For many decades, malaria has remained an increasingly important parasitic disease of human beings. While most infections are manageable, poor prognosis is often marked by respiratory distress due to both inflammation and damage to the alveolar membranes in the lung. It is surprising, then, that a coupling of such an infection with the Influenza A virus (IAV), which is involved in the progressive degradation of the lung epithelia and in the related development of pneumonia and ARDS (acute respiratory distress syndrome), produces a phenotypic survival curve depicting greater survival for co-infected mice. A component of the flu immune response pathway, thus, seems to play a role in suppressing the malaria-related symptoms and contributing to a later onset of fatality. The elevated levels of proinflammatory cytokines and other inflammatory mediators during this flu infection play a significant role in expanding the recruitment and expansion of MDSCs. MDSCs, or Myeloid-derived suppressor cells, are a group of immunosuppressive cells that can modulate antigen specific immune responses during acute and chronic inflammatory conditions, including infection by a Influenza-A virus (INV). They are a critical component of INV's quick-acting, innate response and play a significant role in suppressing T-cell proliferation and activity . Lab data I collected in the past month show greater frequencies of MDSC's in the lung tissue of INV (X31)-infected mice, as opposed to the control ""naive"" mice. The fatal symptoms of the malaria infection are often a result of the hyperactivity of the immune response, wherein healthy cells are often mistaken for and targeted by the body's own immune system. The activity of MDSCs, which work to suppress such responses, thus serves as a plausible explanation for the greater survival depicted in co-infected mice. In a world where both flu and malaria have held potent roles in controlling human-civilized life, exploring MDSCs as potential mediators between the two may lead to a better understanding of how multiple infections interact.