Biology subjects

Briem, E.

Publications and source records attributed to Briem, E..

5 recordsLinked to original sources

bioRxiv2025

Hedonic experiences emerge from an orchestrated balance of synergistic and redundant information processing

Ketamine exerts rapid-acting, pro-hedonic effects, yet its precise mechanism remains elusive. Here, we present behavioral and fMRI data from a randomized, placebo-controlled crossover study in 38 healthy participants investigating ketamines sub-acute effects on multivariate information-processing during music-evoked peak hedonic experiences. Leveraging information-theoretical measures, our findings indicate that hedonic experiences depend on a distinct global (as measured by O-Information) and local (as measured by integrated information) balance between redundant - information shared across nodes - and synergistic - information emerging from joint interactions - processes. As hedonic intensity rises, neural dynamics shift toward greater synergy; with the one exception of a deliberate increase in redundancy particularly for key sensory information to ensure reliable transmission of and access to critical external information for subsequent hedonic processing. In contrast, ketamines sub-acute pro-hedonic effects arise potentially from enhancing redundant dynamics at rest, boosting the brains capability to robustly represent and access critical internal information, and thus, fostering an environment optimized to amplify the phenomenological hedonic experience, while simultaneously allowing for more efficient information integration.

neuroscience↗

bioRxiv2025

Subacute effects of ketamine on neural correlates of reward processing

ObjectivesKetamines prohedonic properties have been linked to enhanced reward-related brain activation during the early post-infusion phase. Its effects during the subacute period ([~]2-24 h post-infusion), when psychotomimetic symptoms fade and neuroplastic adaptations emerge, are less well characterised. This study assessed ketamines subacute effects on reward processing using the Monetary Incentive Delay (MID) task. MethodsIn a randomised, placebo-controlled, crossover study, 28 healthy participants received 0.5 mg/kg racemic ketamine or placebo via 40-minute intravenous infusion. Functional magnetic resonance imaging (fMRI) was acquired [~]5 h post-infusion. Plasma concentrations of ketamine and norketamine were obtained for individual area under the curve (AUC) estimation. Analyses focused on the contrast between expected and actual trial outcomes. ResultsAt five hours post-infusion, ketamine did not significantly modulate MID task-related brain activation, despite pronounced subjective drug effects. Pharmacokinetic modelling confirmed expected ketamine and norketamine profiles, but neither drug exposure (AUC) nor subjective measures correlated with neural activation. ConclusionsProhedonic effects of ketamine may not sufficiently manifest in MID task-related activation in healthy individuals [~]5 hours after infusion. The lack of significant effects provides valuable extension of the existing literature, as ketamines effects might be confined to a more acute time window or differ in clinical populations.

neuroscience↗

bioRxiv2025

Improving RNA-seq protocols

Bulk and single-cell RNA-seq are powerful tools for transcriptomic analysis, providing insights into many aspects of molecular and cellular phenotypes. Costs constrain the amount of biological insight obtainable within a given budget, and as sequencing prices decline, efficient library protocols have become a decisive factor. In this study, we introduce an approach to systematically optimize the number of usable reads that RNA-seq protocols generate. We applied this "funnel strategy" to prime-seq, an early-barcoding bulk RNA-seq protocol, by systematically testing critical protocol steps totaling 1080 samples in 49 libraries. This resulted in the optimized prime-seq2 protocol that increases the number of usable reads by 60 % and improves one of the most cost-efficient bulk RNA-seq protocols available. Our study also suggests that monitoring the filtering of usable reads can serve as a valuable quality control for many RNA-seq protocols and sheds light on the complexity of the conditions and interactions that shape RNA-seq library composition and their interpretation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/671269v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1bf102dorg.highwire.dtl.DTLVardef@bf36bforg.highwire.dtl.DTLVardef@1a3600aorg.highwire.dtl.DTLVardef@f63470_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

High-temporal resolution metabolic connectivity resolved by component-based noise correction

Recent advances in functional PET (fPET) allow for accurate modelling of metabolic processes with a temporal resolution in the range of seconds. This enables new applications such as imaging molecular connectivity at temporal resolutions comparable to fMRI. However, high-temporal resolution fPET data are more sensitive to noise and the extraction of a meaningful signal remains a challenge. We developed a component-based preprocessing approach adapted from fMRI, which models structured noise using tissue-specific regressors and removes low-frequency uptake trends from the fPET signal (CompCor). We applied this method to 20 high-temporal [18F]FDG fPET scans from a next-generation long-axial field of view PET/CT system (1s frames) and 16 scans from a conventional PET/MR scanner (3s frames). We compared filtering methods across frequency bands and examined their effects on metabolic connectivity (M-MC) estimates. Metabolic connectivity was markedly influenced by filtering strategy and scanner type. The CompCor filter produced more consistent and structured networks than standard bandpass filters. Intermediate frequency bands (0.01-0.1 Hz) yielded the most reliable connectivity patterns between PET/CT and PET/MR data (r=0.89). High sensitivity PET/CT data revealed structured connectivity patterns also at a higher frequency band (0.1-0.2 Hz). Compared to fMRI functional connectivity, fPET-derived networks were more spatially cohesive but less differentiated. High-temporal [18F]FDG fPET enables reliable estimation of individual resting-state M-MC when paired with appropriate denoising. Scanner choice and preprocessing significantly affect signal quality and interpretation, whereas the proposed physiologically informed pipeline improves comparability across systems and studies.

neuroscience↗

bioRxiv2024

Recommendations for Bioinformatics in Clinical Practice

Next Generation Sequencing (NGS) is increasingly used in clinical diagnostics, largely driven by the success and robustness of Whole Genome Sequencing (WGS). Whereas updated guidelines exist for how to interpret and report on variants that are identified from NGS using bioinformatics pipelines, there is a need for standardised bioinformatics practices for diagnostics to ensure clinical consensus, accuracy, reproducibility and comparability of the results. This article presents consensus recommendations developed by 13 clinical bioinformatics units taking part in the Nordic Alliance for Clinical Genomics (NACG), by expert bioinformaticians working in clinical production. The recommendations are based on clinical practice and focus on analysis types, test and validation, standardisation and accreditation, as well as core competencies and technical management required for clinical bioinformatics operations. Key recommendations include adopting the hg38 genome build as the reference and a standard set of recommended analyses, including the use of multiple tools for structural variant (SV) calling and in-house data sets for filtering recurrent calls. Clinical bioinformatics production should operate under the ISO 15189 standard, utilising off-grid clinical-grade high-performance computing systems, standardised file formats, and strict code version control. Containerized software containers or environment management systems are needed to ensure reproducibility. Pipelines should be rigorously documented and tested for accuracy and reproducibility, minimally covering unit, integration, and end-to-end testing. Standard truth sets such as GIAB and SEQC2 for germline and somatic variant calling, respectively, should be supplemented by recall testing of previously validated clinical cases. Data integrity must be verified using file hashing, and sample identity should be checked via sample fingerprinting and genetically inferred identification markers such as sex and relatedness. Finally, clinical bioinformatics teams should encompass diverse skills, including software development, data management, quality assurance, and domain expertise in human genetics. These recommendations provide a consensus framework for standardising bioinformatics practices across clinical WGS applications and can serve as a practical guide to facilities that are new to large-scale sequencing-based diagnostics, or as a reference for those who already run high-volume clinical production using NGS.

bioinformatics↗