Activity-dependent dynamics and sequestration of proteasomes in dendritic spines

The regulated degradation of proteins by the ubiquitin proteasome pathway is emerging as an important modulator of synaptic function and plasticity. The proteasome is a large, multi-subunit cellular machine that recognizes, unfolds and degrades target polyubiquitinated proteins. Here we report NMDA (N-methyl-D-aspartate) receptor-dependent redistribution of proteasomes from dendritic shafts to synaptic spines upon synaptic stimulation, providing a mechanism for local protein degradation. Using a proteasome-activity reporter and local perfusion, we show that synaptic stimulation regulates proteasome activity locally in the dendrites. We used restricted photobleaching of individual spines and dendritic shafts to reveal the dynamics that underlie proteasome sequestration, and show that activity modestly enhances the entry rate of proteasomes into spines while dramatically reducing their exit rate. Proteasome sequestration is persistent, reflecting an association with the actin-based cytoskeleton. Together, our data indicate that synaptic activity can promote the recruitment and sequestration of proteasomes to locally remodel the protein composition of synapses.     

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10?12) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10?11) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10??) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10?11) and a tag SNP for NAT2 acetylation status (P = 4 × 10?11), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.     

Optimal forecast error as an unbiased estimator of abnormal return: A proposition

In the event studies, the accuracy of the abnormal returns assessment is highly dependent on the accuracy of the preceding expected return model. If the expected return model is inadequate, there is a possibility that a part of returns is labeled as abnormal returns even though they are not. Currently, we have a variety of options to set up an expected return model. To obtain unbiased abnormal returns, one should pay attention to the performance of the expected return model. In this research, we propose that the optimal forecast lemma can be consulted beforehand so that minimizing the optimal forecast error in the expected return model will yield unbiased abnormal returns. We introduce and prove a proposition that the optimal forecast error is an unbiased estimator for abnormal return. The proposition induces assessing the performance of abnormal return estimation to preemptively evaluate the out-sample forecast accuracy of the model employed. In an illustrative dataset, we examine various models. The approach requires preliminary computational effort; however, it is useful for accurately obtaining the abnormal return predictions.