Biology subjects

Noergaard, M.

Publications and source records attributed to Noergaard, M..

3 recordsLinked to original sources

bioRxiv2026

A Comparison and Validation of BIDS Apps for Preprocessing of UCB-J PET data

Background Preprocessing of Positron Emission Tomography (PET) data can be performed in many different ways and often involves manual steps, resulting in reduced comparability across analyses and pipelines. Apps working on PET data organized according to the Brain Imaging Data Structure (BIDS) seek to automate preprocessing, enabling the application of standardized pipelines that increase comparability and reproducibility. In this study, two of these apps were validated against in-house software. Methods Data were acquired in-house from 14 subjects who received placebo in a randomized controlled clinical trial and underwent two PET measurements using the radioligand [11C]UCB-J. Preprocessing was performed with two BIDS Apps, PETPrep and PICNIC, as well as an in-house software. Arterial blood data were processed using Bloodstream, and [11C]UCB-J total distribution volume (VT) values were calculated using a 1-tissue compartment model using kinfitr. Results VT values for all 9 regions of interest were highly consistent across tools with estimates of Intraclass Correlation Coefficients for consistency ranging between 0.94 and >0.99, although bias between tools measured as signed Percentage Difference was present, ranging from 0.1% - 10.2% depending on the region. Tools performed similarly on test-retest metrics. We observed a negative test-retest bias in [11C]UCB-J VT of unknown origin. Conclusion BIDS Apps produce reliable and consistent results when compared both with each other and with an in-house software optimized for processing and analysis of our in-house data. Region-dependant bias between tools warrants caution for direct comparison of VT between tools. The usage of these apps could enable better comparability across publications

neuroscience↗

bioRxiv2025

EPP1 couples receptor activation to cytoplasmic signaling in root nodule symbiosis

Legume symbiosis with nitrogen-fixing bacteria is controlled by a cascade of signaling events leading to root nodule development. While plant cell-surface receptors initiate this process, the link between receptors and cytoplasmic signaling components remains unclear. Here we identify Early Phosphorylated Protein 1 (EPP1) as a central mediator of this pathway. EPP1 is recruited to the activated SYMRK receptor, where it is phosphorylated on a key serine residue, an event essential and sufficient to propagate symbiotic signaling. We provide structural and functional validation of the SYMRK-EPP1 signaling complex and demonstrate that EPP1 is required for root nodule formation. Synthetic engineering of the SYMRK-EPP1 interaction bypasses the need for symbiotic bacteria to initiate the pathway and triggers nodule organogenesis. These findings establish EPP1 as a crucial cytoplasmic component between receptor activation and intracellular signaling, advancing our understanding of nitrogen-fixing symbiosis.

plant biology↗

bioRxiv2021

Discovering fragment length signatures of circulating tumor DNA using Non-negative Matrix Factorization

Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel method to study fragment lengths in cfDNA samples. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC=0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.

bioinformatics↗