No abstract

Autophagy is an intracellular degradation pathway that functions in protein and organelle turnover in response to starvation and cellular stress. Autophagy is initiated by the formation of a complex containing Beclin 1 (BECN1) and its binding partner Phosphoinositide-3-kinase, class 3 (PIK3C3). Recently, BECN1 deficiency was shown to enhance the pathology of a mouse model of Alzheimer Disease (AD). However, the mechanism by which BECN1 or autophagy mediate these effects are unknown. Here, we report that the levels of Amyloid precursor protein (APP) and its metabolites can be reduced through autophagy activation, indicating that they are a substrate for autophagy. Furthermore, we find that knockdown of Becn1 in cell culture increases the levels of APP and its metabolites. Accumulation of APP and APP C-terminal fragments (APP-CTF) are accompanied by impaired autophagosomal clearance. Pharmacological inhibition of autophagosomal-lysosomal degradation causes a comparable accumulation of APP and APP-metabolites in autophagosomes. Becn1 reduction in cell culture leads to lower levels of its binding partner Pik3c3 and increased presence of Microtubule-associated protein 1, light chain 3 (LC3). Overexpression of Becn1, on the other hand, reduces cellular APP levels. In line with these observations, we detected less BECN1 and PIK3C3 but more LC3 protein in brains of AD patients. We conclude that BECN1 regulates APP processing and turnover. BECN1 is involved in autophagy initiation and autophagosome clearance. Accordingly, BECN1 deficiency disrupts cellular autophagy and autophagosomal-lysosomal degradation and alters APP metabolism. Together, our findings suggest that autophagy and the BECN1-PIK3C3 complex regulate APP processing and play an important role in AD pathology.

BackgroundDelays to intra‐arterial therapy (IAT) lead to worse outcomes in stroke patients with proximal occlusions. Little is known regarding the magnitude of, and reasons for, these delays. In a pilot quality improvement (QI) project, we sought to examine and improve our door‐puncture times.Methods and ResultsFor anterior‐circulation stroke patients who underwent IAT, we retrospectively calculated in‐hospital time delays associated with various phases from patient arrival to groin puncture. We formulated and then implemented a process change targeted to the phase with the greatest delay. We examined the impact on time to treatment by comparing the pre‐ and post‐QI cohorts. One hundred forty‐six patients (93 pre‐ vs. 51 post‐QI) were analyzed. In the pre‐QI cohort (ie, sequential process), the greatest delay occurred from imaging to the neurointerventional (NI) suite (“picture‐suite”: median, 62 minutes; interquartile range [IQR], 40 to 82). A QI measure was instituted so that the NI team and anesthesiologist were assembled and the suite set up in parallel with completion of imaging and decision making. The post‐QI (ie, parallel process) median picture‐to‐suite time was 29 minutes (IQR, 21 to 41; P<0.0001). There was a 36‐minute reduction in median door‐to‐puncture time (143 vs. 107 minutes; P<0.0001). Parallel workflow and presentation during work hours were independent predictors of shorter door‐puncture times.ConclusionsIn‐hospital delays are a major obstacle to timely IAT. A simple approach for achieving substantial time savings is to mobilize the NI and anesthesia teams during patient evaluation and treatment decision making. This parallel workflow resulted in a >30‐minute (25%) reduction in median door‐to‐puncture times.

Background— Comprehensive stroke centers allow for regionalization of subspecialty stroke care. Efficacy of endovascular treatments, however, may be limited by delays in patient transfer. Our goal was to identify where these delays occurred and to assess the impact of such delays on patient outcome. Methods and Results— This was a retrospective study evaluating patients treated with endovascular therapy from November 2010 to July 2012 at our institution. We compared patients transferred from outside hospitals with locally treated patients with respect to demographics, imaging, and treatment times. Good outcomes, as defined by 90-day modified Rankin Scale scores of 0 to 2, were analyzed by transfer status as well as time from initial computed tomography to groin puncture (“picture-to-puncture” time). A total of 193 patients were analyzed, with a mean age of 65.8±14.5 years and median National Institutes of Health Stroke Scale score of 19 (interquartile range, 15–23). More than two thirds of the patients (132 [68%]) were treated from referring facilities. Outside transfers were noted to have longer picture-to-puncture times (205 minutes [interquartile range, 162–274] versus 89 minutes [interquartile range, 70–119]; P <0.001), which was attributable to the delays in transfer. This corresponded to fewer patients with favorable Alberta Stroke Program Early CT Scores on preprocedural computed tomographic imaging (Alberta Stroke Program Early CT Scores >7: 50% versus 76%; P <0.001) and significantly worse clinical outcomes (29% versus 51%; P =0.003). In a logistic regression model, picture-to-puncture times were independently associated with good outcomes (odds ratio, 0.994; 95% confidence interval, 0.990–0.999; P =0.009). Conclusions— Delays in picture-to-puncture times for interhospital transfers reduce the probability of good outcomes among treated patients. Strategies to reduce such delays herald an opportunity for hospitals to improve patient outcomes.