latest news & announcements

Monocytes can and do give rise to self-renewing tissue-resident macrophages if the niche is available

Self-renewing tissue-resident macrophages are thought to be exclusively derived from embryonic progenitors. However, whether circulating monocytes can also give rise to such macrophages has not been formally investigated. Here we use a new model of diphtheria toxin-mediated depletion of liver-resident Kupffer cells to generate niche availability and show that circulating monocytes engraft in the liver, gradually adopt the transcriptional profile of their depleted counterparts and become long-lived self-renewing cells.

A robust transcription-based signature for radiation biodosimetry

Accurate assessment of the individual exposure dose based on easily accessible samples (e.g. blood) immediately following a radiological accident is crucial. We aimed at developing a robust transcription-based signature for biodosimetry from human peripheral blood mononuclear cells irradiated with different doses of X-rays (0.1 and 1.0 Gy) at a dose rate of 0.26 Gy/min. Genome-wide radiation-induced changes in mRNA expression were evaluated at both gene and exon level.

Fuzzy sets progress

In 'A Historical Account of Types of Fuzzy Sets and Their Relationships', we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used.

Ghent University researchers make their mark in Life Sciences and Medicine

With 15 researchers, Ghent University delivers 50% of all Belgian 'Highly Cited Researchers' on Thomson Reuters’ list. “This highlights the excellent quality of our research and its international recognition”, states rector Anne De Paepe.

The research areas in which Ghent University has a high concentration of top papers are mainly situated in the broad areas of life sciences and medicine. For many of these Ghent University experts, biotechnology provides a crucial approach to their research.

Tips for RT-qPCR gene expression of difficult to analyze paraffin-embedded tissue samples

Fragmented RNA from formalin-fixed paraffin-embedded (FFPE) tissue is a known obstacle to gene expression analysis. In this study, the impact of RNA integrity, gene-specific reverse transcription and targeted cDNA preamplification was quantified in terms of reverse transcription polymerase chain reaction (RT-qPCR) sensitivity by measuring 48 protein coding genes on eight duplicate cultured cancer cell pellet FFPE samples and twenty cancer tissue FFPE samples.

Complete mitochondrial genome of the Verticillium-wilt causing plant pathogen Verticillium nonalfalfae

Verticillium nonalfalfae is a fungal plant pathogen that causes wilt disease by colonizing the vascular tissues of host plants. The disease induced by hop isolates of V. nonalfalfae manifests in two different forms, ranging from mild symptoms to complete plant dieback, caused by mild and lethal pathotypes, respectively. Pathogenicity variations between the causal strains have been attributed to differences in genomic sequences and perhaps also to differences in their mitochondrial genomes. We used data from our recent Illumina NGS-based project of genome sequencing V.


A genome-wide search for epigenetically regulated genes in zebra finch using MethylCap-seq and RNA-seq

It's Time for Some "Site"-Seeing: Novel Tools to Monitor the Ubiquitin Landscape in Arabidopsis thaliana

Ubiquitination, the covalent binding of the small protein modifier ubiquitin to a target protein, is an important and frequently studied posttranslational protein modification. Multiple reports provide useful insights into the plant ubiquitinome, but mostly at the protein level without comprehensive site identification. Here, we implemented ubiquitin combined fractional diagonal chromatography (COFRADIC) for proteome-wide ubiquitination site mapping on Arabidopsis thaliana cell cultures.

Peptide-level Robust Ridge Regression Improves Estimation, Sensitivity, and Specificity in Data-dependent Quantitative Label-free Shotgun Proteomics

Peptide intensities from mass spectra are increasingly used for relative quantitation of proteins in complex samples. However, numerous issues inherent to the mass spectrometry workflow turn quantitative proteomic data analysis into a crucial challenge. We and others have shown that modeling at the peptide level outperforms classical summarization-based approaches, which typically also discard a lot of proteins at the data preprocessing step.