It’s the Methodology For Me: A Systematic Review of Early Approaches to Studying TikTok

Research on TikTok has grown along with the app’s rapidly rising global popularity. In this systematic review, we investigate 58 articles examining TikTok, its users, and its content. Focusing on articles published in journals and proceedings across the domains of human-computer interaction, communication, and other related disciplines, we analyze the methods being used to study TikTok, as well as ethical considerations. Based on our analysis, we found that research on TikTok tends to use content analysis as their primary method and mainly focus on user behavior and culture, effects of use, the platform’s policies and governance, and very few articles discuss the ethical implications of collecting and analyzing such data. Additionally, most studies employ traditional forms of data collection when the affordances of TikTok tend to differ from other social media platforms. We conclude with a discussion about possible future directions and contribute to ongoing conversations about ethics and social media data

Genetical genomics: spotlight on QTL hotspots

No abstract available

Cell-to-Cell Stochastic Variation in Gene Expression Is a Complex Genetic Trait

The genetic control of common traits is rarely deterministic, with many genes contributing only to the chance of developing a given phenotype. This incomplete penetrance is poorly understood and is usually attributed to interactions between genes or interactions between genes and environmental conditions. Because many traits such as cancer can emerge from rare events happening in one or very few cells, we speculate an alternative and complementary possibility where some genotypes could facilitate these events by increasing stochastic cell-to-cell variations (or ‘noise’). As a very first step towards investigating this possibility, we studied how natural genetic variation influences the level of noise in the expression of a single gene using the yeast S. cerevisiae as a model system. Reproducible differences in noise were observed between divergent genetic backgrounds. We found that noise was highly heritable and placed under a complex genetic control. Scanning the genome, we mapped three Quantitative Trait Loci (QTL) of noise, one locus being explained by an increase in noise when transcriptional elongation was impaired. Our results suggest that the level of stochasticity in particular molecular regulations may differ between multicellular individuals depending on their genotypic background. The complex genetic architecture of noise buffering couples genetic to non-genetic robustness and provides a molecular basis to the probabilistic nature of complex traits

Moving toward a system genetics view of disease

Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone

Genome-wide expression quantitative trait loci (eQTL) analysis in maize

<p>Abstract</p> <p>Background</p> <p>Expression QTL analyses have shed light on transcriptional regulation in numerous species of plants, animals, and yeasts. These microarray-based analyses identify regulators of gene expression as either cis-acting factors that regulate proximal genes, or trans-acting factors that function through a variety of mechanisms to affect transcript abundance of unlinked genes.</p> <p>Results</p> <p>A hydroponics-based genetical genomics study in roots of a <it>Zea mays </it>IBM2 Syn10 double haploid population identified tens of thousands of cis-acting and trans-acting eQTL. Cases of false-positive eQTL, which results from the lack of complete genomic sequences from both parental genomes, were described. A candidate gene for a trans-acting regulatory factor was identified through positional cloning. The unexpected regulatory function of a class I glutamine amidotransferase controls the expression of an ABA 8'-hydroxylase pseudogene.</p> <p>Conclusions</p> <p>Identification of a candidate gene underlying a trans-eQTL demonstrated the feasibility of eQTL cloning in maize and could help to understand the mechanism of gene expression regulation. Lack of complete genome sequences from both parents could cause the identification of false-positive cis- and trans-acting eQTL.</p

Combining transcriptional profiling and genetic linkage analysis to uncover gene networks operating in hematopoietic stem cells and their progeny

Stem cells are unique in that they possess both the capacity to self-renew and thereby maintain their original pool as well as the capacity to differentiate into mature cells. In the past number of years, transcriptional profiling of enriched stem cell populations has been extensively performed in an attempt to identify a universal stem cell gene expression signature. While stem-cell-specific transcripts were identified in each case, this approach has thus far been insufficient to identify a universal group of core “stemness” genes ultimately responsible for self-renewal and multipotency. Similarly, in the hematopoietic system, comparisons of transcriptional profiles between different hematopoietic cell stages have had limited success in revealing core genes ultimately responsible for the initiation of differentiation and lineage specification. Here, we propose that the combined use of transcriptional profiling and genetic linkage analysis, an approach called “genetical genomics”, can be a valuable tool to assist in the identification of genes and gene networks that specify “stemness” and cell fate decisions. We review past studies of hematopoietic cells that utilized transcriptional profiling and/or genetic linkage analysis, and discuss several potential future applications of genetical genomics

Collective cell migration of smooth muscle and endothelial cells: impact of injury versus non-injury stimuli

BACKGROUND: Cell migration is a vital process for growth and repair. In vitro migration assays, utilized to study cell migration, often rely on physical scraping of a cell monolayer to induce cell migration. The physical act of scrape injury results in numerous factors stimulating cell migration - some injury-related, some solely due to gap creation and loss of contact inhibition. Eliminating the effects of cell injury would be useful to examine the relative contribution of injury versus other mechanisms to cell migration. Cell exclusion assays can tease out the effects of injury and have become a new avenue for migration studies. Here, we developed two simple non-injury techniques for cell exclusion: 1) a Pyrex® cylinder - for outward migration of cells and 2) a polydimethylsiloxane (PDMS) insert - for inward migration of cells. Utilizing these assays smooth muscle cells (SMCs) and human umbilical vein endothelial cells (HUVECs) migratory behavior was studied on both polystyrene and gelatin-coated surfaces. RESULTS: Differences in migratory behavior could be detected for both smooth muscle cells (SMCs) and endothelial cells (ECs) when utilizing injury versus non-injury assays. SMCs migrated faster than HUVECs when stimulated by injury in the scrape wound assay, with rates of 1.26 % per hour and 1.59 % per hour on polystyrene and gelatin surfaces, respectively. The fastest overall migration took place with HUVECs on a gelatin-coated surface, with the in-growth assay, at a rate of 2.05 % per hour. The slowest migration occurred with the same conditions but on a polystyrene surface at a rate of 0.33 % per hour. CONCLUSION: For SMCs, injury is a dominating factor in migration when compared to the two cell exclusion assays, regardless of the surface tested: polystyrene or gelatin. In contrast, the migrating surface, namely gelatin, was a dominating factor for HUVEC migration, providing an increase in cell migration over the polystyrene surface. Overall, the cell exclusion assays - the in-growth and out-growth assays, provide a means to determine pure migratory behavior of cells in comparison to migration confounded by cell wounding and injury.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]

Resource Information Applied to Water Sources and Discharges at Existing and Potential Power Plant Sites in Arizona and the Southwest: Project Completion Report

Project Completion Report, OWRT Project No. A-043-ARIZ / Agreement No. 14-31-0001-4003 / Project Dates: July 1973 - June 1974 / Acknowledgment: The work upon which this report is based was supported in large part by funds provided by the United States Department of the Interior, Office of Water Research and Technology, as authorized under the Water Resources Research Act of 1964.A growing demand for energy production in Arizona has increased the need for assembling and analyzing water resource information relative to energy production, especially electrical power generation. Unit water requirements for cooling of electrical plants, combined with projections of future electrical power demands in Arizona, provide a perspective on future quantities of water needed for cooling. Probabilistic estimates of storage reserves in Arizona groundwater basins indicate that some prospective plant sites can be supplied from groundwater for the 30 -year life of the plant, while others cannot. An estimate of comparative cost for supplying groundwater versus municipal wastewater for cooling electrical plants at selected sites in Arizona showed that use of wastewater would result in considerable savings over use of groundwater, at all sites considered.This item is part of the Water Resources Research Center collection. It was digitized from a physical copy provided by the Water Resources Research Center at The University of Arizona. For more information about items in this collection, please contact the Center, (520) 621-9591 or see http://wrrc.arizona.edu

Collective cell migration of smooth muscle and endothelial cells: impact of injury versus non-injury stimuli

BACKGROUND: Cell migration is a vital process for growth and repair. In vitro migration assays, utilized to study cell migration, often rely on physical scraping of a cell monolayer to induce cell migration. The physical act of scrape injury results in numerous factors stimulating cell migration - some injury-related, some solely due to gap creation and loss of contact inhibition. Eliminating the effects of cell injury would be useful to examine the relative contribution of injury versus other mechanisms to cell migration. Cell exclusion assays can tease out the effects of injury and have become a new avenue for migration studies. Here, we developed two simple non-injury techniques for cell exclusion: 1) a Pyrex® cylinder - for outward migration of cells and 2) a polydimethylsiloxane (PDMS) insert - for inward migration of cells. Utilizing these assays smooth muscle cells (SMCs) and human umbilical vein endothelial cells (HUVECs) migratory behavior was studied on both polystyrene and gelatin-coated surfaces. RESULTS: Differences in migratory behavior could be detected for both smooth muscle cells (SMCs) and endothelial cells (ECs) when utilizing injury versus non-injury assays. SMCs migrated faster than HUVECs when stimulated by injury in the scrape wound assay, with rates of 1.26 % per hour and 1.59 % per hour on polystyrene and gelatin surfaces, respectively. The fastest overall migration took place with HUVECs on a gelatin-coated surface, with the in-growth assay, at a rate of 2.05 % per hour. The slowest migration occurred with the same conditions but on a polystyrene surface at a rate of 0.33 % per hour. CONCLUSION: For SMCs, injury is a dominating factor in migration when compared to the two cell exclusion assays, regardless of the surface tested: polystyrene or gelatin. In contrast, the migrating surface, namely gelatin, was a dominating factor for HUVEC migration, providing an increase in cell migration over the polystyrene surface. Overall, the cell exclusion assays - the in-growth and out-growth assays, provide a means to determine pure migratory behavior of cells in comparison to migration confounded by cell wounding and injury.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]