Efficient spectral neighborhood blocking for entity resolution

Abstract—In many telecom and web applications, there is a need to identify whether data objects in the same source or different sources represent the same entity in the real-world. This problem arises for subscribers in multiple services, customers in supply chain management, and users in social networks when there lacks a unique identifier across multiple data sources to represent a real-world entity. Entity resolution is to identify and discover objects in the data sets that refer to the same entity in the real world. We investigate the entity resolution problem for large data sets where efficient and scalable solutions are needed. We propose a novel unsupervised blocking algorithm, namely SPectrAl Neighborhood (SPAN), which constructs a fast bipartition tree for the records based on spectral clustering such that real entities can be identified accurately by neighborhood records in the tree. There are two major novel aspects in our approach: 1) We develop a fast algorithm that performs spectral clustering without computing pairwise similarities explicitly, which dramatically improves the scalability of the standard spectral clustering algorithm; 2) We utilize a stopping criterion specified by Newman-Girvan modularity in the bipartition process. Our experimental results with both synthetic and real-world data demonstrate that SPAN is robust and outperforms other blocking algorithms in terms of accuracy while it is efficient and scalable to deal with large data sets. I

Experiment and modeling into drilling of micro-hole on TC4 by electrochemical jet machining

This paper studied the rule of micro-hole in electrochemical jet machining (EJM) of TC4 alloy and established the mathematical model of machining process and predicted the machining profile. Considering the influence of machining gap and machining time, orthogonal experiment was designed. This paper established the mathematical model of the electrochemical jet machining process of TC4 alloy based on the response surface analysis (RSA) method. The results indicate that the electrochemical jet can improve the directivity of machining, reducing the machining gap can improve the machining efficiency, but the jet will cause secondary corrosion and abrupt change of current at the edge of inlet. The mathematical model based on response surface analysis is accurate after variance test. The experimental results show that the average error between the established prediction model of machining depth and the actual value is 2.32%, and the average error of the prediction model of inlet radius is 2.18%

Controllable Synthesis of Carboxymethyl Cellulose and Its Application in Tobacco Sheets

Carboxymethyl cellulose (CMC) with different degree of substitution (DS) was prepared by controlling feed ratio and times of alkalization and etherification. CMC with different molecular weight was prepared by degradation of hydrochloric acid solution. Orthogonal experiments were designed to study the effects of addition amount, molecular weight and DS of CMC on the tensile strength of tobacco sheets. The effects of CMC on the thermal properties and aerosol release of tobacco sheets were also studied. The results showed that the addition amount and the molecular weight of CMC had obvious effect on the tensile strength of tobacco sheets. The DS of CMC had no significant effect on the tensile strength of tobacco sheets. The addition of CMC improved the thermal stability of tobacco sheets to a certain extent, and had certain influence on the content of nicotine in aerosol

Preoperative alkaline phosphatase‐to‐platelet count ratio as a prognostic factor for hepatocellular carcinoma with microvascular invasion

Abstract Objectives The association between platelet status and hepatocellular carcinoma (HCC) prognoses remains controversial. Herein, we aimed to clarify the prognostic value of multiple platelet‐related biomarkers, including platelet count, platelet/lymphocyte ratio (PLR), aspartate aminotransferase to platelet ratio index (APRI), and alkaline phosphatase‐to‐platelet count ratio index (APPRI) in HCC with microvascular invasion (MVI) after curative resection or liver transplantation. Materials and Methods A retrospective review of 169 patients with solitary HCC and MVI who underwent resection or liver transplantation between January 2015 and December 2018 was conducted. Preoperative clinical, laboratory, pathologic, and imaging data were collected and analyzed. Overall survival (OS) and disease‐free survival (DFS) were defined as the clinical endpoints. Univariate and multivariate Cox proportional hazards regression analyses were conducted to investigate potential predictors of DFS and OS. Results Multivariate Cox regression analyses revealed that maximum tumor diameter, poor cell differentiation, and APPRI were independent predictors of DFS; while poor cell differentiation, APRI, APPRI, prothrombin time, and alpha‐fetoprotein were independent prognostic factors for OS. The 1‐, 3‐, and 5‐year DFS rates were 66.90%, 48.40%, and 37.40% for patients with APPRI ≤0.74 and 40.40%, 24.20%,and 24.20% for patients with APPRI>0.74. The corresponding rates of OS over 1, 3, and 5 years were 92.40%, 88.10% and 77.70%, and 72.30%, 38.20%, and 19.10%, respectively. The DFS and OS rates of patients whose APPRI was more than 0.74 were substantially lower than those of patients whose APPRI was less than or equal to 0.74 (p = 0.002 and p < 0.001, respectively). Conclusion Elevated preoperative APPRI is a noninvasive, simple, and easily assessable parameter linked to poor prognosis in individuals with single HCC and MVI after resection or liver transplantation

Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers

<div><p>Introduction</p><p>Advances in high-throughput technologies have generated diverse informative molecular markers for cancer outcome prediction. Long non-coding RNA (lncRNA) and DNA methylation as new classes of promising markers are emerging as key molecules in human cancers; however, the prognostic utility of such diverse molecular data remains to be explored.</p><p>Materials and Methods</p><p>We proposed a computational pipeline (IDFO) to predict patient survival by identifying prognosis-related biomarkers using multi-type molecular data (mRNA, microRNA, DNA methylation, and lncRNA) from 3198 samples of five cancer types. We assessed the predictive performance of both single molecular data and integrated multi-type molecular data in patient survival stratification, and compared their relative importance in each type of cancer, respectively. Survival analysis using multivariate Cox regression was performed to investigate the impact of the IDFO-identified markers and traditional variables on clinical outcome.</p><p>Results</p><p>Using the IDFO approach, we obtained good predictive performance of the molecular datasets (bootstrap accuracy: 0.71–0.97) in five cancer types. Impressively, lncRNA was identified as the best prognostic predictor in the validated cohorts of four cancer types, followed by DNA methylation, mRNA, and then microRNA. We found the incorporating of multi-type molecular data showed similar predictive power to single-type molecular data, but with the exception of the lncRNA + DNA methylation combinations in two cancers. Survival analysis of proportional hazard models confirmed a high robustness for lncRNA and DNA methylation as prognosis factors independent of traditional clinical variables.</p><p>Conclusion</p><p>Our study provides insight into systematically understanding the prognostic performance of diverse molecular data in both single and aggregate patterns, which may have specific reference to subsequent related studies.</p></div

Mitoquinone alleviates osteoarthritis progress by activating the NRF2-Parkin axis

Summary: Osteoarthritis (OA) is a prevalent degenerative disease of the elderly. The NRF2 antioxidant system plays a critical role in maintaining redox balance. Mitoquinone (MitoQ) is a mitochondria-targeted antioxidant. This research aimed to determine whether MitoQ alleviated OA and the role of the NRF2/Parkin axis in MitoQ-mediated protective effects. In interleukin (IL)-1β-induced OA chondrocytes, MitoQ activated the NRF2 pathway, reducing extracellular matrix (ECM) degradation and inflammation. MitoQ also increased glutathione peroxidase 4 (GPX4) expression, leading to decreased levels of reactive oxygen species (ROS) and lipid ROS. Silencing NRF2 weakened MitoQ’s protective effects, while knockdown of Parkin upregulated the NRF2 pathway, inhibiting OA progression. Intra-articular injection of MitoQ mitigated cartilage destruction in destabilized medial meniscus (DMM)-induced OA mice. Our study demonstrates that MitoQ maintains cartilage homeostasis in vivo and in vitro through the NRF2/Parkin axis. We supplemented the negative feedback regulation mechanism between NRF2 and Parkin. These findings highlight the therapeutic potential of MitoQ for OA treatment

Correction: Comparison of the Prognostic Utility of Diverse Molecular Data among lncRNA, DNA Methylation, microRNA and mRNA across Five Human Cancers

<p>Correction: Comparison of the Prognostic Utility of Diverse Molecular Data among lncRNA, DNA Methylation, microRNA and mRNA across Five Human Cancers</p

Flowchart of the IDFO approach.

<p>This flowchart contains three basic steps: (i) PRP ranking of molecular features, (ii) model construction and (iii) feature optimization and validation.</p

Survival analysis on IDFO predictors of four types of molecular data in five cancers.

<p>The Kaplan-Meier overall survival curves of two outcome groups classified by MCPHR models using IDFO-identified predictors of each molecular data of each cancer. (a) the BRCA lncRNA cohort; (b) the BRCA DNA methylation cohort; (c) the BRCA microRNA cohort; (d) the BRCA mRNA cohort; (e) the COAD lncRNA cohort; (f) the COAD DNA methylation cohort; (g) the COAD microRNA cohort; (h) the COAD mRNA cohort; (i) the LUSC lncRNA cohort; (j) the LUSC DNA methylation cohort; (k) the LUSC microRNA cohort; (l) the LUSC mRNA cohort;(m) the OV lncRNA cohort; (n) the OV DNA methylation cohort; (o) the OV microRNA cohort; (p) the OV mRNA cohort;(q) the UCEC lncRNA cohort; (r) the UCEC DNA methylation cohort; (s) the UCEC microRNA cohort; (t) the UCEC mRNA cohort. The difference in outcome of two outcome groups was tested using Kaplan-Meier survival analysis. Likelihood ratio = the likelihood ratio test.</p