Cytokinesis, the physical division of one cell into two, is powered by constriction of an actomyosin contractile ring. It has long been assumed that all animal cells divide by a similar molecular mechanism, but growing evidence suggests that cytokinetic regulation in individual cell types has more variation than previously realized. In the four-cell Caenorhabditis elegans embryo, each blastomere has a distinct cell fate, specified by conserved pathways. Using fast-acting temperature-sensitive mutants and acute drug treatment, we identified cell-type-specific variation in the cytokinetic requirement for a robust forminCYK-1-dependent filamentous-actin (F-actin) cytoskeleton. In one cell (P2), this cytokinetic variation is cell-intrinsically regulated, whereas in another cell (EMS) this variation is cell-extrinsically regulated, dependent on both SrcSRC-1 signaling and direct contact with its neighbor cell, P2. Thus, both cell-intrinsic and -extrinsic mechanisms control cytokinetic variation in individual cell types and can protect against division failure when the contractile ring is weakened.

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INTRODUCTION Treatment for intracerebral hemorrhage (ICH) has been largely medical after negative findings from trials evaluating open craniotomy for hematoma evacuation. Location of hemorrhage has always been a determinant of outcome in ICH. This has ramifications for outcomes after minimally invasive (MIS) evacuation. We present analysis of ICH outcome after endoscopic evacuation stratified by hemorrhage location. METHODS Minimally invasive endoscopic ICH evacuation was performed on patients with supratentorial ICH who fit previously published clinical criteria including age = 18, National Institutes of Health Stroke Scale (NIHSS) = 6, hematoma volume = 15, and baseline modified Rankin Score (mRS) = 3 with a computed tomography angiography (CTA) negative for vascular malformation. Retrospective review was performed on patients who were treated in a single health system from December 2015 to August 2018. Hematoma location was stratified as deep or lobar. Univariate analysis and multivariate logistic regression were performed on demographic, radiographic, and clinical outcomes including the location variable with 6 mo mRS as the primary outcome measure. RESULTS Univariate analysis revealed patients with lobar hemorrhage had significantly better initial admission Glasgow Coma Scale (GCS) (11.7 vs 8.9, P < .0001) and NIHSS score (13.7 vs 19.6, P < .0001) but significantly higher preoperative volume (64.1 vs 41.4, P = .001). Those with lobar hemorrhage also had significantly lower neurosurgical and hospital length of stay (8.1 vs 12.9, P = .003 and 16.9 vs 29.0, P = .02, respectively) and higher rate of 6 mo functional independence as defined by mRS 0 to 3 (68.6% vs 31.2%, P = .001). Multivariate analysis showed lobar location was a significant predictor of functional independence at 6 mo (OR 12.8, P = .003). CONCLUSION In our experience, lobar hemorrhage is a predictor of good outcome after endoscopic ICH evacuation. Current and future trials may benefit from stricter patient selection and further studies are needed to confirm the effect of hemorrhage location on outcome.

INTRODUCTION Intracranial aneurysms (IA) occur in approximately 2% of the general population and are the leading cause for spontaneous subarachnoid hemorrhage (SAH). Recent studies have shown that inflammatory and cell adhesion molecules are associated with the formation and progression of aneurysmal growth. In this study, we utilized proteomic data from patients with known intracranial aneurysms and age, sex, and comorbidity matched controls to identify a proteomic signature that is highly consistent with the presence of an intracranial aneurysm. METHODS A total of 56 patients were prospectively enrolled in this study, 28 of which had unruptured intracranial aneurysms. Protein was isolated from peripheral blood samples and sent for Proseek multiplex immunoassay processing. Of the 92 analytes in the selected Olink Inflammatory Panel, 70 had variable expression across our cohort and were included for analyses. Multivariate regression models were constructed to predict the presence of an aneurysm. Support Vector Machine (SVM) learning and naïve Bayes algorithms were developed with an 80/20: training/test data separation to determine the precision and reliability of the proteomic signature. RESULTS Of the 28 patients, 82.1% (n = 23) were female, with a mean aneurysm size of 8.9 mm. Logistic regression analysis revealed 8 highly sensitive analytes that were predictive of the presence of an aneurysm at a threshold of P < .0001. The support vector machine learning and naïve Bayes classification algorithms performed well with a positive predictive value of 100% and 85.7% and a sensitivity of 100% and 100%, respectively (Brier score = 0.032, 0.083). CONCLUSION This study leveraged individualized data from patients with IA to identify specific protein analytes that predict the presence of an aneurysm. To our knowledge this is the first proteomic signature developed for the purpose of identifying IA’s prior to rupture. Future research with increased sample size will allow for the validation and strengthening of this predictive signature.

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