No abstract

Laminins are extracellular matrix proteins that participate in neuronal development, survival, and regeneration. During excitotoxin challenge in the mouse hippocampus, neuron interaction with laminin-10 (alpha5,beta1,gamma1) protects against neuronal death. To investigate how laminin is involved in neuronal viability, we infused laminin-1 (alpha1,beta1,gamma1) into the mouse hippocampus. This infusion specifically disrupted the endogenous laminin layer. This disruption was at least partially due to the interaction of the laminin-1 gamma1 chain with endogenous laminin-10, because infusion of anti-laminin gamma1 antibody had the same effect. The disruption of the laminin layer by laminin-1 1) did not require the intact protein because infusion of plasmin-digested laminin-1 gave similar results; 2) was posttranscriptional, because there was no effect on laminin mRNA expression; and 3) occurred in both tPA(-/-) and plasminogen(-/-) mice, indicating that increased plasmin activity was not responsible. Finally, although tPA(-/-) mice are normally resistant to excitotoxin-induced neurodegeneration, disruption of the endogenous laminin layer by laminin-1 or anti-laminin gamma1 antibody renders the tPA(-/-) hippocampal neurons sensitive to kainate. These results demonstrate that neuron interactions with the deposited matrix are not necessarily recapitulated by interactions with soluble components and that the laminin matrix is a dynamic structure amenable to modification by exogenous molecules.

Neuronal damage in the CNS after excitotoxic injury is correlated with blood-brain barrier (BBB) breakdown. We have used a glutamate analog injection model and genetically altered mice to investigate the relationship between these two processes in the hippocampus. Our results show that BBB dysfunction occurs too late to initiate neurodegeneration. In addition, plasma infused directly into the hippocampus is not toxic and does not affect excitotoxin-induced neuronal death. To test plasma protein recruitment in neuronal degeneration, we used plasminogen-deficient (plg(-/-)) mice, which are resistant to excitotoxin-induced degeneration. Plasminogen is produced in the hippocampus and is also present at high levels in plasma, allowing us to determine the contribution of each source to cell death. Intrahippocampal delivery of plasminogen to plg(-/-) mice restored degeneration to wild-type levels, but intravenous delivery of plasminogen did not. Finally, although the neurons in plg(-/-) mice do not die after excitotoxin injection, BBB breakdown occurs to a similar extent as in wild-type mice, indicating that neuronal death is not necessary for BBB breakdown. These results indicate that excitotoxin-induced neuronal death and BBB breakdown are separable events in the hippocampus.

Background: Despite documented benefits of diabetes technology in managing type 1 diabetes, inequities persist in the use of these devices. Provider bias may be a driver of inequities, but the evidence is limited. Therefore, we aimed to examine the role of race/ethnicity and insurance-mediated provider implicit bias in recommending diabetes technology. Method: We recruited 109 adult and pediatric diabetes providers across 7 U.S. endocrinology centers to complete an implicit bias assessment composed of a clinical vignette and ranking exercise. Providers were randomized to receive clinical vignettes with differing insurance and patient names as proxy for Racial–Ethnic identity. Bias was identified if providers: (1) recommended more technology for patients with an English name (Racial–Ethnic bias) or private insurance (insurance bias), or (2) Race/Ethnicity or insurance was ranked high (Racial–Ethnic and insurance bias, respectively) in recommending diabetes technology. Provider characteristics were analyzed using descriptive statistics and multivariate logistic regression. Result: Insurance-mediated implicit bias was common in our cohort ( n = 66, 61%). Providers who were identified to have insurance-mediated bias had greater years in practice (5.3 ± 5.3 years vs. 9.3 ± 9 years, P = 0.006). Racial–Ethnic-mediated implicit bias was also observed in our study ( n = 37, 34%). Compared with those without Racial–Ethnic bias, providers with Racial–Ethnic bias were more likely to state that they could recognize their own implicit bias (89% vs. 61%, P = 0.001). Conclusion: Provider implicit bias to recommend diabetes technology was observed based on insurance and Race/Ethnicity in our pediatric and adult diabetes provider cohort. These data raise the need to address provider implicit bias in diabetes care.