Cutaneous spindle cell sarcoma: a population-based study in the surveillance, epidemiology, and end results database...

This protocol introduces a standard laboratory operating procedure for diagnostic testing of lyssavirus antigens in bats in...

We present here a cell culture method for inducing mesenchymal-epithelial transitions (MET) in sarcoma cells based on combined ectopic expression of microRNA-200 family members and grainyhead-like 2 (GRHL2). This method is suitable for better understanding the biological impact of phenotypic plasticity on cancer aggressiveness and...

Kaposi sarcoma (KS) is a tumor induced by infection with the oncogenic virus human herpesvirus-8/KS herpesvirus (HHV-8/KSHV). The endothelial cell culture model described here is uniquely suited for studying the mechanisms by which KSHV transforms host cells.

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is: