Browse Articles

Assembling unregulated DNA segments bypasses synthesis screening: regulate fragments as select agents

Waardenburg syndrome type IV: A rare case of neonatal intestinal obstruction and associated anaesthetic challenges

NASA won’t bring Mars samples back to Earth: this is the science that will be lost

Genetic and non-genetic factors distinctly shape the variation of the immune response in cattle

Comparison of dexmedetomidine and ketamine on haemodynamic changes and perioperative analgesia in patients undergoing dorsolumbar spine surgery: A randomized controlled trial

Structure of a Brochothrix thermosphacta bacteriophage reveals cell wall adsorption mechanism in Gram-positive infecting siphophages

Perfusion index as a predictor of hypotension following spinal anaesthesia – A prospective observational study

Will mpox go global again? Research shows it’s evolving in curious ways

Distributed multitudes of bio-inspired, biodegradable Lagrangian sensors for environmental sustainability

Baseline perfusion index as a predictor of hypotension following spinal anaesthesia in elderly patients undergoing lower limb orthopaedic surgery

H3K27me3-dependent imprinting and transcriptional regulation in early mouse embryos requires EZHIP-mediated restriction of PRC2 activity

Post-simulation knowledge, confidence, and satisfaction in simulation-naïve anaesthesia postgraduates: A questionnaire-based survey and quality improvement initiative

Huge Chinese cell atlas reveals surprising immune variation among peoples

Asynchrony and functional diversity couple herbivore community dynamics to host plant diversity

Abstract Biodiversity loss can destabilize ecosystem functioning. How biodiversity–stability relationships are interlinked across trophic levels remains poorly investigated, however, limiting our ability to predict ecosystem-level consequences of declining biodiversity. Here, we analyze the drivers of multi-year herbivore community stability—as a key connector between primary producers and higher trophic levels—and its coupling with host tree diversity and growth stability along a subtropical tree diversity gradient. Phylogenetic diversity, abundance asynchrony and population stability of herbivores emerge as key intra-community regulators of herbivore temporal stability. These regulators, in turn, are strongly affected by changes in tree species richness through tree functional diversity, tree growth asynchrony, and tree growth population stability. Importantly, accounting for herbivore dietary specialization unveils clear stabilizing effects of tree species richness on the community stability of specialists but not of generalists. For the overall herbivore community, higher tree richness results in less stable abundance dynamics. Our findings suggest that biodiversity loss will propagate bottom-up to affect the stability of communities at higher trophic levels, and particularly destabilize communities of more vulnerable specialists. Global change and plantation management may thus also compromise biodiversity conservation by reducing abundance and species richness stability of higher trophic levels.

Analgesic efficacy of thoracic interfascial plane blocks in multiple rib fractures: A prospective, non-randomized, controlled, double-blinded study

Putting immune cells into ‘night mode’ reduces heart-attack damage

Mixed-model and transcriptome-wide association analyses identify transcription factors and genes associated with colorectal cancer susceptibility

Dose–response relationship of local anaesthetic volume to hemidiaphragmatic paralysis following ultrasound-guided supraclavicular brachial plexus block: A randomised controlled trial

Reducibility of higher-order networks from dynamics

Abstract Empirical complex systems can be characterized not only by pairwise interactions, but also by higher-order (group) interactions influencing collective phenomena, from metabolic reactions to epidemics. Nevertheless, higher-order networks’ apparent superior descriptive power—compared to classical pairwise networks—comes with a much increased model complexity and computational cost, challenging their application. Consequently, it is of paramount importance to establish a quantitative method to determine when such a modeling framework is advantageous with respect to pairwise models, and to which extent it provides a valuable description of empirical systems. Here, we propose an information-theoretic framework, accounting for how structures affect diffusion behaviors, quantifying the entropic cost and distinguishability of higher-order interactions to assess their reducibility to lower-order structures while preserving relevant functional information. Empirical analyses indicate that some systems retain essential higher-order structure, whereas in some technological and biological networks it collapses to pairwise interactions. With controlled randomization procedures, we investigate the role of nestedness and degree heterogeneity in this reducibility process. Our findings contribute to ongoing efforts to minimize the dimensionality of models for complex systems.

From gigabytes to the bedside: Small language models as practical clinical AI in anaesthesiology