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De-novo SuperTranscriptome assembly from the nodal root growth zone of maize inbred line FR697

Certain cultivars of maize show increased resistance to water deficit conditions by maintenance of root growth. To better understand the molecular mechanisms related to this adaption, nodal root growth zone samples were collected from the reference inbred line B73 and inbred line FR697, which exhibits a relatively greater ability to maintain root elongation under water

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Design and Evaluation of a Longitudinal Method to Measure Physician Burnout in the Clinical Workflow

Burnout, a condition characterized by emotional exhaustion, listlessness, and an inability to cope, is demonstrably more prevalent among healthcare providers than other occupations.  Burnout is fundamentally a longitudinal problem, but traditional instruments for measurement such as the Maslach Burnout Inventory (MBI) and the Professional Fulfillment Index (PFI) are time-consuming, expensive, and complex to administer, making

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Analysis and Dissemination of School-based Immunization Data to Improve Public Health Outcomes in Missouri

In Missouri, immunization is required for both public and private school students against common vaccine-preventable diseases (VPDs) including polio, pertussis, varicella, measles, mumps, and rubella; however, parents may forego vaccination for their child by claiming medical or religious exemptions. Like many states across the US, Missouri is experiencing increasing vaccine exemption rates. However, health officials

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Computational Subgroups Stratification and Precision Drug Repositioning Using Explainable Artificial Intelligence

Enabling precision medicine requires developing robust patient stratification methods and identifying drugs tailored to homogeneous subgroups of patients from a heterogeneous population. Once discovering these subgroups, we can align patients and medications more specifically to achieve precision-based therapy. Developing de novo drugs is expensive and time-consuming with an ultimately low FDA approval rate. These limitations make developing

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Virtual Campus Visit with NSF CISE AD Dr. Margaret Martonosi

The National Science Foundation (NSF) supports a majority of US academic research in the Computer and Information Science and Engineering (CISE) topic areas. Since February, 2020, Dr. Margaret Martonosi serves as NSF CISE AD, stewarding the CISE directorate’s $1B annual budget on behalf of research, education, workforce and infrastructure funding in CISE topic areas and for science as

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Dissertation Defense – Utilizing Blockchain Technology for Clinical Trial Optimization

Clinical trials are the cornerstone of treatment discovery because they provide comprehensive scientific evidence on the safety, efficacy, and optimal use of therapeutics. However, current clinical trials are facing multiple challenges such as patient recruitment, data capture, and overall management. There are various causes of patient recruitment challenges such as inefficient advertising models, complex protocols,

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Comprehensive Exam Announcement – A Case-Control based Genomic Analysis of Chronic Obstructive Pulmonary Disease

Chronic Obstructive Pulmonary Disease (COPD) is a respiratory illness that affects millions of people all over the world. It is a major cause of chronic morbidity and mortality and a serious global public health problem. COPD is the fourth leading cause of death worldwide. Although the environmental causes of COPD which predominantly include cigarette smoking

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Regulation of gene expression by DNA methylation with cytotoxic T lymphocytes evaluation in consensus molecular subtypes of colorectal cancer

Background: Low cytotoxic T lymphocyte (CTLs) infiltration in colorectal cancer (CRC) tumors is a challenge to treatment with immune checkpoint inhibitors. Consensus molecular subtypes (CMS) classify patients based on tumor attributes, and CMS1 patients include the majority of patients with high CTL infiltration and “inflamed” tumors. Epigenetic modification plays a critical role in gene expression

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Leveraging Unsupervised Machine Learning To Find Trends In The Textual Warnings Generated Using Multi-Modality Time Series Sensor Data

With technology and the internet of things (IoT), smart health care is no longer a dream. The devices that wouldn’t usually be generally expected to have an internet connection can communicate with the network independent of human action, and this is referred to as the internet of things. These devices, in our case, are the

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Information Extraction Framework for Facilitating the Assessment of the Quality of Radiology Interpretations

Assessing the quality of imaging interpretations requires that the results of radiological interpretations be compared with those of subsequent surgical-pathology results, when available. The manual process is inherently slow, tedious and expensive, and unless systematic errors occur in the interpretations, discrepancies are unlikely to be detected. Classical computational methods using Natural Language Processing entail using

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