Retromer binds the FANSHY sorting motif in SorLA to regulate amyloid precursor protein sorting and processing

sorLA is a sorting receptor for amyloid precursor protein (APP) genetically linked to Alzheimer's disease (AD). Retromer, an adaptor complex in the endosome-to-Golgi retrieval pathway, has been implicated in APP transport because retromer deficiency leads to aberrant APP sorting and processing and levels of retromer proteins are altered in AD. Here we report that sorLA and retromer functionally interact in neurons to control trafficking and amyloidogenic processing of APP. We have identified a sequence (FANSHY) in the cytoplasmic domain of sorLA that is recognized by the VPS26 subunit of the retromer complex. Accordingly, we characterized the interaction between the retromer complex and sorLA and determined the role of retromer on sorLA-dependent sorting and processing of APP. Mutations in the VPS26 binding site resulted in receptor redistribution to the endosomal network, similar to the situation seen in cells with VPS26 knockdown. The sorLA mutant retained APP-binding activity but, as opposed to the wild-type receptor, misdirected APP into a distinct non-Golgi compartment, resulting in increased amyloid processing. In conclusion, our data provide a molecular link between reduced retromer expression and increased amyloidogenesis as seen in patients with sporadic AD

Fin Whale Sighting North of Kaua'i, Hawai'i

A rare fin whale (Balaenoptera physalus) sighting occurred on 26 February 1994 during an aerial survey of waters north of the Hawaiian island of Kaua'i. The sighting occurred ca. 24 nm north of Makaha Point, at 220 31.5' N, 1590 44.5' W. The fin whale was accompanied by an adult humpback whale (Megaptera novaeangliae) during the entire 25 min of observation. Fin whales are not unknown in Hawaiian waters, but the most recent confirmed sighting on record for Hawaiian waters was 16 February 1979

Predictive modeling of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands

Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood