing Chemotherapeutic Compounds From Marine-Derived Streptomyces Hygroscopicus From A Marine Sanctuary, Hannah Ruth Flaherty

Honors Theses and Capstones

Nearly one out of six deaths in 2020, around ten million people, were caused by cancer, making it a leading cause of death worldwide (WHO, 2022). This major public health issue, in addition to the rise of multidrug-resistant (MDR) pathogens, provides a high demand for the discovery of new pharmaceutical drugs to be used clinically to treat these conditions. The Streptomyces genus accounts to produce 39% of all microbial metabolites currently approved for human health, indicating its potential as an important species to study for antimicrobial and anticancer agents. The long linear genome of Streptomyces contains specialized sequences known as …

Genetic And Pharmacogenetics Associations Of Cancer Disparities In Appalachia, Nan Lin

Theses and Dissertations--Pharmacy

Individuals residing in Appalachian regions have significant health disparities, including higher cancer incidence and mortality rates. Previous studies have addressed the impact of socioeconomic status and environmental risk factors on Appalachia cancer disparities, while few studies have evaluated genetic risk factors.

Germline whole exome sequencing samples from 7,078 individuals with cancer (759 Appalachians) were evaluated. Demographics and relatedness were assessed using KING. Ethnicity was verified by principal component analysis using TRACE, which included 6,034 individuals (85%) of European genetic ancestry. After QC filtering, 5,980 individuals were analyzed. To assess the overall predisposition of hereditary disease, gene level frequency of likely …

Bioinformatic Analysis Of Proteomic And Genomic Data From Nsclc Tumors On Prognostic And Predictive Factors Of Immunotherapy Treatment, Mark Wuenschel

Theses and Dissertations--Pharmacy

Recent lung cancer research has led to advancements in molecular immunology, resulting in development of small molecule inhibitors, or immune checkpoint inhibitors, that propagate an anti-tumor T cell response. Despite increased overall and progression-free survival with reduced adverse effects compared to traditional chemotherapy, treating advanced stage lung adenocarcinoma patients remains non-curative, and evidence of non-responders or tumor recurrence to immune checkpoint inhibitor therapy is growing. Also, compared to traditional chemotherapy, there is a lower percentage of patients who respond to small molecule inhibitors. In this analysis of proteomic and genomic data from The Cancer Proteome Atlas and Global Data Commons …

Covidanno, Covid-19 Annotation In Human, Yuzhou Feng, Mengyuan Yang, Zhiwei Fan, Weiling Zhao, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 19 (COVID-19), has caused a global health crisis. Despite ongoing efforts to treat patients, there is no universal prevention or cure available. One of the feasible approaches will be identifying the key genes from SARS-CoV-2-infected cells. SARS-CoV-2-infected in vitro model, allows easy control of the experimental conditions, obtaining reproducible results, and monitoring of infection progression. Currently, accumulating RNA-seq data from SARS-CoV-2 in vitro models urgently needs systematic translation and interpretation. To fill this gap, we built COVIDanno, COVID-19 annotation in humans, available at http://biomedbdc.wchscu.cn/COVIDanno/. The aim …

Syllable-Pbwt For Space-Efficient Haplotype Long-Match Query, Victor Wang, Ardalan Naseri, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

MOTIVATION: The positional Burrows-Wheeler transform (PBWT) has led to tremendous strides in haplotype matching on biobank-scale data. For genetic genealogical search, PBWT-based methods have optimized the asymptotic runtime of finding long matches between a query haplotype and a predefined panel of haplotypes. However, to enable fast query searches, the full-sized panel and PBWT data structures must be kept in memory, preventing existing algorithms from scaling up to modern biobank panels consisting of millions of haplotypes. In this work, we propose a space-efficient variation of PBWT named Syllable-PBWT, which divides every haplotype into syllables, builds the PBWT positional prefix arrays on …

Use Gpt-J Prompt Generation With Roberta For Ner Models On Diagnosis Extraction Of Periodontal Diagnosis From Electronic Dental Records, Yao-Shun Chuang, Xiaoqian Jiang, Chun-Teh Lee, Ryan Brandon, Duong Tran, Oluwabunmi Tokede, Muhammad F Walji

Faculty, Staff and Student Publications

This study explored the usability of prompt generation on named entity recognition (NER) tasks and the performance in different settings of the prompt. The prompt generation by GPT-J models was utilized to directly test the gold standard as well as to generate the seed and further fed to the RoBERTa model with the spaCy package. In the direct test, a lower ratio of negative examples with higher numbers of examples in prompt achieved the best results with a F1 score of 0.72. The performance revealed consistency, 0.92-0.97 in the F1 score, in all settings after training with the RoBERTa model. …

Towards Fair Patient-Trial Matching Via Patient-Criterion Level Fairness Constraint, Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu, Na Zou

Faculty, Staff and Student Publications

Clinical trials are indispensable in developing new treatments, but they face obstacles in patient recruitment and retention, hindering the enrollment of necessary participants. To tackle these challenges, deep learning frameworks have been created to match patients to trials. These frameworks calculate the similarity between patients and clinical trial eligibility criteria, considering the discrepancy between inclusion and exclusion criteria. Recent studies have shown that these frameworks outperform earlier approaches. However, deep learning models may raise fairness issues in patient-trial matching when certain sensitive groups of individuals are underrepresented in clinical trials, leading to incomplete or inaccurate data and potential harm. To …

The Kynurenine Pathway In Alzheimer’S Disease: A Meta-Analysis Of Central And Peripheral Levels, Brisa S Fernandes, Mehmet Enes Inam, Nitesh Enduru, Joao Quevedo, Zhongming Zhao

Faculty, Staff and Student Publications

OBJECTIVE: Changes in the kynurenine pathway are recognized in psychiatric disorders, but their role in Alzheimer's disease (AD) is less clear. We aimed to conduct a systematic review and meta-analysis to determine whether tryptophan and kynurenine pathway metabolites are altered in AD.

METHODS: We performed a systematic review and random-effects meta-analyses. Inclusion criteria were studies that compared AD and cognitively normal (CN) groups and assessed tryptophan or kynurenine pathway metabolites in cerebrospinal fluid or peripheral blood.

RESULTS: Twenty-two studies with a total of 1,356 participants (664 with AD and 692 CN individuals) were included. Tryptophan was decreased only in peripheral …

Automated Detection Of Hippocampal Sclerosis Using Real-World Clinical Mri Images, Jingwen Jiang, Jiajun Qiu, Jin Yin, Junren Wang, Xinyue Jiang, Zuo Yi, Yang Chen, Xiaobo Zhou, Xiutian Sima

Faculty, Staff and Student Publications

BACKGROUND: Hippocampal sclerosis (HS) is the most common pathological type of temporal lobe epilepsy (TLE) and one of the important surgical markers. Currently, HS is mainly diagnosed manually by radiologists based on visual inspection of MRI, which greatly relies on MRI quality and physician experience. In clinical practice, non-thin MRI scans are often used due to the time and efficiency needed for the acquisition. However, these scans can be difficult for junior physicians to interpret accurately. Thus, the rapid and accurate diagnosis of HS using real-world MRI images in clinical settings is a challenging task.

OBJECTIVE: Our aim was to …

Generation Of Chimeric Rhinoviruses Presenting Sars-Cov-2 Broadly Neutralizing Epitopes And Their Antigenicity Characterization, Danish Ansari

Biotechnology Theses

The global COVID pandemic is not yet fully under control as there were over 21 million new cases of SARS-CoV-2 infections and over 50,000 deaths globally as of January of 2022. A heavily mutated variant of concern, Omicron is responsible for most of these cases which demands an urgency for a new vaccine. NIH reports over 180 vaccine candidates that use various strategies currently in development. However, a recurring concern with these vaccines is that the continuous viral mutations decrease the efficacy of vaccines. Therefore, we proposed to construct a human rhinovirus (HRV) based chimeric virus containing highly conserved, broadly …

A Query Engine For Self-Controlled Case Series, With An Application To Covid-19 Ehr Data, Xiaojin Li, Yan Huang, Licong Cui, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Self-controlled case series (SCCS) is a statistical method in epidemiological study design that uses individuals as their own controls, with comparisons made within the same individuals at different time points of observation. SCCS has been applied in settings where it is difficult to identify comparison or control groups. To provide computational support for SCCS, we introduce a query engine called Self-Controlled Case Query (SCCQ) and use it to extract cohorts of self-controlled case series from a large-scale COVID-19 Electronic Health Records (EHR) dataset. Visual summary of the queried population through the R-Shiny visualization framework offers SCCQ's query result dashboard to …

Federated Learning Based Futuristic Biomedical Big-Data Analysis And Standardization, Afifa Salsabil Fathima, Syed Muzamil Basha, Syed Thouheed Ahmed, Sandeep Kumar Mathivanan, Sukumar Rajendran, Saurav Mallik, Zhongming Zhao

Faculty, Staff and Student Publications

Medical data processing and analytics exert significant influence in furnishing dependable decision support for prospective biomedical applications. Given the sensitive nature of medical data, specialized techniques and frameworks tailored for application-centric processing are imperative. This article presents a conceptualization for the analysis and uniformitarian of datasets through the implementation of Federated Learning (FL). The realm of medical big data stems from diverse origins, necessitating the delineation of data provenance and attribute paradigms to facilitate feature extraction and dependency assessment. The architecture governing the data collection framework is intricately linked to remote data transmission, thereby engendering efficient customization oversight. The operational …

Machine Learning-Driven Exploration Of Drug Therapies For Triple-Negative Breast Cancer Treatment, Aman Chandra Kaushik, Zhongming Zhao

Faculty, Staff and Student Publications

Breast cancer is the second leading cause of cancer death in women among all cancer types. It is highly heterogeneous in nature, which means that the tumors have different morphologies and there is heterogeneity even among people who have the same type of tumor. Several staging and classifying systems have been developed due to the variability of different types of breast cancer. Due to high heterogeneity, personalized treatment has become a new strategy. Out of all breast cancer subtypes, triple-negative breast cancer (TNBC) comprises ∼10%-15%. TNBC refers to the subtype of breast cancer where cells do not express estrogen receptors, …

Predictive Digital Twin For Optimizing Patient-Specific Radiotherapy Regimens Under Uncertainty In High-Grade Gliomas, Anirban Chaudhuri, Graham Pash, David A Hormuth, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto A B F Lima, Thomas E Yankeelov, Karen Willcox

Faculty, Staff and Student Publications

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties in the underlying tumor biology in high-grade gliomas, where heterogeneity in the response to standard-of-care (SOC) radiotherapy contributes to sub-optimal patient outcomes. The digital twin is initialized through prior distributions derived from population-level clinical data in the literature for a mechanistic model's parameters. Then the digital twin is personalized using Bayesian model calibration for assimilating patient-specific magnetic resonance imaging data. The calibrated digital twin is used to propose optimal …

The Short- And Long-Term Readmission Of Four Major Categories Of Digestive System Cancers: Does Obesity Or Metabolic Disorder Matter?, Yan Li, Xiaoqin Wu, Yongfeng Song, Peipei Wang, Bofei Zhang, Bingzhou Guo, Ziwei Liu, Yafei Wu, Shanshan Shao, Yiping Cheng, Honglin Guo, Xiude Fan, Jiajun Zhao

Faculty, Staff and Student Publications

Purpose: Patients with digestive system cancers (DSCs) are at a high risk for hospitalizations; however, the risk factors for readmission remain unknown. Here, we established a retrospective cohort study to assess the association between metabolic obesity phenotypes and readmission risks of DSC.

Experimental design: A total of 142,753 and 74,566 patients at index hospitalization were ultimately selected from the Nationwide Readmissions Database (NRD) 2018 to establish the 30-day and 180-day readmission cohorts, respectively. The study population was classified into four groups: metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO). Multivariate Cox …

Receptor-Interacting Protein 1 And 3 Kinase Activity Are Required For High-Fat Diet Induced Liver Injury In Mice, Xiaoqin Wu, Rakesh K Arya, Emily Huang, Megan R Mcmullen, Laura E Nagy

Faculty, Staff and Student Publications

BACKGROUND: The RIP1-RIP3-MLKL-mediated cell death pathway is associated with progression of non-alcohol-associated fatty liver/steatohepatitis (NAFL/NASH). Previous work identified a critical role for MLKL, the key effector regulating necroptosis, but not RIP3, in mediating high fat diet-induced liver injury in mice. RIP1 and RIP3 have active N-terminus kinase domains essential for activation of MLKL and subsequent necroptosis. However, little is known regarding domain-specific roles of RIP1/RIP3 kinase in liver diseases. Here, we hypothesized that RIP1/RIP3 kinase activity are required for the development of high fat diet-induced liver injury.

METHODS:Rip1K45A/K45A and Rip3K51A/K51A kinase-dead mice on a C57BL/6J background and their littermate …

Acute Myeloid Leukemia With Concurrent Npm1 And Runx1 Mutations, Zhuang Zuo, L Jeffrey Medeiros, C Cameron Yin

Faculty, Staff and Student Publications

NPM1 mutation, as a founding genetic event, cooperates with other gene mutations, such as DNMT3A and FLT3, to promote the development of acute myeloid leukemia. NPM1 mutation, however, has been reported to be mutually exclusive with RUNX1 mutation in acute myeloid leukemia cases. In this study, we analyzed mutation panel testing data from a relatively large cohort of rare AML cases with both NPM1 and RUNX1 mutations. We describe the dynamic process of the emergence of these mutations, as well as molecular genetic features and clinical outcome of these patients. We show that concurrence of both mutations in acute …

Integrated Clinical Genotype-Phenotype Characteristics Of Early T-Cell Precursor Acute Lymphoblastic Leukemia, Matthew T Ye, Yi Wang, Zhuang Zuo, Steliana Calin, Hua He, Zhenya Tang, Elias J Jabbour, Gautam Borthakur, Yizhuo Zhang, Yaling Yang, M James You

Faculty, Staff and Student Publications

Background: Early T-cell precursor acute lymphoblastic leukemia (ETP-ALL) is a distinct subtype of T-ALL with a unique immunophenotype and high treatment failure rate. The molecular genetic abnormalities and their prognostic impact in ETP-ALL patients are poorly understood.

Methods: The authors performed systematic analyses of the clinicopathologic features with an emphasis on molecular genetic aspects of 32 patients with ETP-ALL.

Results: The median age was 43 years (range, 16-71). The blasts were positive for cytoplasmic CD3 and CD7 and negative for CD1a and CD8. Other markers expressed included CD34 (88%), CD33 (72%), CD117 (68%), CD13 (58%), CD5 (partial, 56%), CD2 (38%), …

Revolutionizing Bone Regeneration: Advanced Biomaterials For Healing Compromised Bone Defects, Kamal Awad, Neelam Ahuja, Ahmed S Yacoub, Leticia Brotto, Simon Young, Antonios Mikos, Pranesh Aswath, Venu Varanasi

Faculty, Staff and Student Publications

In this review, we explore the application of novel biomaterial-based therapies specifically targeted towards craniofacial bone defects. The repair and regeneration of critical sized bone defects in the craniofacial region requires the use of bioactive materials to stabilize and expedite the healing process. However, the existing clinical approaches face challenges in effectively treating complex craniofacial bone defects, including issues such as oxidative stress, inflammation, and soft tissue loss. Given that a significant portion of individuals affected by traumatic bone defects in the craniofacial area belong to the aging population, there is an urgent need for innovative biomaterials to address the …

Ribonuclease 1 Enhances Antitumor Immunity Against Breast Cancer By Boosting T Cell Activation, Ying-Nai Wang, Heng-Huan Lee, Zhou Jiang, Li-Chuan Chan, Gabriel N Hortobagyi, Dihua Yu, Mien-Chie Hung

Faculty, Staff and Student Publications

The secretory enzyme human ribonuclease 1 (RNase1) is involved in innate immunity and anti-inflammation, achieving host defense and anti-cancer effects; however, whether RNase1 contributes to adaptive immune response in the tumor microenvironment (TME) remains unclear. Here, we established a syngeneic immunocompetent mouse model in breast cancer and demonstrated that ectopic RNase1 expression significantly inhibited tumor progression. Overall changes in immunological profiles in the mouse tumors were analyzed by mass cytometry and showed that the RNase1-expressing tumor cells significantly induced CD4+ Th1 and Th17 cells and natural killer cells and reduced granulocytic myeloid-derived suppressor cells, supporting that RNase1 favors an antitumor …

Sound Speed Estimation For Distributed Aberration Correction In Laterally Varying Media, Rehman Ali, Trevor M Mitcham, Melanie Singh, Marvin M Doyley, Richard R Bouchard, Jeremy J Dahl, Nebojsa Duric

Faculty, Staff and Student Publications

Spatial variation in sound speed causes aberration in medical ultrasound imaging. Although our previous work has examined aberration correction in the presence of a spatially varying sound speed, practical implementations were limited to layered media due to the sound speed estimation process involved. Unfortunately, most models of layered media do not capture the lateral variations in sound speed that have the greatest aberrative effect on the image. Building upon a Fourier split-step migration technique from geophysics, this work introduces an iterative sound speed estimation and distributed aberration correction technique that can model and correct for aberrations resulting from laterally varying …

Naproxen Chemoprevention Induces Proliferation Of Cytotoxic Lymphocytes In Lynch Syndrome Colorectal Mucosa, Charles M Bowen, Nan Deng, Laura Reyes-Uribe, Edwin Roger Parra, Pedro Rocha, Luisa M Solis, Ignacio I Wistuba, Valerie O Sepeda, Lana Vornik, Marjorie Perloff, Eva Szabo, Asad Umar, Krishna M Sinha, Powel H Brown, Eduardo Vilar

Faculty, Staff and Student Publications

BACKGROUND: Recent clinical trial data from Lynch Syndrome (LS) carriers demonstrated that naproxen administered for 6-months is a safe primary chemoprevention that promotes activation of different resident immune cell types without increasing lymphoid cellularity. While intriguing, the precise immune cell types enriched by naproxen remained unanswered. Here, we have utilized cutting-edge technology to elucidate the immune cell types activated by naproxen in mucosal tissue of LS patients.

METHODS: Normal colorectal mucosa samples (pre- and post-treatment) from a subset of patients enrolled in the randomized and placebo-controlled 'Naproxen Study' were obtained and subjected to a tissue microarray for image mass cytometry …

Membranous Nephropathy In Chronic Lymphocytic Leukemia Responsive To Ibrutinib: A Case Report, Anna-Eve Turcotte, William F Glass, Jamie S Lin, Jan A Burger

Faculty, Staff and Student Publications

Membranous nephropathy (MN) is an uncommon renal presentation in patients with chronic lymphocytic leukemia (CLL), and as such, there is no standard therapy for these patients. A few cases of MN in CLL have been described with varying success in MN treatment involving alkylating agents and fludarabine. Here we report the first case of MN in a patient with CLL treated with ibrutinib with complete renal response. This presentation underlines the importance of recognizing rare glomerular diseases that may occur with CLL and offers a new therapeutic avenue to the treatment of CLL-associated MN.

Machine Learning-Based Prediction Of Acute Mortality In Emergency Department Patients Using Twelve-Lead Electrocardiogram, Po-Cheng Chang, Zhi-Yong Liu, Yu-Chang Huang, Yu-Chun Hsu, Jung-Sheng Chen, Ching-Heng Lin, Richard Tsai, Chung-Chuan Chou, Ming-Shien Wen, Hung-Ta Wo, Wen-Chen Lee, Hao-Tien Liu, Chun-Chieh Wang, Chang-Fu Kuo

Faculty, Staff and Student Publications

BACKGROUND: The risk of mortality is relatively high among patients who visit the emergency department (ED), and stratifying patients at high risk can help improve medical care. This study aimed to create a machine-learning model that utilizes the standard 12-lead ECG to forecast acute mortality risk in ED patients.

METHODS: The database included patients who visited the EDs and underwent standard 12-lead ECG between October 2007 and December 2017. A convolutional neural network (CNN) ECG model was developed to classify survival and mortality using 12-lead ECG tracings acquired from 345,593 ED patients. For machine learning model development, the patients were …

Artificial Intelligence-Enabled Electrocardiographic Screening For Left Ventricular Systolic Dysfunction And Mortality Risk Prediction, Yu-Chang Huang, Yu-Chun Hsu, Zhi-Yong Liu, Ching-Heng Lin, Richard Tsai, Jung-Sheng Chen, Po-Cheng Chang, Hao-Tien Liu, Wen-Chen Lee, Hung-Ta Wo, Chung-Chuan Chou, Chun-Chieh Wang, Ming-Shien Wen, Chang-Fu Kuo

Faculty, Staff and Student Publications

BACKGROUND: Left ventricular systolic dysfunction (LVSD) characterized by a reduced left ventricular ejection fraction (LVEF) is associated with adverse patient outcomes. We aimed to build a deep neural network (DNN)-based model using standard 12-lead electrocardiogram (ECG) to screen for LVSD and stratify patient prognosis.

METHODS: This retrospective chart review study was conducted using data from consecutive adults who underwent ECG examinations at Chang Gung Memorial Hospital in Taiwan between October 2007 and December 2019. DNN models were developed to recognize LVSD, defined as LVEF

RESULTS: The mean age of patients in the testing dataset was 63.7 ± 16.3 years (46.3% …

Distinct Patterns Of Auto-Reactive Antibodies Associated With Organ-Specific Immune-Related Adverse Events, Mehmet Altan, Quan-Zhen Li, Qi Wang, Natalie I Vokes, Ajay Sheshadri, Jianjun Gao, Chengsong Zhu, Hai T Tran, Saumil Gandhi, Mara B Antonoff, Stephen Swisher, Jing Wang, Lauren A Byers, Noha Abdel-Wahab, Maria C Franco-Vega, Yinghong Wang, J Jack Lee, Jianjun Zhang, John V Heymach

Faculty, Staff and Student Publications

UNLABELLED: The roles of preexisting auto-reactive antibodies in immune-related adverse events (irAEs) associated with immune checkpoint inhibitor therapy are not well defined. Here, we analyzed plasma samples longitudinally collected at predefined time points and at the time of irAEs from 58 patients with immunotherapy naïve metastatic non-small cell lung cancer treated on clinical protocol with ipilimumab and nivolumab. We used a proteomic microarray system capable of assaying antibody reactivity for IgG and IgM fractions against 120 antigens for systemically evaluating the correlations between auto-reactive antibodies and certain organ-specific irAEs. We found that distinct patterns of auto-reactive antibodies at baseline were …

Efficient Federated Kinship Relationship Identification, Xinyue Wang, Leonard Dervishi, Wentao Li, Xiaoqian Jiang, Erman Ayday, Jaideep Vaidya

Faculty, Staff and Student Publications

Kinship relationship estimation plays a significant role in today's genome studies. Since genetic data are mostly stored and protected in different silos, retrieving the desirable kinship relationships across federated data warehouses is a non-trivial problem. The ability to identify and connect related individuals is important for both research and clinical applications. In this work, we propose a new privacy-preserving kinship relationship estimation framework: Incremental Update Kinship Identification (INK). The proposed framework includes three key components that allow us to control the balance between privacy and accuracy (of kinship estimation): an incremental process coupled with the use of auxiliary information and …

Sensitive Data Detection With High-Throughput Machine Learning Models In Electrical Health Records, Kai Zhang, Xiaoqian Jiang

Faculty, Staff and Student Publications

In the era of big data, there is an increasing need for healthcare providers, communities, and researchers to share data and collaborate to improve health outcomes, generate valuable insights, and advance research. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a federal law designed to protect sensitive health information by defining regulations for protected health information (PHI). However, it does not provide efficient tools for detecting or removing PHI before data sharing. One of the challenges in this area of research is the heterogeneous nature of PHI fields in data across different parties. This variability makes rule-based …