Fucosylation of LAMP-1 and LAMP-2 by FUT1 correlates with lysosomal positioning and autophagic flux of breast cancer cells.

Alpha1,2-fucosyltransferases, FUT1 and FUT2, which transfer fucoses onto the terminal galactose of N-acetyl-lactosamine via α1,2-linkage have been shown to be highly expressed in various types of cancers. A few studies have shown the involvement of FUT1 substrates in tumor cell proliferation and migration. Lysosome-associated membrane protein 1, LAMP-1, has been reported to carry alpha1,2-fucosylated Lewis Y (LeY) antigens in breast cancer cells, however, the biological functions of LeY on LAMP-1 remain largely unknown. Whether or not its family member, LAMP-2, displays similar modifications and functions as LAMP-1 has not yet been addressed. In this study, we have presented evidence supporting that both LAMP-1 and 2 are substrates for FUT1, but not FUT2. We have also demonstrated the presence of H2 and LeY antigens on LAMP-1 by a targeted nanoLC-MS(3) and the decreased levels of fucosylation on LAMP-2 by MALDI-TOF analysis upon FUT1 knockdown. In addition, we found that the expression of LeY was substantial in less invasive ER+/PR+/HER- breast cancer cells (MCF-7 and T47D) but negligible in highly invasive triple-negative MDA-MB-231 cells, of which LeY levels were correlated with the levels of LeY carried by LAMP-1 and 2. Intriguingly, we also observed a striking change in the subcellular localization of lysosomes upon FUT1 knockdown from peripheral distribution of LAMP-1 and 2 to a preferential perinuclear accumulation. Besides that, knockdown of FUT1 led to an increased rate of autophagic flux along with diminished activity of mammalian target of rapamycin complex 1 (mTORC1) and enhanced autophagosome-lysosome fusion. This may be associated with the predominantly perinuclear distribution of lysosomes mediated by FUT1 knockdown as lysosomal positioning has been reported to regulate mTOR activity and autophagy. Taken together, our results suggest that downregulation of FUT1, which leads to the perinuclear localization of LAMP-1 and 2, is correlated with increased rate of autophagic flux by decreasing mTOR signaling and increasing autolysosome formation

Skilled emigration and exchange rate : theory and empirics

In this paper we build a theoretical model on the wage effect of skilled emigration to the fluctuations in real exchange rate through the relative prices of nontradables. Our theoretical model predicts that skilled emigration is associated with an increase in the prices of nontradable, which in turn appreciates the exchange rate. We provide robust empirical support to a higher skilled emigration associated with higher prices in nontradables and appreciation of the real effective exchange rate. Based on two samples of countries with 51 and 67 observations, in 1990 and 2000 respectively, we find robust empirical support to a higher skilled emigration associated with higher prices in nontradables and appreciation of the REER. In addition, the support for the remittance-channel of the Dutch disease is also significant; overall, our findings corroborate the remittance-based Dutch disease phenomenon by providing an additional channel through which the labor mobility across borders affects the real exchange rate volatility

Translating Hanja Historical Documents to Contemporary Korean and English

The Annals of Joseon Dynasty (AJD) contain the daily records of the Kings of Joseon, the 500-year kingdom preceding the modern nation of Korea. The Annals were originally written in an archaic Korean writing system, `Hanja', and were translated into Korean from 1968 to 1993. The resulting translation was however too literal and contained many archaic Korean words; thus, a new expert translation effort began in 2012. Since then, the records of only one king have been completed in a decade. In parallel, expert translators are working on English translation, also at a slow pace and produced only one king's records in English so far. Thus, we propose H2KE, a neural machine translation model, that translates historical documents in Hanja to more easily understandable Korean and to English. Built on top of multilingual neural machine translation, H2KE learns to translate a historical document written in Hanja, from both a full dataset of outdated Korean translation and a small dataset of more recently translated contemporary Korean and English. We compare our method against two baselines: a recent model that simultaneously learns to restore and translate Hanja historical document and a Transformer based model trained only on newly translated corpora. The experiments reveal that our method significantly outperforms the baselines in terms of BLEU scores for both contemporary Korean and English translations. We further conduct extensive human evaluation which shows that our translation is preferred over the original expert translations by both experts and non-expert Korean speakers.Comment: 2022 EMNLP Finding

Development of a Computational Framework for Big Data-Driven Prediction of Long-Term Bridge Performance and Traffic Flow

Consistent efforts with dense sensor deployment and data gathering processes for bridge big data have accumulated profound information regarding bridge performance, associated environments, and traffic flows. However, direct applications of bridge big data to long-term decision-making processes are hampered by big data-related challenges, including the immense size and volume of datasets, too many variables, heterogeneous data types, and, most importantly, missing data. The objective of this project was to develop a foundational computational framework that can facilitate data collection, data squashing, data merging, data curing, and, ultimately, data prediction. By using the framework, practitioners and researchers can learn from past data, predict various information regarding long-term bridge performance, and conduct data-driven efficient planning for bridge management and improvement. This research project developed and validated several computational tools for the aforementioned objectives. The programs include (1) a data-squashing tool that can shrink years-long bridge strain sensor data to manageable datasets, (2) a data-merging tool that can synchronize bridge strain sensor data and traffic flow sensor data, (3) a data-curing framework that can fill in arbitrarily missing data with statistically reliable values, and (4) a data-prediction tool that can accurately predict bridge and traffic data. In tandem, this project performed a foundational investigation into dense surface sensors, which will serve as a new data source in the near future. The resultant hybrid datasets, detailed manuals, and examples of all programs have been developed and are shared via web folders. The conclusion from this research was that the developed framework will serve practitioners and researchers as a powerful tool for making big data-driven predictions regarding the long-term behavior of bridges and relevant traffic information

Towards standardizing Korean Grammatical Error Correction: Datasets and Annotation

Research on Korean grammatical error correction (GEC) is limited compared to other major languages such as English and Chinese. We attribute this problematic circumstance to the lack of a carefully designed evaluation benchmark for Korean. Thus, in this work, we first collect three datasets from different sources (Kor-Lang8, Kor-Native, and Kor-Learner) to cover a wide range of error types and annotate them using our newly proposed tool called Korean Automatic Grammatical error Annotation System (KAGAS). KAGAS is a carefully designed edit alignment & classification tool that considers the nature of Korean on generating an alignment between a source sentence and a target sentence, and identifies error types on each aligned edit. We also present baseline models fine-tuned over our datasets. We show that the model trained with our datasets significantly outperforms the public statistical GEC system (Hanspell) on a wider range of error types, demonstrating the diversity and usefulness of the datasets.Comment: Add affiliation and email addres

Multiple Redox Modes in the Reversible Lithiation of High-Capacity, Peierls-Distorted Vanadium Sulfide.

This is the author accepted manuscript. The final version is available from ACS via http://dx.doi.org/10.1021/jacs.5b03395Vanadium sulfide VS4 in the patronite mineral structure is a linear chain compound comprising vanadium atoms coordinated by disulfide anions [S2](2-). (51)V NMR shows that the material, despite having V formally in the d(1) configuration, is diamagnetic, suggesting potential dimerization through metal-metal bonding associated with a Peierls distortion of the linear chains. This is supported by density functional calculations, and is also consistent with the observed alternation in V-V distances of 2.8 and 3.2 Å along the chains. Partial lithiation results in reduction of the disulfide ions to sulfide S(2-), via an internal redox process whereby an electron from V(4+) is transferred to [S2](2-) resulting in oxidation of V(4+) to V(5+) and reduction of the [S2](2-) to S(2-) to form Li3VS4 containing tetrahedral [VS4](3-) anions. On further lithiation this is followed by reduction of the V(5+) in Li3VS4 to form Li3+xVS4 (x = 0.5-1), a mixed valent V(4+)/V(5+) compound. Eventually reduction to Li2S plus elemental V occurs. Despite the complex redox processes involving both the cation and the anion occurring in this material, the system is found to be partially reversible between 0 and 3 V. The unusual redox processes in this system are elucidated using a suite of short-range characterization tools including (51)V nuclear magnetic resonance spectroscopy (NMR), S K-edge X-ray absorption near edge spectroscopy (XANES), and pair distribution function (PDF) analysis of X-ray data.SB acknowledges Schlumberger Stichting Fund and European Research Council (EU ERC) for funding. JC thanks BK21 plus project of Korea. We thank Phoebe Allan and Andrew J. Morris, University of Cambridge, for useful discussions. We also thank Trudy Bolin and Tianpin Wu of Beamline 9-BM, Argonne National Laboratory for help with XANES measurements. The DFT calculations were performed at the UCSB Center for Scientific Computing at UC Santa Barbara, supported by the California Nanosystems Institute (NSF CNS-0960316), Hewlett-Packard, and the Materials Research Laboratory (DMR-1121053). This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357

Genetic Associations of Type 2 Diabetes with Islet Amyloid Polypeptide Processing and Degrading Pathways in Asian Populations

10.1371/journal.pone.0062378PLoS ONE86

Study of production and cold nuclear matter effects in pPb collisions at=5 TeV

Production of mesons in proton-lead collisions at a nucleon-nucleon centre-of-mass energy = 5 TeV is studied with the LHCb detector. The analysis is based on a data sample corresponding to an integrated luminosity of 1.6 nb(-1). The mesons of transverse momenta up to 15 GeV/c are reconstructed in the dimuon decay mode. The rapidity coverage in the centre-of-mass system is 1.5 < y < 4.0 (forward region) and -5.0 < y < -2.5 (backward region). The forward-backward production ratio and the nuclear modification factor for (1S) mesons are determined. The data are compatible with the predictions for a suppression of (1S) production with respect to proton-proton collisions in the forward region, and an enhancement in the backward region. The suppression is found to be smaller than in the case of prompt J/psi mesons