AMPK- mediated formation of stress granules is required for dietary restriction- induced longevity in Caenorhabditis elegans

Stress granules (SGs) are nonmembranous organelles that are dynamically assembled and disassembled in response to various stressors. Under stressed conditions, polyadenylated mRNAs and translation factors are sequestrated in SGs to promote global repression of protein synthesis. It has been previously demonstrated that SG formation enhances cell survival and stress resistance. However, the physiological role of SGs in organismal aging and longevity regulation remains unclear. In this study, we used TIAR- 1::GFP and GTBP- 1::GFP as markers to monitor the formation of SGs in Caenorhabditis elegans. We found that, in addition to acute heat stress, SG formation could also be triggered by dietary changes, such as starvation and dietary restriction (DR). We found that HSF- 1 is required for the SG formation in response to acute heat shock and starvation but not DR, whereas the AMPK- eEF2K signaling is required for starvation and DR- induced SG formation but not heat shock. Moreover, our data suggest that this AMPK- eEF2K pathway- mediated SG formation is required for lifespan extension by DR, but dispensable for the longevity by reduced insulin/IGF- 1 signaling. Collectively, our findings unveil a novel role of SG formation in DR- induced longevity.In addition to heat stress, starvation and dietary restriction (DR) can activate stress granule (SG) formation in Caenorhabditis elegans. HSF- 1 and AMPK are two key regulators for the SG formations. HSF- 1 is required for the SG formation in response to acute heat shock and starvation but not DR, whereas the AMPK- eEF2K pathway is required for starvation and DR- induced SG formation but not heat shock. Furthermore, AMPK- mediated SG formation contributes to DR- induced longevity.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/1/acel13157-sup-0008-Figurelegends.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/2/acel13157-sup-0001-FigS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/3/acel13157-sup-0006-TableS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/4/acel13157-sup-0007-TableS2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/5/acel13157-sup-0005-FigS5.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/6/acel13157-sup-0003-FigS3.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/7/acel13157.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/8/acel13157-sup-0002-FigS2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/9/acel13157-sup-0004-FigS4.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155936/10/acel13157_am.pd

Decay Constants of Pseudoscalar DD-mesons in Lattice QCD with Domain-Wall Fermion

We present the first study of the masses and decay constants of the pseudoscalar $D$ mesons in two flavors lattice QCD with domain-wall fermion. The gauge ensembles are generated on the $24^3 \times 48$ lattice with the extent $N_s = 16$ in the fifth dimension, and the plaquette gauge action at $\beta = 6.10$, for three sea-quark masses with corresponding pion masses in the range $260-475$ MeV. We compute the point-to-point quark propagators, and measure the time-correlation functions of the pseudoscalar and vector mesons. The inverse lattice spacing is determined by the Wilson flow, while the strange and the charm quark masses by the masses of the vector mesons $\phi(1020)$ and $J/\psi(3097)$ respectively. Using heavy meson chiral perturbation theory (HMChPT) to extrapolate to the physical pion mass, we obtain $f_D = 202.3(2.2)(2.6)$ MeV and $f_{D_s} = 258.7(1.1)(2.9)$ MeV.Comment: 15 pages, 3 figures. v2: the statistics of ensemble (A) with m_sea = 0.005 has been increased, more details on the systematic error, to appear in Phys. Lett.

Supervised Collective Classification for Crowdsourcing

Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of crowdsourced data. In this paper, we propose a supervised collective classification algorithm that aims to identify reliable labelers from the training data (e.g., items with known labels). The reliability (i.e., weighting factor) of each labeler is determined via a saddle point algorithm. The results on several crowdsourced data show that supervised methods can achieve better classification accuracy than unsupervised methods, and our proposed method outperforms other algorithms.Comment: to appear in IEEE Global Communications Conference (GLOBECOM) Workshop on Networking and Collaboration Issues for the Internet of Everythin

Boosting Factual Consistency and High Coverage in Unsupervised Abstractive Summarization

Abstractive summarization has gained attention because of the positive performance of large-scale, pretrained language models. However, models may generate a summary that contains information different from the original document. This phenomenon is particularly critical under the abstractive methods and is known as factual inconsistency. This study proposes an unsupervised abstractive method for improving factual consistency and coverage by adopting reinforcement learning. The proposed framework includes (1) a novel design to maintain factual consistency with an automatic question-answering process between the generated summary and original document, and (2) a novel method of ranking keywords based on word dependency, where keywords are used to examine the coverage of the key information preserved in the summary. The experimental results show that the proposed method outperforms the reinforcement learning baseline on both the evaluations for factual consistency and coverage

An Adaptive Load Balance and Handoff Management Strategy for Hierarchical Infrastructure Networks

Hierarchical cellular networks that employ microcells with overlaying macrocells have been proposed to increase the traffic-carrying capacity and circuit quality. Variations in the traffic loads among cells will lessen the traffic-carrying capacity. Moreover, the handoff procedure usually takes place when the call crosses the cell boundary. An ineffective management will increase the system overheads, such as channel switch, data switch, and even network switch. The invetigation proposes an effective load balance and handoff management strategy. This strategy are implemented to solve traffic-adaption problem that can enhance the traffic-carrying capacity for variations in traffic. For the management of handoff procedure, our strategy considers the mobility of mobile hosts and the bandwidth utilization in macrocells. It can descrease the number of handoffs and, accordingly, lessen the system overhead. Furthermore, the simulation results are presented to confirm the efficiency of the proposed strategy

Toward a Human-Centered AI-assisted Colonoscopy System

AI-assisted colonoscopy has received lots of attention in the last decade. Several randomised clinical trials in the previous two years showed exciting results of the improving detection rate of polyps. However, current commercial AI-assisted colonoscopy systems focus on providing visual assistance for detecting polyps during colonoscopy. There is a lack of understanding of the needs of gastroenterologists and the usability issues of these systems. This paper aims to introduce the recent development and deployment of commercial AI-assisted colonoscopy systems to the HCI community, identify gaps between the expectation of the clinicians and the capabilities of the commercial systems, and highlight some unique challenges in Australia.Comment: 9 page

An Integrated Bus and Taxi Routes for a Mobile Trip Planning System

With the popular usage of Google Maps and smart phones, more and more people are using smart phones to surf and inquire about travel information. As a result, every major city plans to push the existing online public transportation trip planning system beyond traditional computer users to mobile phone users. The trip planning system is based on the starting and ending points that a user inputs, and guides the user to take a bus or metro through an electronic map interface. The system usually provides different kind of alternative travel routes with the estimated time of arrival. However, people who use the public transport system may encounter some uncertainties, such as long waiting times, long routes, long walking distances, etc. In each big city, the taxi is a universal transport vehicle which is available at almost anytime, anywhere. Taxis can save passengers’ walking distance and travel time with a deficit of high cost. Therefore, we design a trip planning system to unify the Taipei public transportation system with taxis. The users can inquire of a travel route through the mobile phones. This system uses Google Maps as a base map. The users assign an upper limit of fare which they are willing to pay. The system will balance between travel time and travel cost to obtain a route which may combine usage of the bus and taxi. Because of the high density of bus stations in Taipei city, the route search may consume a lot of system resources. We propose an improvement method to eliminate some intermediate bus stations in route search processing