IntroductionDiabetic ketoacidosis (DKA) causes acute and chronic neuroinflammation that may contribute to cognitive decline in patients with type 1 diabetes. We evaluated the effects of agents that reduce neuroinflammation (triarylmethane-34 (TRAM-34) and minocycline) during and after DKA in a rat model.Research design and methodsJuvenile rats with DKA were treated with insulin and saline, either alone or in combination with TRAM-34 (40 mg/kg intraperitoneally twice daily for 3 days, then daily for 4 days) or minocycline (45 mg/kg intraperitoneally daily for 7 days). We compared cytokine and chemokine concentrations in brain tissue lysates during DKA among the three treatment groups and in normal controls and diabetic controls (n=9–15/group). We also compared brain inflammatory mediator levels in these same groups in adult diabetic rats that were treated for DKA as juveniles.ResultsBrain tissue concentrations of chemokine (C-C) motif ligand (CCL)3, CCL5 and interferon (IFNγ) were increased during acute DKA, as were brain cytokine composite scores. Both treatments reduced brain inflammatory mediator levels during acute DKA. TRAM-34 predominantly reduced chemokine concentrations (chemokine (C-X-C) motif ligand (CXCL-1), CCL5) whereas minocycline had broader effects, (reducing CXCL-1, tumor necrosis factor (TNFα), IFNγ, interleukin (IL) 2, IL-10 and IL-17A). Brain inflammatory mediator levels were elevated in adult rats that had DKA as juveniles, compared with adult diabetic rats without previous DKA, however, neither TRAM-34 nor minocycline treatment reduced these levels.ConclusionsThese data demonstrate that both TRAM-34 and minocycline reduce acute neuroinflammation during DKA, however, treatment with these agents for 1 week after DKA does not reduce long-term neuroinflammation.

Consider a Bellman-Harris [1] age dependent branching process. At t = 0, a cell is born, has lifetime distribution function G(t), G(0) = 0, assumed to be absolutely continuous with density g(t). At the death of the cell, k new cells are born, each proceeding independently and identically as the parent cell, and independent of past history. Denote by h(s) = Σk=0∞pksk and suppose h(1) ≡ m, and assume h”(1) < ∞. Additional assumptions will be added as required.

Consider a Bellman-Harris [1] age dependent branching process. At t = 0, a cell is born, has lifetime distribution function G(t), G(0) = 0, assumed to be absolutely continuous with density g(t). At the death of the cell, k new cells are born, each proceeding independently and identically as the parent cell, and independent of past history. Denote by h(s) = Σ k=0 ∞ pk s k and suppose h(1) ≡ m, and assume h”(1) &lt; ∞. Additional assumptions will be added as required.