Evaluation of chronic disease self-management information on social media using evidenced-based frameworks

The management of chronic diseases requires considerable patient education and self-management. Diabetes, cancer and mental illness are among the top ten searched chronic diseases on social media, a platform where people increasingly seek and disseminate information. Social media platforms such as Twitter can potentially shape online conversations and perceptions about chronic disease management. In this study, we analyze diabetes self-management (DSM) information on Twitter using AADE7™ behavioral guidelines. This study aims to illustrate that social network analysis based on such evidence-based behavioral frameworks can be used to inform the analysis of chronic disease information shared on social media. This approach…

Elucidate the Genome Evolution of Eusocial Corbiculate Bees Using Parent-progeny Sequencing Approach

Understanding the evolution of eusociality, defined by distinct reproductive and nonreproductive castes, at the molecular level, has always been an essential and highly challenging topic of biology. Eusociality has evolved multiple times independently and involved many incremental steps, resulted in intermediate levels of social complexity. The Apinae (corbiculate bees) consists of 4 tribes with a wide range of social complexity: orchid bees (Euglossini), bumble bees (Bombini), stingless bees (Meliponini), and honey bees (Apini); is an ideal group for comparative studies of eusocial evolution in Hymenoptera. The first sequenced genome of the honey bee Apis mellifera in 2006 has become a gateway for…

Analysis of snRNA-seq from CDX Models of Non-Small Cell Lung Cancer Identified Subpopulation of Cells Potentially Responsible for Tumor Progression

Circulating tumor cells (CTCs) are considered as seeds of metastasis and have potential to be used as biomarkers in cancer.  Understanding the biology of CTCs is critical to evaluate tumor progression and response to treatment. Additionally, studying transcriptome of CTCs–derived tumors aids in deciphering the causes underlying metastasis. Single nuclei-RNA-sequencing (snRNA-seq) is an emerging technology that allows investigators to study individual cells with molecular typing to that drives tumor growth and resistance to therapy. In this study, we use novel human CTC-derived xenograft (CDX) mouse models of non-small cell lung cancer (NSCLC) and snRNA-seq to determine genetic and cellular drivers of…

What to Learn and What to Avoid from ClinicalTrials.gov for New Trial Design When Repurposing Drugs for Precision Medicine?

Clinical trials are essential in the process of new drug development and repositioning. As clinical trials involve significant investments of time and money, it is crucial for trial designers to carefully investigate trial settings prior to launching it. In the 356,282 trials registered on ClinicalTrials.gov , one can search similar trial setting with the current trial of interest and identify prior or ongoing trials that share similar patient’s population, genetic characteristics, intervention means, etc. It is a wise strategy to learn from successful trials and to avoid repeating mistakes from failed trials. For example, in our computational drug repositioning project…

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 are well-documented, to this date the genetic underpinnings of COPD remain largely unknown. Furthermore, in the current landscape of a respiratory pandemic, COPD patients are at a much higher risk for developing other respiratory illnesses and co-morbidities. In this study we use genomic data from…

Risk Factors for Thyroid Cancer, a Systematic Review

Thyroid cancer accounted for 1 out of every 20 female cancer diagnoses worldwide in 2018; the etiology of this disease is not well understood, and preventive programs are not established.  It is well known that thyroid cancer incidence has been increasing since the 1980s, largely attributed to the increase in diagnosis of papillary thyroid cancer and improvements in detection and diagnosis.  Currently, exposure to ionizing radiation is the only well-established risk factor for thyroid cancer.   Literature published in the English language between 1946 and September 2020 was searched via MEDLINE. A building-block strategy was used to identify articles of interest: “thyroid neoplasms”…

FatPlants: A Comprehensive Website Platform of Plant Fat Related Genes, Proteins and Metabolism

Increasing seed oil content by plant breeding has resulted in trade-offs or penalties with respect to protein content, seed size, or seed set. The molecular basis for this impasse is mostly speculative. Use of current global profiling approaches to better understand both the metabolic consequences of higher oil and the basis for reduced yield must also deal with off-target genetic mutations (even in near-isogenic lines), ultimately confounding cause-effect interpretations. We propose a diverse, integrated strategy to study the consequences of higher lipid production by studying transgenic plants specifically engineered to produce higher seed oil. As a part of this collaborative project,…

Cancer Surveillance Informatics – Missouri Cancer Registry and Research Center

Cancer surveillance has to be able to monitor trends of cancer cases, subtypes of cancer, and cancer clusters to inform cancer control and policies related to cancer and cancer care. The increasing complexity and depth of cancer care, treatment, and other elements to describe a cancer case require cancer registries to capture data from a wide variety of sources by utilizing many informatics methods to integrate these data. Current and future developments include automated processing of electronic pathology reports, artificial intelligence, natural language processing NLP, and linkage of data sources to expand surveillance goals. Recent developments include a national virtual…

Development of A Blockchain Framework for Virtual Clinical Trials

Clinical trials are essential for discovering new treatments, but there are multiple challenges to patient recruitment, patient engagement, and cost containment. Virtual clinical trials (VCT) are an innovative approach that provides potential solutions by conducting home-based, rather than site-based, clinical trials. Virtual clinical trials are still the exception rather than general practice due to technical barriers. “Blockchain,” a distributed ledger technology, is a perfect match for virtual clinical trials. Its peer-to-peer design, security settings, and data transparency meet the needs of many healthcare applications. The programmable “Smart Contract” feature makes blockchain more suitable and feasible for VCT by solving computational…