Covalent targeting of the vacuolar H+-ATPase activates autophagy via mTORC1 inhibition.

Autophagy is a lysosomal degradation pathway that eliminates aggregated proteins and damaged organelles to maintain cellular homeostasis. A major route for activating autophagy involves inhibition of the mTORC1 kinase, but current mTORC1-targeting compounds do not allow complete and selective mTORC1 blockade. Here, we have coupled screening of a covalent ligand library with activity-based protein profiling to discover EN6, a small-molecule in vivo activator of autophagy that covalently targets cysteine 277 in the ATP6V1A subunit of the lysosomal v-ATPase, which activates mTORC1 via the Rag guanosine triphosphatases. EN6-mediated ATP6V1A modification decouples the v-ATPase from the Rags, leading to inhibition of mTORC1 signaling, increased lysosomal acidification and activation of autophagy. Consistently, EN6 clears TDP-43 aggregates, a causative agent in frontotemporal dementia, in a lysosome-dependent manner. Our results provide insight into how the v-ATPase regulates mTORC1, and reveal a unique approach for enhancing cellular clearance based on covalent inhibition of lysosomal mTORC1 signaling

Screening of High Temperature Organic Materials for Future Stirling Convertors

Along with major advancement of Stirling-based convertors, high temperature organics are needed to develop future higher temperature convertors for much improved efficiencies as well as to improve the margin of reliability for the current SOA (State-of-the-Art) convertors. The higher temperature capabilities would improve robustness of the convertors and also allow them to be used in additional missions, particularly ones that require a Venus flyby for a gravity assist. Various organic materials have been employed as essential components in the convertor for their unique properties and functions such as bonding, potting, sealing, thread locking, insulation, and lubrication. The Stirling convertor radioisotope generators have been developed for potential future space applications including Lunar/Mars surface power or a variety of spacecraft and vehicles, especially with a long mission cycle, sometimes up to 17 years, such as deep space exploration. Thus, performance, durability, and reliability of the organics should be critically evaluated in terms of every possible material structure-process-service environment relations based on the potential mission specifications. The initial efforts in screening the high temperature candidates focused on the most susceptible organics, such as adhesive, potting compound, O-ring, shrink tubing, and thread locker materials in conjunction with commercially available materials. More systematic and practical test methodologies that were developed and optimized based on the extensive organic evaluations and validations performed for various Stirling convertor types were employed to determine thermal stability, outgassing, and material compatibility of the selected organic candidates against their functional requirements. Processing and fabrication conditions and procedures were also optimized. This report presents results of the three-step candidate evaluation processes, their application limitations, and the final selection recommendations

FLEET: Butterfly Estimation from a Bipartite Graph Stream

We consider space-efficient single-pass estimation of the number of butterflies, a fundamental bipartite graph motif, from a massive bipartite graph stream where each edge represents a connection between entities in two different partitions. We present a space lower bound for any streaming algorithm that can estimate the number of butterflies accurately, as well as FLEET, a suite of algorithms for accurately estimating the number of butterflies in the graph stream. Estimates returned by the algorithms come with provable guarantees on the approximation error, and experiments show good tradeoffs between the space used and the accuracy of approximation. We also present space-efficient algorithms for estimating the number of butterflies within a sliding window of the most recent elements in the stream. While there is a significant body of work on counting subgraphs such as triangles in a unipartite graph stream, our work seems to be one of the few to tackle the case of bipartite graph streams.Comment: This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Seyed-Vahid Sanei-Mehri, Yu Zhang, Ahmet Erdem Sariyuce and Srikanta Tirthapura. "FLEET: Butterfly Estimation from a Bipartite Graph Stream". The 28th ACM International Conference on Information and Knowledge Managemen