Grounded theory research: A design framework for novice researchers

Background: Grounded theory is a well-known methodology employed in many research studies. Qualitative andquantitative data generation techniques can be used in a grounded theory study. Grounded theory sets out to discoveror construct theory from data, systematically obtained and analysed using comparative analysis. While grounded theoryis inherently flexible, it is a complex methodology. Thus, novice researchers strive to understand the discourse and thepractical application of grounded theory concepts and processes.Objective: The aim of this article is to provide a contemporary research framework suitable to inform a grounded theorystudy.Result: This article provides an overview of grounded theory illustrated through a graphic representation of the processesand methods employed in conducting research using this methodology. The framework is presented as a diagrammaticrepresentation of a research design and acts as a visual guide for the novice grounded theory researcher.Discussion: As grounded theory is not a linear process, the framework illustrates the interplay between the essentialgrounded theory methods and iterative and comparative actions involved. Each of the essential methods and processes thatunderpin grounded theory are defined in this article.Conclusion: Rather than an engagement in philosophical discussion or a debate of the different genres that can be used ingrounded theory, this article illustrates how a framework for a research study design can be used to guide and inform thenovice nurse researcher undertaking a study using grounded theory. Research findings and recommendations can contributeto policy or knowledge development, service provision and can reform thinking to initiate change in the substantive area ofinquiry

Association between RUNX3 promoter methylation and gastric cancer: a meta-analysis

<p>Abstract</p> <p>Background</p> <p>Runt-related transcription factor 3 (RUNX3) is a member of the runt-domain family of transcription factors and has been reported to be a candidate tumor suppressor in gastric cancer. However, the association between RUNX3 promoter methylation and gastric cancer remains unclear.</p> <p>Methods</p> <p>We systematically reviewed studies of RUNX3 promoter methylation and gastric cancer published in English or Chinese from January 2000 to January 2011, and quantified the association between RUNX3 promoter methylation and gastric cancer using meta-analysis methods.</p> <p>Results</p> <p>A total of 1740 samples in 974 participants from seventeen studies were included in the meta-analysis. A significant association was observed between RUNX3 promoter methylation and gastric cancer, with an aggregated odds ratio (OR) of 5.63 (95%CI 3.15, 10.07). There was obvious heterogeneity among studies. Subgroup analyses (including by tissue origin, country and age), meta-regression were performed to determine the source of the heterogeneity. Meta-regression showed that the trend in ORs was inversely correlated with age. No publication bias was detected. The ORs for RUNX3 methylation in well-differentiated <it>vs </it>undifferentiated gastric cancers, and in intestinal-type <it>vs </it>diffuse-type carcinomas were 0.59 (95%CI: 0.30, 1.16) and 2.62 (95%CI: 1.33, 5.14), respectively. There were no significant differences in RUNX3 methylation in cancer tissues in relation to age, gender, TNM stage, invasion of tumors into blood vessel or lymphatic ducts, or tumor stage.</p> <p>Conclusions</p> <p>This meta-analysis identified a strong association between methylation of the RUNX3 promoter and gastric cancer, confirming the role of RUNX3 as a tumor suppressor gene.</p

MiR-339-5p inhibits breast cancer cell migration and invasion in vitro and may be a potential biomarker for breast cancer prognosis

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play an important role in the regulation of cell growth, differentiation, apoptosis, and carcinogenesis. Detection of their expression may lead to identifying novel markers for breast cancer.</p> <p>Methods</p> <p>We profiled miRNA expression in three breast cancer cell lines (MCF-7, MDA-MB-231, and MDA-MB-468) and then focused on one miRNA, miR-339-5p, for its role in regulation of tumor cell growth, migration, and invasion and target gene expression. We then analyzed miR-339-5p expression in benign and cancerous breast tissue specimens.</p> <p>Results</p> <p>A number of miRNAs were differentially expressed in these cancer cell lines. Real-time PCR indicated that miR-339-5p expression was downregulated in the aggressive cell lines MDA-MB-468 and MDA-MB-231 and in breast cancer tissues compared with benign tissues. Transfection of miR-339-5p oligonucleotides reduced cancer cell growth only slightly but significantly decreased tumor cell migration and invasion capacity compared with controls. Real-time PCR analysis showed that BCL-6, a potential target gene of miR-339-5p, was downregulated in MDA-MB-231 cells by miR-339-5p transfection. Furthermore, the reduced miR-339-5p expression was associated with an increase in metastasis to lymph nodes and with high clinical stages. Kaplan-Meier analyses found that the patients with miR-339-5p expression had better overall and relapse-free survivals compared with those without miR-339-5p expression. Cox proportional hazards analyses showed that miR-339-5p expression was an independent prognostic factor for breast cancer patients.</p> <p>Conclusions</p> <p>MiR-339-5p may play an important role in breast cancer progression, suggesting that miR-339-5p should be further evaluated as a biomarker for predicting the survival of breast cancer patients.</p

Single domain antibody multimers confer protection against rabies infection

Post-exposure prophylactic (PEP) neutralizing antibodies against Rabies are the most effective way to prevent infection-related fatality. The outer envelope glycoprotein of the Rabies virus (RABV) is the most significant surface antigen for generating virus-neutralizing antibodies. The small size and uncompromised functional specificity of single domain antibodies (sdAbs) can be exploited in the fields of experimental therapeutic applications for infectious diseases through formatting flexibilities to increase their avidity towards target antigens. In this study, we used phage display technique to select and identify sdAbs that were specific for the RABV glycoprotein from a naïve llama-derived antibody library. To increase their neutralizing potencies, the sdAbs were fused with a coiled-coil peptide derived from the human cartilage oligomeric matrix protein (COMP48) to form homogenous pentavalent multimers, known as combodies. Compared to monovalent sdAbs, the combodies, namely 26424 and 26434, exhibited high avidity and were able to neutralize 85-fold higher input of RABV (CVS-11 strain) pseudotypes in vitro, as a result of multimerization, while retaining their specificities for target antigen. 26424 and 26434 were capable of neutralizing CVS-11 pseudotypes in vitro by 90–95% as compared to human rabies immunoglobulin (HRIG), currently used for PEP in Rabies. The multimeric sdAbs were also demonstrated to be partially protective for mice that were infected with lethal doses of rabies virus in vivo. The results demonstrate that the combodies could be valuable tools in understanding viral mechanisms, diagnosis and possible anti-viral candidate for RABV infection

Alternative splicing of exon 10 in the tau gene as a target for treatment of tauopathies

Tau aggregation is one of the major features in Alzheimer's disease and in several other tauopathies, including frontotemporal dementia with Parkinsonism linked to chromosome 17 (FTDP-17), and progressive supranuclear palsy (PSP). More than 35 mutations in the tau gene have been identified from FTDP-17 patients. A group of these mutations alters splicing of exon 10, resulting in an increase in exon 10 inclusion into tau mRNA. Abnormal splicing with inclusion of exon 10 into tau mRNA has also been observed in PSP and AD patients. These results indicate that abnormal splicing of exon 10, leading to the production of tau with exon 10, is probably one of the mechanisms by which tau accumulates and aggregates in tauopathic brains. Therefore, modulation of exon 10 splicing in the tau gene could potentially be targeted to prevent tauopathies. To identify small molecules or compounds that could potentially be developed into drugs to treat tauopathies, we established a cell-based high-throughput screening assay. In this review, we will discuss how realistic, specific biological molecules can be found to regulate exon 10 splicing in the tau gene for potential treatment of tauopathies

The JCMT BISTRO Survey: A Spiral Magnetic Field in a Hub-filament Structure, Monoceros R2

We present and analyze observations of polarized dust emission at 850 μm toward the central 1 7 1 pc hub-filament structure of Monoceros R2 (Mon R2). The data are obtained with SCUBA-2/POL-2 on the James Clerk Maxwell Telescope (JCMT) as part of the B-fields in Star-forming Region Observations survey. The orientations of the magnetic field follow the spiral structure of Mon R2, which are well described by an axisymmetric magnetic field model. We estimate the turbulent component of the magnetic field using the angle difference between our observations and the best-fit model of the underlying large-scale mean magnetic field. This estimate is used to calculate the magnetic field strength using the Davis–Chandrasekhar–Fermi method, for which we also obtain the distribution of volume density and velocity dispersion using a column density map derived from Herschel data and the C18O (J = 3 - 2) data taken with HARP on the JCMT, respectively. We make maps of magnetic field strengths and mass-to-flux ratios, finding that magnetic field strengths vary from 0.02 to 3.64 mG with a mean value of 1.0 \ub1 0.06 mG, and the mean critical mass-to-flux ratio is 0.47 \ub1 0.02. Additionally, the mean Alfv\ue9n Mach number is 0.35 \ub1 0.01. This suggests that, in Mon R2, the magnetic fields provide resistance against large-scale gravitational collapse, and the magnetic pressure exceeds the turbulent pressure. We also investigate the properties of each filament in Mon R2. Most of the filaments are aligned along the magnetic field direction and are magnetically subcritical

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

The Experiences of Internationally Qualified Registered Nurses Working in the Australian Healthcare System: An Integrative Literature Review

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