Browsing by Subject "Organ damage"

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    Evaluating Thera-101 as a Low-Volume Resuscitation Fluid in a Model of Polytrauma
    (MDPI, 2022-10-21) Shah, Jessica Stukel; Macaitis, Joseph; Lundquist, Bridney; Johnstone, Brian; Coleman, Michael; Jefferson, Michelle A.; Glaser, Jacob; Rodriguez, Annette R.; Cardin, Sylvain; Wang, Heuy-Ching; Burdette, Alexander; Emergency Medicine, School of Medicine
    Traumatic brain injury (TBI) and hemorrhage remain challenging to treat in austere conditions. Developing a therapeutic to mitigate the associated pathophysiology is critical to meet this treatment gap, especially as these injuries and associated high mortality are possibly preventable. Here, Thera-101 (T-101) was evaluated as low-volume resuscitative fluid in a rat model of TBI and hemorrhage. The therapeutic, T-101, is uniquely situated as a TBI and hemorrhage intervention. It contains a cocktail of proteins and microvesicles from the secretome of adipose-derived mesenchymal stromal cells that can act on repair and regenerative mechanisms associated with poly-trauma. T-101 efficacy was determined at 4, 24, 48, and 72 h post-injury by evaluating blood chemistry, inflammatory chemo/cytokines, histology, and diffusion tensor imaging. Blood chemistry indicated that T-101 reduced the markers of liver damage to Sham levels while the levels remained elevated with the control (saline) resuscitative fluid. Histology supports the potential protective effects of T-101 on the kidneys. Diffusion tensor imaging showed that the injury caused the most damage to the corpus callosum and the fimbria. Immunohistochemistry suggests that T-101 may mitigate astrocyte activation at 72 h. Together, these data suggest that T-101 may serve as a potential field deployable low-volume resuscitation therapeutic.
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    Top-down Mass Spectrometry Analysis of Human Serum Autoantibody Antigen-Binding Fragments
    (Springer Nature, 2019-02-20) Wang, Zhe; Liu, Xiaowen; Muther, Jennifer; James, Judith A.; Smith, Kenneth; Wu, Si; BioHealth Informatics, School of Informatics and Computing
    Detecting autoimmune diseases at an early stage is crucial for effective treatment and disease management to slow disease progression and prevent irreversible organ damage. In many autoimmune diseases, disease-specific autoantibodies are produced by B cells in response to soluble autoantigens due to defects in B cell tolerance mechanisms. Autoantibodies accrue early in disease development, and several are so disease-specific they serve as classification criteria. In this study, we established a high-throughput, sensitive, intact serum autoantibody analysis platform based on the optimization of a one dimensional ultra-high-pressure liquid chromatography top-down mass spectrometry platform (1D UPLC-TDMS). This approach has been successfully applied to a 12 standard monoclonal antibody antigen-binding fragment (Fab) mixture, demonstrating the feasibility to separate and sequence intact antibodies with high sequence coverage and high sensitivity. We then applied the optimized platform to characterize total serum antibody Fabs in a systemic lupus erythematosus (SLE) patient sample and compared it to healthy control samples. From this analysis, we show that the SLE sample has many dominant antibody Fab-related mass features unlike the healthy controls. To our knowledge, this is the first top-down demonstration of serum autoantibody pool analysis. Our proposed approach holds great promise for discovering novel serum autoantibody biomarkers that are of interest for diagnosis, prognosis, and tolerance induction, as well as improving our understanding of pathogenic autoimmune processes.