Search for: All records

Orb-weaver spiders produce upwards of seven different types of silk, each with unique material properties. We focus on the adhesive within orb-weaving spider webs, aggregate glue silk. These droplets are composed of three main components: water, glycoproteins, and a wide range of low molecular mass compounds (LMMCs). These LMMCs are known to play a crucial role in maintaining the material properties of the glycoproteins, aid in water absorption from the environment, and increase surface adhesion. Orb-weavers within the Cyrtarachninae subfamily are moth specialists and have evolved glue droplets with novel material properties. This study investigated the biochemical composition and diversity of the LMMCs present in the aggregate glue of eight moth-specialist species and compared them with five generalist orb-weavers using nuclear magnetic resonance (NMR) spectroscopy. We hypothesized that the novel drying ability of moth-specialist glue was accompanied by novel LMMCs and lower overall percentages by silk weight of LMMCs. We measured no difference in LMMC weight by the type of prey specialization, but observed novel compositions in the glue of all eight moth-catching species. Further, we quantified the presence of a previously reported but unidentified compound that appears in the glue of all moth specialists. These silks can provide insight into the functions of bioadhesives and inform our own synthetic adhesives. 

ABSTRACT Nearly all fish have flexible bodies that bend as a result of internal muscular forces and external fluid forces that are dynamically coupled with the mechanical properties of the body. Swimming is therefore strongly influenced by the body's flexibility, yet we do not know how fish species vary in their flexibility and in their ability to modulate flexibility with muscle activity. A more fundamental problem is our lack of knowledge about how any of these differences in flexibility translate into swimming performance. Thus, flexibility represents a hidden axis of diversity among fishes that may have substantial impacts on swimming performance. Although engineers have made substantial progress in understanding these fluid–structure interactions using physical and computational models, the last biological review of these interactions and how they give rise to fish swimming was carried out more than 20 years ago. In this Review, we summarize work on passive and active body mechanics in fish, physical models of fish and bioinspired robots. We also revisit some of the first studies to explore flexural stiffness and discuss their relevance in the context of more recent work. Finally, we pose questions and suggest future directions that may help reveal important links between flexibility and swimming performance. 

Spiders use various combinations of silks, adhesives, and behaviors to ensnare and trap prey. A common but difficult to catch prey in most spider habitats are moths. They easily escape typical orb-webs because their bodies are covered in sacrificial scales that flake off when in contact with the web’s adhesives. This defense is defeated by spiders of the sub-family of Cyrtarachninae, moth-catching specialists who combine changes in orb-web structure, predatory behavior, and chemistry of the aggregate glue placed in those webs. The most extreme changes in web structure are shown by bolas spiders, who create a solitary capture strand containing only one or two glue droplets at the end of a single thread. They prey on male moths by releasing pheromones to draw them within range of their bolas, which they flick to ensnare the moth. We used a high-speed video camera to capture the behavior of the bolas spider Mastophora hutchinsoni. We calculated the kinematics of spiders and moths in the wild to model the physical and mechanical properties of the bolas during prey capture, the behavior of the moth, and how these factors lead to successful prey capture. We created a numerical model to explain the mechanical behavior of the bolas silk during prey capture. Our kinematic analysis shows that the material properties of the aggregate glue bolas of M. hutchinsoni are distinct from that of the other previously analyzed moth-specialist, Cyrtarachne akirai. The spring-like behavior of the M. hutchinsoni bolas suggests it spins a thicker liquid. 

ABSTRACT Morphological structures and extended phenotypes are made possible by materials that are encoded by the genome. Nearly all biomaterials are viscoelastic, which means that to understand performance, one must understand the strain rate-dependent properties of these materials in relevant ecological interactions, as the behavior of a material can vary dramatically and rapidly. Spider silks are an example of materials whose properties vary substantially intra- and inter-specifically. Here, we focus on aggregate silk, which functions as a biological adhesive. As a case study to understand how a material manifests from genome through organism to ecology, we highlight moth-specialist spiders, the Cyrtarachninae, and their glues as an ideal experimental system to investigate the relationship between genomics and ecologically variable performance of a biological material. There is a clear eco-evolutionary innovation that Cyrtarachne akirai and related species have evolved, a unique trait not found in other spiders, a glue which overcomes the scales of moths. By examining traditional orb-weavers, C. akirai and other subfamily members using biomechanical testing and genomic analysis, we argue that we can track the evolution of this novel bioadhesive and comment on the selection pressures influencing prey specialization. The importance of the ecological context of materials testing is exemplified by the poor performance of C. akirai glue on glass and the exceptional spreading ability and adhesive strength on moths. The genetic basis for these performance properties is experimentally tractable because spider silk genes are minimally pleiotropic and advances in genomic technologies now make possible the discovery of complete silk gene sequences. 

Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite this promise, most contemporary quantum methods require significant resources for variational parameter optimization and face issues with vanishing gradients, leading to experiments that are either limited in scale or lack potential for quantum advantage. To address this, we develop a general-purpose, gradient-free, and scalable quantum reservoir learning algorithm that harnesses the quantum dynamics of neutral-atom analog quantum computers to process data. We experimentally implement the algorithm, achieving competitive performance across various categories of machine learning tasks, including binary and multi-class classification, as well as timeseries prediction. Effective and improving learning is observed with increasing system sizes of up to 108 qubits, demonstrating the largest quantum machine learning experiment to date. We further observe comparative quantum kernel advantage in learning tasks by constructing synthetic datasets based on the geometric differences between generated quantum and classical data kernels. Our findings demonstrate the potential of utilizing classically intractable quantum correlations for effective machine learning. We expect these results to stimulate further extensions to different quantum hardware and machine learning paradigms, including early fault-tolerant hardware and generative machine learning tasks 

Morphological structures and extended phenotypes are made possible by materials that are encoded by the genome. Nearly all biomaterials are viscoelastic, which means that to understand performance, one must understand the strain rate-dependent properties of these materials in relevant ecological interactions, as the behavior of a material can vary dramatically and rapidly. Spider silks are an example of materials whose properties vary substantially intra- and inter-specifically. Here, we focus on aggregate silk, which functions as a biological adhesive. As a case study to understand how a material manifests from genome through organism to ecology, we highlight moth-specialist spiders, the Cyrtarachninae, and their glues as an ideal experimental system to investigate the relationship between genomics and ecologically variable performance of a biological material. There is a clear eco-evolutionary innovation that Cyrtarachne akirai and related species have evolved, a unique trait not found in other spiders, a glue which overcomes the scales of moths. By examining traditional orb-weavers, C. akirai and other subfamily members using biomechanical testing and genomic analysis, we argue that we can track the evolution of this novel bioadhesive and comment on the selection pressures influencing prey specialization. The importance of the ecological context of materials testing is exemplified by the poor performance of C. akirai glue on glass and the exceptional spreading ability and adhesive strength on moths. The genetic basis for these performance properties is experimentally tractable because spider silk genes are minimally pleiotropic and advances in genomic technologies now make possible the discovery of complete silk gene sequences.