Browse our Review Articles

The integration of established psychological and biological models of pain suggests novel interventions to prevent pain persistence.

Open questions of cancer adaptive therapy are discussed through the lens of mathematical modeling, categorized into three sections, (1) integrating appropriate components into mathematical models, (2) dosing protocol design and validation, and (3) challenges and opportunities in clinical translation.

Methods for video analysis of behaving animals are described, with guidance provided on setting up the methods in a research laboratory and best practices for experimenters and developers.

PASC (post-acute sequelae of SARS-CoV-2 infection) is an enduring and debilitating illness caused by a persistent virus that promotes inflammation, coagulation, and autoimmunity complications in millions of patients initially diagnosed with COVID-19, but with no known standardized treatment regimen.

The mechanisms by which non-pathologic short tandem repeats normally influence gene expression and engender rapid genetic variation across phylogeny directly inform how expansions in these same repeats elicit neurological disease.

The primary rhythm generators controlling respiration are integrated in a much larger network of brain regions, including areas not typically considered to be respiratory control centers, and that allow respiration to be adapted to all forms of ongoing behavior.

As macrophages are involved in various aspects of non-small cell lung cancer development and progression it is crucial to develop appropriate 3D co-culture platforms for modeling immune cell-tumor cell interactions, leading to more efficacious macrophage-focused immunotherapies.

Hepatitis B virus infection is a neglected challenge among communities who are under-served by conventional models of healthcare, requiring enhanced interventions to reduce inequity.

Intracellular and interorgan skeletal crosstalk highlights integrative skeletal physiology.

The recent developments in large-scale machine learning, especially with the recent Transformer models, display much potential for solving computational problems within protein biology and outcompete traditional computational methods in many recent studies and benchmarks.