7 results on '"Hartlage, Carson"'
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2. Projecting vaccine demand and impact for emerging zoonotic pathogens
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Lerch, Anita, ten Bosch, Quirine A., L’Azou Jackson, Maïna, Bettis, Alison A., Bernuzzi, Mauro, Murphy, Georgina A. V., Tran, Quan M., Huber, John H., Siraj, Amir S., Bron, Gebbiena M., Elliott, Margaret, Hartlage, Carson S., Koh, Sojung, Strimbu, Kathyrn, Walters, Magdalene, Perkins, T. Alex, and Moore, Sean M.
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- 2022
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3. Widespread microplastic pollution in Indiana, USA, rivers.
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Conard, Whitney M., O'Reilly, Katherine E., Hartlage, Carson, and Lamberti, Gary A.
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PLASTIC marine debris ,EMERGING contaminants ,URBAN land use ,PLASTIC scrap ,ATMOSPHERIC deposition ,CONSUMPTION (Economics) - Abstract
Microplastics (i.e., plastic particles <5 mm in size) are aquatic contaminants of emerging concern but are poorly quantified in flowing waters of the midwestern USA. Microplastics enter streams and rivers through a variety of pathways (e.g., wastewater effluent, breakdown of larger plastic debris, atmospheric deposition) and can potentially harm aquatic organisms through both direct consumption and indirect contamination from sorbed toxins. In this study, we quantified microplastic concentrations and types (i.e., beads, fibers, films, foams, fragments) in nine Indiana watersheds representing a gradient of dominant land use (i.e., agricultural, urban, and forested). We predicted that microplastic concentration would be higher in watersheds with higher percentages of urban and agricultural land use than in forested watersheds. Our results revealed measurable quantities of microplastics in samples from all watersheds, but microplastic concentration did not vary significantly with land use or longitudinally within watersheds. Fibers were the dominant form of microplastic at all sites, suggesting that fibers may be transported primarily through atmospheric deposition rather than via direct runoff from the surrounding landscape. We conclude that rivers have a different microplastic "signature" than large lakes, likely due to retention characteristics of flowing water ecosystems, unique microplastic sources, and a shorter legacy of microplastic pollution. [ABSTRACT FROM AUTHOR]
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- 2023
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4. H3.3-G34 mutations impair DNA repair and promote cGAS/STING-mediated immune responses in pediatric high-grade glioma models
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Haase, Santiago, primary, Banerjee, Kaushik, additional, Mujeeb, Anzar A., additional, Hartlage, Carson S., additional, Núñez, Fernando M., additional, Núñez, Felipe J., additional, Alghamri, Mahmoud S., additional, Kadiyala, Padma, additional, Carney, Stephen, additional, Barissi, Marcus N., additional, Taher, Ayman W., additional, Brumley, Emily K., additional, Thompson, Sarah, additional, Dreyer, Justin T., additional, Alindogan, Caitlin T., additional, Garcia-Fabiani, Maria B., additional, Comba, Andrea, additional, Venneti, Sriram, additional, Ravikumar, Visweswaran, additional, Koschmann, Carl, additional, Carcaboso, Ángel M., additional, Vinci, Maria, additional, Rao, Arvind, additional, Yu, Jennifer S., additional, Lowenstein, Pedro R., additional, and Castro, Maria G., additional
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- 2022
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5. Additional file 1 of Projecting vaccine demand and impact for emerging zoonotic pathogens
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Lerch, Anita, ten Bosch, Quirine A., L’Azou Jackson, Maïna, Bettis, Alison A., Bernuzzi, Mauro, Murphy, Georgina A. V., Tran, Quan M., Huber, John H., Siraj, Amir S., Bron, Gebbiena M., Elliott, Margaret, Hartlage, Carson S., Koh, Sojung, Strimbu, Kathyrn, Walters, Magdalene, Perkins, T. Alex, and Moore, Sean M.
- Subjects
viruses ,virus diseases - Abstract
Additional file 1: Table S1. Overview of data references. Table S2. Sizes of single reactive vaccination campaigns targeting the general population or healthcare workers (HCWs). SI Text. Sensitivity analysis and extended model limitations. Fig. S1. Spillover and reactive vaccination patterns for Lassa fever virus (LASV). Fig. S2. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV). Fig. S3. Spillover and reactive vaccination patterns for Nipah virus (NiV). Fig. S4. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV). Fig. S5. Vaccine regimens required for Lassa fever virus (LASV). Fig. S6. Vaccine regimens required for Middle Eastern respiratory virus (MERS-CoV). Fig. S7. Vaccine regimens required for Nipah virus (NiV). Fig. S8. Vaccine regimens required for Rift Valley fever virus (RVFV). Fig. S9. Vaccine regimens required to vaccinate healthcare workers for Lassa fever virus (LASV). Fig. S10. Vaccine regimens required to vaccinate healthcare workers for Middle Eastern respiratory virus (MERS-CoV). Fig. S11. Vaccine regimens required to vaccinate healthcare workers for Nipah virus (NiV). Fig. S12. Vaccine regimens required to vaccinate veterinarians for Rift Valley fever virus (RVFV). Fig. S13. Vaccination impact sensitivity analysis for LASV. Fig. S14. Vaccination impact sensitivity analysis for NiV. Fig. S15. Vaccination impact sensitivity analysis for RVFV. Fig. S16. Number of cases under different R0 assumptions. Fig. S17. Number of vaccine regimens required under different R0 assumptions. Fig. S18. Number of vaccine regimens required for healthcare workers (HCWs) under different R0 assumptions. Fig. S19. Number of cases averted by vaccinating the general population under different R0 assumptions. Fig. S20. Fraction of cases averted by vaccinating the general population under different R0 assumptions. Fig. S21. Number of cases averted per vaccine regimen administered to the general population under different R0 assumptions. Fig. S22. Number of cases averted per vaccine regimen administered to healthcare workers (HCWs) under different R0 assumptions. Fig. S23. Spillover and reactive vaccination patterns for Lassa fever virus (LASV) within adm1 catchment areas. Fig. S24. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV) within adm1 catchment areas. Fig. S25. Spillover and reactive vaccination patterns for Nipah virus (NiV) within adm1 catchment areas. Fig. S26. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV) within adm1 catchment areas. Fig. S27. Spillover and reactive vaccination patterns for Lassa fever virus (LASV) within adm1 hospital catchment areas. Fig. S28. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV) within adm1 hospital catchment areas. Fig. S29. Spillover and reactive vaccination patterns for Nipah virus (NiV) within adm1 hospital catchment areas. Fig. S30. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV) within adm1 hospital catchment areas. Fig. S31. Geographic distribution of spillover cases and reactive vaccination campaigns for adm1 catchment areas. Fig. S32. Geographic distribution of spillover cases and reactive vaccination campaigns for adm1 hospital catchment areas. Fig. S33. Annual cases and reactive vaccination impacts for adm1 catchment areas. Fig. S34. Annual cases and reactive vaccination impacts for adm1 hospital-based catchment areas.
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- 2022
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6. Targeting Neuroinflammation in Brain Cancer: Uncovering Mechanisms, Pharmacological Targets, and Neuropharmaceutical Developments
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Alghamri, Mahmoud S., primary, McClellan, Brandon L., additional, Hartlage, Carson S., additional, Haase, Santiago, additional, Faisal, Syed Mohd, additional, Thalla, Rohit, additional, Dabaja, Ali, additional, Banerjee, Kaushik, additional, Carney, Stephen V., additional, Mujeeb, Anzar A., additional, Olin, Michael R., additional, Moon, James J., additional, Schwendeman, Anna, additional, Lowenstein, Pedro R., additional, and Castro, Maria G., additional
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- 2021
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7. G-CSF secreted by mutant IDH1 glioma stem cells abolishes myeloid cell immunosuppression and enhances the efficacy of immunotherapy.
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Alghamri MS, McClellan BL, Avvari RP, Thalla R, Carney S, Hartlage CS, Haase S, Ventosa M, Taher A, Kamran N, Zhang L, Faisal SM, Núñez FJ, Garcia-Fabiani MB, Al-Holou WN, Orringer D, Hervey-Jumper S, Heth J, Patil PG, Eddy K, Merajver SD, Ulintz PJ, Welch J, Gao C, Liu J, Núñez G, Hambardzumyan D, Lowenstein PR, and Castro MG
- Abstract
Mutant isocitrate-dehydrogenase 1 ( mIDH1 ) synthesizes the oncometabolite 2-hydroxyglutarate (2HG), which elicits epigenetic reprogramming of the glioma cells’ transcriptome by inhibiting DNA and histone demethylases. We show that the efficacy of immune-stimulatory gene therapy (TK/Flt3L) is enhanced in mIDH1 gliomas, due to the reprogramming of the myeloid cells’ compartment infiltrating the tumor microenvironment (TME). We uncovered that the immature myeloid cells infiltrating the mIDH1 TME are mainly nonsuppressive neutrophils and preneutrophils. Myeloid cell reprogramming was triggered by granulocyte colony-stimulating factor (G-CSF) secreted by mIDH1 glioma stem/progenitor-like cells. Blocking G-CSF in mIDH1 glioma–bearing mice restores the inhibitory potential of the tumor-infiltrating myeloid cells, accelerating tumor progression. We demonstrate that G-CSF reprograms bone marrow granulopoiesis, resulting in noninhibitory myeloid cells within mIDH1 glioma TME and enhancing the efficacy of immune-stimulatory gene therapy.
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- 2021
- Full Text
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