Computational Analysis Suggests That AsnGTT 3'-tRNA-Derived Fragments Are Potential Biomarkers in Papillary Thyroid Carcinoma.

Transfer-RNA-derived fragments (tRFs) are a novel class of small non-coding RNAs that have been implicated in oncogenesis. tRFs may act as post-transcriptional regulators by recruiting AGO proteins and binding to highly complementary regions of mRNA at seed regions, resulting in the knockdown of the transcript. Therefore, tRFs may be critical to tumorigenesis and warrant investigation as potential biomarkers.

Assessing the diagnostic utility of tRNA-derived fragments as biomarkers of head and neck cancer.

Roughly 54,000 individuals are diagnosed with head and neck cancers in the United States yearly. Transfer RNA-derived fragments (tRF) are the products of enzymatic cleavage of precursor tRNAs, and have been proposed for use as biomarkers of head and neck cancer. In this study, we aim to further analyze the utility that tRFs might provide as biomarkers of head and neck cancer.

The intratumor microbiome varies by geographical location and anatomical site in head and neck squamous cell carcinoma.

Head and Neck Squamous Cell Carcinoma (HNSCC) is a highly heterogeneous cancer that is characterized by distinct phenotypes based on anatomical site and etiological agents. Recently, the intratumor microbiome has been implicated in cancer pathogenesis and progression. Although it is well established that the gut microbiome varies with geographical location and is highly influenced by factors such as diet, environment, and genetics, the intratumor microbiome is not very well characterized.

Microbiome Dysbiosis Is Associated with Castration Resistance and Cancer Stemness in Metastatic Prostate Cancer.

Prostate cancer is the second leading cause of death in males in America, with advanced prostate cancers exhibiting a 5-year survival rate of only 32%. Castration resistance often develops during the course of treatment, but its pathogenesis is poorly understood. This study explores the human microbiome for its implications in castration resistance and metastasis in prostate cancer.

Urinary Microbiome Dysbiosis and Immune Dysregulations as Potential Diagnostic Indicators of Bladder Cancer.

There are a total of 82,290 new cases and 16,710 deaths estimated for bladder cancer in the United States in 2023. Currently, urine cytology tests are widely used for bladder cancer diagnosis, though they suffer from variable sensitivity, ranging from 45 to 97%. More recently, the microbiome has become increasingly recognized for its role in human diseases, including cancers.

Clinical characteristics and comorbidities associated with SARS-CoV-2 breakthrough infection in the University of California Healthcare Systems.

Background: To evaluate the degree to which clinical comorbidities or combinations of comorbidities are associated with SARS-CoV-2 breakthrough infection.

Materials And Methods: A breakthrough infection was defined as a positive test at least 14 days after a full vaccination regimen. Logistic regression was used to calculate aORs, which were adjusted for age, sex, and race information.

Characterization of tRNA-Derived Fragments in Lung Squamous Cell Carcinoma with Respect to Tobacco Smoke.

Lung squamous cell carcinoma (LUSC) is a highly heterogeneous cancer that is influenced by etiological agents such as tobacco smoke. Accordingly, transfer RNA-derived fragments (tRFs) are implicated in both cancer onset and development and demonstrate the potential to act as targets for cancer treatments and therapies. Therefore, we aimed to characterize tRF expression with respect to LUSC pathogenesis and clinical outcomes.

Transcriptomic Analysis Reveals Dysregulation of the Mycobiome and Archaeome and Distinct Oncogenic Characteristics according to Subtype and Gender in Papillary Thyroid Carcinoma.

Papillary Thyroid Carcinoma (PTC) is characterized by unique tumor morphology, treatment response, and patient outcomes according to subtype and gender. While previous studies have implicated the intratumor bacterial microbiome in the incidence and progression of PTC, few studies have investigated the potential role of fungal and archaeal species in oncogenesis. In this study, we aimed to characterize the intratumor mycobiome and archaeometry in PTC with respect to its three primary subtypes: Classical (CPTC), Follicular Variant (FVPTC), and Tall Cell (TCPTC), and also with respect to gender.

Effects of Human Papilloma Virus E6/E7 Oncoproteins on Genomic Structure in Head and Neck Squamous Cell Carcinoma.

Human Papilloma Virus (HPV) is highly prevalent within the U.S., with studies estimating that over 80% of individuals will contract the virus in their lifetime.

The Intratumor Bacterial and Fungal Microbiome Is Characterized by HPV, Smoking, and Alcohol Consumption in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) tumor phenotypes and clinical outcomes are significantly influenced by etiological agents, such as HPV infection, smoking, and alcohol consumption. Accordingly, the intratumor microbiome has been increasingly implicated in cancer progression and metastasis. However, few studies characterize the intratumor microbial landscape of HNSCC with respect to these etiological agents.

Archaea Microbiome Dysregulated Genes and Pathways as Molecular Targets for Lung Adenocarcinoma and Squamous Cell Carcinoma.

The human microbiome is a vast collection of microbial species that exist throughout the human body and regulate various bodily functions and phenomena. Of the microbial species that exist in the human microbiome, those within the archaea domain have not been characterized to the extent of those in more common domains, despite their potential for unique metabolic interaction with host cells. Research has correlated tumoral presence of microbial species to the development and progression of lung cancer; however, the impacts and influences of archaea in the microbiome remain heavily unexplored.

Medical student's perception of the COVID-19 pandemic effect on their education and well-being: a cross-sectional survey in the United States.

Background: The effects of drastic curricular changes necessitated by the COVID-19 pandemic on medical students' education and wellbeing have remained largely unstudied. Out study aimed to characterize how medical students were affected by the pandemic, specifically how limitations introduced by the pandemic may have affected the quality, delivery, and experience of medical education.

Methods: Three hundred students from 5 U.

The renal clear cell carcinoma immune landscape.

A comprehensive evaluation of the clear cell renal cell carcinoma (ccRCC) immune landscape was found using 584 RNA-sequencing datasets from The Cancer Genome Atlas (TCGA), we identified 17 key dysregulated immune-associated genes in ccRCC based on association with clinical variables and important immune pathways. Of the numerous findings from our analyses, we found that several of the 17 key dysregulated genes are heavily involved in interleukin and NF-kB signaling and that somatic copy number alteration (SCNA) hotspots may be causally associated with gene dysregulation. More importantly, we also found that key immune-associated genes and pathways are strongly upregulated in ccRCC.

Analysis of the immune landscape in virus-induced cancers using a novel integrative mechanism discovery approach.

Background: The mechanisms of carcinogenesis from viral infections are extraordinarily complex and not well understood. Traditional methods of analyzing RNA-sequencing data may not be sufficient for unraveling complicated interactions between viruses and host cells. Using RNA and DNA-sequencing data from The Cancer Genome Atlas (TCGA), we aim to explore whether virus-induced tumors exhibit similar immune-associated (IA) dysregulations using a new algorithm we developed that focuses on the most important biological mechanisms involved in virus-induced cancers.

Enhancer RNA Profiling in Smoking and HPV Associated HNSCC Reveals Associations to Key Oncogenes.

Smoking and HPV infection are known causes for the vast majority of head and neck squamous cell carcinomas (HNSCC) due to their likelihood of causing gene dysregulation and genomic alterations. Enhancer RNAs (eRNAs) are non-coding RNAs that are known to increase nearby and target gene expression, and activity that has been suggested to be affected by genetic and epigenetic alterations. Here we sought to identify the effects of smoking and HPV status on eRNA expression in HNSCC tumors.

Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status: A Systematic-Review and Meta-analysis.

Importance: COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.

Objective: To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.

Tobacco Smoke and Electronic Cigarette Vapor Alter Enhancer RNA Expression That Can Regulate the Pathogenesis of Lung Squamous Cell Carcinoma.

Tobacco is the primary etiologic agent in worsened lung squamous cell carcinoma (LUSC) outcomes. Meanwhile, it has been shown that etiologic agents alter enhancer RNAs (eRNAs) expression. Therefore, we aimed to identify the effects of tobacco and electronic cigarette (e-cigarette) use on eRNA expression in relation to LUSC outcomes.

The Bladder Microbiome Is Associated with Epithelial-Mesenchymal Transition in Muscle Invasive Urothelial Bladder Carcinoma.

The intra-tumor microbiome has recently been linked to epithelial-mesenchymal transition (EMT) in a number of cancers. However, the relationship between EMT and microbes in bladder cancer has not been explored. In this study, we profiled the abundance of individual microbe species in the tumor samples of over 400 muscle invasive bladder carcinoma (MIBC) patients.

Cardiovascular, cerebrovascular, and renal co-morbidities in COVID-19 patients: A systematic-review and meta-analysis.

Background: COVID-19 has infected over 35 million people worldwide and led to over 1 million deaths. Several risk factors that increase COVID-19 severity have emerged, including age and a history of cardiovascular disease, hypertension, or kidney disease. However, a number of outstanding questions persist, including whether the above comorbidities correlate with increased mortality from COVID-19 or whether age is a significant confounding variable that accounts for the observed relationship between COVID-19 severity and other comorbidities.

Identification of Lung and Blood Microbiota Implicated in COVID-19 Prognosis.

The implications of the microbiome on Coronavirus disease 2019 (COVID-19) prognosis has not been thoroughly studied. In this study we aimed to characterize the lung and blood microbiome and their implication on COVID-19 prognosis through analysis of peripheral blood mononuclear cell (PBMC) samples, lung biopsy samples, and bronchoalveolar lavage fluid (BALF) samples. In all three tissue types, we found panels of microbes differentially abundant between COVID-19 and normal samples correlated to immune dysregulation and upregulation of inflammatory pathways, including key cytokine pathways such as interleukin (IL)-2, 3, 5-10 and 23 signaling pathways and downregulation of anti-inflammatory pathways including IL-4 signaling.

Chronic E-Cigarette Aerosol Inhalation Alters the Immune State of the Lungs and Increases ACE2 Expression, Raising Concern for Altered Response and Susceptibility to SARS-CoV-2.

Conventional smoking is known to both increase susceptibility to infection and drive inflammation within the lungs. Recently, smokers have been found to be at higher risk of developing severe forms of coronavirus disease 2019 (COVID-19). E-cigarette aerosol inhalation (vaping) has been associated with several inflammatory lung disorders, including the recent e-cigarette or vaping product use-associated lung injury (EVALI) epidemic, and recent studies have suggested that vaping alters host susceptibility to pathogens such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

COVID-19 Severity Potentially Modulated by Cardiovascular-Disease-Associated Immune Dysregulation.

Patients with underlying cardiovascular conditions are particularly vulnerable to severe COVID-19. In this project, we aimed to characterize similarities in dysregulated immune pathways between COVID-19 patients and patients with cardiomyopathy, venous thromboembolism (VTE), or coronary artery disease (CAD). We hypothesized that these similarly dysregulated pathways may be critical to how cardiovascular diseases (CVDs) exacerbate COVID-19.

The intratumor microbiome predicts prognosis across gender and subtypes in papillary thyroid carcinoma.

While the intratumor microbiome has become increasingly implicated in cancer development, the microbial landscape of papillary thyroid carcinoma (PTC) is essentially uninvestigated. PTC is characterized by varied prognosis between gender and cancer subtype, but the cause for gender and subtype-based dissimilarities is unclear. Women are more frequently diagnosed with PTC, while men suffer more advanced-staged PTC.

Identification and Characterization of the Intra-Articular Microbiome in the Osteoarthritic Knee.

Osteoarthritis (OA) is the most common joint disorder in the United States, and the gut microbiome has recently emerged as a potential etiologic factor in OA development. Recent studies have shown that a microbiome is present at joint synovia. Therefore, we aimed to characterize the intra-articular microbiome within osteoarthritic synovia and to illustrate its role in OA disease progression.

Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

Background: The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests.

Methods: In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aim to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID-19 patients and influenza patients based on clinical variables alone.