Kinematics Governing Mechanotransduction in the Sensory Hair of the Venus flytrap

Biomechanics on Ultra-Sensitivity of Venus Flytrap's Micronewton Trigger Hairs

Numerous plants evolve ingeniously microcantilever-based hairs to ultra-sensitively detect out-of-plane quasi-static tactile loads, providing a natural blueprint for upgrading the industrial static mode microcantilever sensors, but how do the biological sensory hairs work mechanically? Here, the action potential-producing trigger hairs of carnivorous Venus flytraps (Dionaea muscipula) are investigated in detail from biomechanical perspective. Under tiny mechanical stimulation, the deformable trigger hair, composed of distal stiff lever and proximal flexible podium, will lead to rapid trap closure and prey capture. The multiple features determining the sensitivity such as conical morphology, multi-scale functional structures, kidney-shaped sensory cells, and combined deformation under tiny mechanical stimulation are comprehensively researched. Based on materials mechanics, finite element simulation, and bio-inspired original artificial sensors, it is verified that the omnidirectional ultra-sensitivity of trigger hair is attributed to the stiff-flexible coupling of material, the double stress concentration, the circular distribution of sensory cells, and the positive local buckling. Also, the balance strategy of slender hair between sensitivity and structural stability (i.e., avoiding disastrous collapse) is detailed revealed. The unique basic biomechanical mechanism underlying trigger hairs is essential for significantly enhancing the performance of the traditional industrial static mode microcantilever sensors, and ensure the stability of arbitrary load perception.

Mechanosensor for Proprioception Inspired by Ultrasensitive Trigger Hairs of Venus Flytrap

Mechanosensors, as the core component of a proprioceptive system, can detect many types of mechanical signals in their surroundings, such as force signals, displacement signals, and vibration signals. It is understandable that the development of an all-new mechanosensory structure that can be widely used is highly desirable. This is because it can markedly improve the detection performance of mechanosensors. Coincidentally, in nature, optimized microscale trigger hairs of Venus flytrap are ingeniously used as a mechanosensory structure. These trigger hairs are utilized for tactile mechanosensilla to efficiently detect external mechanical stimuli. Biological trigger hair-based mechanosensilla offer an all-new bio-inspired strategy. This strategy utilizes the notch structure and variable stiffness to enhance the perceptual performance of mechanosensors. In this study, the structure-performance-application coupling relationship of trigger hair-based mechanosensors is explored through experiment and analysis. An artificial trigger hair-based mechanosensor is developed by mimicking the deformation properties of the Venus flytrap trigger hair. This bio-inspired mechanosensor shows excellent performance in terms of mechanical stability, response time, and sensitivity to mechanical signals.

Digital image correlation techniques for motion analysis and biomechanical characterization of plants

Temporally and spatially complex 3D deformation processes appear in plants in a variety of ways and are difficult to quantify in detail by classical cinematographic methods. Furthermore, many biomechanical test methods, e.g. regarding compression or tension, result in quasi-2D deformations of the tested structure, which are very time-consuming to analyze manually regarding strain fields. In materials testing, the contact-free optical 2D- or 3D-digital image correlation method (2D/3D-DIC) is common practice for similar tasks, but is still rather seldom used in the fundamental biological sciences. The present review aims to highlight the possibilities of 2D/3D-DIC for the plant sciences. The equipment, software, and preparative prerequisites are introduced in detail and advantages and disadvantages are discussed. In addition to the analysis of wood and trees, where DIC has been used since the 1990s, this is demonstrated by numerous recent approaches in the contexts of parasite-host attachment, cactus joint biomechanics, fruit peel impact resistance, and slow as well as fast movement phenomena in cones and traps of carnivorous plants. Despite some technical and preparative efforts, DIC is a very powerful tool for full-field 2D/3D displacement and strain analyses of plant structures, which is suitable for numerous in-depth research questions in the fields of plant biomechanics and morphogenesis.

Engineering Themes in Plant Forms and Functions

Living structures constantly interact with the biotic and abiotic environment by sensing and responding via specialized functional parts. In other words, biological bodies embody highly functional machines and actuators. What are the signatures of engineering mechanisms in biology? In this review, we connect the dots in the literature to seek engineering principles in plant structures. We identify three thematic motifs-bilayer actuator, slender-bodied functional surface, and self-similarity-and provide an overview of their structure-function relationships. Unlike human-engineered machines and actuators, biological counterparts may appear suboptimal in design, loosely complying with physical theories or engineering principles. We postulate what factors may influence the evolution of functional morphology and anatomy to dissect and comprehend better the why behind the biological forms.

Shapeshifting in the Venus flytrap (Dionaea muscipula): Morphological and biomechanical adaptations and the potential costs of a failed hunting cycle

The evolutionary roots of carnivory in the Venus flytrap (Dionaea muscipula) stem from a defense response to plant injury caused by, e.g., herbivores. Dionaea muscipula aka. Darwin's most wonderful plant underwent extensive modification of leaves into snap-traps specialized for prey capture. Even the tiny seedlings of the Venus flytrap already produce fully functional, millimeter-sized traps. The trap size increases as the plant matures, enabling capture of larger prey. The movement of snap-traps is very fast (~100-300 ms) and is actuated by a combination of changes in the hydrostatic pressure of the leaf tissue with the release of prestress (embedded energy), triggering a snap-through of the trap lobes. This instability phenomenon is facilitated by the double curvature of the trap lobes. In contrast, trap reopening is a slower process dependent on trap size and morphology, heavily reliant on turgor and/or cell growth. Once a prey item is caught, the trap reconfigures its shape, seals itself off and forms a digestive cavity allowing the plant to release an enzymatic cocktail to draw nutrition from its captive. Interestingly, a failed attempt to capture prey can come at a heavy cost: the trap can break during reopening, thus losing its functionality. In this mini-review, we provide a detailed account of morphological adaptations and biomechanical processes involved in the trap movement during D. muscipula hunting cycle, and discuss possible reasons for and consequences of trap breakage. We also provide a brief introduction to the biological aspects underlying plant motion and their evolutionary background.

Signaling and transport processes related to the carnivorous lifestyle of plants living on nutrient-poor soil

In Eukaryotes, long-distance and rapid signal transmission is required in order to be able to react fast and flexibly to external stimuli. This long-distance signal transmission cannot take place by diffusion of signal molecules from the site of perception to the target tissue, as their speed is insufficient. Therefore, for adequate stimulus transmission, plants as well as animals make use of electrical signal transmission, as this can quickly cover long distances. This update summarises the most important advances in plant electrical signal transduction with a focus on the carnivorous Venus flytrap. It highlights the different types of electrical signals, examines their underlying ion fluxes and summarises the carnivorous processes downstream of the electrical signals.

Mechanical factors contributing to the Venus flytrap's rate-dependent response to stimuli

The sensory hairs of the Venus flytrap (Dionaea muscipula Ellis) detect mechanical stimuli imparted by their prey and fire bursts of electrical signals called action potentials (APs). APs are elicited when the hairs are sufficiently stimulated and two consecutive APs can trigger closure of the trap. Earlier experiments have identified thresholds for the relevant stimulus parameters, namely the angular displacement [Formula: see text] and angular velocity [Formula: see text]. However, these experiments could not trace the deformation of the trigger hair's sensory cells, which are known to transduce the mechanical stimulus. To understand the kinematics at the cellular level, we investigate the role of two relevant mechanical phenomena: viscoelasticity and intercellular fluid transport using a multi-scale numerical model of the sensory hair. We hypothesize that the combined influence of these two phenomena and [Formula: see text] contribute to the flytrap's rate-dependent response to stimuli. In this study, we firstly perform sustained deflection tests on the hair to estimate the viscoelastic material properties of the tissue. Thereafter, through simulations of hair deflection tests at different loading rates, we were able to establish a multi-scale kinematic link between [Formula: see text] and the cell wall stretch [Formula: see text]. Furthermore, we find that the rate at which [Formula: see text] evolves during a stimulus is also proportional to [Formula: see text]. This suggests that mechanosensitive ion channels, expected to be stretch-activated and localized in the plasma membrane of the sensory cells, could be additionally sensitive to the rate at which stretch is applied.

Association between aortic calcification and the presence of kidney stones: calcium oxalate calculi in focus

PURPOSE

The current research is aimed at analyzing the relationship between kidney stone (KS) and abdominal aortic calcification (AAC) and the relationship between KS components and AAC.

METHODS

This is a retrospective, case-control study. Kidney stone formers (KSFs) were treated at the Department of Urology, West China Hospital, Sichuan University for urological calculus disease from January 2014 to January 2020. Matched non-stone formers (non-SFs) were drawn from the same hospital for routine health examination from January 2018 to February 2019. Research-related information was collected and reviewed retrospectively from the hospital's computerized records. AAC were evaluated using available results of computed tomography imaging and abdominal vascular ultrasound. The relationships of AAC between KSFs and non-SFs were compared. The composition of renal calculi was analyzed by Fourier-transform infrared spectrophotometer. KSFs were divided into AAC groups and non-AAC based on AAC. The relationship of the composition of renal calculi between AAC and non-AAC were compared. The independent-sample t test, the chi-squared test and binary logistics regression were performed.

RESULTS

Altogether, 4516 people were included, with 1027 KSFs and 3489 non-SFs. There were no significant differences in the laboratory parameters between KSFs and non-SFs. The association between the presence of AAC and KS was significant in multivariable model 2 [adjusting hypertension, diabetes mellitus, fasting blood glucose, uric acid, serum triglyceride (TG), serum calcium, and urine pH] (OR 5.756, 95% CI 4.616-7.177, p < 0.001). The result of KSFs showed that calcium oxalate calculi (CaOx) was significantly associated with AAC in multivariable model 3 (adjusting age, hypertension, diabetes mellitus, drinking history, smoking history, and TG) (OR 1.351, 95% CI 1.002-1.822, p = 0.048).

CONCLUSIONS

The current study pioneered the revelation of the relationship between CaOx and AAC. Through an elimination of the confounding factors, the study demonstrated that KS and AAC were connected.