Smartphone-Derived Seismocardiography: Robust Approach for Accurate Cardiac Energy Assessment in Patients with Various Cardiovascular Conditions.

Seismocardiography (SCG), a method for measuring heart-induced chest vibrations, is gaining attention as a non-invasive, accessible, and cost-effective approach for cardiac pathologies, diagnosis, and monitoring. This study explores the integration of SCG acquired through smartphone technology by assessing the accuracy of metrics derived from smartphone recordings and their consistency when performed by patients. Therefore, we assessed smartphone-derived SCG's reliability in computing median kinetic energy parameters per record in 220 patients with various cardiovascular conditions. The study involved three key procedures: (1) simultaneous measurements of a validated hardware device and a commercial smartphone; (2) consecutive smartphone recordings performed by both clinicians and patients; (3) patients' self-conducted home recordings over three months. Our findings indicate a moderate-to-high reliability of smartphone-acquired SCG metrics compared to those obtained from a validated device, with intraclass correlation (ICC) > 0.77. The reliability of patient-acquired SCG metrics was high (ICC > 0.83). Within the cohort, 138 patients had smartphones that met the compatibility criteria for the study, with an observed at-home compliance rate of 41.4%. This research validates the potential of smartphone-derived SCG acquisition in providing repeatable SCG metrics in telemedicine, thus laying a foundation for future studies to enhance the precision of at-home cardiac data acquisition.

Is fracture management merely a physical process? Exploring the psychological effects of internal and external fixation.

BACKGROUND: Internal and external fixation are common surgical procedures for treating fractures. However, the impact of different surgical approaches (including internal and external fixations) on patients' psychological status and Quality of Life (QoL) is rarely examined. Herein, we aimed to investigate the effects of internal and external fixation on anxiety, depression, insomnia, and overall mental and physical health in Distal Radius Fractures (DRF) patients. METHODS: We performed a retrospective study on 96 fracture patients who underwent internal fixation (57 patients) or external fixation (39 patients). The Visual Analog Scale (VAS), the Hospital Anxiety and Depression Scale (HADS), the Athens Insomnia Scale (AIS), and the Medical Outcomes Study Short Form 36 (SF-36) questionnaire were used to assess the patients' pain, anxiety, depression, sleep, and QoL before surgery and at seven days, one month, and three months post-surgery. RESULTS: The VAS scores were significantly lower in the Internal Fixation Group (IFG) than in the External Fixation Group (EFG) on the seventh day and one month postoperatively (P < 0.05). Although both groups showed no significant anxiety, depression, or insomnia before surgery (P > 0.05), the EFG showed significantly higher HADS-A, HADS-D, and AIS scores than the IFG at seven days and one and three months postoperatively (P < 0.05). Additionally, changes in HADS-A, HADS-D, and AIS scores were most significant at day seven post-surgery in the EFG (P < 0.05). Furthermore, no significant difference was found between the two groups in the average Physical Component Summary (PCS) and Mental Component Summary (MCS) scores before surgery (P > 0.05). However, both groups showed positive changes in PCS and MCS scores at postoperative day seven and one and three months postoperatively, with the IFG having significantly higher average PCS and MCS scores compared to the EFG (P < 0.05). CONCLUSION: Compared to external fixation, internal fixation did not significantly impact patients' emotions regarding anxiety and depression in the early postoperative period, and physical and mental health recovery was better during the postoperative rehabilitation period. Furthermore, when there are no absolute indications, the impact on patients' psychological well-being should be considered as one of the key factors in the treatment plan during surgical approach selection.

Correlation between acoustic characteristics and sensory evaluation of puffed-grain food based on energy analysis.

Puffed-grain food is a crispy snack whose consumer satisfaction depends on snack crispness and crunchiness, which can be characterized by the sound and the acoustic signals of food breaking. This study aimed to evaluate whether acoustic characteristics can be used to predict the crispness of various puffed-grain food. Sensory evaluation was performed on puffed-grain products with varying hygroscopic durations and different types. The relation between sensory evaluation and acoustic characteristics of nine different types of food was examined. The Hilbert-Huang transform was used to perform energy segmentation of the acoustic signal of puffed-grain food and observe its energy migration process. The results showed that energy release was more concentrated in the low-frequency range for grain-puffed foods with different hygroscopic durations. No notable correlation was observed between the low-frequency interval and sensory crispness for the different types of puffed-grain foods. However, the acoustic features extracted from their inherent low-frequency intervals showed a significantly improved correlation with sensory crispness. Therefore, it provides a theoretical reference for applying acoustic characteristics to describe food texture.

Validation of the IDDSI funnel for liquid flow testing.

In 2017, the International Dysphagia Diet Standardisation Initiative (IDDSI) introduced the IDDSI flow test which enables patients, clinicians, caregivers, food service professionals and researchers to classify liquid thickness into five levels based on the volume of liquid remaining in a standard 10 mL slip tip syringe after 10 s of flow under gravity. Within a few months of publishing the IDDSI flow test instructions, several barriers emerged: (1) the preferred model of syringe (BD 303134) was not equally accessible around the world, causing some users to perform flow tests with alternate models of syringe; (2) differences in syringe geometry across models led to variations in IDDSI flow test results; and (3) the need to use a second syringe for sample loading added complexity and cost to end users. To address these barriers, IDDSI designed the IDDSI funnel, a novel device, which combines the geometry of the BD 303134 syringe with a kitchen funnel to facilitate easy loading of liquid samples without need for a second syringe. In this report, we compare the IDDSI flow test results across two devices: syringe BD 303134 and IDDSI funnel. IDDSI level classifications were in complete agreement with the syringe reference test results in 67/73 (92%) of the test fluids and temperature conditions with mean difference of residual liquid across devices of 0.2 (2% full scale). These results demonstrate excellent correspondence between the two devices.

Substrate evaporation drives collective construction in termites.

Termites build complex nests which are an impressive example of self-organization. We know that the coordinated actions involved in the construction of these nests by multiple individuals are primarily mediated by signals and cues embedded in the structure of the nest itself. However, to date there is still no scientific consensus about the nature of the stimuli that guide termite construction, and how they are sensed by termites. In order to address these questions, we studied the early building behavior of Coptotermes gestroi termites in artificial arenas, decorated with topographic cues to stimulate construction. Pellet collections were evenly distributed across the experimental setup, compatible with a collection mechanism that is not affected by local topography, but only by the distribution of termite occupancy (termites pick pellets at the positions where they are). Conversely, pellet depositions were concentrated at locations of high surface curvature and at the boundaries between different types of substrate. The single feature shared by all pellet deposition regions was that they correspond to local maxima in the evaporation flux. We can show analytically and we confirm experimentally that evaporation flux is directly proportional to the local curvature of nest surfaces. Taken together, our results indicate that surface curvature is sufficient to organize termite building activity and that termites likely sense curvature indirectly through substrate evaporation. Our findings reconcile the apparently discordant results of previous studies.

From an obliquely falling rod in a viscous fluid to the motion of suspended magnetic bead chains that are driven by a gradient magnetic field and that make an arbitrary angle with the magnetic force vector: A Stokes flow study.

In view of the growing role of magnetic particles under magnetic field influence in medical and other applications, and perforce the bead chaining, it is important to understand more generally the chain dynamics. As is well known, in the presence of a magnetic field, magnetic beads tend to form chains that are aligned with the magnetic field vector. In addition, if there is a magnetic field gradient, there will be a magnetic force acting on this chain. The main goal of the present research is to study the motion of a magnetic bead chain that makes an arbitrary angle with the magnetic force vector in the Stokes flow limit, that is, in the limit of zero Reynolds number. We used the public-domain computer program HYDRO++ to calculate the mobility matrix, which relates the magnetic force acting on the chain to the velocity of the chain, for a chain of N beads making an arbitrary angle with the magnetic force vector. Because of the presence of off-diagonal elements of the mobility matrix, as the chain is drawn in the direction of the magnetic force, it is also deflected to the side. We derived analytic solutions for this motion. Also, for bead chains moving in directions both parallel and perpendicular to their lengths, we fit three-parameter functions to solutions from HYDRO++. We found the fits to be excellent. Combining these results with the analytic solutions, we obtained expressions for the velocity components for the bead chains that provide excellent fits to HYDRO++ solutions for arbitrary angles. Finally, we apply the methodology used for the bead chain studies to the study of an obliquely falling rod in a viscous fluid and derive analytic solutions for the velocity components of the obliquely falling rod.

Research on distributionally robust energy storage capacity allocation for output fluctuations in high permeability wind and solar distribution networks.

This paper presents a novel approach to addressing the challenges associated with energy storage capacity allocation in high-permeability wind and solar distribution networks. The proposed method is a two-phase distributed robust energy storage capacity allocation method, which aims to regulate the stochasticity and volatility of net energy output. Firstly, an energy storage capacity allocation model is established, which considers energy storage's investment and operation costs to minimize the total cost. Then, a two-stage distributed robust energy storage capacity allocation model is established with the confidence set of uncertainty probability distribution constrained by 1-norm and ∞-norm. Finally, a Column and Constraint Generation (C&CG) algorithm is used to solve the problem. The validity of the proposed energy storage capacity allocation model is confirmed by examining different wind and solar penetration levels. Furthermore, the model's superiority is demonstrated by comparing it with deterministic and robust models.

Land Resources for Wind Energy Development Requires Regionalized Characterizations.

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. We developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m2/MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m2 and 0.05 ± 0.01 m2/MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

Millimeter-scale magnetic implants paired with a fully integrated wearable device for wireless biophysical and biochemical sensing.

Implantable sensors can directly interface with various organs for precise evaluation of health status. However, extracting signals from such sensors mainly requires transcutaneous wires, integrated circuit chips, or cumbersome readout equipment, which increases the risks of infection, reduces biocompatibility, or limits portability. Here, we develop a set of millimeter-scale, chip-less, and battery-less magnetic implants paired with a fully integrated wearable device for measuring biophysical and biochemical signals. The wearable device can induce a large amplitude damped vibration of the magnetic implants and capture their subsequent motions wirelessly. These motions reflect the biophysical conditions surrounding the implants and the concentration of a specific biochemical depending on the surface modification. Experiments in rat models demonstrate the capabilities of measuring cerebrospinal fluid (CSF) viscosity, intracranial pressure, and CSF glucose levels. This miniaturized system opens the possibility for continuous, wireless monitoring of a wide range of biophysical and biochemical conditions within the living organism.

Energy and Speed Landscapes of the Membrane Internalization Behavior of Soft Nanoparticles.

The cellular endocytosis of nanoparticles (NPs) is a fundamental biological process with significant potential in biomedical applications. However, a comprehensive understanding of the mechanistic aspects of endocytosis and the impact of particle properties on this process remains elusive. In this study, we investigated the membrane-wrapping behavior of soft NPs (SNPs) with varying rigidities using theoretical calculations. Our findings reveal that the membrane-wrapping process of SNPs involves a complex energy change including the possible existence of an energy barrier; moreover, it is found that the location and height of this barrier strongly depend on the mechanistic properties of the NPs and membranes. Additionally, by considering force balance in the membrane-wrapping process, we calculated the speed at which NP is internalized by the membrane, showing a nonmonotonic dependence on particle rigidity and/or wrapping degree. These phenomena can be attributed to competition between different energy components associated with NP-membrane binding, membrane tension, and deformations occurring during SNP-membrane interaction processes. Our results contribute to a deeper understanding of cellular-level endocytosis mechanisms and offer potential applications for soft NPs in biomedicine.

Floating photocatalysts as promising materials for environmental detoxification and energy production: A review.

The oxygenation process of the catalyst surface, the incident-light harvesting capability, and facile recycling of utilized photocatalysts play key role in the outstanding photocatalytic performances. The typical existing photocatalysts in powder form have many drawbacks, such as difficult separation from the treated water, insufficient surface oxygenation, poor active surface area, low incident-light harvesting ability, and secondary pollution of the environment. A great number of scientific works introduced novel and fresh ideas related to designing floating photocatalytic systems by immobilizing highly active photocatalysts onto a floatable substrate. Thanks to direct contact with the illuminated light and oxygen molecules in the interface of water/air, the photocatalytic performance is maximized through production of more reactive species, employed in the photocatalytic reactions. Furthermore, facile recovering of the utilized photocatalysts for next processes avoids secondary pollution as well as diminishes the process's price. This review highlights the performance of developed floating photocatalysts for diverse applications. Furthermore, different floating substrates and possible mechanisms in floating photocatalysts are briefly mentioned. In addition, several emerging self-floating photocatalytic systems are taken attention and discussed. Specially, coupling photo-thermal and photocatalytic effects seems to be a good strategy for introducing a new class of floating photocatalyst to utilize the free, abundant, and green sunlight energy for the aims of water desalination and purification. Despite of a large number of attempts about the floating photocatalysts, there are still plenty of rooms for more in-depth research to be carried out for attaining the required characteristics of the large scale utilizations of these materials.

Tunable evaporation-induced surface morphologies on chitosan film for light management.

The surface morphologies of polymer films have been used to improve the performance or enable new applications of films, such as controllable adhesion, shape morphing and light management. However, complicated and destructive methods were applied to produce surface morphologies on chitosan (CS) film. To overcome this challenge, we report an evaporation-induced self-assembly to form the tunable morphologies on the surface of short-chain chitosan film by varying the evaporation rates that influence the aggregation behavior of polymer chains between order and disorder. It enables the simple, tunable and scalable fabrication of surface morphologies on CS film (CS solution concentration: 2 wt%, drying from room temperature (RT) to 80 °C) that provides controllable haze (3-74 %) and high transmittance (>85 %) for the production of hazy and transparent window coatings. This simple approach to producing tunable surface morphologies could inspire the synthesis of multifunctional polymer films with different surface structures, whose applications can be extended to cell culture interfaces, flexible bioelectronic and optoelectronic devices.

DNA nanomachines reveal an adaptive energy mode in confinement-induced amoeboid migration powered by polarized mitochondrial distribution.

Energy metabolism is highly interdependent with adaptive cell migration in vivo. Mechanical confinement is a critical physical cue that induces switchable migration modes of the mesenchymal-to-amoeboid transition (MAT). However, the energy states in distinct migration modes, especially amoeboid-like stable bleb (A2) movement, remain unclear. In this report, we developed multivalent DNA framework-based nanomachines to explore strategical mitochondrial trafficking and differential ATP levels during cell migration in mechanically heterogeneous microenvironments. Through single-particle tracking and metabolomic analysis, we revealed that fast A2-moving cells driven by biomimetic confinement recruited back-end positioning of mitochondria for powering highly polarized cytoskeletal networks, preferentially adopting an energy-saving mode compared with a mesenchymal mode of cell migration. We present a versatile DNA nanotool for cellular energy exploration and highlight that adaptive energy strategies coordinately support switchable migration modes for facilitating efficient metastatic escape, offering a unique perspective for therapeutic interventions in cancer metastasis.

Study of Hydration Repulsion of Zwitterionic Polymer Brushes Resistant to Protein Adhesion through Molecular Simulations.

The fabrication of antifouling zwitterionic polymer brushes represents a leading approach to mitigate nonspecific adhesion on the surfaces of medical devices. This investigation seeks to elucidate the correlation between the material composition and structural attributes of these polymer brushes in preventing protein adhesion. To achieve this goal, we modeled three different zwitterionic brushes, namely, carboxybetaine methacrylate (CBMA), sulfobetaine methacrylate (SBMA), and (2-(methacryloyloxy)ethyl)-phosphorylcholine (MPC). The simulations revealed that elevating the grafting density enhances the structural stability, hydration strength, and resistance to protein adhesion exhibited by the polymer brushes. PCBMA manifests a more robust hydration layer, while PMPC demonstrates the slightest interaction with proteins. In a comprehensive evaluation, PSBMA polymer brushes emerged as the best choice with superior stability, enhanced protein repulsion, and minimally induced protein deformation, resulting in effective resistance to nonspecific adhesion. The high-density SBMA polymer brushes significantly reduce the level of protein adhesion in AFM testing. In addition, we have pioneered the quantitative characterization of hydration repulsion in polymer brushes by analyzing the hydration repulsion characteristics at different materials and graft densities. In summary, our study provides a nuanced understanding of the material and structural determinants influencing the capacity of zwitterionic polymer brushes to thwart protein adhesion. Additionally, it presents a quantitative elucidation of hydration repulsion, contributing to the advancement and application of antifouling polymer brushes.

Enhanced deep unrolling networks for snapshot compressive hyperspectral imaging.

Snapshot compressive hyperspectral imaging necessitates the reconstruction of a complete hyperspectral image from its compressive snapshot measurement, presenting a challenging inverse problem. This paper proposes an enhanced deep unrolling neural network, called EDUNet, to tackle this problem. The EDUNet is constructed via the deep unrolling of a proximal gradient descent algorithm and introduces two innovative modules for gradient-driven update and proximal mapping reflectivity. The gradient-driven update module leverages a memory-assistant descent approach inspired by momentum-based acceleration techniques, for enhancing the unrolled reconstruction process and improving convergence. The proximal mapping is modeled by a sub-network with a cross-stage spectral self-attention, which effectively exploits the inherent self-similarities present in hyperspectral images along the spectral axis. It also enhances feature flow throughout the network, contributing to reconstruction performance gain. Furthermore, we introduce a spectral geometry consistency loss, encouraging EDUNet to prioritize the geometric layouts of spectral curves, leading to a more precise capture of spectral information in hyperspectral images. Experiments are conducted using three benchmark datasets including KAIST, ICVL, and Harvard, along with some real data, comprising a total of 73 samples. The experimental results demonstrate that EDUNet outperforms 15 competing models across four metrics including PSNR, SSIM, SAM, and ERGAS.

Multi-energy blended CBCT spectral imaging and scatter-decoupled material decomposition using a spectral modulator with flying focal spot (SMFFS).

BACKGROUND: Cone-beam CT (CBCT) has been extensively employed in industrial and medical applications, such as image-guided radiotherapy and diagnostic imaging, with a growing demand for quantitative imaging using CBCT. However, conventional CBCT can be easily compromised by scatter and beam hardening artifacts, and the entanglement of scatter and spectral effects introduces additional complexity. PURPOSE: The intertwined scatter and spectral effects within CBCT pose significant challenges to the quantitative performance of spectral imaging. In this work, we present the first attempt to develop a stationary spectral modulator with flying focal spot (SMFFS) technology as a promising, low-cost approach to accurately solving the x-ray scattering problem and physically enabling spectral imaging in a unified framework, and with no significant misalignment in data sampling of spectral projections. METHODS: To deal with the intertwined scatter-spectral challenge, we propose a novel scatter-decoupled material decomposition (SDMD) method for SMFFS, which consists of four steps in total, including (1) spatial resolution-preserved and noise-suppressed multi-energy "residual" projection generation free from scatter, based on a hypothesis of scatter similarity; (2) first-pass material decomposition from the generated multi-energy residual projections in non-penumbra regions, with a structure similarity constraint to overcome the increased noise and penumbra effect; (3) scatter estimation for complete data; and (4) second-pass material decomposition for complete data by using a multi-material spectral correction method. Monte Carlo simulations of a pure-water cylinder phantom with different focal spot deflections are conducted to validate the scatter similarity hypothesis. Both numerical simulations using a clinical abdominal CT dataset, and physics experiments on a tabletop CBCT system using a Gammex multi-energy CT phantom and an anthropomorphic chest phantom, are carried out to demonstrate the feasibility of CBCT spectral imaging with SMFFS and our proposed SDMD method. RESULTS: Monte Carlo simulations show that focal spot deflections within a range of 2 mm share quite similar scatter distributions overall. Numerical simulations demonstrate that SMFFS with SDMD method can achieve better material decomposition and CT number accuracy with fewer artifacts. In physics experiments, for the Gammex phantom, the average error of the mean values ( E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ ) in selected regions of interest (ROIs) of virtual monochromatic image (VMI) at 70 keV is 8 HU in SMFFS cone-beam (CB) scan, and 19 and 210 HU in sequential 80/120 kVp (dual kVp, DKV) CB scan with and without scatter correction, respectively. For the chest phantom, the E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ in selected ROIs of VMIs is 12 HU for SMFFS CB scan, and 15 and 438 HU for sequential 80/140 kVp CB scan with and without scatter correction, respectively. Also, the non-uniformity among selected regions of the chest phantom is 14 HU for SMFFS CB scan, and 59 and 184 HU for the DKV CB scan with and without a traditional scatter correction method, respectively. CONCLUSIONS: We propose a SDMD method for CBCT with SMFFS. Our preliminary results show that SMFFS can enable spectral imaging with simultaneous scatter correction for CBCT and effectively improve its quantitative imaging performance.

Research on energy-saving control of agricultural hybrid tractors integrating working condition prediction.

To address the issues of tractors using too much fuel and not being energy efficient, a predictive control strategy based on Pontryagin's minimum principle integrating working condition prediction is proposed for agricultural hybrid tractors. The Dongfanghong 1804 tractor is being used for research. Firstly, the main parameters of the hybrid drive system are determined and modeled. Secondly, based on the adaptive cubic exponential forecasting method, the working condition information for a period of time in the future is predicted through historical working condition information. Furthermore, combining the predicted working conditions information, the goal is to minimize the total energy consumption cost of the entire machine. Motor power and diesel engine power are control variables. The battery state of charge is a state variable. Subsequently, a predictive control strategy based on Pontryagin's minimum principle integrating working condition prediction is proposed. Finally, the simulation test is carried out based on the MATLAB simulation platform. Research indicates: under plowing conditions, compared with the power following control strategy, the proposed predictive control strategy can effectively manage the performance of the diesel engine and motor, ensuring they operate at their most efficient level. The total energy consumption costs of the power following control and predictive control strategies are 37.17 China Yuan (CNY) and 33.67 CNY, respectively. The cost of energy used is decreased by 9. 42%, which helps make tractor field plowing more efficient and economical.

Structural performance of the concrete-filled tube column with internal triangular units subjected to axial compression.

This study introduces a novel concrete-filled tube (CFT) column system featuring a steel tube comprised of four internal triangular units. The incorporation of these internal triangular units serves to reduce the width-thickness ratio of the steel tube and augment the effective confinement area of the infilled concrete. This design enhancement is anticipated to result in improved structural strength and ductility, contributing to enhanced overall performance and sustainability. To assess the effectiveness of the newly proposed column system, a full-scale test was conducted on five square steel tube column specimens subjected to axial compression. Among these specimens, two adhered to the conventional steel tube column design, while the remaining three featured the new CFT columns with internal triangular units. The shape of the CFT column, the presence of infilled concrete and the presence of openings on the ITUs were considered as test parameters. The test results reveal that the ductility of the newly proposed CFT column system exhibited a minimum 30% improvement compared to the conventional CFT column. In addition, the initial stiffness and axial compressive strength of the new system were found to be comparable to those of the conventional CFT column.

A minimal physical model for curvotaxis driven by curved protein complexes at the cell's leading edge.

Cells often migrate on curved surfaces inside the body, such as curved tissues, blood vessels, or highly curved protrusions of other cells. Recent in vitro experiments provide clear evidence that motile cells are affected by the curvature of the substrate on which they migrate, preferring certain curvatures to others, termed "curvotaxis." The origin and underlying mechanism that gives rise to this curvature sensitivity are not well understood. Here, we employ a "minimal cell" model which is composed of a vesicle that contains curved membrane protein complexes, that exert protrusive forces on the membrane (representing the pressure due to actin polymerization). This minimal-cell model gives rise to spontaneous emergence of a motile phenotype, driven by a lamellipodia-like leading edge. By systematically screening the behavior of this model on different types of curved substrates (sinusoidal, cylinder, and tube), we show that minimal ingredients and energy terms capture the experimental data. The model recovers the observed migration on the sinusoidal substrate, where cells move along the grooves (minima), while avoiding motion along the ridges. In addition, the model predicts the tendency of cells to migrate circumferentially on convex substrates and axially on concave ones. Both of these predictions are verified experimentally, on several cell types. Altogether, our results identify the minimization of membrane-substrate adhesion energy and binding energy between the membrane protein complexes as key players of curvotaxis in cell migration.

Stickiness in shear: stiffness, shape, and sealing in bioinspired suction cups affect shear performance on diverse surfaces.

Aquatic organisms utilizing attachment often contend with unpredictable environments that can dislodge them from substrates. To counter these forces, many organisms (e.g. fish, cephalopods) have evolved suction-based organs for adhesion. Morphology is diverse, with some disc shapes deviating from a circle to more ovate designs. Inspired by the diversity of multiple aquatic species, we investigated how bioinspired cups with different disc shapes performed in shear loading conditions. These experiments highlighted pertinent physical characteristics found in biological discs (regions of stiffness, flattened margins, a sealing rim), as well as ecologically relevant shearing conditions. Disc shapes of fabricated cups included a standard circle, ellipses, and other bioinspired designs. To consider the effects of sealing, these stiff silicone cups were produced with and without a soft rim. Cups were tested using a force-sensing robotic arm, which directionally sheared them across surfaces of varying roughness and compliance in wet conditions while measuring force. In multiple surface and shearing conditions, elliptical and teardrop shapes outperformed the circle, which suggests that disc shape and distribution of stiffness may play an important role in resisting shear. Additionally, incorporating a soft rim increased cup performance on rougher substrates, highlighting interactions between the cup materials and surfaces asperities. To better understand how these cup designs may resist shear, we also utilized a visualization technique (frustrated total internal reflection; FTIR) to quantify how contact area evolves as the cup is sheared.