Pushing the Limits of Capacitively Coupled Contactless Conductivity Detection for Capillary Electrophoresis.

Capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D) has proven to be an efficient technique for the separation and detection of charged inorganic, organic, and biochemical analytes. It offers several advantages, including cost-effectiveness, nanoliter injection volume, short analysis time, good separation efficiency, suitability for miniaturization, and portability. However, the routine determination of common inorganic cations (NH4+, K+, Na+, Ca2+, Mg2+, and Li+) and inorganic anions (F-, Cl-, Br-, NO2-, NO3-, PO43-, and SO42-) in water quality monitoring typically exhibits limits of detection of about 0.3-1 µM without preconcentration. This sensitivity often proves insufficient for the applications of CE-C4D in trace analysis situations. Here, we explore methods to push the detection limits of CE-C4D through a comprehensive consideration of signal and noise sources. In particular, we (i) studied the model of C4D and its guiding roles in C4D and CE-C4D, (ii) optimized the bandwidth and noise performance of the current-to-voltage (I-V) converter, and (iii) reduced the noise level due to the strong background signal of the background electrolyte by adaptive differential detection. We characterized the system with Li+; the 3-fold signal-to-noise (S/N) detection limit for Li+ was determined at 20 nM, with a linear range spanning from 60 nM to 1.6 mM. Moreover, the optimized CE-C4D method was applied to the analysis of common mixed inorganic cations (K+, Na+, Ca2+, Mg2+, and Li+), anions (F-, Cl-, Br-, NO2-, NO3-, PO43-, and SO42-), toxic halides (BrO3-) and heavy metal ions (Pb2+, Cd2+, Cr3+, Co2+, Ni2+, Zn2+, and Cu2+) at trace concentrations of 200 nM. All electropherograms showed good S/N ratios, thus proving its applicability and accuracy. Our results have shown that the developed CE-C4D method is feasible for trace ion analysis in water quality control.

Analysis of the Distribution Characteristics of Jellyfish and Environmental Factors in the Seawater Intake Area of the Haiyang Nuclear Power Plant in China.

In recent years, there have been frequent jellyfish outbreaks in Chinese coastal waters, significantly impacting the structure, functionality, safety, and economy of nuclear power plant cooling water intake and nearby ecosystems. Therefore, this study focuses on jellyfish outbreaks in Chinese coastal waters, particularly near the Shandong Peninsula. By analyzing jellyfish abundance data, a Generalized Additive Model integrating environmental factors reveals that temperature and salinity greatly influence jellyfish density. The results show variations in jellyfish density among years, with higher densities in coastal areas. The model explains 42.2% of the variance, highlighting the positive correlation between temperature (20-26 °C) and jellyfish density, as well as the impact of salinity (27.5-29‱). Additionally, ocean currents play a significant role in nearshore jellyfish aggregation, with a correlation between ocean currents and site coordinates. This study aims to investigate the relationship between jellyfish blooms and environmental factors. The results obtained from the study provide data support for the prevention and control of blockages in nuclear power plant cooling systems, and provide a data basis for the implementation of monitoring measures in nuclear power plants.

Correction: A compact and high-performance setup of capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D).

Correction for 'A compact and high-performance setup of capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D)' by Lin Li et al., Analyst, 2024, https://doi.org/10.1039/d4an00354c.

A compact and high-performance setup of capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D).

Capillary electrophoresis with capacitively coupled contactless conductivity detection (CE-C4D) has the advantages of high throughput (simultaneous detection of multiple ions), high separation efficiency (higher than 105 theoretical plates) and rapid analysis capability (less than 5 min for common inorganic ions). A compact CE-C4D system is ideal for water quality control and on-site analysis. It is suitable not only for common cations (e.g. Na+, K+, Li+, NH4+, Ca2+, etc.) and anions (e.g. Cl-, SO42-, BrO3-, etc.) but also for some ions (e.g. lanthanide ions, Pb2+, Cd2+, etc.) that require complex derivatization procedures to be detected by ion chromatography (IC). However, an obvious limitation of the CE-C4D method is that its sensitivity (e.g. 0.3-1 µM for common inorganic ions) is often insufficient for trace analysis (e.g. 1 ppb or 20 nM level for common inorganic ions) without preconcentration. For this technology to become a powerful and routine analytical technique, the system should be made compact while maintaining trace analysis sensitivity. In this study, we developed an all-in-one version of the CE-C4D instrument with custom-made modular components to make it a convenient, compact and high-performance system. The system was designed using direct digital synthesis (DDS) technology to generate programmable sinusoidal waveforms with any frequency for excitation, a kilovolt high-voltage power supply for capillary electrophoresis separation, and an "effective" differential C4D cell with a low-noise circuitry for high-sensitivity detection. We characterized the system with different concentrations of Cs+, and even a low concentration of 20 nM was detectable without preconcentration. Moreover, the optimized CE-C4D setup was applied to analyse mixed ions at a trace concentration of 200 nM with excellent signal-to-noise ratios. In typical applications, the limits of detection based on the 3σ criterion (without baseline filtering) were 9, 10, 24, 5, and 12 nM for K+, Cs+, Li+, Ca2+, and Mg2+, respectively, and about 7, 6, 6 and 6 nM for Br-, ClO4-, BrO3- and SO42-, respectively. Finally, the setup was also applied for the analysis of all 14 lanthanide ions and rare-earth minerals, and it showed an improvement in sensitivity by more than 25 times.

A three-dimensional (3D) liver-kidney on a chip with a biomimicking circulating system for drug safety evaluation.

The liver and kidney are the major detoxifying organs in the human body and play an important role in pharmacokinetics. Drug-induced hepatotoxicity and nephrotoxicity can cause irreversible damage to the liver and kidney and are a major cause of drug failure in later stages. Both animal models and conventional cell culture have a number of limitations, such as animal ethics and gene mismatching and there is an urgent need to develop a new drug toxicity evaluation approach. In this paper, a 3D liver-kidney on a chip with a biomimicking circulating system (LKOCBCS) was constructed to obtain kidney and liver models in vitro for drug safety evaluation. LKOCBCS, which has a parallel circulating system mimicking biological circulation, consists of 3D biomimetic tissue of liver lobules similar to that of the human liver constructed by 3D bioprinting and renal proximal tubule barriers fabricated by ultrafast laser assisted etching. The proposed LKOCBCS facilitates the communication between the liver and the kidney, including the exchange of nutrients, compounds, and metabolites. The results revealed that the glucose concentration and cell metabolism stabilized after 7 days. A dynamically repeated low-dose administration of cyclosporine A (CsA) was fed to the system, and hepatotoxicity and nephrotoxicity were observed on day 3 according to the changes in toxicity markers. The high levels of drug induced biomarkers expressed in LKOCBCS indicate that this system is more sensitive than the monoculture liver chip and it is highly potential in replacing animal models for effective drug toxicity screening.

Viral Communities Contribute More to the Lysis of Antibiotic-Resistant Bacteria than the Transduction of Antibiotic Resistance Genes in Anaerobic Digestion Revealed by Metagenomics.

Ecological role of the viral community on the fate of antibiotic resistance genes (ARGs) (reduction vs proliferation) remains unclear in anaerobic digestion (AD). Metagenomics revealed a dominance of Siphoviridae and Podoviridae among 13,895 identified viral operational taxonomic units (vOTUs) within AD, and only 21 of the vOTUs carried ARGs, which only accounted for 0.57 ± 0.43% of AD antibiotic resistome. Conversely, ARGs locating on plasmids and integrative and conjugative elements accounted for above 61.0%, indicating a substantial potential for conjugation in driving horizontal gene transfer of ARGs within AD. Virus-host prediction based on CRISPR spacer, tRNA, and homology matches indicated that most viruses (80.2%) could not infect across genera. Among 480 high-quality metagenome assembly genomes, 95 carried ARGs and were considered as putative antibiotic-resistant bacteria (pARB). Furthermore, lytic phages of 66 pARBs were identified and devoid of ARGs, and virus/host abundance ratios with an average value of 71.7 indicated extensive viral activity and lysis. The infectivity of lytic phage was also elucidated through laboratory experiments concerning changes of the phage-to-host ratio, pH, and temperature. Although metagenomic evidence for dissemination of ARGs by phage transduction was found, the higher proportion of lytic phages infecting pARBs suggested that the viral community played a greater role in reducing ARB numbers than spreading ARGs in AD.

Enhancing effluent quality prediction in wastewater treatment plants through the integration of factor analysis and machine learning.

Precisely predicting the concentration of nitrogen-based pollutants from the wastewater treatment plants (WWTPs) remains a challenging yet crucial task for optimizing operational adjustments in WWTPs. In this study, an integrated approach using factor analysis (FA) and machine learning (ML) models was employed to accurately predict effluent total nitrogen (Ntoteff) and nitrate nitrogen (NO3-Neff) concentrations of the WWTP. The input values for the ML models were honed through FA to optimize factors, thereby significantly enhancing the ML prediction accuracy. The prediction model achieved a highest coefficient of determination (R2) of 97.43 % (Ntoteff) and 99.38 % (NO3-Neff), demonstrating satisfactory generalization ability for predictions up to three days ahead (R2 >80 %). Moreover, the interpretability analysis identified that the denitrification factor, the pollutant load factor, and the meteorological factor were significant. The model framework proposed in this study provides a valuable reference for optimizing the operation and management of wastewater treatment.

Machine learning framework for intelligent aeration control in wastewater treatment plants: Automatic feature engineering based on variation sliding layer.

Intelligent control of wastewater treatment plants (WWTPs) has the potential to reduce energy consumption and greenhouse gas emissions significantly. Machine learning (ML) provides a promising solution to handle the increasing amount and complexity of generated data. However, relationships between the features of wastewater datasets are generally inconspicuous, which hinders the application of artificial intelligence (AI) in WWTPs intelligent control. In this study, we develop an automatic framework of feature engineering based on variation sliding layer (VSL) to control the air demand precisely. Results demonstrated that using VSL in classic machine learning, deep learning, and ensemble learning could significantly improve the efficiency of aeration intelligent control in WWTPs. Bayesian regression and ensemble learning achieved the highest accuracy for predicting air demand. The developed models with VSL-ML models were also successfully implemented under the full-scale wastewater treatment plant, showing a 16.12 % reduction in demand compared to conventional aeration control of preset dissolved oxygen (DO) and feedback to the blower. The VSL-ML models showed great potential to be applied for the precision air demand prediction and control. The package as a tripartite library of Python is called wwtpai, which is freely accessible on GitHub and CSDN to remove technical barriers to the application of AI technology in WWTPs.

Antifungal efficiency and cytocompatibility of polymethyl methacrylate modified with zinc dimethacrylate.

Objectives: Considering the high incidence rates of denture stomatitis, research that providing dental biomaterials with antifungal property are essential for clinical dentistry. The objectives of the present study were to investigate the effect of zinc dimethacrylate (ZDMA) modification on the antifungal and cytotoxic properties, as well as the variance in surface characteristics and other physicochemical properties of polymethyl methacrylate (PMMA) denture base resin. Methods: PMMA with various mass fraction of ZDMA (1 wt%, 2.5 wt% and 5 wt%) were prepared for experimental groups, and unmodified PMMA for the control. Fourier-transform infrared spectroscopy (FTIR) was applied for characterization. Thermogravimetric analysis, atomic force microscopy and water contact angle were performed to investigate the thermal stability and surface characteristics (n=5). Antifungal capacities and cytocompatibility were evaluated with Candida albicans (C. albicans) and human oral fibroblasts (HGFs), respectively. Colony-forming unit counting, crystal violet assay, live/dead biofilm staining and scanning electron microscopy observation were performed to assess antifungal effects, and the detection of intracellular reactive oxygen species production was applied to explore the possible antimicrobial mechanism. Finally, the cytotoxicity of ZDMA modified PMMA resin was evaluated by the 3-(4,5-dimethyl-thiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) assay and live/dead double staining. Results: The FTIR analyses confirmed some variation in chemical bonding and physical blend of the composites. Incorporation of ZDMA significantly enhanced the thermal stability and hydrophilicity compared with unmodified PMMA (p < 0.05). The surface roughness increased with the addition of ZDMA while remained below the suggested threshold (≤ 0.2 µm). The antifungal activity significantly improved with ZDMA incorporation, and cytocompatibility assays indicated no obvious cytotoxicity on HGFs. Conclusions: In the present study, the ZDMA mass fraction up to 5 wt% in PMMA performed better thermal stability, and an increase in surface roughness and hydrophilicity without enhancing microbial adhesion. Moreover, the ZDMA modified PMMA showed effective antifungal activity without inducing any cellular side effects.

Manufacture of Three-Dimensional Optofluidic Spot-Size Converters in Fused Silica Using Hybrid Laser Microfabrication.

We propose a hybrid laser microfabrication approach for the manufacture of three-dimensional (3D) optofluidic spot-size converters in fused silica glass by a combination of femtosecond (fs) laser microfabrication and carbon dioxide laser irradiation. Spatially shaped fs laser-assisted chemical etching was first performed to form 3D hollow microchannels in glass, which were composed of embedded straight channels, tapered channels, and vertical channels connected to the glass surface. Then, carbon dioxide laser-induced thermal reflow was carried out for the internal polishing of the whole microchannels and sealing parts of the vertical channels. Finally, 3D optofluidic spot-size converters (SSC) were formed by filling a liquid-core waveguide solution into laser-polished microchannels. With a fabricated SSC structure, the mode spot size of the optofluidic waveguide was expanded from ~8 µm to ~23 µm with a conversion efficiency of ~84.1%. Further measurement of the waveguide-to-waveguide coupling devices in the glass showed that the total insertion loss of two symmetric SSC structures through two ~50 µm-diameter coupling ports was ~6.73 dB at 1310 nm, which was only about half that of non-SSC structures with diameters of ~9 µm at the same coupling distance. The proposed approach holds great potential for developing novel 3D fluid-based photonic devices for mode conversion, optical manipulation, and lab-on-a-chip sensing.

Fine Mapping and Gene Analysis of restorer-of-fertility Gene CaRfHZ in Pepper (Capsicum annuum L.).

Cytoplasmic male sterility (CMS) is a common biological phenomenon used in hybrid production of peppers (Capsicum annuum L.). Although several restorer-of-fertility (Rf) genes of pepper CMS lines have been mapped, there is no report that the Rf gene with clear gene function has been isolated. Here, pepper CMS line HZ1A and its restorer line HZ1C were used to construct (HZ1A × HZ1C) F2 populations and map the Rf gene. A single dominant gene CaRfHZ conferred male fertility according to inheritance analysis. Using sterile plants from (HZ1A × HZ1C) F2 populations and bulked segregant analysis (BSA), the CaRfHZ gene was mapped between P06gInDel-66 and P06gInDel-89 on chromosome 6. This region spans 533.81 kb, where four genes are annotated according to Zunla-1 V2.0 gene models. Based on the analysis of genomic DNA sequences, gene expressions, and protein structures, Capana06g002968 was proposed as the strongest candidate for the CaRfHZ gene. Our results may help with hybrid pepper breeding and to elucidate the mechanism of male fertility restoration in peppers.

Three-Dimensional Large-Scale Fused Silica Microfluidic Chips Enabled by Hybrid Laser Microfabrication for Continuous-Flow UV Photochemical Synthesis.

We demonstrate a hybrid laser microfabrication approach, which combines the technical merits of ultrafast laser-assisted chemical etching and carbon dioxide laser-induced in situ melting for centimeter-scale and bonding-free fabrication of 3D complex hollow microstructures in fused silica glass. With the developed approach, large-scale fused silica microfluidic chips with integrated 3D cascaded micromixing units can be reliably manufactured. High-performance on-chip mixing and continuous-flow photochemical synthesis under UV irradiation at ~280 nm were demonstrated using the manufactured chip, indicating a powerful capability for versatile fabrication of highly transparent all-glass microfluidic reactors for on-chip photochemical synthesis.

High-Throughput Continuous-Flow Separation in a Micro Free-Flow Electrophoresis Glass Chip Based on Laser Microfabrication.

Micro free-flow electrophoresis (µFFE) provides a rapid and straightforward route for the high-performance online separation and purification of targeted liquid samples in a mild manner. However, the facile fabrication of a µFFE device with high throughput and high stability remains a challenge due to the technical barriers of electrode integration and structural design for the removal of bubbles for conventional methods. To address this, the design and fabrication of a high-throughput µFFE chip are proposed using laser-assisted chemical etching of glass followed by electrode integration and subsequent low-temperature bonding. The careful design of the height ratio of the separation chamber and electrode channels combined with a high flow rate of buffer solution allows the efficient removal of electrolysis-generated bubbles along the deep electrode channels during continuous-flow separation. The introduction of microchannel arrays further enhances the stability of on-chip high-throughput separation. As a proof-of-concept, high-performance purification of fluorescein sodium solution with a separation purity of ~97.9% at a voltage of 250 V from the mixture sample solution of fluorescein sodium and rhodamine 6G solution is demonstrated.

The tomato Mediator subunit MED8 positively regulates plant response to Botrytis cinerea.

The Mediator complex acts as a bridge between specific transcription factors and the RNA polymerase II transcriptional machinery and plays a central role in plant immunity. Biological induction of plant resistance against pathogens requires endogenous hormone jasmonic acid (JA) and involves profound transcriptional changes controlled by the key transcription factor MYC2. Arabidopsis thaliana Mediator subunit 25 (AtMED25) regulates JA-dependent defense response through interacting with MYC2. Here, we report that the tomato (Solanum lycopersicum, Sl) Mediator subunit 8 (SlMED8) is another essential component in JA-dependent defense response. The transcript levels of SlMED8 could not be affected by treatment with MeJA, SA, ABA, and mechanical wounding. Yeast two-hybrid assays showed that SlMED8 could interact with itself, SlMYC2, and SlMED25, respectively. In addition, ectopic overexpression of SlMED8 complemented the late flowering and pathogen hypersensitivity phenotypes of Arabidopsis med8 mutant. Overexpression of SlMED8 rendered transgenic plants higher tolerance to necrotrophic pathogen Botrytis cinerea. Meanwhile, SlMED8 antisense plants displayed compromised resistance to Botrytis cinerea. Consistent with this, differential expression levels of several JA-responsive genes were detected within the transgenic plants. Overall, our results identified an important control point in the regulation of the JA signaling pathway within the transcriptional machinery.

Author Correction: Cryo-EM structures of PAC1 receptor reveal ligand binding mechanism.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cryo-EM structures of PAC1 receptor reveal ligand binding mechanism.

The pituitary adenylate cyclase-activating polypeptide type I receptor (PAC1R) belongs to the secretin receptor family and is widely distributed in the central neural system and peripheral organs. Abnormal activation of the receptor mediates trigeminovascular activation and sensitization, which is highly related to migraine, making PAC1R a potential therapeutic target. Elucidation of PAC1R activation mechanism would benefit discovery of therapeutic drugs for neuronal disorders. PAC1R activity is governed by pituitary adenylate cyclase-activating polypeptide (PACAP), known as a major vasodilator neuropeptide, and maxadilan, a native peptide from the sand fly, which is also capable of activating the receptor with similar potency. These peptide ligands have divergent sequences yet initiate convergent PAC1R activity. It is of interest to understand the mechanism of PAC1R ligand recognition and receptor activity regulation through structural biology. Here we report two near-atomic resolution cryo-EM structures of PAC1R activated by PACAP38 or maxadilan, providing structural insights into two distinct ligand binding modes. The structures illustrate flexibility of the extracellular domain (ECD) for ligands with distinct conformations, where ECD accommodates ligands in different orientations while extracellular loop 1 (ECL1) protrudes to further anchor the ligand bound in the orthosteric site. By structure-guided molecular modeling and mutagenesis, we tested residues in the ligand-binding pockets and identified clusters of residues that are critical for receptor activity. The structures reported here for the first time elucidate the mechanism of specificity and flexibility of ligand recognition and binding for PAC1R, and provide insights toward the design of therapeutic molecules targeting PAC1R.

Structure-guided discovery of a single-domain antibody agonist against human apelin receptor.

Developing antibody agonists targeting the human apelin receptor (APJ) is a promising therapeutic approach for the treatment of chronic heart failure. Here, we report the structure-guided discovery of a single-domain antibody (sdAb) agonist JN241-9, based on the cocrystal structure of APJ with an sdAb antagonist JN241, the first cocrystal structure of a class A G protein-coupled receptor (GPCR) with a functional antibody. As revealed by the structure, JN241 binds to the extracellular side of APJ, makes critical contacts with the second extracellular loop, and inserts the CDR3 into the ligand-binding pocket. We converted JN241 into a full agonist JN241-9 by inserting a tyrosine into the CDR3. Modeling and molecular dynamics simulation shed light on JN241-9-stimulated receptor activation, providing structural insights for finding agonistic antibodies against class A GPCRs.

A High-Throughput, Multi-Index Isothermal Amplification Platform for Rapid Detection of 19 Types of Common Respiratory Viruses Including SARS-CoV-2.

Fast and accurate diagnosis and the immediate isolation of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are regarded as the most effective measures to restrain the coronavirus disease 2019 (COVID-19) pandemic. Here, we present a high-throughput, multi-index nucleic acid isothermal amplification analyzer (RTisochip™-W) employing a centrifugal microfluidic chip to detect 19 common respiratory viruses, including SARS-CoV-2, from 16 samples in a single run within 90 min. The limits of detection of all the viruses analyzed by the RTisochip™-W system were equal to or less than 50 copies·µL-1, which is comparable to those of conventional reverse transcription polymerase chain reaction. We also demonstrate that the RTisochip™-W system possesses the advantages of good repeatability, strong robustness, and high specificity. Finally, we analyzed 201 cases of preclinical samples, 14 cases of COVID-19-positive samples, 25 cases of clinically diagnosed samples, and 614 cases of clinical samples from patients or suspected patients with respiratory tract infections using the RTisochip™-W system. The test results matched the referenced results well and reflected the epidemic characteristics of the respiratory infectious diseases. The coincidence rate of the RTisochip™-W with the referenced kits was 98.15% for the detection of SARS-CoV-2. Based on these extensive trials, we believe that the RTisochip™-W system provides a powerful platform for fighting the COVID-19 pandemic.

Fragment-Based Computational Method for Designing GPCR Ligands.

G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors, which is arguably the most important family of drug target. With the technology breakthroughs in X-ray crystallography and cryo-electron microscopy, more than 300 GPCR-ligand complex structures have been publicly reported since 2007, covering about 60 unique GPCRs. Such abundant structural information certainly will facilitate the structure-based drug design by targeting GPCRs. In this study, we have developed a fragment-based computational method for designing novel GPCR ligands. We first extracted the characteristic interaction patterns (CIPs) on the binding interfaces between GPCRs and their ligands. The CIPs were used as queries to search the chemical fragments derived from GPCR ligands, which were required to form similar interaction patterns with GPCR. Then, the selected chemical fragments were assembled into complete molecules by using the AutoT&T2 software. In this work, we chose ß-adrenergic receptor (ß-AR) and muscarinic acetylcholine receptor (mAChR) as the targets to validate this method. Based on the designs suggested by our method, samples of 63 compounds were purchased and tested in a cell-based functional assay. A total of 15 and 22 compounds were identified as active antagonists for ß2-AR and mAChR M1, respectively. Molecular dynamics simulations and binding free energy analysis were performed to explore the key interactions (e.g., hydrogen bonds and π-π interactions) between those active compounds and their target GPCRs. In summary, our work presents a useful approach to the de novo design of GPCR ligands based on the relevant 3D structural information.

Molecular Mechanism for Ligand Recognition and Subtype Selectivity of α2C Adrenergic Receptor.

Adrenergic G-protein-coupled receptors (GPCRs) mediate different cellular signaling pathways in the presence of endogenous catecholamines and play important roles in both physiological and pathological conditions. Extensive studies have been carried out to investigate the structure and function of ß adrenergic receptors (ßARs). However, the structure of α adrenergic receptors (αARs) remains to be determined. Here, we report the structure of the human α2C adrenergic receptor (α2CAR) with the non-selective antagonist, RS79948, at 2.8 Å. Our structure, mutations, modeling, and functional experiments indicate that a α2CAR-specific D206ECL2-R409ECL3-Y4056.58 network plays a role in determining α2 adrenergic subtype selectivity. Furthermore, our results show that a specific loosened helix at the top of TM4 in α2CAR is involved in receptor activation. Together, our structure of human α2CAR-RS79948 provides key insight into the mechanism underlying the α2 adrenergic receptor activation and subtype selectivity.