Using a thermal gradient table to study plant temperature signalling and response across a temperature spectrum.

Plants must cope with ever-changing temperature conditions in their environment. In many plant species, suboptimal high and low temperatures can induce adaptive mechanisms that allow optimal performance. Thermomorphogenesis is the acclimation to high ambient temperature, whereas cold acclimation refers to the acquisition of cold tolerance following a period of low temperatures. The molecular mechanisms underlying thermomorphogenesis and cold acclimation are increasingly well understood but neither signalling components that have an apparent role in acclimation to both cold and warmth, nor factors determining dose-responsiveness, are currently well defined. This can be explained in part by practical limitations, as applying temperature gradients requires the use of multiple growth conditions simultaneously, usually unavailable in research laboratories. Here we demonstrate that commercially available thermal gradient tables can be used to grow and assess plants over a defined and adjustable steep temperature gradient within one experiment. We describe technical and thermodynamic aspects and provide considerations for plant growth and treatment. We show that plants display the expected morphological, physiological, developmental and molecular responses that are typically associated with high temperature and cold acclimation. This includes temperature dose-response effects on seed germination, hypocotyl elongation, leaf development, hyponasty, rosette growth, temperature marker gene expression, stomatal conductance, chlorophyll content, ion leakage and hydrogen peroxide levels. In conclusion, thermal gradient table systems enable standardized and predictable environments to study plant responses to varying temperature regimes and can be swiftly implemented in research on temperature signalling and response.

Transport coefficient approach for characterizing nonequilibrium dynamics in soft matter.

Nonequilibrium states in soft condensed matter require a systematic approach to characterize and model materials, enhancing predictability and applications. Among the tools, X-ray photon correlation spectroscopy (XPCS) provides exceptional temporal and spatial resolution to extract dynamic insight into the properties of the material. However, existing models might overlook intricate details. We introduce an approach for extracting the transport coefficient, denoted as [Formula: see text], from the XPCS studies. This coefficient is a fundamental parameter in nonequilibrium statistical mechanics and is crucial for characterizing transport processes within a system. Our method unifies the Green-Kubo formulas associated with various transport coefficients, including gradient flows, particle-particle interactions, friction matrices, and continuous noise. We achieve this by integrating the collective influence of random and systematic forces acting on the particles within the framework of a Markov chain. We initially validated this method using molecular dynamics simulations of a system subjected to changes in temperatures over time. Subsequently, we conducted further verification using experimental systems reported in the literature and known for their complex nonequilibrium characteristics. The results, including the derived [Formula: see text] and other relevant physical parameters, align with the previous observations and reveal detailed dynamical information in nonequilibrium states. This approach represents an advancement in XPCS analysis, addressing the growing demand to extract intricate nonequilibrium dynamics. Further, the methods presented are agnostic to the nature of the material system and can be potentially expanded to hard condensed matter systems.

Value of quantitative microsurface structure analysis for evaluating the invasion depth of type 0-II early gastric cancer.

Background and Aim: The microsurface structure reflects the degree of damage to the glands, which is related to the invasion depth of early gastric cancer. To evaluate the diagnostic value of quantitative microsurface structure analysis for estimating the invasion depth of early gastric cancer. Methods: White-light imaging and narrow-band imaging (NBI) endoscopy were used to visualize the lesions of the included patients. The area ratio and depth-predicting score (DPS) of each patient were calculated; meanwhile, each lesion was examined by endoscopic ultrasonography (EUS). Results: Ninety-three patients were included between 2016 and 2019. Microsurface structure is related to the histological differentiation and progression of early gastric cancer. The receiver operating characteristic curve showed that when an area ratio of 80.3% was used as a cut-off value for distinguishing mucosal (M) and submucosal (SM) type 0-II gastric cancers, the sensitivity, specificity, and accuracy were 82.9%, 80.2%, and 91.6%, respectively. The accuracies for distinguishing M/SM differentiated and undifferentiated early gastric cancers were 87.4% and 84.8%, respectively. The accuracy of EUS for distinguishing M/SM early gastric cancer was 74.9%. DPS can only distinguish M-SM1 (SM infiltration <500 µm)/SM (SM infiltration ≥500 µm) with an accuracy of 83.8%. The accuracy of using area ratio for distinguishing 0-II early gastric cancers was better than those of using DPS and EUS (P < 0.05). Conclusion: Quantitative analysis of microsurface structure can be performed to assess M/SM type 0-II gastric cancer and is expected to be effective for judging the invasion depth of gastric cancer.

Stretching of immersed polyelectrolyte brushes in shear flow.

The way that polymer brushes respond to shear flow has important implications in various applications, including antifouling, corrosion protection, and stimuli-responsive materials. However, there is still much to learn about the behaviours and mechanisms that govern these responses. To address this gap in knowledge, our study uses in situ X-ray reflectivity to investigate how poly(styrene sulfonate) (PSS) brushes stretch and change in different environments, such as isopropanol (a poor solvent), water (a good solvent), and aqueous solutions containing various cations (Cs+, Ba2+, La3+, and Y3+). We have designed a custom apparatus that exposes the PSS brushes to both tangential shear forces from the primary flow and upward drag forces from a secondary flow. Our experimental findings clearly show that shear forces have a significant impact on how the chains in PSS brushes are arranged. At low shear rates, the tangential shear force causes the chains to tilt, leading to brush contraction. In contrast, higher shear rates generate an upward shear force that stretches and expands the chains. By analysing electron density profiles obtained from X-ray reflectivity, we gain valuable insights into how the PSS brushes respond structurally, especially the role of the diffuse layer in this dynamic behaviour. Our results highlight the importance of the initial chain configuration, which is influenced by the solvent and cations present, in shaping how polymer brushes respond to shear flow. The strength of the salt bridge network also plays a crucial role in determining how easily the brushes can stretch, with stronger networks offering more resistance to stretching. Ultimately, our study aims to enhance our understanding of polymer physics at interfaces, with a particular focus on practical applications involving polymer brushes.

Probing three-dimensional mesoscopic interfacial structures in a single view using multibeam X-ray coherent surface scattering and holography imaging.

Visualizing surface-supported and buried planar mesoscale structures, such as nanoelectronics, ultrathin-film quantum dots, photovoltaics, and heterogeneous catalysts, often requires high-resolution X-ray imaging and scattering. Here, we discovered that multibeam scattering in grazing-incident reflection geometry is sensitive to three-dimensional (3D) structures in a single view, which is difficult in conventional scattering or imaging approaches. We developed a 3D finite-element-based multibeam-scattering analysis to decode the heterogeneous electric-field distribution and to faithfully reproduce the complex scattering and surface features. This approach further leads to the demonstration of hard-X-ray Lloyd's mirror interference of scattering waves, resembling dark-field, high-contrast surface holography under the grazing-angle scattering conditions. A first-principles calculation of the single-view holographic images resolves the surface patterns' 3D morphology with nanometer resolutions, which is critical for ultrafine nanocircuit metrology. The holographic method and simulations pave the way for single-shot structural characterization for visualizing irreversible and morphology-transforming physical and chemical processes in situ or operando.

Kinetics of Shear-Induced Structural Ordering in Dense Colloids.

The macroscopic rheological response of a colloidal solution is highly correlated with the local microscopic structure, as revealed by an in situ Rheo-SAXS experiment with a high temporal resolution. Oscillatory shear can induce a strain-controlled ordering-to-disorder transition, resulting in a shear-thickening process that is different from the normal shear-thickening behavior that is driven by hydrodynamics and particle friction. We reveal that there is a complex time-dependent kinetics toward structural ordering under different applied strains. When the strain amplitude reaches a critical value that starts to induce disordering in the system, the pathway toward the dynamic equilibrium can also become highly non-monotonic. Within the same oscillatory cycle, there is a strong correlation of ordering with different phases of the oscillation, with the system oscillating between two dynamic metastable states.

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures.

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

Arabidopsis latent virus 1, a comovirus widely spread in Arabidopsis thaliana collections.

Transcriptome studies of Illumina RNA-Seq datasets of different Arabidopsis thaliana natural accessions and T-DNA mutants revealed the presence of two virus-like RNA sequences which showed the typical two-segmented genome characteristics of a comovirus. This comovirus did not induce any visible symptoms in infected A. thaliana plants cultivated under standard laboratory conditions. Hence it was named Arabidopsis latent virus 1 (ArLV1). Virus infectivity in A. thaliana plants was confirmed by quantitative reverse transcription polymerase chain reaction, transmission electron microscopy and mechanical inoculation. Arabidopsis latent virus 1 can also mechanically infect Nicotiana benthamiana, causing distinct mosaic symptoms. A bioinformatics investigation of A. thaliana RNA-Seq repositories, including nearly 6500 Sequence Read Archives (SRAs) in the NCBI SRA database, revealed the presence of ArLV1 in 25% of all archived natural A. thaliana accessions and in 8.5% of all analyzed SRAs. Arabidopsis latent virus 1 could also be detected in A. thaliana plants collected from the wild. Arabidopsis latent virus 1 is highly seed-transmissible with up to 40% incidence on the progeny derived from infected A. thaliana plants. This has probably led to a worldwide distribution in the model plant A. thaliana with as yet unknown effects on plant performance in a substantial number of studies.

Modulating the Rise and Decay Dynamics of Upconversion Luminescence through Controlling Excitations.

Different from organic dye/quantum dot possessing one luminescent center, upconversion luminescence (UCL) is actually a statistic of temporal behaviors of countless individual activators. Our experimental results have shown that the rise and decay dynamics of UCL is directly associated with the relative contribution of sensitizer-to-activator energy transfer and energy migration among sensitizers, which can be physically modulated by simply tuning the excitation laser. Therefore, dynamic UCL with record-wide 20-fold lifetime, ≈70-fold red-to-green intensity ratio, and reversibly definable emission color is easily realized by just modulating the excitation laser. Moreover, this generally applicable strategy only requires a simplest-possible UCL system whereas prevalent material engineering such as complicated composition design, sophisticated core-shell construction, or tedious chemical synthesis, is no longer needed.

Cardiovascular Imaging in China: Yesterday, Today, and Tomorrow.

The high prevalence and mortality of cardiovascular diseases in China's large population has increased the use of cardiovascular imaging for the assessment of conditions in recent years. In this study, we review the past 20 years of cardiovascular imaging in China, the increasingly important role played by cardiovascular computed tomography in coronary artery disease and pulmonary embolism assessment, magnetic resonance imaging's use for cardiomyopathy assessment, the development and application of artificial intelligence in cardiovascular imaging, and the future of Chinese cardiovascular imaging.

Small-world complex network generation on a digital quantum processor.

Quantum cellular automata (QCA) evolve qubits in a quantum circuit depending only on the states of their neighborhoods and model how rich physical complexity can emerge from a simple set of underlying dynamical rules. The inability of classical computers to simulate large quantum systems hinders the elucidation of quantum cellular automata, but quantum computers offer an ideal simulation platform. Here, we experimentally realize QCA on a digital quantum processor, simulating a one-dimensional Goldilocks rule on chains of up to 23 superconducting qubits. We calculate calibrated and error-mitigated population dynamics and complex network measures, which indicate the formation of small-world mutual information networks. These networks decohere at fixed circuit depth independent of system size, the largest of which corresponding to 1,056 two-qubit gates. Such computations may enable the employment of QCA in applications like the simulation of strongly-correlated matter or beyond-classical computational demonstrations.

pyXPCSviewer: an open-source interactive tool for X-ray photon correlation spectroscopy visualization and analysis.

pyXPCSviewer, a Python-based graphical user interface that is deployed at beamline 8-ID-I of the Advanced Photon Source for interactive visualization of XPCS results, is introduced. pyXPCSviewer parses rich X-ray photon correlation spectroscopy (XPCS) results into independent PyQt widgets that are both interactive and easy to maintain. pyXPCSviewer is open-source and is open to customization by the XPCS community for ingestion of diversified data structures and inclusion of novel XPCS techniques, both of which are growing demands particularly with the dawn of near-diffraction-limited synchrotron sources and their dedicated XPCS beamlines.

Effects of sublethal single, simultaneous and sequential abiotic stresses on phenotypic traits of Arabidopsis thaliana.

Plant responses to abiotic stresses are complex and dynamic, and involve changes in different traits, either as the direct consequence of the stress, or as an active acclimatory response. Abiotic stresses frequently occur simultaneously or in succession, rather than in isolation. Despite this, most studies have focused on a single stress and single or few plant traits. To address this gap, our study comprehensively and categorically quantified the individual and combined effects of three major abiotic stresses associated with climate change (flooding, progressive drought and high temperature) on 12 phenotypic traits related to morphology, development, growth and fitness, at different developmental stages in four Arabidopsis thaliana accessions. Combined sublethal stresses were applied either simultaneously (high temperature and drought) or sequentially (flooding followed by drought). In total, we analysed the phenotypic responses of 1782 individuals across these stresses and different developmental stages. Overall, abiotic stresses and their combinations resulted in distinct patterns of effects across the traits analysed, with both quantitative and qualitative differences across accessions. Stress combinations had additive effects on some traits, whereas clear positive and negative interactions were observed for other traits: 9 out of 12 traits for high temperature and drought, 6 out of 12 traits for post-submergence and drought showed significant interactions. In many cases where the stresses interacted, the strength of interactions varied across accessions. Hence, our results indicated a general pattern of response in most phenotypic traits to the different stresses and stress combinations, but it also indicated a natural genetic variation in the strength of these responses. This includes novel results regarding the lack of a response to drought after submergence and a decoupling between leaf number and flowering time after submergence. Overall, our study provides a rich characterization of trait responses of Arabidopsis plants to sublethal abiotic stresses at the phenotypic level and can serve as starting point for further in-depth physiological research and plant modelling efforts.

Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo.

Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis. Hamiltonian MCMC, a state-of-the-art development in the field of MCMC, has become popular in recent years. It utilizes Hamiltonian dynamics for indirect but much more efficient drawings of the model parameters. We described the principle of the Hamiltonian MCMC for inversion problems in X-ray scattering analysis by estimating high-dimensional models for several motivating scenarios in small-angle X-ray scattering, reflectivity, and X-ray fluorescence holography. Hamiltonian MCMC with appropriate preconditioning can deliver superior performance over the random-walk MCMC, and thus can be used as an efficient tool for the statistical analysis of the parameter distributions, as well as model predictions and confidence analysis.

Time-crystalline eigenstate order on a quantum processor.

Quantum many-body systems display rich phase structure in their low-temperature equilibrium states1. However, much of nature is not in thermal equilibrium. Remarkably, it was recently predicted that out-of-equilibrium systems can exhibit novel dynamical phases2-8 that may otherwise be forbidden by equilibrium thermodynamics, a paradigmatic example being the discrete time crystal (DTC)7,9-15. Concretely, dynamical phases can be defined in periodically driven many-body-localized (MBL) systems via the concept of eigenstate order7,16,17. In eigenstate-ordered MBL phases, the entire many-body spectrum exhibits quantum correlations and long-range order, with characteristic signatures in late-time dynamics from all initial states. It is, however, challenging to experimentally distinguish such stable phases from transient phenomena, or from regimes in which the dynamics of a few select states can mask typical behaviour. Here we implement tunable controlled-phase (CPHASE) gates on an array of superconducting qubits to experimentally observe an MBL-DTC and demonstrate its characteristic spatiotemporal response for generic initial states7,9,10. Our work employs a time-reversal protocol to quantify the impact of external decoherence, and leverages quantum typicality to circumvent the exponential cost of densely sampling the eigenspectrum. Furthermore, we locate the phase transition out of the DTC with an experimental finite-size analysis. These results establish a scalable approach to studying non-equilibrium phases of matter on quantum processors.

Comparison between the Linked Color and White Light Imaging Combined Score in the Evaluation of High-Risk Population of Gastric Cancer.

BACKGROUND: For patients undergoing gastroscopy, it is necessary to judge whether there is Helicobacter pylori infection, atrophy/intestinal metaplasia. This study aimed to evaluate and compare the light color imaging (LCI) and white light imaging (WLI) combined score during gastroscopy. METHODS: Each included patient underwent normalized gastroscopy with WLI and LCI, and all notable findings were photographed. Four endoscopists reviewed the endoscopic images of each patient. The clinical information, results of the H. pylori tests were unavailable at review. The total LCI and WLI scores of each patient were calculated and their detection in high-risk populations of gastric cancer were evaluated. The diagnostic values of LCI and WLI for intestinal metaplasia were also calculated. RESULTS: In total, 392 patients were included in the study. The degree of inflammation and proportion of active inflammation cases were significantly higher in the H. pylori gastritis group than in the non-H. pylori gastritis group; their endoscopic manifestations were also different. The LCI combined score improved the diagnostic value of each individual observation index in the diagnosis of H. pylori infection compared with the WLI combined score. The sensitivity, specificity, and accuracy were 91.9% (91.9% vs 81.5%), 91.1% (91.1% vs 80.2%), and 95.8% (95.8% vs 93.2%), respectively. The accuracy of LCI in the diagnosis of intestinal metaplasia was higher than that of WLI (83.4% vs 69.6%). CONCLUSION: The LCI and LCI combined score improved the diagnosis of H. pylori gastritis and intestinal metaplasia, and it is considered valuable in identifying the high-risk population of gastric cancer.

Information scrambling in quantum circuits.

Interactions in quantum systems can spread initially localized quantum information into the exponentially many degrees of freedom of the entire system. Understanding this process, known as quantum scrambling, is key to resolving several open questions in physics. Here, by measuring the time-dependent evolution and fluctuation of out-of-time-order correlators, we experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor. We engineer quantum circuits that distinguish operator spreading and operator entanglement and experimentally observe their respective signatures. We show that whereas operator spreading is captured by an efficient classical model, operator entanglement in idealized circuits requires exponentially scaled computational resources to simulate. These results open the path to studying complex and practically relevant physical observables with near-term quantum processors.

Resource allocation strategies among vegetative growth, sexual reproduction, asexual reproduction and defense during growing season of Aconitum kusnezoffii Reichb.

Natural plants must actively allocate their limited resources for survival and reproduction. Although vegetative growth, sexual reproduction, asexual reproduction and defense are all basic processes in the life cycle of plants, the strategies used to allocate resources between these processes are poorly understood. These processes are conspicuous in naturally grown Aconitum kusnezoffii Reichb., which makes it a suitable study subject. Here, the morphology, dry matter, total organic carbon, total nitrogen and aconitum alkaloid levels of shoot, principal root (PR) and lateral roots were measured throughout the growing season. Then, transcriptome and metabolite content analyses were performed. We found that vegetative growth began first. After vegetative growth ceased, sexual development began. Flower organ development was accompanied by increased photosynthesis and the PR consumed temporarily stored resources after flower formation. Asexual propagule development initiated earlier than sexual reproduction and kept accumulating resources after that. Development was slow before flower formation, mainly manifesting as increasing length; then, after flower formation it accelerated via enhanced material transport and accumulation. Defense compounds were maintained at low levels before flowering. In particular, the turnover of defense compounds was enhanced before and after flower bud emergence, providing resources for other processes. After flower formation, defense compounds were accumulated. The pattern found herein provides a vivid example for further studies on resource allocation strategies. The exciting finding that the PR, as a more direct storage site for photosynthate, is a buffer unit for resources, and that defense compounds can be reused for other processes, suggests a need to explore potential mechanisms.

Templated-Construction of Hollow MoS2 Architectures with Improved Photoresponses.

Despite the outstanding optoelectronic properties of MoS2 and its analogues, synthesis of such materials with desired features including fewer layers, arbitrary hollow structures, and particularly specifically customized morphologies, via inorganic reactions has always been challenging. Herein, using predesigned lanthanide-doped upconversion luminescent materials (e.g., NaYF4:Ln) as templates, arbitrary MoS2 hollow structures with precisely defined morphologies, widely variable dimensions, and very small shell thickness (≈2.5 nm) are readily constructed. Most importantly, integration of the near-infrared-responsive template significantly improves the photoresponse of up to 600 fold in device made of NaYF4:Yb/Er@MoS2 compared with that of MoS2 nanosheets under 980 nm laser illumination. Multichannel optoelectronic device is further fabricated by simply changing luminescent ions in the template, e.g., NaYF4:Er@MoS2, operating at 1532 nm light excitation with a 276-fold photoresponse enhancement. The simple chemistry, easy operation, high reliability, variable morphologies, and wide universality represent the most important advantages of this novel strategy that has not been accessed before.

Reconstruction of evolving nanostructures in ultrathin films with X-ray waveguide fluorescence holography.

Controlled synthesis of nanostructure ultrathin films is critical for applications in nanoelectronics, photonics, and energy generation and storage. The paucity of structural probes that are sensitive to nanometer-thick films and also capable of in-operando conditions with high spatiotemporal resolutions limits the understanding of morphology and dynamics in ultrathin films. Similar to X-ray fluorescence holography for crystals, where holograms are formed through the interference between the reference and the object waves, we demonstrated that an ultrathin film, being an X-ray waveguide, can also generate fluorescence holograms as a result of the establishment of X-ray standing waves. Coupled with model-independent reconstruction algorithms based on rigorous dynamical scattering theories, the thin-film-based X-ray waveguide fluorescence holography becomes a unique in situ and time-resolved imaging probe capable of elucidating the real-time nanostructure kinetics with unprecedented resolutions. Combined with chemical sensitive spectroscopic analysis, the reconstruction can yield element-specific morphology of embedding nanostructures in ultrathin films.