Search results for "Clusterin"

Protein Corona: Prevention of Dominant IgG Adsorption on Nanocarriers in IgG‐Enriched Blood Plasma by Clusterin Precoating (Adv. Sci. 10/2019)

2019

The development of nanocarriers for drug delivery is challenged by individual blood composition fluctuations. In article number 1802199, Svenja Morsbach and co‐workers report the accumulation of immunoglobulins in the protein corona of nanocarriers in IgG‐enriched blood plasma resulting in increased cell uptake. This could be prevented by pre‐coating the nanocarriers with the “stealth” protein clusterin. Cover design by Stefan Schuhmacher.

Penalized regression and clustering in high-dimensional data

The main goal of this Thesis is to describe numerous statistical techniques that deal with high-dimensional genomic data. The Thesis begins with a review of the literature on penalized regression models, with particular attention to least absolute shrinkage and selection operator (LASSO) or L1-penalty methods. L1 logistic/multinomial regression models are used for variable selection and discriminant analysis with a binary/categorical response variable. The Thesis discusses and compares several methods that are commonly utilized in genetics, and introduces new strategies to select markers according to their informative content and to discriminate clusters by offering reduced panels for popul…

How challenging RADseq data turned out to favor coalescent-based species tree inference. A case study in Aichryson (Crassulaceae)

2022

Analysing multiple genomic regions while incorporating detection and qualification of discordance among regions has become standard for understanding phylogenetic relationships. In plants, which usually have comparatively large genomes, this is feasible by the combination of reduced-representation library (RRL) methods and high-throughput sequencing enabling the cost effective acquisition of genomic data for thousands of loci from hundreds of samples. One popular RRL method is RADseq. A major disadvantage of established RADseq approaches is the rather short fragment and sequencing range, leading to loci of little individual phylogenetic information. This issue hampers the application of coa…

An Extension of the DgLARS Method to High-Dimensional Relative Risk Regression Models

2020

In recent years, clinical studies, where patients are routinely screened for many genomic features, are becoming more common. The general aim of such studies is to find genomic signatures useful for treatment decisions and the development of new treatments. However, genomic data are typically noisy and high dimensional, not rarely outstripping the number of patients included in the study. For this reason, sparse estimators are usually used in the study of high-dimensional survival data. In this paper, we propose an extension of the differential geometric least angle regression method to high-dimensional relative risk regression models.

A 3-D marker-free system for the analysis of movement disabilities--an application to the legs.

2001

The aim of this paper is to describe an approach allowing the analysis of human motion in three-dimensional (3-D) space. The system that we developed is composed of three charge-coupled-device cameras that capture synchronized image sequences of a human body in motion without the use of markers. Characteristic points belonging to the boundaries of the body in motion are first extracted from the initial images. Two-dimensional superquadrics are then adjusted on these points by a fuzzy clustering process. After that, the position of a 3-D model based on a set of articulated superquadrics, each of them describing a part of the human body, is reconstructed. An optical flow process allows the pr…

A novel clustering-based algorithm for solving spatially-constrained robotic task sequencing problems

2021

The robotic task sequencing problem (RTSP) appears in various forms across many industrial applications and consists of developing an optimal sequence of motions to visit a set of target points defined in a task space. Developing solutions to problems involving complex spatial constraints remains challenging due to the existence of multiple inverse kinematic solutions and the requirements for collision avoidance. So far existing studies have been limited to relaxed RTSPs involving a small number of target points and relatively uncluttered environments. When extending existing methods to problems involving greater spatial constraints and large sets of target points, they either require subst…

Bayesian Markov switching models for the early detection of influenza epidemics

2008

The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…

An evolutionary restricted neighborhood search clustering approach for PPI networks

2014

Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of a group of proteins strictly related can be useful to predict protein functions. Clustering techniques have been widely employed to detect significant biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions intr…

Statistical power of disease cluster and clustering tests for rare diseases: A simulation study of point sources

2012

Abstract Two recent epidemiological studies on clustering of childhood leukemia showed different results on the statistical power of disease cluster and clustering tests, possibly an effect of spatial data aggregation. Eight different leukemia cluster scenarios were simulated using individual addresses of all 1,009,332 children living in Denmark in 2006. For each scenario, a number of point sources were defined with an increased risk ratio at centroid, decreasing linearly to 1.0 at the edge; aggregation levels were administrative units of Danish municipalities and squares of 5, 12.5 and 25 km 2 . Six statistical methods were compared. Generally, statistical power decreased with increasing s…

Tensor clustering on outer-product of coefficient and component matrices of independent component analysis for reliable functional magnetic resonance…

2019

Background. Stability of spatial components is frequently used as a post-hoc selection criteria for choosing the dimensionality of an independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data. Although the stability of the ICA temporal courses differs from that of spatial components, temporal stability has not been considered during dimensionality decisions. New method. The current study aims to (1) develop an algorithm to incorporate temporal course stability into dimensionality selection and (2) test the impact of temporal course on the stability of the ICA decomposition of fMRI data via tensor clustering. Resting state fMRI data were analyzed with two popu…