Lactoferrin (Lf) is a potential-targeting ligand for hepatocellular carcinoma (HCC) cells because of its specific binding with asialoglycoprotein receptor (ASGPR). In this present work, a doxorubicin (DOX)-loaded, Lf-modified, polyethylene glycol (PEG)ylated liposome (Lf-PLS) system was developed, and its targeting effect and antitumor efficacy to HCC was also explored. The DOX-loaded Lf-PLS sy...

Genomic selection involves computing a prediction equation from the estimated effects of a large number of DNA markers based on a limited number of genotyped animals with phenotypes. The number of observations is much smaller than the number of independent variables, and the challenge is to find methods that perform well in this context. Partial least squares regression (PLS) and sparse PLS wer...

The concept of green manufacturing is a topical discourse in sustainability studies, but its adoption seems to be lagging due an unclear link financial performance. study aims test the relationship between and performance, with quality performance as mediator entrepreneurial orientation moderator. partial least square (PLS) method was applied for hypotheses testing. Data were randomly obtained ...

The most popular microblogging service, Twitter, has established a large user base, in spite of numerous criticisms. This study aims to examine why this is the case. In particular, the study develops a model of microblogging use continuance based on theories of continuance, habit and critical mass. The model is then tested via a Web survey of Twitter users and PLS path modeling. The results sug...

IOS integration (IOSI) is becoming a competitive necessity in an industrial environment that emphasizes competition between supply chains. In the supply chain, dominant firms often try to exert their power to influence their dependent firms to implement IOSI. Misunderstanding about how power operates will impede firms for developing IOSI. Based on the circuits of power framework and the concept...

In this paper I review covariance-based Partial Least Squares (PLS) methods, focusing on common features of their respective algorithms and optimization criteria. I then show how these algorithms can be adjusted for use as optimal scaling tools. Three new PLS-type algorithms are proposed for the analysis of one, two or several blocks of variables: the NonMetric NIPALS, the Non-Metric PLS Regres...

Partial least squares (PLS) methods have recently been used for many pattern recognition problems in computer vision. Here, PLS is primarily used as a supervised dimensionality reduction tool to obtain effective feature combinations for better learning. However, application of PLS to large datasets is hindered by its higher computational cost. We propose an approach to accelerate the classical ...

PLS Generalised Linear Regression: foundations and recent advances with variable selection and validation procedures Vincenzo Esposito Vinzi Universita degli Studi di Napoli; [email protected] PLS (Partial Least Squares) univariate regression (PLS1) is a model linking a numerical dependent variable to a set of numerical (or dummy) explanatory variables especially feasible in situa...