Publications by authors named "S D Airhart"

Summary: Short tandem repeat (STR) profiling is commonly performed for authentication of biomedical models of human origin, yet no tools exist to easily compare sets of STR profiles to each other or an existing database in a high-throughput manner. Here, we present STRprofiler, a Python package, command line tool, and Shiny application providing methods for STR profile comparison and cross-contamination detection. STRprofiler can be run with custom databases or used to query against the Cellosaurus cell line database.

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Age is among the main risk factors for cancer, and any cancer study in adults is faced with an aging tissue and organism. Yet, pre-clinical studies are carried out using young mice and are not able to address the impact of aging and associated comorbidities on disease biology and treatment outcomes. Here, we discuss the limitations of current mouse cancer models and suggest strategies for developing novel models to address these major gaps in knowledge and experimental approaches.

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The mitochondrial dysfunction characteristic of heart failure (HF) is associated with changes in intracellular nicotinamide adenine dinucleotide (NAD) and NADH levels. Raising NAD levels with the NAD precursor, nicotinamide riboside (NR), may represent a novel HF treatment. In this 30-participant trial of patients with clinically stable HF with reduced ejection fraction, NR, at a dose of 1,000 mg twice daily, appeared to be safe and well tolerated, and approximately doubled whole blood NAD levels.

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Article Synopsis
  • Patient-derived xenograft (PDX) models offer a valuable platform for testing new cancer drugs, specifically for lung cancer, with a repository of 79 extensively characterized models.
  • The collection mainly includes non-small cell lung cancer (NSCLC) variants, such as adenocarcinoma and squamous cell carcinoma, and incorporates models that exhibit resistance to targeted therapies.
  • The genomic features of the PDXs align with those in actual patient tumors, confirming their relevance for preclinical research and their ability to predict treatment responses.
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