Biology subjects

Rodino, J.

Publications and source records attributed to Rodino, J..

3 recordsLinked to original sources

bioRxiv2025

Effects of Electrocardiograms QRS Detection Algorithms in Heart Rate Variability Metrics

Heart Rate Variability (HRV) is a marker used for assessing autonomic nervous system function, derived from the timing between R-peaks in electrocardiogram (ECG) signals. Accurate detection of QRS complexes is essential for reliable HRV computation. While many R-wave detection algorithms exist, their impact on the accuracy of HRV metrics remains underexplored. This study addresses this gap by assessing how QRS detection errors affect HRV analysis across different algorithms and recording setups. We evaluated eight widely used QRS detectors using ECG recordings from 25 healthy participants under rest, cognitive load, and physical activity conditions. Two acquisition setups were considered: "chest strap" and "loose cables." We used the manually annotated R-peaks to calculate the ground-truth HRV metric values. The relationship between the detector performance and HRV errors was evaluated for 11 metrics using the concordance correlation coefficient (CCC). Results showed significant variability in detector performance across algorithms and setups. No single QRS detection algorithm outperformed across all scenarios. Loose cable recordings yielded higher CCC values than chest straps, particularly for MeanNN and LF power. These findings highlight the critical role of QRS detector selection and signal acquisition conditions in HRV analysis. They underscore the need for context-specific benchmarking, particularly for wearable and ambulatory applications where signal quality can vary. Ultimately, this study offers practical recommendations for clinicians and researchers on selecting QRS detection algorithms that best align with their specific analytical objectives and recording conditions.

bioengineering↗

bioRxiv2025

Multi-omics and biochemical reconstitution reveal CDK7-dependent mechanisms controlling RNA polymerase II function at gene 5'- and 3'-ends

CDK7 regulates RNA polymerase II (RNAPII) initiation, elongation, and termination through incompletely understood mechanisms. Because contaminating kinases precluded CDK7 analysis with nuclear extracts, we completed biochemical assays with purified factors. Reconstitution of RNAPII transcription initiation showed CDK7 inhibition slowed and/or paused RNAPII promoter-proximal transcription, which reduced re-initiation. These CDK7-regulatory functions were Mediator- and TFIID-dependent. Similarly in human cells, CDK7 inhibition reduced transcription by suppressing RNAPII activity at promoters, consistent with reduced initiation and/or re-initiation. Moreover, widespread 3-end readthrough transcription was observed in CDK7-inhibited cells; mechanistically, this occurred through rapid nuclear depletion of RNAPII elongation and termination factors, including high-confidence CDK7 targets. Collectively, these results define how CDK7 governs RNAPII function at gene 5-ends and 3-ends, and reveal that nuclear abundance of elongation and termination factors is kinase-dependent. Because 3-readthrough transcription is commonly induced during stress, our results further suggest regulated suppression of CDK7 activity may enable this RNAPII transcriptional response.

biochemistry↗

bioRxiv2023

Gaming expertise induces meso-scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling

Video games are a valuable tool for studying the effects of training and neural plasticity on the brain. However, the underlaying mechanisms related to plasticity-induced brain structural changes and their impact in brain dynamics are unknown. Here, we used a semi-empirical whole-brain model to study structural neural plasticity mechanisms linked to video game expertise. We hypothesized that video game expertise is associated with neural plasticity-mediated changes in structural connectivity that manifest at the meso-scale level, resulting in a more segregated functional network topology. To test this hypothesis, we combined structural connectivity data of StarCraft II video game players (VGPs, n = 31) and non-players (NVGPs, n = 31), with generic fMRI data from the Human Connectome Project and computational models, with the aim of generating simulated fMRI recordings. Graph theory analysis on simulated data was performed during both resting-state conditions and external stimulation. VGPs simulated functional connectivity was characterized by a meso-scale integration, with increased local connectivity in frontal, parietal and occipital brain regions. The same analyses at the level of structural connectivity showed no differences between VGPs and NVGPs. Regions that increased their connectivity strength in VGPs are known to be involved in cognitive processes crucial for task performance such as attention, reasoning, and inference. In-silico stimulation suggested that differences in FC between VGPs and NVGPs emerge in noisy contexts, specifically when the noisy level of stimulation is increased. This indicates that the connectomes of VGPs may facilitate the filtering of noise from stimuli. These structural alterations drive the meso-scale functional changes observed in individuals with gaming expertise. Overall, our work sheds light into the mechanisms underlying structural neural plasticity triggered by video game experiences.

neuroscience↗