The Neuronal EGF-Related Gene Nell2 Interacts with Macf1 and Supports Survival of Retinal Ganglion Cells after Optic Nerve Injury

Nell2 is a neuron-specific protein containing six epidermal growth factor-like domains. We have identified Nell2 as a retinal ganglion cell (RGC)-expressed gene by comparing mRNA profiles of control and RGC-deficient rat retinas. The aim of this study was to analyze Nell2 expression in wild-type and optic nerve axotomized retinas and evaluate its potential role in RGCs. Nell2-positive in situ and immunohistochemical signals were localized to irregularly shaped cells in the ganglion cell layer (GCL) and colocalized with retrogradely-labeled RGCs. No Nell2-positive cells were detected in 2 weeks optic nerve transected (ONT) retinas characterized with approximately 90% RGC loss. RT-PCR analysis showed a dramatic decrease in the Nell2 mRNA level after ONT compared to the controls. Immunoblot analysis of the Nell2 expression in the retina revealed the presence of two proteins with approximate MW of 140 and 90 kDa representing glycosylated and non-glycosylated Nell2, respectively. Both products were almost undetectable in retinal protein extracts two weeks after ONT. Proteome analysis of Nell2-interacting proteins carried out with MALDI-TOF MS (MS) identified microtubule-actin crosslinking factor 1 (Macf1), known to be critical in CNS development. Strong Macf1 expression was observed in the inner plexiform layer and GCL where it was colocalizied with Thy-1 staining. Since Nell2 has been reported to increase neuronal survival of the hippocampus and cerebral cortex, we evaluated the effect of Nell2 overexpression on RGC survival. RGCs in the nasal retina were consistently more efficiently transfected than in other areas (49% vs. 13%; n = 5, p<0.05). In non-transfected or pEGFP-transfected ONT retinas, the loss of RGCs was approximately 90% compared to the untreated control. In the nasal region, Nell2 transfection led to the preservation of approximately 58% more cells damaged by axotomy compared to non-transfected (n = 5, p<0.01) or pEGFP-transfected controls (n = 5, p<0.01)

ClusterFetch: A lightweight prefetcher that responds to intensive disk read patterns

Application launch and loading times are important determinants of user experience in the personal computing environment. Since these delays largely depend on the performance of secondary storage, they can be reduced by prefetching disk blocks. However, existing prefetching schemes for general workloads incur a significant overhead in analyzing correlations between blocks so as to choose the blocks to prefetch, and, more significantly, these analyses lack accuracy. We propose a lightweight prefetcher called ClusterFetch which records the sequences of I/O requests that are triggered by file requests during launch and loading. When the same application is run again, the disk blocks that correspond to the stored sequences of I/O requests are prefetched when the related files are opened. Experimental results show that ClusterFetch can reduce application launch times by up to 30.9%, and loading times by up to 15.9%

ClusterFetch: A lightweight prefetcher for general workloads

Application loading times can be reduced by prefetching disk blocks into the buffer cache. Existing prefetching schemes for general workloads suffer from significant overheads and low accuracy. ClusterFetch is a lightweight prefetcher that identifies continuous sequences of I/O requests and identifies the files that trigger them. The next time that the same files are opened, the corresponding disk blocks are prefetched. In experiments, ClusterFetch reduced the launch time, by which we refer to the latency that occurs when a programfirst runs, by 15.2 to 30.9%, and loading times, meaning the delays that are incurred while additional data is loaded from the disk during program execution, by 15.9%. Copyright &amp;copy; 2015 AC