Distinct Modes Research Articles

Surface-Driven Particle Dynamics: Sequential Synchronization of Colloidal Flow Attempted in a Static Fluidic Environment.

The collective behavior of colloids in microsystems is characterized by precise micro-object control, broadening the applications of cargo manipulation in drug delivery, microfluidics, and nanotechnology. To further investigate this potential, we introduce a cargo-manipulating platform that utilizes micromagnetic patterns and fluid flow rather than conventional fluidic components. This platform, called the flowless micropump, comprises an encapsulating fluid system within a chip, containing both actuation particles (2.8 μm in diameter) and control targets, thereby eliminating external interactions. This platform enables two distinct modes of cargo manipulation: direct control of nonmagnetic cargo (e.g., MCF-7 and THP-1 cells) and indirect manipulation of particles (e.g., polymer particles) through secondary localized fluid flow. Direct manipulation is achieved via coordinated particle collisions, facilitated by an optimized guiding wall with a height of 25 μm. Conversely, indirect manipulation allows for high-speed control and mode change of individual targets. These manipulation events are achieved using two patterned structures: railway-track and connected half-disk (conductor) patterns. By employing a conductor pattern in conjunction with a railway-track pattern, precise and agile control of microcargo (MCF-7 and THP-1 cells and polymer bead clusters) was achieved at frequencies of 1-3 Hz and a magnetic field strength of 10 mT. This study establishes a programmable platform for designing flowless micropumps with diverse functionalities for various experimental purposes. By using colloidal flow and localized fluid flow generated by the shape of magnetic patterns and semi-three-dimensional (3D) structures, this platform holds significant promise for applications in drug screening, cell-cell interaction studies, and organoid-on-chip research.

Moesin integrates cortical and lamellar actin networks during Drosophila macrophage migration

Cells are thought to adopt mechanistically distinct migration modes depending on cell-type and environmental factors. These modes are assumed to be driven by mutually exclusive actin cytoskeletal organizations, which are either lamellar (flat, branched network) or cortical (crosslinked to the plasma membrane). Here we exploit Drosophila macrophage (hemocyte) developmental dispersal to reveal that these cells maintain both a lamellar actin network at their cell front and a cortical actin network at the rear. Loss of classical actin cortex regulators, such as Moesin, perturb hemocyte morphology and cell migration. Furthermore, cortical and lamellipodial actin networks are interregulated. Upon phosphorylation and binding to the plasma membrane, Moesin is advected to the rear by lamellar actin flow. Simultaneously, the cortical actin network feeds back on the lamella to help regulate actin flow speed and leading-edge dynamics. These data reveal that hemocyte motility requires both lamellipodial and cortical actin architectures in homeostatic equilibrium.

Cortical tracking of hierarchical rhythms orchestrates the multisensory processing of biological motion

When observing others’ behaviors, we continuously integrate their movements with the corresponding sounds to enhance perception and develop adaptive responses. However, how the human brain integrates these complex audiovisual cues based on their natural temporal correspondence remains unclear. Using electroencephalogram (EEG), we demonstrated that rhythmic cortical activity tracked the hierarchical rhythmic structures in audiovisually congruent human walking movements and footstep sounds. Remarkably, the cortical tracking effects exhibit distinct multisensory integration modes at two temporal scales: an additive mode in a lower-order, narrower temporal integration window (step cycle) and a super-additive enhancement in a higher-order, broader temporal window (gait cycle). Furthermore, while neural responses at the lower-order timescale reflect a domain-general audiovisual integration process, cortical tracking at the higher-order timescale is exclusively engaged in the integration of biological motion cues. In addition, only this higher-order, domain-specific cortical tracking effect correlates with individuals’ autistic traits, highlighting its potential as a neural marker for autism spectrum disorder. These findings unveil the multifaceted mechanism whereby rhythmic cortical activity supports the multisensory integration of human motion, shedding light on how neural coding of hierarchical temporal structures orchestrates the processing of complex, natural stimuli across multiple timescales.

Cortical tracking of hierarchical rhythms orchestrates the multisensory processing of biological motion.

When observing others' behaviors, we continuously integrate their movements with the corresponding sounds to enhance perception and develop adaptive responses. However, how the human brain integrates these complex audiovisual cues based on their natural temporal correspondence remains unclear. Using electroencephalogram (EEG), we demonstrated that rhythmic cortical activity tracked the hierarchical rhythmic structures in audiovisually congruent human walking movements and footstep sounds. Remarkably, the cortical tracking effects exhibit distinct multisensory integration modes at two temporal scales: an additive mode in a lower-order, narrower temporal integration window (step cycle) and a super-additive enhancement in a higher-order, broader temporal window (gait cycle). Furthermore, while neural responses at the lower-order timescale reflect a domain-general audiovisual integration process, cortical tracking at the higher-order timescale is exclusively engaged in the integration of biological motion cues. In addition, only this higher-order, domain-specific cortical tracking effect correlates with individuals' autistic traits, highlighting its potential as a neural marker for autism spectrum disorder. These findings unveil the multifaceted mechanism whereby rhythmic cortical activity supports the multisensory integration of human motion, shedding light on how neural coding of hierarchical temporal structures orchestrates the processing of complex, natural stimuli across multiple timescales.

Multiple independent acquisitions of ACE2 usage in MERS-related coronaviruses.

The angiotensin-converting enzyme 2 (ACE2) receptor is shared by various coronaviruses with distinct receptor-binding domain (RBD) architectures, yet our understanding of these convergent acquisition events remains elusive. Here, we report that two bat MERS-related coronaviruses (MERSr-CoVs) infecting Pipistrellus nathusii (P.nat)-MOW15-22 and PnNL2018B-use ACE2 as their receptor, with narrow ortholog specificity. Cryoelectron microscopy structures of the MOW15-22/PnNL2018B RBD-ACE2 complexes unveil an unexpected and entirely distinct binding mode, mapping >45Å away from that of any other known ACE2-using coronaviruses. Functional profiling of ACE2 orthologs from 105 mammalian species led to the identification of host tropism determinants, including an ACE2 N432-glycosylation restricting viral recognition, and the design of a soluble P.nat ACE2 mutant with potent viral neutralizing activity. Our findings reveal convergent acquisition of ACE2 usage for merbecoviruses found in European bats, underscoring the extraordinary diversity of ACE2 recognition modes among coronaviruses and the promiscuity of this receptor.

In silico based re-engineering of a computationally designed biosensor with altered signalling mode and improved dynamic range.

A current challenge in the rational design of biomolecular sensors is the ability to custom design binding affinities and detection mode in silico. To this end, we re-engineered a previously reported computationally-designed fluorescent maltooligosaccharide (MOS)-detecting biosensor to both alter its ligand-binding affinity and to analyse the underlying sensing mechanism. The dynamic range of the biosensor was expanded through the computer aided introduction of a series of amino acid substitutions in the starting protein scaffold (MalX from Streptococcus pneumoniae), which generated a biosensor set with binding affinities spanning over five orders of magnitude. The impact of the introduced substitutions on the underlying mode of signal generation was assessed in silico using our previously reported Computational Identification of Non-disruptive Conjugation sites (CINC) pipeline. CINC utilizes molecular dynamics simulations and an in-house developed algorithm to examine and exploit the structural dynamics of a protein at amino acid-level resolution. Using CINC, we demonstrate that re-engineering of the MOS-detecting biosensor set resulted in sensors with two distinct output modes which differed based on local conformational changes at the fluorescently modified reporter position. These output modes were classified as "ligand-sensing"-type biosensors (readout based on the tool sensing a unique conformation in the ligand-bound state), and "apo-sensing"-type biosensors (readout based on the tool sensing a unique conformation in the apo state). Together, these results demonstrate that structural dynamics at the individual amino acid residue level can be used as an engineer-able feature to rationally alter the fluorescence reporting properties of a biosensing device. Moving forward, the CINC workflow can also be adapted for the rational design of protein dynamic properties maximizing its utility as an in silico design platform for custom biomolecular tools.

Experimental DMD Analysis of Combustion Modes and Instabilities in a Scramjet Combustor

Experimental DMD Analysis of Combustion Modes and Instabilities in a Scramjet Combustor

Improving laser directed energy deposition with wire feed-stock through beam shaping with a deformable mirror

Improving laser directed energy deposition with wire feed-stock through beam shaping with a deformable mirror

Bimodal Photothermal-driven Self-sustained Oscillator Based on MXene Structure

Bimodal Photothermal-driven Self-sustained Oscillator Based on MXene Structure

Mode recognition in a kerosene-fueled scramjet combustor by a Swin Transformer neural network

Recognizing the combustion mode in scramjet engines is critical for suppressing oscillations and stabilizing the combustion process in hypersonic aircrafts. Current accesses mainly depend on mechanical measurement and dominant frequencies based on image analysis methods, such as proper orthogonal decomposition and dynamic mode decomposition. However, these traditional methods either lack of precision or fall short of the need for prior knowledge, poor generalization, and low efficiency, posing challenges in practical implementations, especially when online controlling is highlighted in the scramjet combustions. Recently, machine learning (ML) has been introduced to the combustion community due to its superiority in high flexibility and efficiency in addressing complex problems. The classical convolutional neural network (CNN) architectures have been reported to achieve efficient combustion mode recognition in furnace combustion, swirling combustor, and rotating detonation engines. However, those CNN-based models are incapable of utilizing the global flame features and the coherences of local areas, resulting in insufficient accuracy and robustness in scramjet combustions with high inflow speed and distinct mode variations. To address this problem, this paper reports a Swin (shifted window) Transformer model, an advanced ML structure outstanding in capturing both global and local features by its self-attention mechanism with high computational efficiency, to identify combustion modes in scramjet engines. The Swin-T was trained and validated in a kerosene-fueled cavity-based scramjet combustor, and results show that it can achieve a considerable accuracy of 95.28%. Comparisons with CNN-based models further indicate that Swin-T outperforms in accuracy, efficiency, and robustness by around 0.7%, 80%, and 3%, respectively.

Rationalizing hydrogel-integrated peroxidase-mimicking nanozymes for combating drug-resistant bacteria and colorimetric sensing.

Due to the easy preparation, high stability and environmental friendliness, nanozymes are frequently used as promising substitutes to natural enzymes. However, the efficacy of nanozymes in biomedicine aspects is often hampered by their potential biotoxicity and limited bioavailability, which prompted structure adaption or carrier design to maximize nanozymes performance. Despite considerable efforts on carriers to deliver nanozymes efficiently, the systematic studies on enzyme-like activities of nanozymes related to platforms of nanozyme@carrier are sparse. Here, five types of hydrogel carriers composed by sodium alginate (SA), chitosan, gelatin, gelatin methacryloyl (GelMA), and polyacrylamide (PAM) were formed by distinct mode of polymerization to optimize the suitable carrier for peroxidase (POD)-mimic nanozyme consisted of hemin and bovine serum albumin (BSA). Among these proposed carriers, SA hydrogel emerged as the most effective carrier due to its compatible crosslinking mechanism and desirable stability for nanozyme functioning. By incorporating the POD-mimic nanozyme into the SA hydrogel, the catalytic performance of the nanozyme was effectively preserved, leading to improved antibacterial effects and superior sensing ability towards the colorimetric measurement of H2O2. Based on the rationalization of hydrogel carriers, the proposed study not only helped to understand the structure-function relationship between nanozyme and carriers, but provided an integrated nanoplatform of POD-mimic nanozyme with environmental disinfection as well as biomedical applications.

Comparative Analysis of Flow in U-Turn Rectangular Ducts with Direct Numerical Simulation

Fluid flow within U-turn rectangular ducts plays a significant role in engineering applications, particularly in heat exchangers. Efficient design and optimization of these ducts are crucial for achieving optimal performance, especially concerning heat transfer. Previous research has predominantly utilized experimental methods to study flow behaviour in U-turn ducts, focusing on factors such as pressure loss and heat transfer. Computational fluid dynamics (CFD) has also been employed to explore flow characteristics, revealing the influence of parameters such as Reynolds number and gap size on flow behaviour. However, a detailed investigation into the flow structure within U-turn ducts has been lacking. To address this gap, this study employs Direct Numerical Simulation (DNS) to conduct a thorough investigation of flow in U-turn rectangular ducts. The study is conducted by varying the Reynolds numbers from 100 to 2000 and the gap size from 50% to 150% of the duct inlet diameter. Based on the simulation, it is found three distinct flow modes: Mode 1, representing attached laminar flow; Mode 2, representing detached laminar flow; and Mode 3, representing attached vortices flow. Of the three models, it is known that high Re numbers and narrow gaps have good heat transfer performance. These findings offer crucial guidance for designing efficient U-turn duct systems and lay the foundation for future research exploring more complex flow scenarios.

Degeneracy-breaking and long-lived multimode microwave electromechanical systems enabled by cubic silicon-carbide membrane crystals

Cubic silicon-carbide crystals (3C-SiC), known for their high thermal conductivity and in-plane stress, hold significant promise for the development of high-quality (Q) mechanical oscillators. We reveal degeneracy-breaking phenomena in 3C-phase crystalline silicon-carbide membrane and present high-Q mechanical modes in pairs or clusters. The 3C-SiC material demonstrates excellent microwave compatibility with superconducting circuits. Thus, we can establish a coherent electromechanical interface, enabling precise control over 21 high-Q mechanical modes from a single 3C-SiC square membrane. Benefiting from extremely high mechanical frequency stability, this interface enables tunable light slowing with group delays extending up to an impressive duration of an hour. Coherent energy transfer between distinct mechanical modes are also presented. In this work, the studied 3C-SiC membrane crystal with their significant properties of multiple acoustic modes and high-quality factors, provide unique opportunities for the encoding, storage, and transmission of quantum information via bosonic phonon channels.

Antibody-secreting cell repertoires hold high-affinity anti-rocuronium specificities that can induce anaphylaxis in vivo.

Neuromuscular blocking agents (NMBA) are muscle relaxants used to assist mechanical ventilation but lead in 1/10,000 anesthesia to severe acute hypersensitivity reactions i.e., anaphylaxis. Incidences vary between types of NMBAs. Rocuronium, a widely used non-depolarizing aminosteroid NMBA, induces among the highest anaphylaxis rates. Rocuronium-induced anaphylaxis is proposed to rely on pre-existing rocuronium-binding antibodies, but no such antibodies have ever been identified. Identify rocuronium-specific antibody repertoires from plasma cells or plasmablasts of rocuronium-immunized mice, and determine the affinities, structures and anaphylactogenic potential of these antibodies for rocuronium. Herein, we engrafted rocuronium onto carrier proteins allowing immunization of mice against rocuronium, screening for rocuronium-specific antibody responses, and sorting of rocuronium-specific plasma cells using droplet microfluidics coupled to single-cell antibody gene (VH and VL) sequencing. The two different repertoires of >500 VH-VL pairs were oligoclonal, comprised of three major clonal families, and displayed convergence. Expressed as human IgG1, these antibodies demonstrated subnanomolar affinities for rocuronium with families either monospecific for rocuronium or cross-reactive only for closely-related NMBAs. Expressed as human IgE, they triggered human mast cell and basophil activation, and severe passive systemic anaphylaxis in mice humanized for the IgE receptor FcεRI. Co-crystal structures between rocuronium and antibody representatives of three different VH-VL families revealed distinct interaction modes with, however, the ammonium group involved systematically in the binding interface. This work identifies the epitopes of antibody reactivity to rocuronium, demonstrates anaphylactogenic potential of anti-rocuronium IgE and establishes the first mouse model of NMBA anaphylaxis.

Variability in Protein Expression and Fitness Under Stress: Distinct Modes of Early Adaptation of Populations

Early proteomic adaptations in cells serve as an initial line of defense, allowing populations to cope with environmental changes before long-term genetic alterations occur. Therefore, they are important in determining the trajectory taken by populations experiencing stress. Using a representative set of genes and DNA barcoding in , we examine how two facets of these adaptations, gene expression and fitness, are distributed within populations experiencing different types and levels of abiotic stress. Together, our data reveal two fundamentally distinct modes of population-level stress response in yeast. The first mode is complex and exploratory, in which individual members adjust the expression of a large part of their genes, seemingly searching phenotypic space for a solution. This leads to phenotypic and fitness heterogeneity within the population. The second mode is degenerate, with all individuals adopting similar gene-expression levels and obtaining uniform fitness. The first mode is employed when a prevalent stress is encountered, and the second under a rare one. This hints at a role for historical encounters in phenotypic plasticity. Published by the American Physical Society 2025

Characterization of motor nerve stimulation using sinusoidal low frequency alternating currents and cuff electrodes.

Direct electrical neurostimulation using continuous sinusoidal low frequency alternating currents (LFAC) is an emerging modality for neuromodulation. As opposed to the traditional rectangular pulse stimulation, there is limited background on the characteristics of peripheral nerves responses to sinusoidal LFAC stimulation; especially within the low frequency range (<50Hz). In this study, we demonstrate LFAC activation as a means to activate motor nerves by direct bipolar nerve stimulation via cuff electrodes, and characterize the factors of activation. We study and quantify the effects of sinusoidal frequency and electrode geometry on the motor nerve activation threshold in-vivo and in computational models, in-silico. Acute in-vivo experiments (N=34) were conducted on isoflurane-anaesthetized rats. A pure tone continuous sinusoidal current was applied to the rat sciatic nerve in bipolar configurations via bipolar or tripolar nerve cuff electrodes (different contact separations). LFAC activation thresholds were quantified by measuring the electromyogram (EMG) response of the triceps surae muscles and the induced twitch force to LFAC stimulation at six frequencies (1, 2, 3, 4, 8, and 20Hz). Computationally, we utilized a volume conductor model of a bipolar cuff electrode around a single rat-size fascicle and projected the potentials to the McIntyre-Richardson-Grill (MRG) models of myelinated motor nerve fibers. We compared the in-silico responses of a range of fiber diameters (5.7 to 16μm) to LFAC stimulation and their activation thresholds to the in-vivo findings. Sinusoidal LFAC stimulation elicited motor nerve activity in-vivo and in-silico, with a remarkable convergence of the in-silico predictions to the in-vivo observations. The EMG activity showed that muscle responses to LFAC stimulation were phase-locked to the sinusoidal cycle but exhibited two distinct activation modes. These modes were classified as burst and unitary, indicating the presence of two distinct patterns of muscle activation during LFAC stimulation. The LFAC motor activation threshold was significantly dependent on frequency and influenced by the contact separation of the cuff electrode, with a greater extent of reduction at a higher frequency or wider separation. Moreover, the order of fiber recruitment was found to be normal-physiological (small-to-large caliber) given the nature of the induced EMG activity and in-silico predictions. These findings provide significant insights into the nature of sinusoidal LFAC stimulation, at the explored range of frequency, and the expected mammalian peripheral motor nerve responses to LFAC. The characteristics of sinusoidal LFAC stimulation would facilitate selectivity approaches in a broader range of therapeutic and rehabilitative neuromodulation applications.

P-2230. Light Transmission-based Quantitation of Bacterial Growth on an Agar Plate

Abstract Background The growth of microorganisms in liquid culture is usually evaluated by measuring light transmission and calculating optical density (OD). We have developed a new thin-film transistor image sensor (1000 x 1000 pixels) to measure light transmission through agar plates (Figure 1). Similar to OD in liquid culture, cells grown on the surface of agar plates scatter light and reduce the intensity of transmitted light as the cells grow. This device captures a single image every 5 minutes, enabling in-depth time-lapse studies of cell growth when combined with digital image analysis. Here we present proof-of-concept studies to apply this growth monitoring system for quantitative growth assessment. Figure 1. Schematic representation of the bacterial growth monitoring system. Methods Escherichia coli cells were spread on a plate count agar plate and the growth was monitored over 745 min using the device. The optical density was calculated in the same way as OD of liquid culture: OD = -log10(I/I0) where I0 and I represent the intensity of incident light and transmitted light, respectively. The intensity of I0 and I was measured pixel by pixel; I0 was defined as the average of the first ten frames; I was defined as the average of the three consecutive frames (n-1, n, n+1) to reduce noise. The pixel size is 100 x 100 μm. Figure 2. Quantitative evaluation of E. coli colony growth on an agar plate. (A) The last (149th) frame was binarized at the threshold of OD 0.02 to extract colony contours. The circled and numbered colonies were analyzed in (B). The numbers along the horizontal and vertical axes represent the pixel positions. (B) The OD values of the central pixels of the colonies were tracked over time. Results Colony contours were extracted from the binary image, at the threshold of OD 0.02, of the last (149th) frame (Figure 2A). Five colonies with the highest and lowest OD were selected and the OD values of their central pixels were plotted over time, showing distinct modes of increase (Figure 2B). Next, one colony (#3) was chosen to analyze whether the OD correlated with colony size. One axis represents the OD of its central pixel. The other represents the number of pixels that showed OD 0.02 or more in the 20 x 20 pixel area surrounding the central pixel. As shown in Figure 3, after approximately 550 min, the cell growing area began to expand in correlation with the continued increase in OD. The binarized images, at the indicated time points, also showed the area expansion. Cell growth Figure 3. Cell growth in a single pixel and colony expansion in a wider area. The colony #3 in Figure 2 was analyzed. Shown are the OD of the central pixel (light green) and the number of the pixels that showed OD 0.02 or more in the 20 x 20 pixel area surrounding the central pixel (dark green). The binarized images, at the indicated time points, also showed the area expansion. Conclusion The light transmission-based growth monitoring system enabled us to quantitatively evaluate growth on the agar plate. The pixel-by-pixel analysis provided detailed information on the colony formation and growth. This system can be used in a broad spectrum of microorganism research and inspection. Disclosures Masakazu Nakajima, B. Engineering, CarbGeM Inc.: Board Member|CarbGeM Inc.: Ownership Interest

London dispersion forces and steric effects within nanocomposites tune interaction energies and chain conformation

The interplay between attractive London dispersion forces and steric effects due to repulsive forces resulting from the Pauli principle often determines the geometry and stability of nanostructures. Aromatic polyimides (PI) and carbon nanotubes (CNT) were chosen as building blocks as two components in the hetero delocalized electron nanostructures. Two PIs, having the same diamine part and different linkage substituents between two phenyl rings of dianhydride part, one linked with ether bond (C-O-C) (OPI), the other with C-(CF3)2 (FPI), were investigated. Surprisingly, two CNT/PI nanocomposites show distinct failure mode from CNT yielding to CNT pull-out failure. Calculation of the interaction energy and chain conformations of each PI upon CNT was performed by accurate density functional theory (DFT) calculations and molecular dynamic simulation (MDS). OPI chain adopt helically wrapping conformation around CNT with relatively strong interaction energy. FPI chain take the one-side wavelike conformation upon CNT with relatively weak interaction energy.

Analyzing Travel and Emission Characteristics of Hazardous Material Transportation Trucks Using BeiDou Satellite Navigation System Data

Road hazardous material transportation plays a critical role in road traffic management. Due to the dangerous nature of the cargo, hazardous material transportation trucks (HMTTs) have different route selection and driving characteristics compared to traditional freight trucks. These differences lead to unique travel and emission patterns, which in turn affect traffic management strategies and emission control measures. However, existing research predominantly focuses on safety aspects related to individual vehicle behavior, with limited exploration of the broader travel and emission characteristics of HMTTs. To bridge this gap, this study develops a comprehensive framework for analyzing the travel patterns and emissions of HMTTs. The methodology begins by applying a Gaussian mixture distribution model to identify vehicle stop points, eliminating biases associated with subjective settings. Origin–destination (OD) pairs are then determined through stop time clustering, followed by the extraction of travel characteristics using non-negative matrix factorization. Emissions are subsequently calculated based on the identified trip data. The relationship between emissions and land use characteristics is further analyzed using geographically weighted regression (GWR). Crucially, this study leverages data from the BeiDou Satellite Navigation System, focusing on HMTTs operating within Shanghai. The processed data reveal three distinct travel modes of HMTTs, categorized by spatiotemporal patterns: Daytime—Surrounding cities, Early morning—In-city, and Midnight—Scattered. Moreover, unlike other road vehicles, HMTT emissions are heavily influenced by industrial and company-related points of interest (POIs). These findings highlight the significant role of BeiDou Satellite Navigation System data in optimizing HMTT management strategies to reduce emissions and improve overall safety.

Molecular mechanism of ligand recognition and activation of lysophosphatidic acid receptor LPAR6

Lysophosphatidic acid (LPA) exerts its physiological roles through the endothelialdifferentiation gene (EDG) family LPA receptors (LPAR1-3) or the non-EDG family LPA receptors (LPAR4-6). LPAR6 plays crucial roles in hair loss and cancer progression, yet its structural information is very limited. Here, we report the cryoelectron microscopy structure of LPA-bound human LPAR6 in complex with a mini G13 or Gq protein. These structures reveal a distinct ligand binding and recognition mode that differs significantly from that of LPAR1. Specifically, LPA uses its charged head to form an extensive polar interaction network with key polar residues on the extracellular side of transmembrane helix 5-6 and the extracellular loop 2. Structural comparisons and homology analysis suggest that the EDG and non-EDG families use two distinct modes for LPA binding. The structural observations are validated through functional mutagenesis studies. We further uncover the mechanisms of LPAR6 activation and principles of G-protein coupling. The structural information revealed by our study lays the groundwork for understanding LPAR6 signaling and provides a rational basis for designing compounds targeting LPAR6.