Biology subjects

Hirt, M.

Publications and source records attributed to Hirt, M..

4 recordsLinked to original sources

bioRxiv2026

Dynamic BMP10 Release Reflects Atrial Fibrillation Burden in Human Atrial Engineered Heart Tissue

Background: Atrial fibrillation (AF) burden is increasingly recognized as a determinant of clinical risk. Currently, AF burden can only be estimated using long-term rhythm monitoring. Bone morphogenetic protein 10 (BMP10) is a protein secreted from cardiac atria associated with AF and AF-related complications. This study evaluated whether BMP10 concentrations are associated with AF burden in a human atrial model: atrial engineered heart tissue (aEHT). Methods: Human induced pluripotent stem cell-derived atrial cardiomyocytes were cast into atrial engineered heart tissues (aEHTs). To mimic AF burden, mature aEHTs were optogenetically-paced at a high rate of 4 Hz, either intermittently for 4 hours every 2 days (~10% burden) or continuously for 24 hours per day (100% burden). After 18 days of high-rate pacing intervention, 7 days of recovery without pacing followed. BMP10 release was quantified by ELISA and contractile function was assessed by video analysis. EHT transcriptional remodeling in response to mimicked AF burden was assessed by RNA sequencing and the effect of recovery was analyzed by qPCR. Results: High-rate optogenetic pacing mimicking AF lead to a dynamic, burden-dependent BMP10 release: BMP10 concentrations in the medium were increased by intermittent optogenetic pacing (~10% burden) and highest under continuous optogenetic pacing (100% burden). BMP10 release declined toward control levels during recovery. Contractile dysfunction was most impaired after continuous pacing and showed only partial recovery within 7 days after pacing cessation. RNA sequencing revealed distinct burden-dependent transcriptional states. Pacing-regulated transcripts were related to BMP/TGF{beta} signaling, atrial identity, calcium handling, contractile phenotype, and electrophysiological remodeling. After recovery, BMP10 mRNA expression remained elevated despite normalization of BMP10 protein release. Conclusions: AF burden dynamically regulates BMP10 release and functional and molecular remodeling in human aEHTs. BMP10 release depicts a secreted protein-based readout of current or recent atrial high-rate stress, whereas persistent transcriptional changes indicate molecular memory of prior AF burden. These findings support BMP10 release as a burden-sensitive AF biomarker

pharmacology and toxicology↗

bioRxiv2023

A Pose-Informed De-Noising Diffusion Model for Adult Naturalistic EEG Signals

Artifact contamination in EEG (electroencephalogram) signals is a significant problem, especially in naturalistic settings where participants can move freely. This contamination stems from various sources like eye movements, muscle activity, sweat, and electrical interference, whose effects differ greatly from each other. Traditional denoising methods, such as Independent Component Analysis, are limited because they assume a linear relationship between the source of the artifacts and the EEG signals, and often require the dominance of one noise source over others. Moreover, these methods need expert knowledge in EEG analysis and lack an objective standard for evaluation. To overcome these challenges, we propose two innovations: Firstly, we introduce the use of "video-estimated" pose coordinates - the x and y positions of different body points (like wrists, eyes, and ankles) - to assist in the EEG denoising process. Secondly, we present a denoising diffusion model, EEG-DDM, that utilizes both the contaminated EEG signals and these pose coordinates to effectively denoise the EEG. Our findings show that incorporating keypoints (pose coordinates) improves denoising performance and helps maintain cross-spatial dependencies in the data. Additionally, we enhance human interpretability of the process by displaying saliency maps generated by our model, which explain the contributions of these keypoints in the denoising process.

neuroscience↗

bioRxiv2022

Heat dissipation drives the hump-shaped scaling of animal dispersal speed with body mass

Dispersal is critical to animal survival and thus biodiversity in fragmented landscapes. Increasing fragmentation in the Anthropocene necessitates predictions about the dispersal capabilities of the many species that inhabit natural ecosystems. This requires mechanistic, trait-based models of animal dispersal which are sufficiently general as well as biologically realistic. While larger animals should generally be able to travel greater distances, reported trends in their speeds across a range of body sizes suggest limited locomotor capacities among the largest species. Here, we show that this also applies to dispersal speeds and that this arises because of their limited heat-dissipation capacities. We derive a model considering how fundamental biophysical constraints of animal body mass associated with energy utilisation (i.e. larger animals have a lower metabolic energy cost of locomotion) and heat-dissipation (i.e. larger animals require more time to dissipate metabolic heat) limit sustained (i.e. aerobic) dispersal speeds. Using an extensive empirical dataset of animal dispersal speeds (531 species), we show that this allometric heat-dissipation model best captures the hump-shaped trends in dispersal speed with body mass for flying, running and swimming animals. This implies that the inability to dissipate metabolic heat leads to the saturation and eventual decrease in dispersal speed with increasing body mass as larger animals must reduce their realised dispersal speeds in order to avoid hyperthermia during extended dispersal bouts. As a result, the highest dispersal speeds are achieved by animals of intermediate body mass, whereas the largest species might suffer from stronger dispersal limitations in fragmented landscapes than previously anticipated. Consequently, we provide a mechanistic understanding of animal dispersal speed that can be generalised across species, even when the details of an individual species biology are unknown, to facilitate more realistic predictions of biodiversity dynamics in fragmented landscapes.

ecology↗

bioRxiv2016

Universal scaling of maximum speed with body mass - Why the largest animals are not the fastest

Speed is the fundamental constraint on animal movement, yet there is no general consensus on the determinants of maximum speed itself. Here, we provide a universal scaling model of maximum speed with body mass, which holds across locomotion modes, ecosystem types and taxonomic groups. In contrast to traditional power-law scaling, we predict a hump-shaped relationship due to a finite acceleration time for animals. This model is strongly supported by extensive empirical data (470 species with body masses ranging from 5.7x10-8 to 108,000 kg) from terrestrial as well as aquatic ecosystems. Our approach offers a novel concept of what determines the upper limit of animal movement, thus enabling a better understanding of realized movement patterns in nature and their multifold ecological consequences.

ecology↗