The lipid sulfatide is a novel myelin-associated inhibitor of CNS axon outgrowth.

CNS myelin is strongly inhibitory to growing axons and is thought to be a major contributor to CNS axon regenerative failure. Although a number of proteins present in myelin, including Nogo, MAG, and oligodendrocyte-myelin glycoprotein (OMgp), have been identified as myelin-associated inhibitors, studies of mice lacking these genes suggest that additional inhibitors present in CNS myelin remain to be identified. Here we have investigated the hypothesis that myelin lipids contribute to CNS regenerative failure. We identified sulfatide, a major constituent of CNS myelin, as a novel myelin-associated inhibitor of neurite outgrowth. Sulfatide, but not galactocerebroside or ceramide, strongly inhibited the neurite outgrowth of retinal ganglion cells (RGCs) when used as a purified lipid substrate. The mechanism involved in sulfatide-mediated inhibition may share features with other known inhibitors, because the Rho inhibitor C3 transferase lessened these effects. Myelin in which sulfatide was lacking or blocked using specific antibodies was significantly less inhibitory to RGC neurite outgrowth in vitro than was wild-type myelin, indicating that sulfatide is a major component of the inhibitory activity of CNS myelin. Mice unable to make sulfatide did not regenerate RGC axons more robustly after optic nerve crush than wild-type littermates under normal conditions but did exhibit a small but significant enhancement in the extent of zymosan-induced regeneration. These results demonstrate that specific lipids can powerfully inhibit axon growth, identify sulfatide as a novel myelin-associated axon growth inhibitor, and provide evidence that sulfatide inhibition contributes to axon regenerative failure in vivo.

Validation of a Mortality Composite Score in the Real-World Setting: Overcoming Source-Specific Disparities and Biases.

PURPOSE: This study tested whether a composite mortality score could overcome gaps and potential biases in individual real-world mortality data sources. Complete and accurate mortality data are necessary to calculate important outcomes in oncology, including overall survival. However, in the United States, there is not a single complete and broadly applicable mortality data source. It is further likely that available data sources are biased in their coverage of sex, race, age, and socioeconomic status (SES). METHODS: Six individual real-world data sources were combined to develop a high-quality composite mortality score. The composite score was benchmarked against the gold standard for mortality data, the National Death Index. Subgroup analyses were then conducted to evaluate the completeness and accuracy by sex, race, age, and SES. RESULTS: The composite mortality score achieved a sensitivity of 94.9% and specificity of 92.8% compared with the National Death Index, with concordance within 1 day of 98.6%. Although some individual data sources show significant coverage gaps related to sex, race, age, and SES, the composite score maintains high sensitivity (84.6%-96.1%) and specificity (77.9%-99.2%) across subgroups. CONCLUSION: A composite score leveraging multiple scalable sources for mortality in the real-world setting maintained strong sensitivity, specificity, and concordance, including across sex, race, age, and SES subgroups.