A LaCl3-based lithium superionic conductor compatible with lithium metal.

Inorganic superionic conductors possess high ionic conductivity and excellent thermal stability but their poor interfacial compatibility with lithium metal electrodes precludes application in all-solid-state lithium metal batteries1,2. Here we report a LaCl3-based lithium superionic conductor possessing excellent interfacial compatibility with lithium metal electrodes. In contrast to a Li3MCl6 (M = Y, In, Sc and Ho) electrolyte lattice3-6, the UCl3-type LaCl3 lattice has large, one-dimensional channels for rapid Li+ conduction, interconnected by La vacancies via Ta doping and resulting in a three-dimensional Li+ migration network. The optimized Li0.388Ta0.238La0.475Cl3 electrolyte exhibits Li+ conductivity of 3.02 mS cm-1 at 30 °C and a low activation energy of 0.197 eV. It also generates a gradient interfacial passivation layer to stabilize the Li metal electrode for long-term cycling of a Li-Li symmetric cell (1 mAh cm-2) for more than 5,000 h. When directly coupled with an uncoated LiNi0.5Co0.2Mn0.3O2 cathode and bare Li metal anode, the Li0.388Ta0.238La0.475Cl3 electrolyte enables a solid battery to run for more than 100 cycles with a cutoff voltage of 4.35 V and areal capacity of more than 1 mAh cm-2. We also demonstrate rapid Li+ conduction in lanthanide metal chlorides (LnCl3; Ln = La, Ce, Nd, Sm and Gd), suggesting that the LnCl3 solid electrolyte system could provide further developments in conductivity and utility.

1T'-transition metal dichalcogenide monolayers stabilized on 4H-Au nanowires for ultrasensitive SERS detection.

Unconventional 1T'-phase transition metal dichalcogenides (TMDs) have aroused tremendous research interest due to their unique phase-dependent physicochemical properties and applications. However, due to the metastable nature of 1T'-TMDs, the controlled synthesis of 1T'-TMD monolayers (MLs) with high phase purity and stability still remains a challenge. Here we report that 4H-Au nanowires (NWs), when used as templates, can induce the quasi-epitaxial growth of high-phase-purity and stable 1T'-TMD MLs, including WS2, WSe2, MoS2 and MoSe2, via a facile and rapid wet-chemical method. The as-synthesized 4H-Au@1T'-TMD core-shell NWs can be used for ultrasensitive surface-enhanced Raman scattering (SERS) detection. For instance, the 4H-Au@1T'-WS2 NWs have achieved attomole-level SERS detections of Rhodamine 6G and a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins. This work provides insights into the preparation of high-phase-purity and stable 1T'-TMD MLs on metal substrates or templates, showing great potential in various promising applications.

The Reconstruction of Pt(001) Surface and the Shell-Like Reconstruction of the Vicinal Pt(001) Surfaces Revealed by Neural Network Potential.

In this work, a highly accurate neural network potential (NNP) is presented, named PtNNP, and the exploration of the reconstruction of the Pt(001) surface and its vicinal surfaces with it. Contrary to the most accepted understanding of the Pt(001) surface reconstruction, the study reveals that the main driving force behind Pt(001) quasi-hexagonal reconstruction is not the surface stress relaxation but the increased coordination number of the surface atoms resulting in stronger intralayer binding in the reconstructed surface layer. In agreement with experimental observations, the optimized supercell size of the reconstructed Pt(001) surface contains (5 × 20) unit cells. Surprisingly, the reconstruction of the vicinal Pt(001) surfaces leads to a smooth shell-like surface layer covering the whole surface and diminishing sharp step edges.

Doping Ability Modulated by Interlayer Coupling in AA' and AB Stacked Bilayer V-WS2 Grown with Chemical Vapor Deposition.

Doping in transition metal dichalcogenide (TMD) has received extensive attention for its prospect in the application of photoelectric devices. Currently researchers focus on the doping ability and doping distribution in monolayer TMD and have obtained a series of achievements. Bilayer TMD has more excellent properties compared with monolayer TMD. Moreover, bilayer TMD with different stacking structures presents varying performance due to the difference in interlayer coupling. Herein, this work focuses on doping ability of dopants in different bilayer stacking structures that has not been studied yet. Results of this work show that the doping ability of V atoms in bilayer AA' and AB stacked WS2 is different, and the doping concentration of V atoms in AB stacked WS2 is higher than in AA' stacked WS2. Moreover, dopants from top and bottom layer can be distinguished by scanning transmission electron microscopy (STEM) image. Density functional theory (DFT) calculation further confirms the doping rule. This study reveals the mechanism of the different doping ability caused by stacking structures in bilayer TMD and lays a foundation for further preparation of controllable-doping bilayer TMD materials.

Out-of-Plane Single-Copper-Site Catalysts for Room-Temperature Benzene Oxidation.

Crafting single-atom catalysts (SACs) that possess "just right" modulated electronic and geometric structures, granting accessible active sites for direct room-temperature benzene oxidation is a coveted objective. However, achieving this goal remains a formidable challenge. Here, we introduce an innovative in situ phosphorus-immitting strategy using a new phosphorus source (phosphorus nitride, P3N5) to construct the phosphorus-rich copper (Cu) SACs, designated as Cu/NPC. These catalysts feature locally protruding metal sites on a nitrogen (N)-phosphorus (P)-carbon (C) support (NPC). Rigorous analyses, including X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS), validate the coordinated bonding of nitrogen and phosphorus with atomically dispersed Cu sites on NPC. Crucially, systematic first-principles calculations, coupled with the climbing image nudged-elastic-band (CI-NEB) method, provide a comprehensive understanding of the structure-property-activity relationship of the distorted Cu-N2P2 centers in Cu/NPC for selective oxidation of benzene to phenol production. Interestingly, Cu/NPC has shown more energetically favorable C-H bond activation compared to the benchmark Cu/NC SACs in the direct oxidation of benzene, resulting in outstanding benzene conversion (50.3 %) and phenol selectivity (99.3 %) at room temperature. Furthermore, Cu/NPC achieves a remarkable turnover frequency of 263 h-1 and mass-specific activity of 35.2 mmol g-1 h-1, surpassing the state-of-the-art benzene-to-phenol conversion catalysts to date.

Concentration Phase Separation of Substitution-Doped Atoms in TMDCs Monolayer.

The density and spatial distribution of substituted dopants affect the transition metal dichalcogenides (TMDCs) materials properties. Previous studies have demonstrated that the density of dopants in TMDCs increases with the amount of doping, and the phenomenon of doping concentration difference between the nucleation center and the edge is observed, but the spatial distribution law of doping atoms has not been carefully studied. Here, it is demonstrated that the spatial distribution of dopants changes at high doping concentrations. The spontaneous formation of an interface with a steep doping concentration change is named concentration phase separation (CPS). The difference in the spatial distribution of dopants on both sides of the interface can be identified by an optical microscope. This is consistent with the results of spectral analysis and microstructure characterization of scanning transmission electron microscope. According to the calculation results of density functional theory, the chemical potential has two relatively stable energies as the doping concentration increases, which leads to the spontaneous formation of CPS. Understanding the abnormal phenomena is important for the design of TMDCs devices. This work has great significance in the establishment and improvement of the doping theory and the design of the doping process for 2D materials.

Controlled synthesis of van der Waals CoS2for improved p-type transistor contact.

Two-dimensional (2D) van der Waals (vdW) p-type semiconductors have shown attractive application prospects as atomically thin channels in electronic devices. However, the high Schottky hole barrier of p-type semiconductor-metal contacts induced by Fermi-level pinning is hardly removed. Herein, we prepare a vdW 1T-CoS2nanosheet as the contact electrode of a WSe2field-effect transistor (FET), which shows a considerably high on/off ratio > 107and a hole mobility of ∼114.5 cm2V-1s-1. The CoS2nanosheets exhibit metallic conductivity with thickness dependence, which surpasses most 2D transition metal dichalcogenide metals or semimetals. The excellent FET performance of the CoS2-contacted WSe2FET device can be attributed to the high work function of CoS2, which lowers the Schottky hole barrier. Our work provides an effective method for growing vdW CoS2and opens up more possibilities for the application of 2D p-type semiconductors in electronic devices.

Overexpression of NDR1 leads to pathogen resistance at elevated temperatures.

Abiotic and biotic environments influence a myriad of plant-related processes, including growth, development, and the establishment and maintenance of interaction(s) with microbes. In the case of the latter, elevated temperature has been shown to be a key factor that underpins host resistance and pathogen virulence. In this study, we elucidate a role for Arabidopsis NON-RACE-SPECIFIC DISEASE RESISTANCE1 (NDR1) by exploiting effector-triggered immunity to define the regulation of plant host immunity in response to both pathogen infection and elevated temperature. We generated time-series RNA sequencing data of WT Col-0, an NDR1 overexpression line, and ndr1 and ics1-2 mutant plants under elevated temperature. Not surprisingly, the NDR1-overexpression line showed genotype-specific gene expression changes related to defense response and immune system function. The results described herein support a role for NDR1 in maintaining cell signaling during simultaneous exposure to elevated temperature and avirulent pathogen stressors.

Deep learning-based endoscopic anatomy classification: an accelerated approach for data preparation and model validation.

BACKGROUND: Photodocumentation during endoscopy procedures is one of the indicators for endoscopy performance quality; however, this indicator is difficult to measure and audit in the endoscopy unit. Emerging artificial intelligence technology may solve this problem, which requires a large amount of material for model development. We developed a deep learning-based endoscopic anatomy classification system through convolutional neural networks with an accelerated data preparation approach. PATIENTS AND METHODS: We retrospectively collected 8,041 images from esophagogastroduodenoscopy (EGD) procedures and labeled them using two experts for nine anatomical locations of the upper gastrointestinal tract. A base model for EGD image multiclass classification was first developed, and an additional 6,091 images were enrolled and classified by the base model. A total of 5,963 images were manually confirmed and added to develop the subsequent enhanced model. Additional internal and external endoscopy image datasets were used to test the model performance. RESULTS: The base model achieved total accuracy of 96.29%. For the enhanced model, the total accuracy was 96.64%. The overall accuracy improved with the enhanced model compared with the base model for the internal test dataset without narrowband images (93.05% vs. 91.25%, p < 0.01) or with narrowband images (92.74% vs. 90.46%, p < 0.01). The total accuracy was 92.56% of the enhanced model on the external test dataset. CONCLUSIONS: We constructed a deep learning-based model with an accelerated approach that can be used for quality control in endoscopy units. The model was also validated with both internal and external datasets with high accuracy.

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant information in the endoscopy reporting system to facilitate data collection, which may be inaccurate. The current study aimed to develop a full deep learning-based algorithm to identify and analyze intra-procedural colonoscopy quality indicators based on endoscopy images obtained during the procedure. METHODS: A deep learning system for classifying colonoscopy images for quality assurance purposes was developed and its performance was assessed with an independent dataset. The system was utilized to analyze captured images and results were compared with those of real-world reports. RESULTS: In total, 10,417 images from the hospital endoscopy database and 3157 from Hyper-Kvasir open dataset were utilized to develop the quality assurance algorithm. The overall accuracy of the algorithm was 96.72% and that of the independent test dataset was 94.71%. Moreover, 761 real-world reports and colonoscopy images were analyzed. The accuracy of electronic reports about cecal intubation rate was 99.34% and that of the algorithm was 98.95%. The agreement rate for the assessment of polypectomy rates using the electronic reports and the algorithm was 0.87 (95% confidence interval 0.83-0.90). A good correlation was found between the withdrawal time calculated using the algorithm and that entered by the physician (correlation coefficient r = 0.959, p < 0.0001). CONCLUSION: We proposed a novel deep learning-based algorithm that used colonoscopy images for quality assurance purposes. This model can be used to automatically assess intra-procedural colonoscopy quality indicators in clinical practice.

Upper endoscopy photodocumentation quality evaluation with novel deep learning system.

OBJECTIVES: Visualization and photodocumentation during endoscopy procedures are suggested to be one indicator for endoscopy performance quality. However, this indicator is difficult to measure and audit manually in clinical practice. Artificial intelligence (AI) is an emerging technology that may solve this problem. METHODS: A deep learning model with an accuracy of 96.64% was developed from 15,305 images for upper endoscopy anatomy classification in the unit. Endoscopy images for asymptomatic patients receiving screening endoscopy were evaluated with this model to assess the completeness of photodocumentation rate. RESULTS: A total of 15,723 images from 472 upper endoscopies performed by 12 endoscopists were enrolled. The complete photodocumentation rate from the pharynx to the duodenum was 53.8% and from the esophagus to the duodenum was 78.0% in this study. Endoscopists with a higher adenoma detection rate had a higher complete examination rate from the pharynx to duodenum (60.0% vs. 38.7%, P < 0.0001) and from esophagus to duodenum (83.0% vs. 65.7%, P < 0.0001) compared with endoscopists with lower adenoma detection rate. The pharynx, gastric angle, gastric retroflex view, gastric antrum, and the first portion of duodenum are likely to be missed by endoscopists with lower adenoma detection rates. CONCLUSIONS: We report the use of a deep learning model to audit endoscopy photodocumentation quality in our unit. Endoscopists with better performance in colonoscopy had a better performance for this quality indicator. The use of such an AI system may help the endoscopy unit audit endoscopy performance.

Photoacoustic imaging of cells in a three-dimensional microenvironment.

Imaging live cells in a three-dimensional (3D) culture system yields more accurate information and spatial visualization of the interplay of cells and the surrounding matrix components compared to using a two-dimensional (2D) cell culture system. However, the thickness of 3D cultures results in a high degree of scattering that makes it difficult for the light to penetrate deeply to allow clear optical imaging. Photoacoustic (PA) imaging is a powerful imaging modality that relies on a PA effect generated when light is absorbed by exogenous contrast agents or endogenous molecules in a medium. It combines a high optical contrast with a high acoustic spatiotemporal resolution, allowing the noninvasive visualization of 3D cellular scaffolds at considerable depths with a high resolution and no image distortion. Moreover, advances in targeted contrast agents have also made PA imaging capable of molecular and cellular characterization for use in preclinical personalized diagnostics or PA imaging-guided therapeutics. Here we review the applications and challenges of PA imaging in a 3D cellular microenvironment. Potential future developments of PA imaging in preclinical applications are also discussed.

Enhanced Radiosensitization for Cancer Treatment with Gold Nanoparticles through Sonoporation.

We demonstrate the megavoltage (MV) radiosensitization of a human liver cancer line by combining gold-nanoparticle-encapsulated microbubbles (AuMBs) with ultrasound. Microbubbles-mediated sonoporation was administered for 5 min, at 2 h prior to applying radiotherapy. The intracellular concentration of gold nanoparticles (AuNPs) increased with the inertial cavitation of AuMBs in a dose-dependent manner. A higher inertial cavitation dose was also associated with more DNA damage, higher levels of apoptosis markers, and inferior cell surviving fractions after MV X-ray irradiation. The dose-modifying ratio in a clonogenic assay was 1.56 ± 0.45 for a 10% surviving fraction. In a xenograft mouse model, combining vascular endothelial growth factor receptor 2 (VEGFR2)-targeted AuMBs with sonoporation significantly delayed tumor regrowth. A strategy involving the spatially and temporally controlled release of AuNPs followed by clinically utilized MV irradiation shows promising results that make it worthy of further translational investigations.

Battlefield Cytoskeleton: Turning the Tide on Plant Immunity.

The plant immune system comprises a complex network of signaling processes, regulated not only by classically defined immune components (e.g., resistance genes) but also by a suite of developmental, environmental, abiotic, and biotic-associated factors. In total, it is the sum of these interactions-the connectivity to a seemingly endless array of environments-that ensures proper activation, and control, of a system that is responsible for cell surveillance and response to threats presented by invading pests and pathogens. Over the past decade, the field of plant pathology has witnessed the discovery of numerous points of convergence between immunity, growth, and development, as well as overlap with seemingly disparate processes such as those that underpin plant response to changes in the environment. Toward defining how immune signaling is regulated, recent studies have focused on dissecting the mechanisms that underpin receptor-ligand interactions, phospho-regulation of signaling cascades, and the modulation of host gene expression during infection. As one of the major regulators of these immune signaling cascades, the plant cytoskeleton is the stage from which immune-associated processes are mobilized and oriented and, in this role, it controls the movement of the organelles, proteins, and chemical signals that support plant defense signaling. In short, the cytoskeleton is the battlefield from which pathogens and plants volley virulence and resistance, transforming resistance to susceptibility. Herein, we discuss the role of the eukaryotic cytoskeleton as a platform for the function of the plant immune system.

Shear-wave elasticity measurements of three-dimensional cell cultures for mechanobiology.

Studying mechanobiology in three-dimensional (3D) cell cultures better recapitulates cell behaviors in response to various types of mechanical stimuli in vivo Stiffening of the extracellular matrix resulting from cell remodeling potentiates many pathological conditions, including advanced cancers. However, an effective tool for measuring the spatiotemporal changes in elastic properties of such 3D cell cultures without directly contacting the samples has not been reported previously. We describe an ultrasonic shear-wave-based platform for quantitatively evaluating the spatiotemporal dynamics of the elasticity of a matrix remodeled by cells cultured in 3D environments. We used this approach to measure the elasticity changes of 3D matrices grown with highly invasive lung cancer cells and cardiac myoblasts, and to delineate the principal mechanism underlying the stiffening of matrices remodeled by these cells. The described approach can be a useful tool in fields investigating and manipulating the mechanotransduction of cells in 3D contexts, and also has potential as a drug-screening platform.

Atomistic Simulations of Graphene Growth: From Kinetics to Mechanism.

Epitaxial growth is a promising strategy to produce high-quality graphene samples. At the same time, this method has great flexibility for industrial scale-up. To optimize growth protocols, it is essential to understand the underlying growth mechanisms. This is, however, very challenging, as the growth process is complicated and involves many elementary steps. Experimentally, atomic-scale in situ characterization methods are generally not feasible at the high temperature of graphene growth. Therefore, kinetics is the main experimental information to study growth mechanisms. Theoretically, first-principles calculations routinely provide atomic structures and energetics but have a stringent limit on the accessible spatial and time scales. Such gap between experiment and theory can be bridged by atomistic simulations using first-principles atomic details as input and providing the overall growth kinetics, which can be directly compared with experiment, as output. Typically, system-specific approximations should be applied to make such simulations computationally feasible. By feeding kinetic Monte Carlo (kMC) simulations with first-principles parameters, we can directly simulate the graphene growth process and thus understand the growth mechanisms. Our simulations suggest that the carbon dimer is the dominant feeding species in the epitaxial growth of graphene on both Cu(111) and Cu(100) surfaces, which enables us to understand why the reaction is diffusion limited on Cu(111) but attachment limited on Cu(100). When hydrogen is explicitly considered in the simulation, the central role hydrogen plays in graphene growth is revealed, which solves the long-standing puzzle into why H2 should be fed in the chemical vapor deposition of graphene. The simulation results can be directly compared with the experimental kinetic data, if available. Our kMC simulations reproduce the experimentally observed quintic-like behavior of graphene growth on Ir(111). By checking the simulation results, we find that such nonlinearity is caused by lattice mismatch, and the induced growth front inhomogeneity can be universally used to predict growth behaviors in other heteroepitaxial systems. Notably, although experimental kinetics usually gives useful insight into atomic mechanisms, it can sometimes be misleading. Such pitfalls can be avoided via atomistic simulations, as demonstrated in our study of the graphene etching process. Growth protocols can be designed theoretically with computational kinetic and mechanistic information. By contrasting the different activation energies involved in an atom-exchange-based carbon penetration process for monolayer and bilayer graphene, we propose a three-step strategy to grow high-quality bilayer graphene. Based on first-principles parameters, a kinetic pathway toward the high-density, ordered N doping of epitaxial graphene on Cu(111) using a C5NCl5 precursor is also identified. These studies demonstrate that atomistic simulations can unambiguously produce or reproduce the kinetic information on graphene growth, which is pivotal to understanding the growth mechanism and designing better growth protocols. A similar strategy can be used in growth mechanism studies of other two-dimensional atomic crystals.

Laser-speckle-contrast projection tomography for three-dimensional shear wave imaging.

Laser-speckle-contrast shear wave (LSC-SW) imaging is an optical method for tracking the propagation of a transient shear wave. With high spatial resolution and sensitivity in detecting displacements, this method is suitable for performing mechanical measurements in vitro. Here, we present a LSC-SW tomographic imaging system for visualizing the propagating shear wave wavefront in four dimensions [i.e., three-dimensional (3D) space plus time]. The volumetric elasticity distribution of a sample is constructed by estimating the speeds of the shear waves propagating along multiple paths at different angles. The proposed method enables multidirectional estimations of the shear wave speed. The capabilities of the imaging system are demonstrated by evaluating isotropy (both homogeneous and heterogeneous) and anisotropy in semiturbid phantoms. The proposed system is suitable for the mechanical characterization of a 3D cell culture system, such as monitoring changes in fiber orientation during the remodeling of the extracellular matrix that is known to be strongly associated with the progression and characterization of tumors.

Study of diffusive- and convective-transport mediated microtumor growth in a controlled microchamber.

In this paper, we report on using mass transport to control nutrition supply of colorectal cancer cells for developing a microtumor in a confined microchamber. To mimic the spatial heterogeneity of a tumor, two microfluidic configurations based on resistive circuits are designed. One has a convection-dominated microchamber to simulate the tumor region proximal to leaky blood vessels. The other has a diffusion-dominated microchamber to mimic the tumor core that lacks blood vessels and nutrient supply. Thus, the time for nutrition to fill the microchamber can vary from tens of minutes to several hours. Results show that cells cultured under a diffusive supply of nutrition have a high glycolytic rate and a nearly constant oxygen consumption rate. In contrast, cells cultured under convective supply of nutrition have a gradual increase of oxygen consumption rate with a low glycolytic rate. This suggests that cancer cells have distinct reactions under different mass transport and nutrition supply. Using these two microfluidic platforms to create different rate of nutrition supply, it is found that a continuous microtumor that almost fills the mm-size microchamber can be developed under a low-nutrient supply environment, but not for the convective condition. It also is demonstrated that microchannels can simulate the delivery of anti-cancer drugs to the microtumor under controlled mass-transport. This method provides a means to develop a larger scale microtumor in a lab-on-a-Chip system for post development and stimulations, and microchannels can be applied to control the physical and chemical environment for anti-cancer drug screening.

The Ralstonia solanacearum effector RipAK suppresses plant hypersensitive response by inhibiting the activity of host catalases.

The destructive bacterial pathogen Ralstonia solanacearum delivers effector proteins via a type-III secretion system for its pathogenesis of plant hosts. However, the biochemical functions of most of these effectors remain unclear. RipAK of R. solanacearum GMI1000 is a type-III effector with unknown functions. Functional analysis demonstrated that in tobacco leaves, ripAK knockout bacteria produced an obvious hypersensitive response; also, infected tissues accumulated reactive oxygen species in a shorter period postinfection, compared with wild type. This strongly indicates that RipAK can inhibit hypersensitive response during infection. Further analysis showed that RipAK localizes to peroxisomes and interacts with host catalases (CATs) in plant cells. Truncation of 2 putative domains of RipAK caused it to fail to target the peroxisome and fail to interact with AtCATs, suggesting that RipAK localization depends on its interaction with CATs. Furthermore, heterologous expression of RipAK inhibited CAT activity in vivo and in vitro. Finally, compared with the ripAK mutant, infection with a bacterial strain overexpressing RipAK inhibited the transcription of many immunity-associated genes in infected tobacco leaves at 2- and 4-hr postinfection, although mRNA levels of NtCAT1 were upregulated. These data indicate that GMI1000 suppresses hypersensitive response by inhibiting host CATs through RipAK at early stages of infection.

Ultrasound Strain Imaging to Assess the Biceps Brachii Muscle in Chronic Poststroke Spasticity.

OBJECTIVES: The aim of the study was to assess the feasibility of ultrasound strain imaging in characterizing the biceps brachii muscle in chronic poststroke spasticity. METHODS: We prospectively analyzed strain imaging data from bilateral biceps brachii muscles in 8 healthy volunteers and 7 patients with poststroke chronic spasticity. Axial deformations of the biceps brachii muscle and overlying subcutaneous tissue were produced by external compression using a sandbag (1.0 kg) attached to a transducer. The lengthening and shortening of the biceps brachii muscle and subcutaneous tissue were produced by manual passive elbow extension (from 90° to 0°) and flexion (from 0° to 90°), respectively. We used offline 2-dimensional speckle tracking to estimate axial and longitudinal strain ratios (biceps brachii strain/subcutaneous tissue strain), and the longitudinal tissue velocity of the biceps brachii muscle. Statistical analyses included analysis of variance for testing differences in strain imaging parameters among healthy, nonspastic, and spastic biceps brachii muscles, the Bonferroni correction for further testing differences in US strain imaging among paired groups (healthy versus spastic, nonspastic versus spastic, and healthy versus nonspastic), and the Pearson correlation coefficient for assessing the intraobserver reliability of performing strain imaging in stroke survivors. RESULTS: The differences in strain imaging parameters between healthy and spastic and between nonspastic and spastic biceps brachii muscles were significant at both 90° elbow flexion and maximal elbow extension (P < .01). There was no significant difference in axial strain ratios at 90° of elbow flexion or longitudinal tissue velocities between healthy and nonspastic muscles (P > .05). The intraobserver reliability of performing strain imaging in stroke survivors was good (r = 0.85; P < .01). CONCLUSIONS: Ultrasound strain imaging seems to be feasible for characterizing the biceps brachii muscle in chronic poststroke spasticity.