Search results for "work"

Tumor- and cytokine-primed human natural killer cells exhibit distinct phenotypic and transcriptional signatures.

2019

An emerging cellular immunotherapy for cancer is based on the cytolytic activity of natural killer (NK) cells against a wide range of tumors. Although in vitro activation, or "priming," of NK cells by exposure to pro-inflammatory cytokines, such as interleukin (IL)-2, has been extensively studied, the biological consequences of NK cell activation in response to target cell interactions have not been thoroughly characterized. We investigated the consequences of co-incubation with K562, CTV-1, Daudi RPMI-8226, and MCF-7 tumor cell lines on the phenotype, cytokine expression profile, and transcriptome of human NK cells. We observe the downregulation of several activation receptors including CD…

Directional high-throughput sequencing of RNAs without gene-specific primers.

2018

Ribosomal RNA analysis is a useful tool for characterization of microbial communities. However, the lack of broad-range primers has hampered the simultaneous analysis of eukaryotic and prokaryotic members by amplicon sequencing. We present a complete workflow for directional, primer-independent sequencing of size-selected small subunit ribosomal RNA fragments. The library preparation protocol includes gel extraction of the target RNA, ligation of an RNA oligo to the 5′-end of the target, and cDNA synthesis with a tailed random-hexamer primer and further barcoding. The sequencing results of a phytoplankton mock community showed a highly similar profile to the biomass indicators. This method…

2015

The University of Minnesota Biocatalysis/Biodegradation Database and Pathway Prediction System (UM-BBD/PPS) has been a unique resource covering microbial biotransformation pathways of primarily xenobiotic chemicals for over 15 years. This paper introduces the successor system, enviPath (The Environmental Contaminant Biotransformation Pathway Resource), which is a complete redesign and reimplementation of UM-BBD/PPS. enviPath uses the database from the UM-BBD/PPS as a basis, extends the use of this database, and allows users to include their own data to support multiple use cases. Relative reasoning is supported for the refinement of predictions and to allow its extensions in terms of previo…

A framework for data-driven adaptive GUI generation based on DICOM

2018

Computer applications for diagnostic medical imaging provide generally a wide range of tools to support physicians in their daily diagnosis activities. Unfortunately, some functionalities are specialized for specific diseases or imaging modalities, while other ones are useless for the images under investigation. Nevertheless, the corresponding Graphical User Interface (GUI) widgets are still present on the screen reducing the image visualization area. As a consequence, the physician may be affected by cognitive overload and visual stress causing a degradation of performances, mainly due to unuseful widgets. In clinical environments, a GUI must represent a sequence of steps for image investi…

Identification of novel drug resistance mechanisms by genomic and transcriptomic profiling of glioblastoma cells with mutation-activated EGFR.

2021

Abstract Aims Epidermal growth factor receptor (EGFR) is not only involved in carcinogenesis, but also in chemoresistance. We characterized U87.MGΔEGFR glioblastoma cells with constitutively active EGFR due to deletion at the ligand binding domain in terms of gene expression profiling and chromosomal aberrations. Wild-type U87.MG cells served as control. Materials and methods RNA sequencing and network analyses (Ingenuity Pathway Analysis) were performed to identify novel drug resistance mechanisms related to expression of mutation activated EGFR. Chromosomal aberrations were characterized by multicolor fluorescence in situ hybridization (mFISH) and array comparative genomic hybridization (…

Towards patient stratification and treatment in the autoimmune disease lupus erythematosus using a systems pharmacology approach

2015

Drug development in Systemic Lupus Erythematosus (SLE) has been hindered by poor translation from successful preclinical experiments to clinical efficacy. This lack of success has been attributed to the high heterogeneity of SLE patients and to the lack of understanding of disease physiopathology. Modelling approaches could be useful for supporting the identification of targets, biomarkers and patient subpopulations with differential response to drugs. However, the use of traditional quantitative models based on differential equations is not justifiable in a sparse data situation. Boolean networks models are less demanding on the required data to be implemented and can provide insights into…

On a Planar Dynamical System Arising in the Network Control Theory

2016

We study the structure of attractors in the two-dimensional dynamical system that appears in the network control theory. We provide description of the attracting set and follow changes this set suffers under the changes of positive parameters µ and Θ.

Analysis of normal human retinal vascular network architecture using multifractal geometry

2017

AIM To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. METHODS Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyse…

Discovering Differential Equations from Earth Observation Data

2020

Modeling and understanding the Earth system is a constant and challenging scientific endeavour. When a clear mechanistic model is unavailable, complex or uncertain, learning from data can be an alternative. While machine learning has provided excellent methods for detection and retrieval, understanding the governing equations of the system from observational data seems an elusive problem. In this paper we introduce sparse regression to uncover a set of governing equations in the form of a system of ordinary differential equations (ODEs). The presented method is used to explicitly describe variable relations by identifying the most expressive and simplest ODEs explaining data to model releva…

Inferring causation from time series in earth system sciences

2019

The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers.