LAGOS-AND: A Large Gold Standard Dataset for Scholarly Author Name Disambiguation

In this paper, we present a method to automatically build large labeled datasets for the author ambiguity problem in the academic world by leveraging the authoritative academic resources, ORCID and DOI. Using the method, we built LAGOS-AND, two large, gold-standard datasets for author name disambiguation (AND), of which LAGOS-AND-BLOCK is created for clustering-based AND research and LAGOS-AND-PAIRWISE is created for classification-based AND research. Our LAGOS-AND datasets are substantially different from the existing ones. The initial versions of the datasets (v1.0, released in February 2021) include 7.5M citations authored by 798K unique authors (LAGOS-AND-BLOCK) and close to 1M instances (LAGOS-AND-PAIRWISE). And both datasets show close similarities to the whole Microsoft Academic Graph (MAG) across validations of six facets. In building the datasets, we reveal the variation degrees of last names in three literature databases, PubMed, MAG, and Semantic Scholar, by comparing author names hosted to the authors' official last names shown on the ORCID pages. Furthermore, we evaluate several baseline disambiguation methods as well as the MAG's author IDs system on our datasets, and the evaluation helps identify several interesting findings. We hope the datasets and findings will bring new insights for future studies. The code and datasets are publicly available.Comment: 33 pages, 7 tables, 7 figure

Allocating Limited Resources to Protect a Massive Number of Targets using a Game Theoretic Model

Resource allocation is the process of optimizing the rare resources. In the area of security, how to allocate limited resources to protect a massive number of targets is especially challenging. This paper addresses this resource allocation issue by constructing a game theoretic model. A defender and an attacker are players and the interaction is formulated as a trade-off between protecting targets and consuming resources. The action cost which is a necessary role of consuming resource, is considered in the proposed model. Additionally, a bounded rational behavior model (Quantal Response, QR), which simulates a human attacker of the adversarial nature, is introduced to improve the proposed model. To validate the proposed model, we compare the different utility functions and resource allocation strategies. The comparison results suggest that the proposed resource allocation strategy performs better than others in the perspective of utility and resource effectiveness.Comment: 14 pages, 12 figures, 41 reference

Determination of Pentachlorophenol in Milk Powder by Isotope Dilution Liquid Chromatography-Tandem Mass Spectrometry

In this study, an analytical method was established to determine pentachlorophenol (PCP) in milk powder by isotope dilution-liquid chromatography-tandem mass spectrometry (LC-MS/MS). The sample was dissolved in water, extracted by the quick, effective, cheap, easy, rugged and safe (QuEChERS) method using acetonitrile as the extraction solvent and protein precipitant, purified on a Captiva EMR-Lipid column, and diluted with the same volume of water before analysis. The chromatographic separation was achieved on a C18 column (100 mm × 2.1 mm, 1.7 μm) with gradient elution using a mobile phase composed of methanol and 5 mmol/L ammonium acetate solution (containing 0.05% formic acid), and then the analyte was detected with negative electrospray ionization (ESI-) in the multiple reaction monitoring (MRM) mode. Matrix matching-isotope dilution internal standard method was used for identification and quantification of the analyte. The results indicated that the calibration curve of PCP was linear in the concentration range of 0.2‒150 μg/L with correlation coefficients (r) not less than 0.996 0. The limits of detection (LOD) and quantitation (LOQ) of the method were 0.5 and 1.5 μg/kg, respectively. The average recoveries for spiked milk powder ranged from 90.3% to 119.2%, with relative standard deviation (RSD, n = 6) equal to or less than 7.5%. The method has the advantages of simple pretreatment without concentration or dissolution, high sensitivity, accuracy and reliability, and can be used as an effective method for detecting pentachlorophenol in milk powder

Dihydro-CDDO-Trifluoroethyl Amide (dh404), a Novel Nrf2 Activator, Suppresses Oxidative Stress in Cardiomyocytes

Targeting Nrf2 signaling appears to be an attractive approach for the treatment of maladaptive cardiac remodeling and dysfunction; however, pharmacological modulation of the Nrf2 pathway in the cardiovascular system remains to be established. Herein, we report that a novel synthetic triterpenoid derivative, dihydro-CDDO-trifluoroethyl amide (dh404), activates Nrf2 and suppresses oxidative stress in cardiomyocytes. Dh404 interrupted the Keap1-Cul3-Rbx1 E3 ligase complex-mediated Nrf2 ubiquitination and subsequent degradation saturating the binding capacity of Keap1 to Nrf2, thereby rendering more Nrf2 to be translocated into the nuclei to activate Nrf2-driven gene transcription. A mutant Keap1 protein containing a single cysteine-to-serine substitution at residue 151 within the BTB domain of Keap1 was resistant to dh404-induced stabilization of Nrf2 protein. In addition, dh404 did not dissociate the interaction of Nrf2 with the Keap1-Cul3-Rbx1 E3 ligase complex. Thus, it is likely that dh404 inhibits the ability of Keap1-Cul3-Rbx1 E3 ligase complex to target Nrf2 for ubiquitination and degradation via modifying Cys-151 of Keap1 to change the conformation of the complex. Moreover, dh404 was able to stabilize Nrf2 protein, to enhance Nrf2 nuclear translocation, to activate Nrf2-driven transcription, and to suppress angiotensin II (Ang II)-induced oxidative stress in cardiomyocytes. Knockdown of Nrf2 almost blocked the anti-oxidative effect of dh404. Dh404 activated Nrf2 signaling in the heart. Taken together, dh404 appears to be a novel Nrf2 activator with a therapeutic potential for cardiac diseases via suppressing oxidative stress