Summary The functional and molecular similarities and distinctions between human and murine astrocytes are poorly understood. Here we report the development of an immunopanning method to acutely purify astrocytes from fetal, juvenile, and adult human brains, and to maintain these cells in serum-free cultures. We found that human astrocytes have similar abilities to murine astrocytes in promoting neuronal survival, inducing functional synapse formation, and engulfing synaptosomes. In contrast to existing observations in mice, we found that mature human astrocytes respond robustly to glutamate. We next performed RNA-sequencing of healthy human astrocytes along with astrocytes from epileptic and tumor foci, and compared these to human neurons, oligodendrocytes, microglia, and endothelial cells. With these profiles, we identified novel human-specific astrocyte genes, and discovered a transcriptome-wide transformation between astrocyte precursor cells and mature post-mitotic astrocytes. These data represent some of the first cell type-specific molecular profiles of the healthy and diseased human brain.

SignificanceThe brain comprises an immense number of cells and cellular connections. We describe the first, to our knowledge, single cell whole transcriptome analysis of human adult cortical samples. We have established an experimental and analytical framework with which the complexity of the human brain can be dissected on the single cell level. Using this approach, we were able to identify all major cell types of the brain and characterize subtypes of neuronal cells. We observed changes in neurons from early developmental to late differentiated stages in the adult. We found a subset of adult neurons which express major histocompatibility complex class I genes and thus are not immune privileged.

Given the natural history of these inaccessible lesions and the high risks of surgery, we conclude that heavy-charged-particle radiation is an effective therapy for symptomatic, surgically inaccessible intracranial arteriovenous malformations. The current procedure has two disadvantages: a prolonged latency period before complete obliteration of the vascular lesion and a small risk of serious neurologic complications.

OBJECTIVEThe ability to assess the risk of adverse events based on known patient factors and comorbidities would provide more effective preoperative risk stratification. Present risk assessment in spine surgery is limited. An adverse event prediction tool was developed to predict the risk of complications after spine surgery and tested on a prospective patient cohort.METHODSThe spinal Risk Assessment Tool (RAT), a novel instrument for the assessment of risk for patients undergoing spine surgery that was developed based on an administrative claims database, was prospectively applied to 246 patients undergoing 257 spinal procedures over a 3-month period. Prospectively collected data were used to compare the RAT to the Charlson Comorbidity Index (CCI) and the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator. Study end point was occurrence and type of complication after spine surgery.RESULTSThe authors identified 69 patients (73 procedures) who experienced a complication over the prospective study period. Cardiac complications were most common (10.2%). Receiver operating characteristic (ROC) curves were calculated to compare complication outcomes using the different assessment tools. Area under the curve (AUC) analysis showed comparable predictive accuracy between the RAT and the ACS NSQIP calculator (0.670 [95% CI 0.60–0.74] in RAT, 0.669 [95% CI 0.60–0.74] in NSQIP). The CCI was not accurate in predicting complication occurrence (0.55 [95% CI 0.48–0.62]). The RAT produced mean probabilities of 34.6% for patients who had a complication and 24% for patients who did not (p = 0.0003). The generated predicted values were stratified into low, medium, and high rates. For the RAT, the predicted complication rate was 10.1% in the low-risk group (observed rate 12.8%), 21.9% in the medium-risk group (observed 31.8%), and 49.7% in the high-risk group (observed 41.2%). The ACS NSQIP calculator consistently produced complication predictions that underestimated complication occurrence: 3.4% in the low-risk group (observed 12.6%), 5.9% in the medium-risk group (observed 34.5%), and 12.5% in the high-risk group (observed 38.8%). The RAT was more accurate than the ACS NSQIP calculator (p = 0.0018).CONCLUSIONSWhile the RAT and ACS NSQIP calculator were both able to identify patients more likely to experience complications following spine surgery, both have substantial room for improvement. Risk stratification is feasible in spine surgery procedures; currently used measures have low accuracy.