Biology subjects

Love, T. M. T.

Publications and source records attributed to Love, T. M. T..

2 recordsLinked to original sources

bioRxiv2023

Local Delivery of SBRT and IL12 by mRNA Technology Overcomes Immunosuppressive Barriers to Eliminate Pancreatic Cancer

The immunosuppressive milieu in pancreatic cancer (PC) is a significant hurdle to treatments, resulting in survival statistics that have barely changed in 5 decades. Here we present a combination treatment consisting of stereotactic body radiation therapy (SBRT) and IL-12 mRNA lipid nanoparticles delivered directly to pancreatic murine tumors. This treatment was effective against primary and metastatic models, achieving cures in both settings. IL-12 protein concentrations were transient and localized primarily to the tumor. Depleting CD4 and CD8 T cells abrogated treatment efficacy, confirming they were essential to treatment response. Single cell RNA sequencing from SBRT/IL-12 mRNA treated tumors demonstrated not only a complete loss of T cell exhaustion, but also an abundance of highly proliferative and effector T cell subtypes. SBRT elicited T cell receptor clonal expansion, whereas IL-12 licensed these cells with effector function. This is the first report demonstrating the utility of SBRT and IL-12 mRNA in PC. Statement of significanceThis study demonstrates the use of a novel combination treatment consisting of radiation and immunotherapy in murine pancreatic tumors. This treatment could effectively treat local and metastatic disease, suggesting it may have the potential to treat a cancer that has not seen a meaningful increase in survival in 5 decades.

cancer biology↗

bioRxiv2022

Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data

While fecal indicator bacteria (FIB) testing is used to monitor surface waters for potential health hazards, recent studies report substantial variation in FIB levels and that observed variation appeared dependent on scale of analysis (SOA). Citizen science data and random effects models were used to quantify variance in FIB levels attributable to spatial versus temporal factors. Separately, Bayesian models were used to quantify the ratio of spatial to nonspatial variance in FIB levels, and identify associations between environmental factors and FIB levels. Separate analyses were performed for each stream, lake, and watershed as well as at the state-level (three SOAs). As SOA increased (from waterway to watershed to statewide models), variance attributable to spatial sources generally increased and variance attributable to temporal sources generally decreased. While relationships between FIB levels and environmental factors, such as flow conditions, were constant across SOA, the effect of land cover was both highly dependent on SOA and consistently smaller than the effect of outfalls. This study demonstrates the importance of scale when designing monitoring programs or using FIB monitoring to inform management. Moreover, these data represent a comprehensive survey of water quality in Upstate NY, and the study highlights a valuable publicly available database.

microbiology↗