A. Palmer

Light-induced Extracellular Vesicle Adsorption

This paper introduces LEVA, a label-free, high-resolution, tunable platform for EV adsorption and characterization, demonstrating its versatility with various EV sources and applications.

Advancing childhood cancer research through young investigator and advocate collaboration

This paper describes a collaborative model between young investigators and cancer advocates to enhance pediatric cancer research through improved communication and team science.

Individual differences in members of Actinobacteria, Bacteroidetes, and Firmicutes is associated with resistance or vulnerability to addiction-like behaviors in heterogeneous stock rats

The paper identifies microbiome composition and metabolic pathways associated with resistance or vulnerability to addiction-like behaviors in rats using a large cohort and extended cocaine self-administration.

Infection of immune competent macrophages expressing functional Slc11a1 alters global gene expression, regulation of metal ions, and infection outcomes

This study shows that functional Slc11a1 in macrophages alters metal ion regulation and infection outcomes during Salmonella infection by changing zinc availability and immune response profiles.

Public LC-Orbitrap-MS/MS Spectral Library for Metabolite Identification

The paper constructs and shares an open LC-MS/MS spectral library with over 1600 fragmentation spectra for metabolite identification.

Myosin VI moves on nuclear actin filaments and supports long-range chromatin rearrangements

This study shows nuclear myosin VI moves along actin filaments and facilitates transcription-dependent chromatin rearrangements.

Combined inhibition of mTOR and PIKKs exploits replicative and checkpoint vulnerabilities to induce death of PI3K-activated triple-negative breast cancer cells

The paper shows that combining mTOR and PIKK inhibitors kills triple-negative breast cancer cells by exploiting replication and checkpoint vulnerabilities.

Drug-target binding quantitatively predicts optimal antibiotic dose levels

This paper develops a computational model to predict antibiotic dose-response relationships from drug-target binding parameters and validates it with clinical isolates.