Machine Learning Method Reconstructs Hidden Muscular Forces in Bird Respiratory Systems
Researchers used Kolmogorov-Arnold networks, an interpretable machine learning framework, to infer the muscular forces driving avian respiratory dynamics from air-sac pressure measurements alone. The method revealed a two-phase activation pattern in expiratory muscles that was not apparent from pressure data alone and was independently validated through electromyographic recordings. This demonstrates a general approach for reconstructing hidden driving forces in partially observed dynamical systems across physics and biology.
A new study published on arXiv demonstrates that data-driven machine learning can reconstruct unobserved forces in biological systems by inferring governing equations directly from partial observations. Using Kolmogorov-Arnold networks applied to avian respiratory dynamics, researchers inferred the effective muscular forcing from air-sac pressure measurements. The reconstructed dynamics predicted a two-phase activation pattern within each respiratory cycle that was independently validated through electromyographic recordings of expiratory muscles. The work addresses a fundamental challenge in physics: distinguishing between different underlying mechanisms that produce similar observable dynamics. The interpretable nature of the learning framework allowed researchers to uncover nontrivial structure in the underlying forcing that was hidden in the pressure signal alone, which appeared to follow a simple relaxation-like oscillation.
What different sources said
- arXiv cs.LGCenter
Inferring hidden forcing in a biological oscillator using Kolmogorov-Arnold networks
Related
Gut Bacteria Enzyme Found to Break Down Heat-Processed Food Compounds, Producing Novel Biogenic Amines
Researchers have discovered that an enzyme in common gut bacteria can degrade N-epsilon-carboxymethyllysine (CML), a compound formed during thermal food processing, producing previously unknown biogenic amines. The enzyme, ornithine decarboxylase SpeC from enterobacteria, acts on CML and related modified lysine derivatives through a low-level 'underground' catalytic activity. This finding suggests a previously unrecognized communication axis between thermally processed dietary compounds and gut microbial physiology, with potential implications for host health.
Full-Length Gene Sequencing Reveals Two Distinct Bacterial Communities in Black-Legged Ticks Expanding Into Canada
Researchers used Oxford Nanopore full-length 16S rRNA gene sequencing to characterize the microbiome of Ixodes scapularis black-legged ticks collected in Nova Scotia, Canada, distinguishing between tick-adapted bacteria and environmentally acquired bacteria. The study comes as I. scapularis — the primary vector of Lyme disease — is rapidly expanding northward into Canada due to climate change. The findings suggest that environmentally derived bacteria in tick microbiomes are not mere contamination, which has implications for how tick microbiome data is collected and interpreted across surveillance studies.
Study Identifies Metabolic Link Between Cell Envelope Stress and Biofilm Formation in Bacteria
Researchers have discovered that the metabolite acetyl-CoA directly inhibits enzymes that degrade the bacterial signaling molecule c-di-GMP, connecting cell envelope biosynthesis stress to biofilm formation in Pseudomonas aeruginosa. The study found that sub-inhibitory concentrations of antibiotics targeting early peptidoglycan biosynthesis — but not other antibiotic classes — elevate c-di-GMP levels by reducing phosphodiesterase activity, with acetyl-CoA competing for the enzyme active site. Because the relevant enzyme domain is broadly conserved across bacterial species, this checkpoint mechanism may be widespread and could have implications for understanding antibiotic-induced biofilm responses.